Rainfall erosivity in the Fukushima Prefecture: implications for radiocesium mobilization and migration

NASA Astrophysics Data System (ADS)

Laceby, J. Patrick; Chartin, Caroline; Degan, Francesca; Onda, Yuichi; Evrard, Olivier; Cerdan, Olivier; Ayrault, Sophie

2015-04-01

The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 led to the fallout of predominantly radiocesium (137Cs and 134Cs) on soils of the Fukushima Prefecture. This radiocesium was primarily fixated to fine soil particles. Subsequently, rainfall and snow melt run-off events result in significant quantities of radiocesium being eroded and transported throughout the coastal catchments and ultimately exported to the Pacific Ocean. Erosion models, such as the Universal Soil Loss Equation (USLE), relate rainfall directly to soil erosion in that an increase in rainfall one month will directly result in a proportional increase in sediment generation. Understanding the rainfall regime of the region is therefore fundamental to modelling and predicting long-term radiocesium export. Here, we analyze rainfall data for ~40 stations within a 100 km radius of the FDNPP. First we present general information on the rainfall regime in the region based on monthly and annual rainfall totals. Second we present general information on rainfall erosivity, the R-factor of the USLE equation and its relationship to the general rainfall data. Third we examine rainfall trends over the last 100 years at several of the rainfall stations to understand temporal trends and whether ~20 years of data is sufficient to calculate the R-factor for USLE models. Fourth we present monthly R-factor maps for the Fukushima coastal catchments impacted by the FDNPP accident. The variability of the rainfall in the region, particularly during the typhoon season, is likely resulting in a similar variability in the transfer and migration of radiocesium throughout the coastal catchments of the Fukushima Prefecture. Characterizing the region's rainfall variability is fundamental to modelling sediment and the concomitant radiocesium migration and transfer throughout these catchments and ultimately to the Pacific Ocean.

The relationship between the Southern Oscillation Index, rainfall and the occurrence of canine tick paralysis, feline tick paralysis and canine parvovirus in Australia.

PubMed

Rika-Heke, Tamara; Kelman, Mark; Ward, Michael P

2015-07-01

The aim of this study was to describe the association between climate, weather and the occurrence of canine tick paralysis, feline tick paralysis and canine parvovirus in Australia. The Southern Oscillation Index (SOI) and monthly average rainfall (mm) data were used as indices for climate and weather, respectively. Case data were extracted from a voluntary national companion animal disease surveillance resource. Climate and weather data were obtained from the Australian Government Bureau of Meteorology. During the 4-year study period (January 2010-December 2013), a total of 4742 canine parvovirus cases and 8417 tick paralysis cases were reported. No significant (P ≥ 0.05) correlations were found between the SOI and parvovirus, canine tick paralysis or feline tick paralysis. A significant (P < 0.05) positive cross-correlation was found between parvovirus occurrence and rainfall in the same month (0.28), and significant negative cross-correlations (-0.26 to -0.36) between parvovirus occurrence and rainfall 4-6 months previously. Significant (P < 0.05) negative cross-correlations (-0.34 to -0.39) were found between canine tick paralysis occurrence and rainfall 1-3 months previously, and significant positive cross-correlations (0.29-0.47) between canine tick paralysis occurrence and rainfall 7-10 months previously. Significant positive cross-correlations (0.37-0.68) were found between cases of feline tick paralysis and rainfall 6-10 months previously. These findings may offer a useful tool for the management and prevention of tick paralysis and canine parvovirus, by providing an evidence base supporting the recommendations of veterinarians to clients thus reducing the impact of these diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of water-level fluctuations of Lakes Winona and Winnemissett-- two landlocked lakes in a karst terrane in Volusia County, Florida

USGS Publications Warehouse

Hughes, G.H.

1979-01-01

The water levels of Lakes Winona and Winnemissett in Volusia County, Fla., correlate reasonably well during dry spells but only poorly during wet spells. Disparities develop mostly at times when the lake levels rise abruptly owing to rainstorms passing over the lake basins. The lack of correlation is attributed to the uneven distribution of the storm rainfall, even though the average annual rainfall at National Weather Service gages in the general area of the lakes is about the same. Analyses of the monthly rainfall data show that the rainfall variability between gages is sufficient to account for most of the disparity between monthly changes in the levels of the two lakes. The total annual rainfall at times may differ between rainfall gages by as much as 15 to 20 inches. Such differences tend to balance over the long term but may persist in the same direction for two or more years, causing apparent anomalies in lake-level fluctuations. (Woodard-USGS)

Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis

NASA Astrophysics Data System (ADS)

Chattopadhyay, Surajit; Chattopadhyay, Goutami

2012-10-01

In the work discussed in this paper we considered total ozone time series over Kolkata (22°34'10.92″N, 88°22'10.92″E), an urban area in eastern India. Using cloud cover, average temperature, and rainfall as the predictors, we developed an artificial neural network, in the form of a multilayer perceptron with sigmoid non-linearity, for prediction of monthly total ozone concentrations from values of the predictors in previous months. We also estimated total ozone from values of the predictors in the same month. Before development of the neural network model we removed multicollinearity by means of principal component analysis. On the basis of the variables extracted by principal component analysis, we developed three artificial neural network models. By rigorous statistical assessment it was found that cloud cover and rainfall can act as good predictors for monthly total ozone when they are considered as the set of input variables for the neural network model constructed in the form of a multilayer perceptron. In general, the artificial neural network has good potential for predicting and estimating monthly total ozone on the basis of the meteorological predictors. It was further observed that during pre-monsoon and winter seasons, the proposed models perform better than during and after the monsoon.

NASA Applied Sciences' DEVELOP National Program: Summer 2010 Florida Agriculture

NASA Technical Reports Server (NTRS)

Cooley, Zachary C.; Billiot, Amanda; Lee, Lucas; McKee, Jake

2010-01-01

The main agricultural areas in South Florida are located within the fertile land surrounding Lake Okeechobee. The Atlantic Watershed monthly rainfall anomalies showed a weak but statistically significant correlation to the Oceanic Nino Index (ONI). No other watershed s anomalies showed significant correlations with ONI or the Southern Oscillation Index (SOI). During La Nina months, less sea breeze days and more disturbed days were found to occur compared to El Nino and neutral months. The increase in disturbed days can likely by attributed to the synoptic pattern during La Nina, which is known to be favorable for tropical systems to follow paths that affect South Florida. Overall, neither sea breeze rainfall patterns nor total rainfall patterns in South Florida s main agricultural areas were found to be strongly influenced by the El Nino Southern Oscillation during our study time.

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

PubMed

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

2016-12-15

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

Rainfall and evapotranspiration data for southwest Medina County, Texas, August 2006-December 2009

USGS Publications Warehouse

Slattery, Richard N.; Asquith, William H.; Ockerman, Darwin J.

2011-01-01

During August 2006-December 2009, the U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers, Fort Worth District, collected rainfall and evapotranspiration data to help characterize the hydrology of the Nueces River Basin, Texas. The USGS installed and operated a station to collect continuous (30-minute interval) rainfall and evapotranspiration data in southwest Medina County approximately 14 miles southwest of D'Hanis, Texas, and 23 miles northwest of Pearsall, Texas. Rainfall data were collected by using an 8-inch tipping bucket raingage. Meteorological and surface-energy flux data used to calculate evapotranspiration were collected by using an extended Open Path Eddy Covariance system from Campbell Scientific, Inc. Data recorded by the system were used to calculate evapotranspiration by using the eddy covariance and Bowen ratio closure methods and to analyze the surface energy budget closure. During August 2006-December 2009 (excluding days of missing record), measured rainfall totaled 86.85 inches. In 2007, 2008, and 2009, annual rainfall totaled 40.98, 12.35, and 27.15 inches, respectively. The largest monthly rainfall total, 12.30 inches, occurred in July 2007. During August 2006-December 2009, evapotranspiration calculated by using the eddy covariance method totaled 69.91 inches. Annual evapotranspiration calculated by using the eddy covariance method totaled 34.62 inches in 2007, 15.24 inches in 2008, and 15.57 inches in 2009. During August 2006-December 2009, evapotranspiration calculated by using the Bowen ratio closure method (the more refined of the two datasets) totaled 68.33 inches. Annual evapotranspiration calculated by using the Bowen ratio closure method totaled 32.49, 15.54, and 15.80 inches in 2007, 2008, and 2009, respectively (excluding days of missing record).

Models for estimating daily rainfall erosivity in China

NASA Astrophysics Data System (ADS)

Xie, Yun; Yin, Shui-qing; Liu, Bao-yuan; Nearing, Mark A.; Zhao, Ying

2016-04-01

The rainfall erosivity factor (R) represents the multiplication of rainfall energy and maximum 30 min intensity by event (EI30) and year. This rainfall erosivity index is widely used for empirical soil loss prediction. Its calculation, however, requires high temporal resolution rainfall data that are not readily available in many parts of the world. The purpose of this study was to parameterize models suitable for estimating erosivity from daily rainfall data, which are more widely available. One-minute resolution rainfall data recorded in sixteen stations over the eastern water erosion impacted regions of China were analyzed. The R-factor ranged from 781.9 to 8258.5 MJ mm ha-1 h-1 y-1. A total of 5942 erosive events from one-minute resolution rainfall data of ten stations were used to parameterize three models, and 4949 erosive events from the other six stations were used for validation. A threshold of daily rainfall between days classified as erosive and non-erosive was suggested to be 9.7 mm based on these data. Two of the models (I and II) used power law functions that required only daily rainfall totals. Model I used different model coefficients in the cool season (Oct.-Apr.) and warm season (May-Sept.), and Model II was fitted with a sinusoidal curve of seasonal variation. Both Model I and Model II estimated the erosivity index for average annual, yearly, and half-month temporal scales reasonably well, with the symmetric mean absolute percentage error MAPEsym ranging from 10.8% to 32.1%. Model II predicted slightly better than Model I. However, the prediction efficiency for the daily erosivity index was limited, with the symmetric mean absolute percentage error being 68.0% (Model I) and 65.7% (Model II) and Nash-Sutcliffe model efficiency being 0.55 (Model I) and 0.57 (Model II). Model III, which used the combination of daily rainfall amount and daily maximum 60-min rainfall, improved predictions significantly, and produced a Nash-Sutcliffe model efficiency for daily erosivity index prediction of 0.93. Thus daily rainfall data was generally sufficient for estimating annual average, yearly, and half-monthly time scales, while sub-daily data was needed when estimating daily erosivity values.

The interaction rainfall vs. weight as determinant of total mercury concentration in fish from a tropical estuary.

PubMed

Barletta, M; Lucena, L R R; Costa, M F; Barbosa-Cintra, S C T; Cysneiros, F J A

2012-08-01

Mercury loads in tropical estuaries are largely controlled by the rainfall regime that may cause biodilution due to increased amounts of organic matter (both live and non-living) in the system. Top predators, as Trichiurus lepturus, reflect the changing mercury bioavailability situations in their muscle tissues. In this work two variables [fish weight (g) and monthly total rainfall (mm)] are presented as being important predictors of total mercury concentration (T-Hg) in fish muscle. These important explanatory variables were identified by a Weibull Regression model, which best fit the dataset. A predictive model using readily available variables as rainfall is important, and can be applied for human and ecological health assessments and decisions. The main contribution will be to further protect vulnerable groups as pregnant women and children. Nature conservation directives could also improve by considering monitoring sample designs that include this hypothesis, helping to establish complete and detailed mercury contamination scenarios. Copyright © 2012 Elsevier Ltd. All rights reserved.

Association between Rainfall and Pediatric Emergency Department Visits for Acute Gastrointestinal Illness

PubMed Central

Drayna, Patrick; McLellan, Sandra L.; Simpson, Pippa; Li, Shun-Hwa; Gorelick, Marc H.

2010-01-01

Background Microbial water contamination after periods of heavy rainfall is well described, but its link to acute gastrointestinal illness (AGI) in children is not well known. Objectives We hypothesize an association between rainfall and pediatric emergency department (ED) visits for AGI that may represent an unrecognized, endemic burden of pediatric disease in a major U.S. metropolitan area served by municipal drinking water systems. Methods We conducted a retrospective time series analysis of visits to the Children’s Hospital of Wisconsin ED in Wauwatosa, Wisconsin. Daily visit totals of discharge International Classification of Diseases, 9th Revision codes of gastroenteritis or diarrhea were collected along with daily rainfall totals during the study period from 2002 to 2007. We used an autoregressive moving average model, adjusting for confounding variables such as sewage release events and season, to look for an association between daily visits and rainfall after a lag of 1–7 days. Results A total of 17,357 AGI visits were identified (mean daily total, 7.9; range, 0–56). Any rainfall 4 days prior was significantly associated with an 11% increase in AGI visits. Expected seasonal effects were also seen, with increased AGI visits in winter months. Conclusions We observed a significant association between rainfall and pediatric ED visits for AGI, suggesting a waterborne component of disease transmission in this population. The observed increase in ED visits for AGI occurred in the absence of any disease outbreaks reported to public health officials in our region, suggesting that rainfall-associated illness may be underestimated. Further study is warranted to better address this association. PMID:20515725

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

USGS Publications Warehouse

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

2009-01-01

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

Effect of monthly areal rainfall uncertainty on streamflow simulation

NASA Astrophysics Data System (ADS)

Ndiritu, J. G.; Mkhize, N.

2017-08-01

Areal rainfall is mostly obtained from point rainfall measurements that are sparsely located and several studies have shown that this results in large areal rainfall uncertainties at the daily time step. However, water resources assessment is often carried out a monthly time step and streamflow simulation is usually an essential component of this assessment. This study set out to quantify monthly areal rainfall uncertainties and assess their effect on streamflow simulation. This was achieved by; i) quantifying areal rainfall uncertainties and using these to generate stochastic monthly areal rainfalls, and ii) finding out how the quality of monthly streamflow simulation and streamflow variability change if stochastic areal rainfalls are used instead of historic areal rainfalls. Tests on monthly rainfall uncertainty were carried out using data from two South African catchments while streamflow simulation was confined to one of them. A non-parametric model that had been applied at a daily time step was used for stochastic areal rainfall generation and the Pitman catchment model calibrated using the SCE-UA optimizer was used for streamflow simulation. 100 randomly-initialised calibration-validation runs using 100 stochastic areal rainfalls were compared with 100 runs obtained using the single historic areal rainfall series. By using 4 rain gauges alternately to obtain areal rainfall, the resulting differences in areal rainfall averaged to 20% of the mean monthly areal rainfall and rainfall uncertainty was therefore highly significant. Pitman model simulations obtained coefficient of efficiencies averaging 0.66 and 0.64 in calibration and validation using historic rainfalls while the respective values using stochastic areal rainfalls were 0.59 and 0.57. Average bias was less than 5% in all cases. The streamflow ranges using historic rainfalls averaged to 29% of the mean naturalised flow in calibration and validation and the respective average ranges using stochastic monthly rainfalls were 86 and 90% of the mean naturalised streamflow. In calibration, 33% of the naturalised flow located within the streamflow ranges with historic rainfall simulations and using stochastic rainfalls increased this to 66%. In validation the respective percentages of naturalised flows located within the simulated streamflow ranges were 32 and 72% respectively. The analysis reveals that monthly areal rainfall uncertainty is significant and incorporating it into streamflow simulation would add validity to the results.

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

Singh, Narendra; Solanki, Raman; Ojha, N.

We present the measurements of cloud-base height variations over Aryabhatta Research Institute of Observational Science, Nainital (79.45 degrees E, 29.37 degrees N, 1958 m amsl) obtained from Vaisala Ceilometer, during the nearly year-long Ganges Valley Aerosol Experiment (GVAX). The cloud-base measurements are analysed in conjunction with collocated measurements of rainfall, to study the possible contributions from different cloud types to the observed monsoonal rainfall during June to September 2011. The summer monsoon of 2011 was a normal monsoon year with total accumulated rainfall of 1035.8 mm during June-September with a maximum during July (367.0 mm) and minimum during September (222.3more » mm). The annual mean monsoon rainfall over Nainital is 1440 +/- 430 mm. The total rainfall measured during other months (October 2011-March 2012) was only 9% of that observed during the summer monsoon. The first cloud-base height varied from about 31 m above ground level (AGL) to a maximum of 7.6 km AGL during the summer monsoon period of 2011. It is found that about 70% of the total rain is observed only when the first cloud-base height varies between surface and 2 km AGL, indicating that most of the rainfall at high altitude stations such as Nainital is associated with stratiform low-level clouds. However, about 25% of the total rainfall is being contributed by clouds between 2 and 6 km. The occurrences of high-altitude cumulus clouds are observed to be only 2-4%. This study is an attempt to fill a major gap of measurements over the topographically complex and observationally sparse northern Indian region providing the evaluation data for atmospheric models and therefore, have implications towards the better predictions of monsoon rainfall and the weather components over this region.« less

Parameter Tuning and Calibration of RegCM3 with MIT-Emanuel Cumulus Parameterization Scheme over CORDEX East Asian Domain

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

Zou, Liwei; Qian, Yun; Zhou, Tianjun

2014-10-01

In this study, we calibrated the performance of regional climate model RegCM3 with Massachusetts Institute of Technology (MIT)-Emanuel cumulus parameterization scheme over CORDEX East Asia domain by tuning the selected seven parameters through multiple very fast simulated annealing (MVFSA) sampling method. The seven parameters were selected based on previous studies, which customized the RegCM3 with MIT-Emanuel scheme through three different ways by using the sensitivity experiments. The responses of model results to the seven parameters were investigated. Since the monthly total rainfall is constrained, the simulated spatial pattern of rainfall and the probability density function (PDF) distribution of daily rainfallmore » rates are significantly improved in the optimal simulation. Sensitivity analysis suggest that the parameter “relative humidity criteria” (RH), which has not been considered in the default simulation, has the largest effect on the model results. The responses of total rainfall over different regions to RH were examined. Positive responses of total rainfall to RH are found over northern equatorial western Pacific, which are contributed by the positive responses of explicit rainfall. Followed by an increase of RH, the increases of the low-level convergence and the associated increases in cloud water favor the increase of the explicit rainfall. The identified optimal parameters constrained by the total rainfall have positive effects on the low-level circulation and the surface air temperature. Furthermore, the optimized parameters based on the extreme case are suitable for a normal case and the model’s new version with mixed convection scheme.« less

Stochastic Generation of Monthly Rainfall Data

NASA Astrophysics Data System (ADS)

Srikanthan, R.

2009-03-01

Monthly rainfall data is generally needed in the simulation of water resources systems, and in the estimation of water yield from large catchments. Monthly streamflow data generation models are usually applied to generate monthly rainfall data, but this presents problems for most regions, which have significant months of no rainfall. In an earlier study, Srikanthan et al. (J. Hydrol. Eng., ASCE 11(3) (2006) 222-229) recommended the modified method of fragments to disaggregate the annual rainfall data generated by a first-order autoregressive model. The main drawback of this approach is the occurrence of similar patterns when only a short length of historic data is available. Porter and Pink (Hydrol. Water Res. Symp. (1991) 187-191) used synthetic fragments from a Thomas-Fiering monthly model to overcome this drawback. As an alternative, a new two-part monthly model is nested in an annual model to generate monthly rainfall data which preserves both the monthly and annual characteristics. This nested model was applied to generate rainfall data from seven rainfall stations located in eastern and southern parts of Australia, and the results showed that the model performed satisfactorily.

Ground-foraging ants (Hymenoptera: Formicidae) and rainfall effect on pitfall trapping in a deciduous thorn woodland (caatinga), Northeastern Brazil.

PubMed

Nunes, Francyregis A; Segundo, Glauco B Martins; Vasconcelos, Yuri B; Azevedo, Raul; Quinet, Yves

2011-12-01

The semi-arid Caatinga is the fourth largest biome of Brazil, which biota still remains one of the most poorly known, especially with regard to invertebrate groups. In this study, a ground-foraging ant assemblage was surveyed during one year and the effect of rainfall on pitfall trapping was assessed. The study was performed in an area located in the municipality of Pentecoste (3 degrees 48' S - 39 degrees 20' W), in the State of Ceará. A 200m transect with 20 equidistant sampling points was established. Transect sampling was performed once a month during 12 months, over the period August 2008-August 2009. At each sampling point, a pitfall trap partially filled with a mixture of ethanol and monoethylene glycol was placed at the beginning of each month and remained in the field for seven days. 39 species belonging to six subfamilies and 19 genera, plus two unidentified species, were collected, with Pheidole (10 spp.) and Camponotus (8 spp.) being the taxa with the most species. 23 species were frequent, being found in more than 50% of the 12 transect samplings. Five species had an intermediate frequency (25 to 50%), while 13 were relatively infrequent (less than 25%). Most of the species (22) showed low occurrence, being found in less than 10% of the 240 samples (20 samples each month, during 12 months). Only five species were collected in more than 50% of the samples, those species being also responsible for most of the total abundance (number of captured individuals of all species) observed each month. The species-accumulation curves (observed and estimated) indicated that sampling sufficiency was attained, and that about 92% of the estimated ground-foraging ant fauna had been collected. 40 and 29 species were collected in the dry and rainy season, respectively, with monthly species richness ranging from 13 to 28. The total ant abundance showed a drastic decrease during the rainy season, and a negative linear correlation was found between rainfall and total ant abundance (R2 = 0.68). A similar negative linear correlation was found for species occurrences against rainfall (R2 = 0.71), and for mean number of species per pitfall trap against rainfall (R2 = 0.71). However, some species showed equal abundance, occurrence and mean number of individuals per pitfall trap in both seasons, while others showed a much higher abundance and occurrence during the rainy season. Pitfall trapping as a method to sample ground-foraging ant assemblage of the Caatinga biome and potential factors responsible for lower pitfall trap performance during rainy season are discussed.

[Prevalence of respiratory syncytial virus infection in hospitalized children at a children's hospital and effects of climate change on the prevalence in Suzhou, China].

PubMed

Geng, Jia; Guo, Wan-Liang; Zhang, Xue-Lan

2015-05-01

To investigate the prevalence of respiratory syncytial virus (RSV) infection in hospitalized children and the relationship between the prevalence and the climate change in Suzhou, China. A total of 42 664 nasopharyngeal secretions from hospitalized children with acute respiratory infection at the Suzhou Children's Hospital were screened for RSV antigens using direct immunofluorescence. Monthly meteorological data (mean monthly air temperature, monthly relative humidity, monthly rainfall, total monthly sunshine duration, and mean monthly wind velocity) in Suzhou between 2001 and 2011 were collected. The correlations between RSV detection rate and climatic factors were evaluated using correlation and stepwise regression analysis. The annual RSV infection rate in hospitalized children with respiratory infection in the Suzhou Children's Hospital varied between 11.85% and 27.30% from 2001 to 2011. In the 9 epidemic seasons, each spanning from November to April of the next year, from 2001 to 2010, the RSV detection rates were 40.75%, 22.72%, 39.93%, 27.37%, 42.71%, 21.28%, 38.57%, 19.86%, and 29.73%, respectively; there were significant differences in the detection rate between the epidemic seasons. The monthly RSV detection rate was negatively correlated with mean monthly air temperature, total monthly sunshine duration, monthly rainfall, monthly relative humidity, and mean monthly wind velocity (P<0.05). Stepwise regression analysis showed that mean monthly air temperature fitted into a linear model (R(2)=0.64, P<0.01). From 2001 to 2011, RSV infection in Suzhou was predominantly prevalent between November and April of the next year. As a whole, the infection rate of RSV reached a peak every other year. Air temperature played an important role in the epidemics of RSV infection in Suzhou.

Study of acid mine drainage management with evaluating climate and rainfall in East Pit 3 West Banko coal mine

NASA Astrophysics Data System (ADS)

Rochyani, Neny

2017-11-01

Acid mine drainage is a major problem for the mining environment. The main factor that formed acid mine drainage is the volume of rainfall. Therefore, it is important to know clearly the main climate pattern of rainfall and season on the management of acid mine drainage. This study focuses on the effects of rainfall on acid mine water management. Based on daily rainfall data, monthly and seasonal patterns by using Gumbel approach is known the amount of rainfall that occurred in East Pit 3 West Banko area. The data also obtained the highest maximum daily rainfall on 165 mm/day and the lowest at 76.4 mm/day, where it is known that the rainfall conditions during the period 2007 - 2016 is from November to April so the use of lime is also slightly, While the low rainfall is from May to October and the use of lime will be more and more. Based on calculation of lime requirement for each return period, it can be seen the total of lime and financial requirement for treatment of each return period.

Reconstruction of rainfall in Zafra (southwest Spain) from 1750 to 1840 from documentary sources

NASA Astrophysics Data System (ADS)

Fernández-Fernández, M. I.; Gallego, M. C.; Domínguez-Castro, F.; Vaquero, J. M.; Moreno González, J. M.; Castillo Durán, J.

2011-11-01

This work presents the first high-resolution reconstruction of rainfall in southwestern Spain during the period 1750-1840. The weather descriptions used are weekly reports describing the most relevant events that occurred in the Duchy of Feria. An index was defined to characterise the weekly rainfall. Monthly indices were obtained by summing the corresponding weekly indices, obtaining cumulative monthly rainfall indices. The reconstruction method consisted of establishing a linear correlation between the monthly rainfall index and monthly instrumental data (1960-1990). The correlation coefficients were greater than 0.80 for all months. The rainfall reconstruction showed major variability similar to natural variability. The reconstructed rainfall series in Zafra was compared with the rainfall series of Cadiz, Gibraltar and Lisbon for the period 1750-1840, with all four series found to have a similar pattern. The influence of the North Atlantic Oscillation (NAO) on the winter rainfall reconstruction was found to behave similarly to that of modern times. Other studies described are of the SLP values over the entire North Atlantic in the months with extreme values of rainfall, and unusual meteorological events (hail, frost, storms and snowfall) in the reports of the Duchy of Feria.

Exploring the relationship between malaria, rainfall intermittency, and spatial variation in rainfall seasonality

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Wimberly, M. C.; Henebry, G. M.; Senay, G. B.

2014-12-01

Malaria is a major public health problem throughout tropical regions of the world. Successful prevention and treatment of malaria requires an understanding of the environmental factors that affect the life cycle of both the malaria pathogens, protozoan parasites, and its vectors, anopheline mosquitos. Because the egg, larval, and pupal stages of mosquito development occur in aquatic habitats, information about the spatial and temporal distribution of rainfall is critical for modeling malaria risk. Potential sources of hydrological data include satellite-derived rainfall estimates (TRMM and GPM), evapotranspiration derived from a simplified surface energy balance, and estimates of soil moisture and fractional water cover from passive microwave imagery. Previous studies have found links between malaria cases and total monthly or weekly rainfall in areas where both are highly seasonal. However it is far from clear that monthly or weekly summaries are the best metrics to use to explain malaria outbreaks. It is possible that particular temporal or spatial patterns of rainfall result in better mosquito habitat and thus higher malaria risk. We used malaria case data from the Amhara region of Ethiopia and satellite-derived rainfall estimates to explore the relationship between malaria outbreaks and rainfall with the goal of identifying the most useful rainfall metrics for modeling malaria occurrence. First, we explored spatial variation in the seasonal patterns of both rainfall and malaria cases in Amhara. Second, we assessed the relative importance of different metrics of rainfall intermittency, including alternation of wet and dry spells, the strength of intensity fluctuations, and spatial variability in these measures, in determining the length and severity of malaria outbreaks. We also explored the sensitivity of our results to the choice of method for describing rainfall intermittency and the spatial and temporal scale at which metrics were calculated. Results demonstrate that information about the seasonality and intermittency of rainfall has the potential to improve our understanding of malaria epidemiology and improve our ability to forecast malaria outbreaks.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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.

Changing climate and endangered high mountain ecosystems in Colombia.

PubMed

Ruiz, Daniel; Moreno, Hernán Alonso; Gutiérrez, María Elena; Zapata, Paula Andrea

2008-07-15

High mountain ecosystems are among the most sensitive environments to changes in climatic conditions occurring on global, regional and local scales. The article describes the changing conditions observed over recent years in the high mountain basin of the Claro River, on the west flank of the Colombian Andean Central mountain range. Local ground truth data gathered at 4150 m, regional data available at nearby weather stations, and satellite info were used to analyze changes in the mean and the variance, and significant trends in climatic time series. Records included minimum, mean and maximum temperatures, relative humidity, rainfall, sunshine, and cloud characteristics. In high levels, minimum and maximum temperatures during the coldest days increased at a rate of about 0.6 degrees C/decade, whereas maximum temperatures during the warmest days increased at a rate of about 1.3 degrees C/decade. Rates of increase in maximum, mean and minimum diurnal temperature range reached 0.6, 0.7, and 0.5 degrees C/decade. Maximum, mean and minimum relative humidity records showed reductions of about 1.8, 3.9 and 6.6%/decade. The total number of sunny days per month increased in almost 2.1 days. The headwaters exhibited no changes in rainfall totals, but evidenced an increased occurrence of unusually heavy rainfall events. Reductions in the amount of all cloud types over the area reached 1.9%/decade. In low levels changes in mean monthly temperatures and monthly rainfall totals exceeded + 0.2 degrees C and - 4% per decade, respectively. These striking changes might have contributed to the retreat of glacier icecaps and to the disappearance of high altitude water bodies, as well as to the occurrence and rapid spread of natural and man-induced forest fires. Significant reductions in water supply, important disruptions of the integrity of high mountain ecosystems, and dramatic losses of biodiversity are now a steady menu of the severe climatic conditions experienced by these fragile tropical environments.

Rainfall variation and child health: effect of rainfall on diarrhea among under 5 children in Rwanda, 2010.

PubMed

Mukabutera, Assumpta; Thomson, Dana; Murray, Megan; Basinga, Paulin; Nyirazinyoye, Laetitia; Atwood, Sidney; Savage, Kevin P; Ngirimana, Aimable; Hedt-Gauthier, Bethany L

2016-08-05

Diarrhea among children under 5 years of age has long been a major public health concern. Previous studies have suggested an association between rainfall and diarrhea. Here, we examined the association between Rwandan rainfall patterns and childhood diarrhea and the impact of household sanitation variables on this relationship. We derived a series of rain-related variables in Rwanda based on daily rainfall measurements and hydrological models built from daily precipitation measurements collected between 2009 and 2011. Using these data and the 2010 Rwanda Demographic and Health Survey database, we measured the association between total monthly rainfall, monthly rainfall intensity, runoff water and anomalous rainfall and the occurrence of diarrhea in children under 5 years of age. Among the 8601 children under 5 years of age included in the survey, 13.2 % reported having diarrhea within the 2 weeks prior to the survey. We found that higher levels of runoff were protective against diarrhea compared to low levels among children who lived in households with unimproved toilet facilities (OR = 0.54, 95 % CI: [0.34, 0.87] for moderate runoff and OR = 0.50, 95 % CI: [0.29, 0.86] for high runoff) but had no impact among children in household with improved toilets. Our finding that children in households with unimproved toilets were less likely to report diarrhea during periods of high runoff highlights the vulnerabilities of those living without adequate sanitation to the negative health impacts of environmental events.

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.

Runoff and leaching of metolachlor from Mississippi River alluvial soil during seasons of average and below-average rainfall.

PubMed

Southwick, Lloyd M; Appelboom, Timothy W; Fouss, James L

2009-02-25

The movement of the herbicide metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide] via runoff and leaching from 0.21 ha plots planted to corn on Mississippi River alluvial soil (Commerce silt loam) was measured for a 6-year period, 1995-2000. The first three years received normal rainfall (30 year average); the second three years experienced reduced rainfall. The 4-month periods prior to application plus the following 4 months after application were characterized by 1039 +/- 148 mm of rainfall for 1995-1997 and by 674 +/- 108 mm for 1998-2000. During the normal rainfall years 216 +/- 150 mm of runoff occurred during the study seasons (4 months following herbicide application), accompanied by 76.9 +/- 38.9 mm of leachate. For the low-rainfall years these amounts were 16.2 +/- 18.2 mm of runoff (92% less than the normal years) and 45.1 +/- 25.5 mm of leachate (41% less than the normal seasons). Runoff of metolachlor during the normal-rainfall seasons was 4.5-6.1% of application, whereas leaching was 0.10-0.18%. For the below-normal periods, these losses were 0.07-0.37% of application in runoff and 0.22-0.27% in leachate. When averages over the three normal and the three less-than-normal seasons were taken, a 35% reduction in rainfall was characterized by a 97% reduction in runoff loss and a 71% increase in leachate loss of metolachlor on a percent of application basis. The data indicate an increase in preferential flow in the leaching movement of metolachlor from the surface soil layer during the reduced rainfall periods. Even with increased preferential flow through the soil during the below-average rainfall seasons, leachate loss (percent of application) of the herbicide remained below 0.3%. Compared to the average rainfall seasons of 1995-1997, the below-normal seasons of 1998-2000 were characterized by a 79% reduction in total runoff and leachate flow and by a 93% reduction in corresponding metolachlor movement via these routes. An added observation in the study was that neither runoff of rainfall nor runoff loss of metolachlor was influenced by the presence of subsurface drains, compared to the results from plots without such drains that were described in an earlier paper.

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.

Developing Multi-model Ensemble for Precipitation and Temperature Seasonal Forecasts: Implications for Karkheh River Basin in Iran

NASA Astrophysics Data System (ADS)

Najafi, Husain; Massah Bavani, Ali Reza; Wanders, Niko; Wood, Eric; Irannejad, Parviz; Robertson, Andrew

2017-04-01

Water resource managers can utilize reliable seasonal forecasts for allocating water between different users within a water year. In the west of Iran where a decline of renewable water resources has been observed, basin-wide water management has been the subject of many inter-provincial conflicts in recent years. The problem is exacerbated when the environmental water requirements is not provided leaving the Hoor-al-Azim marshland in the downstream dry. It has been argued that information on total seasonal rainfall can support the Iranian Ministry of Energy within the water year. This study explores the skill of the North America Multi Model Ensemble for Karkheh River Basin in the of west Iran. NMME seasonal precipitation and temperature forecasts from eight models are evaluated against PERSIANN-CDR and Climate Research Unit (CRU) datasets. Analysis suggests that anomaly correlation for both precipitation and temperature is greater than 0.4 for all individual models. Lead time-dependent seasonal forecasts are improved when a multi-model ensemble is developed for the river basin using stepwise linear regression model. MME R-squared exceeds 0.6 for temperature for almost all initializations suggesting high skill of NMME in Karkheh river basin. The skill of MME for rainfall forecasts is high for 1-month lead time for October, February, March and October initializations. However, for months when the amount of rainfall accounts for a significant proportion of total annual rainfall, the skill of NMME is limited a month in advance. It is proposed that operational regional water companies incorporate NMME seasonal forecasts into water resource planning and management, especially during growing seasons that are essential for agricultural risk management.

Application of Statistical Downscaling Techniques to Predict Rainfall and Its Spatial Analysis Over Subansiri River Basin of Assam, India

NASA Astrophysics Data System (ADS)

Barman, S.; Bhattacharjya, R. K.

2017-12-01

The River Subansiri is the major north bank tributary of river Brahmaputra. It originates from the range of Himalayas beyond the Great Himalayan range at an altitude of approximately 5340m. Subansiri basin extends from tropical to temperate zones and hence exhibits a great diversity in rainfall characteristics. In the Northern and Central Himalayan tracts, precipitation is scarce on account of high altitudes. On the other hand, Southeast part of the Subansiri basin comprising the sub-Himalayan and the plain tract in Arunachal Pradesh and Assam, lies in the tropics. Due to Northeast as well as Southwest monsoon, precipitation occurs in this region in abundant quantities. Particularly, Southwest monsoon causes very heavy precipitation in the entire Subansiri basin during May to October. In this study, the rainfall over Subansiri basin has been studied at 24 different locations by multiple linear and non-linear regression based statistical downscaling techniques and by Artificial Neural Network based model. APHRODITE's gridded rainfall data of 0.25˚ x 0.25˚ resolutions and climatic parameters of HadCM3 GCM of resolution 2.5˚ x 3.75˚ (latitude by longitude) have been used in this study. It has been found that multiple non-linear regression based statistical downscaling technique outperformed the other techniques. Using this method, the future rainfall pattern over the Subansiri basin has been analyzed up to the year 2099 for four different time periods, viz., 2020-39, 2040-59, 2060-79, and 2080-99 at all the 24 locations. On the basis of historical rainfall, the months have been categorized as wet months, months with moderate rainfall and dry months. The spatial changes in rainfall patterns for all these three types of months have also been analyzed over the basin. Potential decrease of rainfall in the wet months and months with moderate rainfall and increase of rainfall in the dry months are observed for the future rainfall pattern of the Subansiri basin.

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.

Hydrologic conditions and water quality in an agricultural area in Kleberg and Nueces Counties, Texas, 1996-98

USGS Publications Warehouse

Ockerman, Darwin J.; Petri, Brian L.

2001-01-01

During 1996?98, rainfall and runoff were monitored on a 49,680-acre agricultural watershed in Kleberg and Nueces Counties in South Texas. Nineteen rainfall samples were analyzed for selected nutrients, and runoff samples from 29 storms were analyzed for major ions, nutrients, and pesticides. Loads of nutrients in rainfall and loads of nutrients and pesticides in runoff were computed. For a 40,540-acre part of the watershed (lower study area), constituent loads entering the watershed in rainfall, in runoff from the upper study area, and from agricultural chemical applications to the lower study area were compared with runoff loads exiting the lower study area. Total rainfall for 1996?98 averaged 25.86 inches per year, which is less than the long-term annual average rainfall of 29.80 inches for the area. Rainfall and runoff during 1996?98 were typical of historical patterns, with periods of below average rainfall and runoff interspersed with extreme events. Five individual storms accounted for about 38 percent of the total rainfall and 94 percent of the total runoff. During the 3-year study, the total nitrogen runoff yield from the lower study area was 1.3 pounds per acre per year, compared with 49 pounds per acre per year applied as fertilizer and 3.1 pounds per acre per year from rainfall. While almost all of the fertilizer and rainfall nitrogen was ammonia and nitrate, most of the nitrogen in runoff was particulate organic nitrogen, associated with crop residue. Total nitrogen exiting the lower study area in surface-water runoff was about 2.5 percent of the nitrogen inputs (fertilizer and rainfall nitrogen). Annual deposition of total nitrogen entering the lower study area in rainfall exceeded net yields of total nitrogen exiting the watershed in runoff because most of the rainfall does not contribute to runoff. During the study, the total phosphorus runoff yield from the lower study area was 0.48 pound per acre per year compared with 4.2 pounds per acre per year applied as fertilizer and 0.03 pound per acre per year from rainfall. Twenty-one pesticides were detected in runoff with varying degrees of frequency during the study. The herbicide atrazine was detected in all runoff samples. All of the most frequently detected pesticides (atrazine, trifluralin, simazine, pendimethalin, and diuron) exhibited higher concentrations during the pre-harvest period (March? May) than during the post-harvest period (August? October). During 1996?98, an average of 0.37 pound per acre per year of atrazine was applied to the lower study area. During the same period, 0.0027 pound per acre per year of atrazine and its breakdown product deethylatrazine exited the lower study area in runoff (about 0.7 percent of the total atrazine applied to the cropland). During 1997, when heavy rainfall occurred during the months of April and May, the atrazine plus deethylatrazine exiting the lower study area was 1.8 percent of the applied atrazine. The 1996?98 average sediment yield was 610 pounds per acre per year. Sediment loads from the study area are associated with large storm events. Of the 45,300 tons of sediment transported from the study area during 1996?98 about 87 percent was transported during the three largest runoff events (April 1997, October 1997, and October 1998). Runoff-weighted average concentrations were computed for selected nutrients and pesticides. The 1996?98 runoff-weighted concentrations for total nitrogen and total phosphorus were 1.3 and 0.50 milligrams per liter, respectively. The 1996?98 runoff-weighted concentration for atrazine plus deethylatrazine was 2.7 micrograms per liter.

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

2000-01-01

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

NASA Astrophysics Data System (ADS)

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago; Giangrande, Scott; Silva Dias, Maria A. F.; Cecchini, Micael A.; Albrecht, Rachel; Andreae, Meinrat O.; Araujo, Wagner F.; Artaxo, Paulo; Borrmann, Stephan; Braga, Ramon; Burleyson, Casey; Eichholz, Cristiano W.; Fan, Jiwen; Feng, Zhe; Fisch, Gilberto F.; Jensen, Michael P.; Martin, Scot T.; Pöschl, Ulrich; Pöhlker, Christopher; Pöhlker, Mira L.; Ribaud, Jean-François; Rosenfeld, Daniel; Saraiva, Jaci M. B.; Schumacher, Courtney; Thalman, Ryan; Walter, David; Wendisch, Manfred

2018-05-01

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. This study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weighted mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.

Breeding period in the mangrove crab Goniopsis cruentata (Decapoda: Grapsidae) in Northeast Brazil.

PubMed

de Lira, José Jonathas Pereira Rodrigues; Calado, Tereza Cristina dos Santos; de Araújo, Marina de Sá Leitão Câmara

2013-03-01

The brachyuran crabs are iteroparous species which present a high diversification of reproduction patterns, which may have evolved as a species-specific response to environmental conditions. Tropical species commonly present a year-round reproduction due to stable environment conditions. Goniopsis cruentata is a crab species widely distributed along the Western Atlantic, inhabiting practically every microhabitat in the mangrove ecosystem. The aim of the present study is to determine the breeding period of the crab Goniopsis cruentata in Northeastern Brazil and also to evaluate the influence of water salinity, rainfall and air and water temperature on it. A total of 71 ovigerous females, captured from August-2007 to July-2008, were used to assess the breeding period of this species. It was analyzed by the monthly proportion of ovigerous females. A correlation was applied to verify the influence of the abiotic factors on the breeding period. The present population bred seasonal-continuously with peaks in the dry period, which was not associated with monthly variations of salinity, rainfall and air and water temperatures. Therefore, according to statistical analyses, our hypothesis was refuted. However, breeding was intensified in the dry period, when salinity and temperatures were higher and rainfall was lower. We conclude that, even though breeding is not related to monthly variation of environmental factors, it occurs in periods of higher salinity and temperatures and lower rainfall.

On the association between pre-monsoon aerosol and all-India summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Patil, S. D.; Preethi, B.; Bansod, S. D.; Singh, H. N.; Revadekar, J. V.; Munot, A. A.

2013-09-01

Summer monsoon rainfall which gives 75-90% of the annual rainfall plays vital role in Indian economy as the food grain production in India is very much dependent on the summer monsoon rainfall. It has been suggested by recent studies that aerosol loading over the Indian region plays significant role in modulating the monsoon circulation and consequent rainfall distribution over the Indian sub-continent. Increased industrialization and the increasing deforestation over past few decades probably cause a gradual increase in the aerosol concentration. A significant negative relationship between pre-monsoon (March-May i.e. MAM) aerosol loading over BOB and IGP regions and the forthcoming monsoon rainfall have been observed from the thorough analysis of the fifteen years (1997-2011) monthly Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) and All-India Summer Monsoon Rainfall (AISMR) data. Composite analysis revealed that AI anomalies during pre-monsoon season are negative for excess year and positive for deficient monsoon years over the Indian subcontinent, with strong variation over Bay of Bengal (BOB) and Indo-Gangetic Plain (IGP) regions from the month of March onwards. The correlation coefficients between AISMR and pre-monsoon AI over BOB and IGP regions are found to be negative and significant at 5% level. The study clearly brings out that the pre-monsoon aerosol loading over the BOB and IGP regions has a significant correlational link with the forthcoming monsoon intensity; however a further study of the aerosol properties and their feedback to the cloud microphysical properties is asked for establishing their causal linkage.

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.

Temporal and spatial characteristics of annual and seasonal rainfall in Malawi

NASA Astrophysics Data System (ADS)

Ngongondo, Cosmo; Xu, Chong-Yu; Gottschalk, Lars; Tallaksen, Lena M.; Alemaw, Berhanu

2010-05-01

An understanding of the temporal and spatial characteristics of rainfall is central to water resources planning and management. However, such information is often limited in many developing countries like Malawi. In an effort to bridge the information gap, this study examined the temporal and spatial charecteristics of rainfall in Malawi. Rainfall readings from 42 stations across Malawi from 1960 to 2006 were analysed at monthly, annual and seasonal scales. The Malawian rainfall season lasts from November to April. The data were firstly subjected to quality checks through the cumulative deviations test and the Standard Normal Homogeinity Test (SNHT). Monthly distribution in a typical year, called heterogeneity, was investigated using the Precipitation Concentration Index (PCI). Further, normalized precipitation anomaly series of annual rainfall series (AR) and the PCI (APCI) were used to test for interannual rainfall variability. Spatial variability was characterised by fitting the Spatial Correlation function (SCF). The nonparametric Mann-Kendall statistic was used to investigate the temporal trends of the various rainfall variables. The results showed that 40 of the stations passed both data quality tests. For the two stations that failed, the data were adjusted using nearby stations. Annual and seasonal rainfall were found to be characterised by high spatial variation. The country mean annual rainfall was 1095 mm with mean interannual variability of 26%. The highland areas to the north and southeast of the country exhibited the highest rainfall and lowest interannual variability. Lowest rainfall coupled with high interannual variability was found in the Lower Shire basin, in the southern part of Malawi. This simillarity is the pattern of annual and seasonal rainfall should be expected because all stations had over 90% of their observed annual rainfall in the six month period between November and April. Monthly rainfall was found to be highly variable both temporally and spatially. None of the stations have stable monthly rainfall regimes (mean PCI of less than 10). Stations with the highest mean rainfall were found to have a lower interannual variability. The rainfall stations showed low spatial correlations for annual, monthly as well as seasonal timescales indicating that the data may not be suitable for spatial interpolation. However, some structure (i.e. lower correlation with distance) could be observed when aggregating the data at 50 mile intervals. The annual and seasonal rainfall series were dominated by negative trends. The spatial distribution of the trends can be described as heterogeneous, although most of the stations in the southern region have negative trends. At the monthly timescale, 37 of the stations show a negative trend with four of the stations, all in the south, showing significant negative trends. On the other hand, only 5 stations show positive trends with only one significant trend in the south. Keywords: Malawi, rainfall trends, spatial variation

Spatial and Temporal Variation of Meteorological Drought in the Parambikulam-Aliyar Basin, Tamil Nadu

NASA Astrophysics Data System (ADS)

Manikandan, M.; Tamilmani, D.

2015-09-01

The present study aims to investigate the spatial and temporal variation of meteorological drought in the Parambikulam-Aliyar basin, Tamil Nadu using the Standardized Precipitation Index (SPI) as an indicator of drought severity. The basin was divided into 97 grid-cells of 5 × 5 km with each grid correspondence to approximately 1.03 % of total area. Monthly rainfall data for the period of 40 years (1972-2011) from 28 rain gauge stations in the basin was spatially interpolated and gridded monthly rainfall was created. Regional representative of SPI values calculated from mean areal rainfall were used to analyse the temporal variation of drought at multiple time scales. Spatial variation of drought was analysed based on highest drought severity derived from the monthly gridded SPI values. Frequency analyse was applied to assess the recurrence pattern of drought severity. The temporal analysis of SPI indicated that moderate, severe and extreme droughts are common in the basin and spatial analysis of drought severity identified the areas most frequently affected by drought. The results of this study can be used for developing drought preparedness plan and formulating mitigation strategies for sustainable water resource management within the basin.

Evaluation of the impacts of the Madden-Julian Oscillation on rainfall and hurricanes in Central and South America and the Atlantic Ocean using ICI-RAFT

NASA Astrophysics Data System (ADS)

Giovannettone, J. P.

2013-12-01

Based on the method of Regional Frequency Analysis (RFA) and L-moments (Hosking & Wallis, 1997), a tool was developed to estimate the frequency/intensity of a rainfall event of a particular duration using ground-based rainfall observations. Some of the code used to develop this tool was taken from the FORTRAN code provided by Hosking & Wallis and rewritten in Visual Basic 2010. This tool was developed at the International Center for Integrated Water Resources Management (ICIWaRM) and is referred to as the ICIWaRM Regional Analysis of Frequency Tool (ICI-RAFT) (Giovannettone & Wright, 2012). In order to study the effectiveness of ICI-RAFT, three case studies were selected for the analysis. The studies take place in selected regions within Argentina, Nicaragua, and Venezuela. Rainfall data were provided at locations throughout each country; total rainfall for specific periods were computed and analyzed with respect to several global climate indices using lag times ranging from 1 to 6 months. Each analysis attempts to identify a global climate index capable of predicting above or below average rainfall several months in advance, qualitatively and using an equation that is developed. The index that had the greatest impact was the MJO (Madden-Julian Oscillation), which is the focus of the current study. The MJO is considered the largest element of intra-seasonal (30 - 90 days) variability in the tropical atmosphere and, unlike other indices, is characterized by the eastward propagation of large areas of convective anomalies near the equator, propagating from the Indian Ocean east into the Pacific Ocean. The anomalies are monitored globally using ten different indices located on lines of longitude near the equator, with seven in the eastern hemisphere and three in the western hemisphere. It has been found in previous studies that the MJO is linked to summer rainfall in Southeast China (Zhang et al., 2009) and southern Africa (Pohl et al., 2007) and to rainfall patterns in Australia (Wheeler et al., 2009). The current study found that similar strong relationships between MJO activity over Africa and the western Indian Ocean and rainfall totals in central Argentina, Nicaragua, and northwestern Venezuela. For example, in Nicaragua, the 20-year event almost doubles depending on the phase of the MJO. A fourth case study attempts to develop a relationship between the annual number of hurricanes in the Atlantic Ocean and Caribbean during the hurricane season (July - October) and the average value of the Madden-Julian Oscillation over Africa during a period 3 - 4 months prior to the hurricane season. Similar work has been performed in the northern Atlantic by Villarini et al. (2010), except the authors focused on other indices, including tropical mean sea-surface temperatures (SST's), the North Atlantic Oscillation (NAO), and the Southern Oscillation Index (SOI). Even though the NAO and SOI show some correlation with hurricane activity, the results of the current study show that there is a stronger link between the MJO prior to hurricane season and the total number of hurricanes that form. The greatest correlation again comes from MJO activity over Africa.

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Monthly Rainfall Erosivity Assessment for Switzerland

NASA Astrophysics Data System (ADS)

Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

Water erosion is crucially controlled by rainfall erosivity, which is quantified out of the kinetic energy of raindrop impact and associated surface runoff. Rainfall erosivity is often expressed as the R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). Just like precipitation, the rainfall erosivity of Switzerland has a characteristic seasonal dynamic throughout the year. This inter-annual variability is to be assessed by a monthly and seasonal modelling approach. We used a network of 86 precipitation gauging stations with a 10-minute temporal resolution to calculate long-term average monthly R-factors. Stepwise regression and Monte Carlo Cross Validation (MCCV) was used to select spatial covariates to explain the spatial pattern of R-factor for each month across Switzerland. The regionalized monthly R-factor is mapped by its individual regression equation and the ordinary kriging interpolation of its residuals (Regression-Kriging). As covariates, a variety of precipitation indicator data has been included like snow height, a combination of hourly gauging measurements and radar observations (CombiPrecip), mean monthly alpine precipitation (EURO4M-APGD) and monthly precipitation sums (Rhires). Topographic parameters were also significant explanatory variables for single months. The comparison of all 12 monthly rainfall erosivity maps showed seasonality with highest rainfall erosivity in summer (June, July, and August) and lowest rainfall erosivity in winter months. Besides the inter-annual temporal regime, a seasonal spatial variability was detectable. Spatial maps of monthly rainfall erosivity are presented for the first time for Switzerland. The assessment of the spatial and temporal dynamic behaviour of the R-factor is valuable for the identification of more susceptible seasons and regions as well as for the application of selective erosion control measures. A combination with monthly vegetation cover (C-factor) maps would enable the assessment of seasonal dynamics of erosion processes in Switzerland.

Interception loss, throughfall and stemflow in a maritime pine stand. II. An application of Gash's analytical model of interception

NASA Astrophysics Data System (ADS)

Loustau, D.; Berbigier, P.; Granier, A.

1992-10-01

Interception, throughfall and stemflow were determined in an 18-year-old maritime pine stand for a period of 30 months. This involved 71 rainfall events, each corresponding either to a single storm or to several storms. Gash's analytical model of interception was used to estimate the sensitivity of interception to canopy structure and climatic parameters. The seasonal cumulative interception loss corresponded to 12.6-21.0% of the amount of rainfall, whereas throughfall and stemflow accounted for 77-83% and 1-6%, respectively. On a seasonal basis, simulated data fitted the measured data satisfactorily ( r2 = 0.75). The rainfall partitioning between interception, throughfall and stemflow was shown to be sensitive to (1) the rainfall regime, i.e. the relative importance of light storms to total rainfall, (2) the climatic parameters, rainfall rate and average evaporation rate during storms, and (3) the canopy structure parameters of the model. The low interception rate of the canopy was attributed primarily to the low leaf area index of the stand.

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

PubMed

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

2011-02-01

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

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.

Month-to-month variability of Indian summer monsoon rainfall in 2016: role of the Indo-Pacific climatic conditions

NASA Astrophysics Data System (ADS)

Chowdary, Jasti S.; Srinivas, G.; Du, Yan; Gopinath, K.; Gnanaseelan, C.; Parekh, Anant; Singh, Prem

2018-03-01

Indian summer monsoon (ISM) rainfall during 2016 exhibited a prominent month-to-month fluctuations over India, with below normal rainfall in June and August and above normal rainfall in July. The factors determining the month-to-month fluctuations in ISM rainfall during 2016 are investigated with main focus on the Indo-Pacific climatic anomalies. Warm sea surface temperature (SST) anomalies associated with super El Niño 2015 disappeared by early summer 2016 over the central and eastern Pacific. On the other hand, negative Indian Ocean dipole (IOD) like SST anomaly pattern over the equatorial Indian Ocean and anomalous anticyclonic circulation over the western North Pacific (WNP) are reported in summer 2016 concurrently with decaying El Niño/developing La Niña phase. Observations revealed that the low rainfall over central north India in June is due to moisture divergence caused by the westward extension of ridge corresponding to WNP anticyclone and subsidence induced by local Hadley cell partly related to negative IOD. Low level convergence of southeasterly wind from Bay of Bengal associated with weak WNP anticyclone and northwesterly wind corresponding to anticyclonic circulation over the northwest India remarkably contributed to positive rainfall in July over most of the Indian subcontinent. While reduced rainfall over the Indian subcontinent in August 2016 is associated with the anomalous moisture transport from ISM region to WNP region, in contrast to July, due to local cyclogenesis corroborated by number of tropical cyclones in the WNP. In addition to this, subsidence related to strong convection supported by cyclonic circulation over the WNP also resulted in low rainfall over the ISM region. Coupled General Circulation model sensitivity experiments confirmed that strong convective activities associated with cyclonic circulation over the WNP is primarily responsible for the observed negative ISM rainfall anomalies in August 2016. It is noted that the Indo-Western Pacific circulation anomalies in August 2016 are well predicted when the coupled model is initiated with initial conditions from end of July and beginning of August compared to May. This analysis suggests the importance of the WNP circulation in forcing strong sub-seasonal/month to month rainfall variations over India.

Application of satellite precipitation data to analyse and model arbovirus activity in the tropics

PubMed Central

2011-01-01

Background Murray Valley encephalitis virus (MVEV) is a mosquito-borne Flavivirus (Flaviviridae: Flavivirus) which is closely related to Japanese encephalitis virus, West Nile virus and St. Louis encephalitis virus. MVEV is enzootic in northern Australia and Papua New Guinea and epizootic in other parts of Australia. Activity of MVEV in Western Australia (WA) is monitored by detection of seroconversions in flocks of sentinel chickens at selected sample sites throughout WA. Rainfall is a major environmental factor influencing MVEV activity. Utilising data on rainfall and seroconversions, statistical relationships between MVEV occurrence and rainfall can be determined. These relationships can be used to predict MVEV activity which, in turn, provides the general public with important information about disease transmission risk. Since ground measurements of rainfall are sparse and irregularly distributed, especially in north WA where rainfall is spatially and temporally highly variable, alternative data sources such as remote sensing (RS) data represent an attractive alternative to ground measurements. However, a number of competing alternatives are available and careful evaluation is essential to determine the most appropriate product for a given problem. Results The Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 product was chosen from a range of RS rainfall products to develop rainfall-based predictor variables and build logistic regression models for the prediction of MVEV activity in the Kimberley and Pilbara regions of WA. Two models employing monthly time-lagged rainfall variables showed the strongest discriminatory ability of 0.74 and 0.80 as measured by the Receiver Operating Characteristics area under the curve (ROC AUC). Conclusions TMPA data provide a state-of-the-art data source for the development of rainfall-based predictive models for Flavivirus activity in tropical WA. Compared to ground measurements these data have the advantage of being collected spatially regularly, irrespective of remoteness. We found that increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Pilbara at a time-lag of two months. Increases in monthly rainfall and monthly number of days above average rainfall increased the risk of MVEV activity in the Kimberley at a lag of three months. PMID:21255449

Rainfall and water-level data for a wetland area near Millington, Shelby County, Tennessee, October 1995 through September 1996

USGS Publications Warehouse

Knight, R.R.

1997-01-01

Rainfall amounts and water levels were collected at a wetland area near Millington, Shelby County, Tennessee, to assist the Tennessee Department of Transportation with a program of wetland restoration. The site is located along a channelized reach of Big Creek Drainage Canal, east of State Route 240, and near the southern boundary of Naval Support Activity Memphis. Rainfall amounts and water levels for the site were recorded from October 1, 1995 to September 30, 1996. Total rainfall for this period was 47.58 inches. In general, water levels at the wetland were above or near the ground surface during the 6-month period from the first of January through the end of June 1996. For the remainder of the year, water levels generally subsided to several feet below land surface. However, some locations within the wetland were wet or highly saturated year round.

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

DOE PAGES

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago; ...

2018-05-07

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. Here, this study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weightedmore » mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.« less

Overview: Precipitation characteristics and sensitivities to environmental conditions during GoAmazon2014/5 and ACRIDICON-CHUVA

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

Machado, Luiz A. T.; Calheiros, Alan J. P.; Biscaro, Thiago

This study provides an overview of precipitation processes and their sensitivities to environmental conditions in the Central Amazon Basin near Manaus during the GoAmazon2014/5 and ACRIDICON-CHUVA experiments. Here, this study takes advantage of the numerous measurement platforms and instrument systems operating during both campaigns to sample cloud structure and environmental conditions during 2014 and 2015; the rainfall variability among seasons, aerosol loading, land surface type, and topography has been carefully characterized using these data. Differences between the wet and dry seasons were examined from a variety of perspectives. The rainfall rates distribution, total amount of rainfall, and raindrop size distribution (the mass-weightedmore » mean diameter) were quantified over both seasons. The dry season generally exhibited higher rainfall rates than the wet season and included more intense rainfall periods. However, the cumulative rainfall during the wet season was 4 times greater than that during the total dry season rainfall, as shown in the total rainfall accumulation data. The typical size and life cycle of Amazon cloud clusters (observed by satellite) and rain cells (observed by radar) were examined, as were differences in these systems between the seasons. Moreover, monthly mean thermodynamic and dynamic variables were analysed using radiosondes to elucidate the differences in rainfall characteristics during the wet and dry seasons. The sensitivity of rainfall to atmospheric aerosol loading was discussed with regard to mass-weighted mean diameter and rain rate. This topic was evaluated only during the wet season due to the insignificant statistics of rainfall events for different aerosol loading ranges and the low frequency of precipitation events during the dry season. The impacts of aerosols on cloud droplet diameter varied based on droplet size. For the wet season, we observed no dependence between land surface type and rain rate. However, during the dry season, urban areas exhibited the largest rainfall rate tail distribution, and deforested regions exhibited the lowest mean rainfall rate. Airplane measurements were taken to characterize and contrast cloud microphysical properties and processes over forested and deforested regions. Vertical motion was not correlated with cloud droplet sizes, but cloud droplet concentration correlated linearly with vertical motion. Clouds over forested areas contained larger droplets than clouds over pastures at all altitudes. Finally, the connections between topography and rain rate were evaluated, with higher rainfall rates identified at higher elevations during the dry season.« less

Rainfall erosivity in Europe.

PubMed

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale; Meusburger, Katrin; Klik, Andreas; Rousseva, Svetla; Tadić, Melita Perčec; Michaelides, Silas; Hrabalíková, Michaela; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Beguería, Santiago; Alewell, Christine

2015-04-01

Rainfall is one the main drivers of soil erosion. 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 USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

A Two-year Record of Daily Rainfall Isotopes from Fiji: Implications for Reconstructing Precipitation from Speleothem δ18O

NASA Astrophysics Data System (ADS)

Brett, M.; Mattey, D.; Stephens, M.

2015-12-01

Oxygen isotopes in speleothem provide opportunities to construct precisely dated records of palaeoclimate variability, underpinned by an understanding of both the regional climate and local controls on isotopes in rainfall and groundwater. For tropical islands, a potential means to reconstruct past rainfall variability is to exploit the generally high correlation between rainfall amount and δ18O: the 'amount effect'. The GNIP program provides δ18O data at monthly resolution for several tropical Pacific islands but there are few data for precipitation isotopes at daily resolution, for investigating the amount effect over different timescales in a tropical maritime setting. Timescales are important since meteoric water feeding a speleothem has undergone storage and mixing in the aquifer system and understanding how the isotope amount effect is preserved in aquifer recharge has fundamental implications on the interpretation of speleothem δ18O in terms of palaeo-precipitation. The islands of Fiji host speleothem caves. Seasonal precipitation is related to the movement of the South Pacific Convergence Zone, and interannual variations in rainfall are coupled to ENSO behaviour. Individual rainfall events are stratiform or convective, with proximal moisture sources. We have daily resolution isotope data for rainfall collected at the University of the South Pacific in Suva, covering every rain event in 2012 and 2013. δ18O varies between -18‰ and +3‰ with the annual weighted averages at -7.6‰ and -6.8‰ respectively, while total recorded rainfall amount is similar in both years. We shall present analysis of our data compared with GNIP, meteorological data and back trajectory analyses to demonstrate the nature of the relationship between rainfall amount and isotopic signatures over this short timescale. Comparison with GNIP data for 2012-13 will shed light on the origin of the amount effect at monthly and seasonal timescales in convective, maritime, tropical climates.

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.

Evaluation and prediction of anomalous El Niño generated rainfalls in Peruvian and Ecuadorian coastal zone

NASA Astrophysics Data System (ADS)

Cadier, E.; Rossel, F.; Pouyaud, B.; Raymond, M.

2003-04-01

Coastal regions of Southern Ecuador and Northern Peru rainfalls are well known for their sensitivity to the El Niño/Southern Oscillation (ENSO) phenomenon. New monthly rainfall index series were set up from a network of 200 rainfall stations in the Ecuadorian and Peruvian coastal region. Throughout the study, rainfall was modelled keeping a distinction between a "dependent" data set used as a training period and an "independent" portion of the record reserved for validation. Multiple regression models were proposed to predict monthly rainfall in the Guayaquil and in northern coastal Peru, using as predictors, sea surface temperature, precipitation, meridional and zonal wind in the eastern equatorial Pacific. Then, the resulting equations were used to predict rainfall anomalies in the independent data set. In the Guayaquil zone, there is considerable predictable expertise for the rainy months of the year, the best predictability being assessed from March to May. The multiple linear correlations explain 60 to 82% of the monthly-precipitation variance. Northern coastal Ecuadorian region's preseason rainfall is the most powerful predictor for the rainy season peak in Guayaquil, while the eastern equatorial Pacific sea surface temperature is the most powerful predictor for the end of rainy season. KEY WORDS: El Niño, Rainfall Prediction, Ecuador.

Tropical Rainfall Variability on Interannual-to-Interdecadal/Longer-Time Scales Derived from the GPCP Monthly Product

NASA Technical Reports Server (NTRS)

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

2006-01-01

Global and large regional rainfall variations and possible long-term changes are examined using the 26-year (1979-2004) GPCP monthly dataset (Adler et al., 2003). Our emphasis is to discriminate among variations due to ENSO, volcanic events, and possible long-term climate changes in the tropics. Although the global linear change of precipitation in the data set is near zero during the time period, an increase in tropical rainfall is noted, with a weaker decrease over northern hemisphere middle latitudes. Focusing on the tropics (25degS-25degN), the data set indicates an upward trend (0.06 mm/day/decade) and a downward trend (-0.02 mm/day/decade) over tropical ocean and land, respectively. This corresponds to an about 4.9% increase (ocean) and 1.6% decrease (land) during the entire 26-year time period. Techniques are applied to isolate and quantify variations due to ENSO and two major volcanic eruptions (El Chichon, March 1982; Pinatubo, June 1991) in order to examine longer time-scale changes. The ENSO events generally do not impact the tropical total rainfall, but, of course, induce significant anomalies with opposite signs over tropical land and ocean. The impact of the two volcanic eruptions is estimated to be about a 5% reduction in tropical rainfall over both land and ocean. A modified data set (with ENSO and volcano effects removed) retains the same approximate linear change slopes, but with reduced variance, thereby increasing the confidence levels associated with the long-term rainfall changes in the tropics 2

Asian Summer Monsoon Rainfall associated with ENSO and its Predictability

NASA Astrophysics Data System (ADS)

Shin, C. S.; Huang, B.; Zhu, J.; Marx, L.; Kinter, J. L.; Shukla, J.

2015-12-01

The leading modes of the Asian summer monsoon (ASM) rainfall variability and their seasonal predictability are investigated using the CFSv2 hindcasts initialized from multiple ocean analyses over the period of 1979-2008 and observation-based analyses. It is shown that the two leading empirical orthogonal function (EOF) modes of the observed ASM rainfall anomalies, which together account for about 34% of total variance, largely correspond to the ASM responses to the ENSO influences during the summers of the developing and decaying years of a Pacific anomalous event, respectively. These two ASM modes are then designated as the contemporary and delayed ENSO responses, respectively. It is demonstrated that the CFSv2 is capable of predicting these two dominant ASM modes up to the lead of 5 months. More importantly, the predictability of the ASM rainfall are much higher with respect to the delayed ENSO mode than the contemporary one, with the predicted principal component time series of the former maintaining high correlation skill and small ensemble spread with all lead months whereas the latter shows significant degradation in both measures with lead-time. A composite analysis for the ASM rainfall anomalies of all warm ENSO events in this period substantiates the finding that the ASM is more predictable following an ENSO event. The enhanced predictability mainly comes from the evolution of the warm SST anomalies over the Indian Ocean in the spring of the ENSO maturing phases and the persistence of the anomalous high sea surface pressure over the western Pacific in the subsequent summer, which the hindcasts are able to capture reasonably well. The results also show that the ensemble initialization with multiple ocean analyses improves the CFSv2's prediction skill of both ENSO and ASM rainfall. In fact, the skills of the ensemble mean hindcasts initialized from the four different ocean analyses are always equivalent to the best ones initialized from any individual ocean analysis, although the best performer varies with lead-time and starting calendar month.

Monthly monsoon rainfall forecasting using artificial neural networks

NASA Astrophysics Data System (ADS)

Ganti, Ravikumar

2014-10-01

Indian agriculture sector heavily depends on monsoon rainfall for successful harvesting. In the past, prediction of rainfall was mainly performed using regression models, which provide reasonable accuracy in the modelling and forecasting of complex physical systems. Recently, Artificial Neural Networks (ANNs) have been proposed as efficient tools for modelling and forecasting. A feed-forward multi-layer perceptron type of ANN architecture trained using the popular back-propagation algorithm was employed in this study. Other techniques investigated for modeling monthly monsoon rainfall include linear and non-linear regression models for comparison purposes. The data employed in this study include monthly rainfall and monthly average of the daily maximum temperature in the North Central region in India. Specifically, four regression models and two ANN model's were developed. The performance of various models was evaluated using a wide variety of standard statistical parameters and scatter plots. The results obtained in this study for forecasting monsoon rainfalls using ANNs have been encouraging. India's economy and agricultural activities can be effectively managed with the help of the availability of the accurate monsoon rainfall forecasts.

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.

On Utilization of NEXRAD Scan Strategy Information to Infer Discrepancies Associated With Radar and Rain Gauge Surface Volumetric Rainfall Accumulations

NASA Technical Reports Server (NTRS)

Roy, Biswadev; Datta, Saswati; Jones, W. Linwood; Kasparis, Takis; Einaudi, Franco (Technical Monitor)

2000-01-01

To evaluate the Tropical Rainfall Measuring Mission (TRMM) monthly Ground Validation (GV) rain map, 42 quality controlled tipping bucket rain gauge data (1 minute interpolated rain rates) were utilized. We have compared the gauge data to the surface volumetric rainfall accumulation of NEXRAD reflectivity field, (converting to rain rates using a 0.5 dB resolution smooth Z-R table). The comparison was carried out from data collected at Melbourne, Florida during the month of July 98. GV operational level 3 (L3 monthly) accumulation algorithm was used to obtain surface volumetric accumulations for the radar. The gauge records were accumulated using the 1 minute interpolated rain rates while the radar Volume Scan (VOS) intervals remain less than or equal to 75 minutes. The correlation coefficient for the radar and gauge totals for the monthly time-scale remain at 0.93, however, a large difference was noted between the gauge and radar derived rain accumulation when the radar data interval is either 9 minute, or 10 minute. This difference in radar and gauge accumulation is being explained in terms of the radar scan strategy information. The discrepancy in terms of the Volume Coverage Pattern (VCP) of the NEXRAD is being reported where VCP mode is ascertained using the radar tilt angle information. Hourly radar and gauge accumulations have been computed using the present operational L3 method supplemented with a threshold period of +/- 5 minutes (based on a sensitivity analysis). These radar and gauge accumulations are subsequently improved using a radar hourly scan weighting factor (taking ratio of the radar scan frequency within a time bin to the 7436 total radar scans for the month). This GV procedure is further being improved by introducing a spatial smoothing method to yield reasonable bulk radar to gauge ratio for the hourly and daily scales.

Potential impact of climate variability on respiratory diseases in infant and children in Semarang

NASA Astrophysics Data System (ADS)

Budiyono; Rismawati; Jati, S. P.; Ginandjar, P.

2017-02-01

Temperature, humidity, and rainfall may influence respiratory disease, including acute respiratory infection (ARI) and pneumonia. In Semarang, the temperature and humidity has increased 0.1°C and 1.6% respectively during 2002-2011. ARI and pneumonia in children under 5 years had increased during 2012-2014. This study aimed to analyze the relationship of climate variability and ARI and pneumonia incidence. It was an ecological study. Subject consisted of patients visited primary health care of Bandarharjo from 2011 to 2015. Pneumonia was related to infants (<1-year-old) and children (1-4 years old), while ARI was related to children (≥5 years old). Data of climate was obtained from Agency for Meteorology, Climatology and Geophysics (BMKG) Semarang. Pearson correlation (α=0.05) was used to analyse the correlation of the 60 samples. Mean of temperature was 27.96° C, relative humidity was 74.73%, and rainfall was 179.98 mm/month. The total of ARI was 38523 cases and pneumonia was 1558 cases. Temperature, humidity, and rainfall had no correlation to pneumonia. Humidity had a significant correlation to ARI on female children and total ARI (r=0.3 and r=0.26; p-value=0.02 and 0.04 respectively). Rainfall and temperature had no correlation to total ARI. This study concluded humidity has potential impact to ARI.

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

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.

Status of ground-water resources at U.S. Navy Support Facility, Diego Garcia; summary of hydrologic and climatic data, January 1992 through September 1994

USGS Publications Warehouse

Torikai, J.D.

1995-01-01

This report contains hydrologic and climatic data that describe the status of ground-water resources at U.S. Navy Support Facility, Diego Garcia. Data are presented from January 1992 through September 1994. This report concentrates on data from July through September 1994, and references historic data from 1992 through June 1994. Total rainfall for the first nine months of 1994 was about 77 inches which is 72 percent of the mean annual rainfall of 106 inches. In comparison, total rainfall for the first nine months of 1992 and 1993 was 67 inches and 69 inches, respectively. Annual rainfall totals in 1992 and 1993 were 93 inches and 95 inches, respectively. Ground-water withdrawal during July through September 1994 has averaged 919,400 gallons per day, while annual withdrawals in 1992 and 1993 averaged 935,900 gallons per day and 953,800 gallons per day, respectively. At the end of September 1994, the chloride concentration of the composite water supply was 56 milligrams per liter, well below the 250 milligrams per liter secondary drinking-water standard established by the U.S. Environmental Protection Agency. Chloride concentrations of the composite water supply from July through September 1994 ranged between 51 and 78 milligrams per liter. Chloride concentration of ground water in monitoring wells at Cantonment and Air Operations increased in July and August, but have leveled off or decreased in September. There has been a general trend of increasing chloride concentrations in the deeper monitoring wells since the 1992 dry season, which began in March 1992. A fuel leak at Air Operations caused the shutdown of ten wells in May 1991. Four of the wells resumed pumping for water-supply purposes in April 1992. The remaining six wells are being used to hydraulically contain and divert fuel migration by recirculating 150,000 gallons of water each day.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Downscaling of Global Climate Change Estimates to Regional Scales: An Application to Iberian Rainfall in Wintertime.

NASA Astrophysics Data System (ADS)

von Storch, Hans; Zorita, Eduardo; Cubasch, Ulrich

1993-06-01

A statistical strategy to deduct regional-scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique.The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It is shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM).The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous `2 C02' doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of 1 mm/month, with maximum values of 4 mm/month in the northwest of the peninsula. In contrast, for the four GCM grid points representing the Iberian Peninsula, the change is 10 mm/month, with a minimum of 19 mm/month in the southwest. In the second experiment, with the IPCC scenario A ("business as usual") increase Of C02, the statistical-model results partially differ from the directly simulated rainfall changes: in the experimental range of 100 years, the area-averaged rainfall decreases by 7 mm/month (statistical model), and by 9 mm/month (GCM); at the same time the amplitude of the interdecadal variability is quite different.

Skilful rainfall forecasts from artificial neural networks with long duration series and single-month optimization

NASA Astrophysics Data System (ADS)

Abbot, John; Marohasy, Jennifer

2017-11-01

General circulation models, which forecast by first modelling actual conditions in the atmosphere and ocean, are used extensively for monthly rainfall forecasting. We show how more skilful monthly and seasonal rainfall forecasts can be achieved through the mining of historical climate data using artificial neural networks (ANNs). This technique is demonstrated for two agricultural regions of Australia: the wheat belt of Western Australia and the sugar growing region of coastal Queensland. The most skilful monthly rainfall forecasts measured in terms of Ideal Point Error (IPE), and a score relative to climatology, are consistently achieved through the use of ANNs optimized for each month individually, and also by choosing to input longer historical series of climate indices. Using the longer series restricts the number of climate indices that can be used.

Rainfall and water-level data for a wetland area near Millington, Shelby County, Tennessee, October 1996 through September 1997

USGS Publications Warehouse

Knight, R.R.

1998-01-01

Rainfall amounts and water levels at a degraded wetland area near Millington, Shelby County, Tennessee, were collected to assist the Tennessee Department of Transportation with a program designed to restore the wetland to a more natural condition. The site is located along a channelized reach of Big Creek Drainage Canal, east of State Route 240, and near the southeastern boundary of the Naval Support Activity Memphis, Millington. Rainfall amounts were recorded at 5-minute intervals using a tipping-bucket rain gage from October 1, 1996 through September 30, 1997. Total rainfall for this period was 70.16 inches. In general, water levels at the wetland were above or near the ground surface during the 6-month period from the first of January through June 1997. For the remainder of the year, water levels generally subsided to several feet below land surface. However, some locations within the wetland were wet or highly saturated year round.

Distributional changes in rainfall and river flow in Sarawak, Malaysia

NASA Astrophysics Data System (ADS)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

Climate change may not change the rainfall mean, but the variability and extremes. Therefore, it is required to explore the possible distributional changes of rainfall characteristics over time. The objective of present study is to assess the distributional changes in annual and northeast monsoon rainfall (November-January) and river flow in Sarawak where small changes in rainfall or river flow variability/distribution may have severe implications on ecology and agriculture. A quantile regression-based approach was used to assess the changes of scale and location of empirical probability density function over the period 1980-2014 at 31 observational stations. The results indicate that diverse variation patterns exist at all stations for annual rainfall but mainly increasing quantile trend at the lowers, and higher quantiles for the month of January and December. The significant increase in annual rainfall is found mostly in the north and central-coastal region and monsoon month rainfalls in the interior and north of Sarawak. Trends in river flow data show that changes in rainfall distribution have affected higher quantiles of river flow in monsoon months at some of the basins and therefore more flooding. The study reveals that quantile trend can provide more information of rainfall change which may be useful for climate change mitigation and adaptation planning.

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.

Overland flow, sediment output and nutrient loss from certain forested sites in the central Himalaya, India

NASA Astrophysics Data System (ADS)

Pathak, P. C.; Pandey, A. N.; Singh, J. S.

1984-03-01

Overland flow, sediment output and input and output of precipitation nutrients were evaluated on six forested sites in the central Himalaya during the 1981 and 1982 monsoon seasons. Overland flow was significantly different across the forests and the months of the rainy season. It was positively related with rainfall quantity and intensity, and was negatively related with tree canopy cover and with ground vegetation cover. Average overland flow was only 0.66% of the total incident rainfall, indicating that these sites are subsurface-flow systems. Sediment output was positively related to overland flow. Rainfall added a significant amount of nutrients to the forests. This extra-system input was greater than loss through overland flow + sediment output. The loss of nutrients from the forested sites was in the order: Mg > C > Ca > K = N = P.

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)

Year-round breeding equatorial Larks from three climatically-distinct populations do not use rainfall, temperature or invertebrate biomass to time reproduction

PubMed Central

Ndithia, Henry K.; Matson, Kevin D.; Versteegh, Maaike A.; Muchai, Muchane; Tieleman, B. Irene

2017-01-01

Timing of reproduction in birds is important for reproductive success and is known to depend on environmental cues such as day length and food availability. However, in equatorial regions, where day length is nearly constant, other factors such as rainfall and temperature are thought to determine timing of reproduction. Rainfall can vary at small spatial and temporal scales, providing a highly fluctuating and unpredictable environmental cue. In this study we investigated the extent to which spatio-temporal variation in environmental conditions can explain the timing of breeding of Red-capped Lark, Calandrella cinerea, a species that is capable of reproducing during every month of the year in our equatorial east African study locations. For 39 months in three climatically-distinct locations, we monitored nesting activities, sampled ground and flying invertebrates, and quantified rainfall, maximum (Tmax) and minimum (Tmin) temperatures. Among locations we found that lower rainfall and higher temperatures did not coincide with lower invertebrate biomasses and decreased nesting activities, as predicted. Within locations, we found that rainfall, Tmax, and Tmin varied unpredictably among months and years. The only consistent annually recurring observations in all locations were that January and February had low rainfall, high Tmax, and low Tmin. Ground and flying invertebrate biomasses varied unpredictably among months and years, but invertebrates were captured in all months in all locations. Red-capped Larks bred in all calendar months overall but not in every month in every year in every location. Using model selection, we found no clear support for any relationship between the environmental variables and breeding in any of the three locations. Contrary to popular understanding, this study suggests that rainfall and invertebrate biomass as proxy for food do not influence breeding in equatorial Larks. Instead, we propose that factors such as nest predation, female protein reserves, and competition are more important in environments where weather and food meet minimum requirements for breeding during most of the year. PMID:28419105

Modelling Ecuador's rainfall distribution according to geographical characteristics.

NASA Astrophysics Data System (ADS)

Tobar, Vladimiro; Wyseure, Guido

2017-04-01

It is known that rainfall is affected by terrain characteristics and some studies had focussed on its distribution over complex terrain. Ecuador's temporal and spatial rainfall distribution is affected by its location on the ITCZ, the marine currents in the Pacific, the Amazon rainforest, and the Andes mountain range. Although all these factors are important, we think that the latter one may hold a key for modelling spatial and temporal distribution of rainfall. The study considered 30 years of monthly data from 319 rainfall stations having at least 10 years of data available. The relatively low density of stations and their location in accessible sites near to main roads or rivers, leave large and important areas ungauged, making it not appropriate to rely on traditional interpolation techniques to estimate regional rainfall for water balance. The aim of this research was to come up with a useful model for seasonal rainfall distribution in Ecuador based on geographical characteristics to allow its spatial generalization. The target for modelling was the seasonal rainfall, characterized by nine percentiles for each one of the 12 months of the year that results in 108 response variables, later on reduced to four principal components comprising 94% of the total variability. Predictor variables for the model were: geographic coordinates, elevation, main wind effects from the Amazon and Coast, Valley and Hill indexes, and average and maximum elevation above the selected rainfall station to the east and to the west, for each one of 18 directions (50-135°, by 5°) adding up to 79 predictors. A multiple linear regression model by the Elastic-net algorithm with cross-validation was applied for each one of the PC as response to select the most important ones from the 79 predictor variables. The Elastic-net algorithm deals well with collinearity problems, while allowing variable selection in a blended approach between the Ridge and Lasso regression. The model fitting produced explained variances of 59%, 81%, 49% and 17% for PC1, PC2, PC3 and PC4, respectively, backing up the hypothesis of good correlation between geographical characteristics and seasonal rainfall patterns (comprised in the four principal components). With the obtained coefficients from the regression, the 108 rainfall percentiles for each station were back estimated giving very good results when compared with the original ones, with an overall 60% explained variance.

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).

Hydrologic data for North Creek, Trinity River basin, Texas, 1975

USGS Publications Warehouse

Kidwell, C.C.

1977-01-01

This report contains the rainfall, runoff, and storage data collected during the 1975 water year for the 21.6-square-mile area above the stream-gaging station North Creek near Jacksboro, Texas. The weighted-mean rainfall in the study area during the water year was 39.01 inches, which is greater than the 18-year average of 30.21 inches for the period 1958-75. Monthly rainfall totals ranged from 1.04 inches in November to 7.94 inches in May. The mean discharge for 1975 at the stream-gaging station was 5.98 cfs, compared with the 14-year (1957-70) average of 5.75 cfs. The annual runoff from the basin above the stream-gaging station was 4,330 acre-feet or 3.76 inches. Three storms were selected for detailed computations for the 1975 water year. The storms occurred on Oct. 30-31, 1974, May 2, 1975 , and Aug. 26, 1975. Rainfall and discharge were computed on the basis of a refined time breakdown. Patterns of the storms are illustrated by hydrographs and mass curves. A summary of rainfall-runoff data is tabulated. There are five floodwater-retarding structures in the study area. These structures have a total capacity of 4,425 acre-feet below flood-spillway crests and regulate streamflow from 16.3 square miles, or 75 percent of the study area. A summary of the physical data at each of the floodwater-retarding structures is included. (Woodard-USGS)

Identifying a rainfall event threshold triggering herbicide leaching by preferential flow

NASA Astrophysics Data System (ADS)

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

2010-02-01

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

Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

NASA Astrophysics Data System (ADS)

Kashid, Satishkumar S.; Maity, Rajib

2012-08-01

SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different 'homogeneous monsoon regions'.

Rainfall pattern variability as climate change impact in The Wallacea Region

NASA Astrophysics Data System (ADS)

Pujiastuti, I.; Nurjani, E.

2018-04-01

The objective of the study is to observe the characteristic variability of rainfall pattern in the city located in every rainfall type, local (Kendari), monsoon (Manado), and equatorial (Palu). The result will be compared to determine which has the most significantly precipitation changing due to climate change impact. Rainfall variability in Indonesia illustrates precipitation variation thus the important variability is the variability of monthly rainfall. Monthly precipitation data for the period of 1961-2010 are collected from Indonesian Agency for Meteorological, Climatological, and Geophysical Agency. This data is calculated with the normal test statistical method to analyze rainfall variability. The result showed the pattern of trend and variability of rainfall in every city with the own characteristic which determines the rainfall type. Moreover, there is comparison of rainfall pattern changing between every rainfall type. This information is useful for climate change mitigation and adaptation strategies especially in water resource management form precipitation as well as the occurrence of meteorological disasters.

Constraining relationships between rainfall and landsliding with satellite derived rainfall measurements and landslide inventories.

NASA Astrophysics Data System (ADS)

Marc, Odin; Malet, Jean-Philippe; Stumpf, Andre; Gosset, Marielle

2017-04-01

In mountainous and hilly regions, landslides are an important source of damage and fatalities. Landsliding correlates with extreme rainfall events and may increase with climate change. Still, how precipitation drives landsliding at regional scales is poorly understood quantitatively in part because constraining simultaneously landsliding and rainfall across large areas is challenging. By combining optical images acquired from satellite observation platforms and rainfall measurements from satellite constellations we are building a database of landslide events caused by with single storm events. We present results from storm-induced landslides from Brazil, Taiwan, Micronesia, Central America, Europe and the USA. We present scaling laws between rainfall metrics derived by satellites (total rainfall, mean intensity, antecedent rainfall, ...) and statistical descriptors of landslide events (total area and volume, size distribution, mean runout, ...). Total rainfall seems to be the most important parameter driving non-linearly the increase in total landslide number, and area and volume. The maximum size of bedrock landslides correlates with the total number of landslides, and thus with total rainfall, within the limits of available topographic relief. In contrast, the power-law scaling exponent of the size distribution, controlling the relative abundance of small and large landslides, appears rather independent of the rainfall metrics (intensity, duration and total rainfall). These scaling laws seem to explain both the intra-storm pattern of landsliding, at the scale of satellite rainfall measurements ( 25kmx25km), and the different impacts observed for various storms. Where possible, we evaluate the limits of standard rainfall products (TRMM, GPM, GSMaP) by comparing them to in-situ data. Then we discuss how slope distribution and other geomorphic factors (lithology, soil presence,...) modulate these scaling laws. Such scaling laws at the basin scale and based only on a-priori information (topography, lithology, …) and rainfall metrics available from meteorological forecast may allow to better anticipate and mitigates landsliding associated with extreme rainfall events.

Differential behaviour of a Lesser Himalayan watershed in extreme rainfall regimes

NASA Astrophysics Data System (ADS)

Chauhan, Pankaj; Singh, Nilendu; Chauniyal, Devi Datt; Ahluwalia, Rajeev S.; Singhal, Mohit

2017-03-01

Climatic extremes including precipitation are bound to intensify in the global warming environment. The present study intends to understand the response of the Tons sub-watershed in Lesser Himalaya, in 3 years with entirely different hydrological conditions (July 2008-June 2011) in terms of discharge, sediment flux and denudation rates. Within an uncertainty limit of ±20%, the mean interannual discharge (5.74 ± 1.44 m 3 s -1) (±SE), was found highly variable (CV: 151%; 0.8-38 m 3 s -1). In a normal rainfall year (2008-2009; ˜1550 mm), the discharge was 5.12 ± 1.75 m 3 s -1, whereas in a drought year (2009-2010), it reduced by 30% with the reduction in ˜23% rainfall (CV: 85%). In an excessive rainfall year (once-in-a-century event) (2010-2011; ˜3050 mm), discharge as well as total solid load was ˜200% higher. Monsoon months (July-September) accounted for more than 90% of the annual solid load transport. The ratio of dissolved to suspended solid (C/P ratio) was consistently low (<1) during monsoon months and higher (1-7) during the rest of the dry period. C/P ratio was inversely ( R 2=0.49), but significantly ( P <0.001) related to the rainfall. The average mechanical erosion rate in the three different rainfall years was 0.24, 0.19 and 1.03 mmyr -1, whereas the chemical erosion was estimated at 0.12, 0.11 and 0.46 mmyr -1, respectively. Thus, the average denudation rate of the Tons sub-watershed has been estimated at 0.33 mmyr -1 (excluding extreme rainfall year: 1.5 mmyr -1). Our results have implications to understand the hydrological behaviour of the Lesser Himalayan watersheds and will be valuable for the proposed and several upcoming small hydropower plants in the region in the context of regional ecology and natural resource management.

Hydrology of a zero-order Southern Piedmont watershed through 45 years of changing agricultural land use. Part 1. Monthly and seasonal rainfall-runoff relationships

NASA Astrophysics Data System (ADS)

Endale, Dinku M.; Fisher, Dwight S.; Steiner, Jean L.

2006-01-01

Few studies have reported runoff from small agricultural watersheds over sufficiently long period so that the effect of different cover types on runoff can be examined. We analyzed 45-yrs of monthly and annual rainfall-runoff characteristics of a small (7.8 ha) zero-order typical Southern Piedmont watershed in southeastern United States. Agricultural land use varied as follows: 1. Row cropping (5-yrs); 2. Kudzu ( Pueraria lobata; 5-yrs); 3. Grazed kudzu and rescuegrass ( Bromus catharticus; 7-yrs); and 4. Grazed bermudagrass and winter annuals ( Cynodon dactylon; 28-yrs). Land use and rainfall variability influenced runoff characteristics. Row cropping produced the largest runoff amount, percentage of the rainfall partitioned into runoff, and peak flow rates. Kudzu reduced spring runoff and almost eliminated summer runoff, as did a mixture of kudzu and rescuegrass (KR) compared to row cropping. Peak flow rates were also reduced during the kudzu and KR. Peak flow rates increased under bermudagrass but were lower than during row cropping. A simple process-based 'tanh' model modified to take the previous month's rainfall into account produced monthly rainfall and runoff correlations with coefficient of determination ( R2) of 0.74. The model was tested on independent data collected during drought. Mean monthly runoff was 1.65 times the observed runoff. Sustained hydrologic monitoring is essential to understanding long-term rainfall-runoff relationships in agricultural watersheds.

Climatological Processing and Product Development for the TRMM Ground Validation Program

NASA Technical Reports Server (NTRS)

Marks, D. A.; Kulie, M. S.; Robinson, M.; Silberstein, D. S.; Wolff, D. B.; Ferrier, B. S.; Amitai, E.; Fisher, B.; Wang, J.; Augustine, D.;

Nonlinear Meridional Moisture Advection and the ENSO-Southern China Rainfall Teleconnection

NASA Astrophysics Data System (ADS)

Wang, Qiang; Cai, Wenju; Zeng, Lili; Wang, Dongxiao

2018-05-01

In the boreal cooler months of 2015, southern China (SC) experienced the largest rainfall since 1950, exceeding 4 times the standard deviation of SC rainfall. Although an El Niño typically induces a positive SC rainfall anomaly during these months, the unprecedented rainfall increase cannot be explained by the strong El Niño of 2015/2016, and the dynamics is unclear. Here we show that a nonlinear meridional moisture advection contributes substantially to the unprecedented rainfall increase. During cooler months of 2015, the meridional flow anomaly over the South China Sea region, which acts on an El Niño-induced anomalous meridional moisture gradient, is particularly large and is supported by an anomalous zonal sea surface temperature gradient over the northwestern Pacific, which recorded its largest value in 2015 since 1950. Our study highlights, for the first time, the importance of the nonlinear process associated with the combined impact of a regional sea surface temperature gradient and large-scale El Niño anomalies in forcing El Niño rainfall teleconnection.

Sensitivity of monthly streamflow forecasts to the quality of rainfall forcing: When do dynamical climate forecasts outperform the Ensemble Streamflow Prediction (ESP) method?

NASA Astrophysics Data System (ADS)

Tanguy, M.; Prudhomme, C.; Harrigan, S.; Smith, K. A.; Parry, S.

2017-12-01

Forecasting hydrological extremes is challenging, especially at lead times over 1 month for catchments with limited hydrological memory and variable climates. One simple way to derive monthly or seasonal hydrological forecasts is to use historical climate data to drive hydrological models using the Ensemble Streamflow Prediction (ESP) method. This gives a range of possible future streamflow given known initial hydrologic conditions alone. The degree of skill of ESP depends highly on the forecast initialisation month and catchment type. Using dynamic rainfall forecasts as driving data instead of historical data could potentially improve streamflow predictions. A lot of effort is being invested within the meteorological community to improve these forecasts. However, while recent progress shows promise (e.g. NAO in winter), the skill of these forecasts at monthly to seasonal timescales is generally still limited, and the extent to which they might lead to improved hydrological forecasts is an area of active research. Additionally, these meteorological forecasts are currently being produced at 1 month or seasonal time-steps in the UK, whereas hydrological models require forcings at daily or sub-daily time-steps. Keeping in mind these limitations of available rainfall forecasts, the objectives of this study are to find out (i) how accurate monthly dynamical rainfall forecasts need to be to outperform ESP, and (ii) how the method used to disaggregate monthly rainfall forecasts into daily rainfall time series affects results. For the first objective, synthetic rainfall time series were created by increasingly degrading observed data (proxy for a `perfect forecast') from 0 % to +/-50 % error. For the second objective, three different methods were used to disaggregate monthly rainfall data into daily time series. These were used to force a simple lumped hydrological model (GR4J) to generate streamflow predictions at a one-month lead time for over 300 catchments representative of the range of UK's hydro-climatic conditions. These forecasts were then benchmarked against the traditional ESP method. It is hoped that the results of this work will help the meteorological community to identify where to focus their efforts in order to increase the usefulness of their forecasts within hydrological forecasting systems.

Hydrologic response in karstic-ridge wetlands to rainfall and evapotranspiration, central Florida, 2001-2003

USGS Publications Warehouse

Knowles, Leel; Phelps, G.G.; Kinnaman, Sandra L.; German, Edward R.

2005-01-01

Two internally drained karstic wetlands in central Florida-Boggy Marsh at the Hilochee Wildlife Management Area and a large unnamed wetland at the Lyonia Preserve-were studied during 2001-03 to gain a better understanding of the net-recharge function that these wetlands provide, the significance of exchanges with ground water with regard to wetland water budgets, and the variability in wetland hydrologic response to a range of climate conditions. These natural, relatively remote and unaltered wetlands were selected to provide a baseline of natural wetland hydrologic variability to which anthropogenic influences on wetland hydrology could be compared. Large departures from normal rainfall during the study were fortuitous, and allowed monitoring of hydrologic processes over a wide range of climate conditions. Wetland responses varied greatly as a result of climate conditions that ranged from moderate drought to extremely moist. Anthropogenic activities influenced water levels at both study sites; however, because these activities were brief relative to the duration of the study, sufficient data were collected during unimpacted periods to allow for the following conclusions to be made. Water budgets developed for Boggy Marsh and the Lyonia large wetland showed strong similarity between the flux terms of rainfall, evaporation, net change in storage, and the net ground-water exchange residual. Runoff was assumed to be negligible. Of the total annual flux at Boggy Marsh, rainfall accounted for 45 percent; evaporation accounted for 25 percent; net change in storage accounted for 25 percent; and the net residual accounted for 5 percent. At the Lyonia large wetland, rainfall accounted for 44 percent; evaporation accounted for 29 percent; net change in storage accounted for 21 percent; and the net residual accounted for 6 percent of the total annual flux. Wetland storage and ground-water exchange were important when compared to the total water budget at both wetlands. Even though rainfall was far above average during the study, wetland evaporation volumetrically exceeded rainfall. Ground-water inflow was effective in partially offsetting the negative residual between rainfall and evaporation, thus adding to wetland storage. Ground-water inflow was most common at both wetlands when rainfall continued for days or weeks, or during a week with more than about 2.5 inches of rainfall. Large decreases in wetland storage were associated with large negative fluxes of evaporation and ground-water exchange. The response of wetland water levels to rainfall showed a strong and similar relation at both study sites; however, the greater variability in the relation of wetland water-level change to rainfall at higher rainfall rates indicated that hydrologic processes other than rainfall became more important in the response of the wetland. Changes in wetland water levels seemed to be related more to vertical gradients than to lateral gradients. The largest wetland water-level rises were associated mostly with lower vertical gradients, when vertical head differences were below the 18-month average; however, at the Lyonia large wetland, extremely large lateral gradients toward the wetland during late June 2002 may have contributed to substantial gains in wetland water. During the remainder of the study, wetland water-level rises were associated mostly with decreasing vertical gradients and highly variable lateral gradients. Conversely, wetland water-level decreases were associated mostly with increasing vertical gradients and lateral gradients away from the wetland, particularly during the dry season. The potential for lateral ground-water exchange with the wetlands varied substantially more than that for vertical exchange. Potential for vertical losses of wetland water to ground water was highest during a dry period from December 2001 to June 2002, during the wet season of 2002, and for several months into the following dry season. Lateral he

Post-fire drought effects and their legacy on soil functionality and microbial community structure in a Mediterranean shrubland

NASA Astrophysics Data System (ADS)

Belen Hinojosa, M.; Parra, Antonio; Laudicina, V. Armando; Moreno, José M.

2017-04-01

Climate change in subtropical areas, like the Mediterranean, is projected to decrease precipitation and to lengthen the seasonal drought period. Fire danger is also projected to increase under the most severe conditions. Little is known about the effects of increasing drought and, particularly, its legacy when precipitation resumes to normal, on the recovery of burned ecosystems. Here we studied the effects of post-fire drought and its legacy two years after it stopped on soil microbial community structure and functionality of a Cistus-Erica shrubland. To do this, a manipulative experiment was setup in which rainfall total patterns were modified by means of a rain-out shelters and irrigation system in a fully replicated set of previously burned plots. The treatments were: environmental control (natural rainfall), historical control (average rainfall, 2 months drought), moderate drought (25% reduction of historical control, 5 months drought) and severe drought (45% reduction, 7 months drought). One set of unburned plots under natural rainfall served as an additional control. Availability of the main soil nutrients and microbial community composition and functionality were monitored over 4 years under these rainfall manipulation treatments. Thereafter, treatments were discontinued and plots were subjected to ambient rainfall for two additional years. Post-fire drought had not effect on total C or N. Fire increased soil P and N availability. However, post-fire drought reduced available soil P and increased nitrate in the short term. Post- fire reduction of available K was accentuated by continued drought. Fire significantly reduced soil organic matter, enzyme activities and carbon mineralization, mainly in drought treated soils. Fire also decreased soil microbial biomass and the proportion of fungi, while that of actinomycetes increased in the short term. Post-fire drought accentuated the decrease of soil total microbial biomass and fungi, with bacteria becoming more abundant. After discontinuing the drought treatments, the effect of the previous drought was significant for available P and enzyme activities. Although the microbial biomass did not show a drought legacy effect of the previous drought period, the proportion of fungi was still lower in post-fire drought treatments and the proportion of bacteria (mainly Gram+) higher. Our results show that post-fire drought had an effect on soil functionality and microbial community structure, and that once the drought ceased its effects on some biogeochemical constituents and microbial groups were still visible two years thereafter. The fact that in a lapse of two years some variables had resume to normal while others still differed among drought treatment signifies that the legacies will last for some additional years, impairing during this time the normal functioning of the soil. However, these legacy was related to the magnitude of drought and, although not tested in our study, on the time since the occurrence of the phenomenon, and the sensitivity of the ecological system.

Lysimeter study to investigate the effect of rainfall patterns on leaching of isoproturon.

PubMed

Beulke, Sabine; Brown, Colin D; Fryer, Christopher J; Walker, Allan

2002-01-01

The influence of five rainfall treatments on water and solute leaching through two contrasting soil types was investigated. Undisturbed lysimeters (diameter 0.25 m, length 0.5 m) from a sandy loam (Wick series) and a moderately structured clay loam (Hodnet series) received autumn applications of the radio-labelled pesticide isoproturon and bromide tracer. Target rainfall plus irrigation from the end of November 1997 to May 1998 ranged from drier to wetter than average (235 to 414 mm); monthly rainfall was varied according to a pre-selected pattern or kept constant (triplicate lysimeters per regime). Leachate was collected at intervals and concentrations of the solutes were determined. Total flow (0.27-0.94 pore volumes) and losses of bromide (3-80% of applied) increased with increasing inputs of water and were larger from the Wick sandy loam than from the Hodnet clay loam soil. Matrix flow appeared to be the main mechanism for transport of isoproturon through the Wick soil whereas there was a greater influence of preferential flow for the Hodnet lysimeters. The total leached load of isoproturon from the Wick lysimeters was 0.02-0.26% of that applied. There was no clear variation in transport processes between the rainfall treatments investigated for this soil and there was an approximately linear relationship (r2 = 0.81) between leached load and total flow. Losses of isoproturon from the Hodnet soil were 0.03-0.39% of applied and there was evidence of enhanced preferential flow in the driest and wettest treatments. Leaching of isoproturon was best described by an exponential relationship between load and total flow (r2 = 0.62). A 45% increase in flow between the two wettest treatments gave a 100% increase in leaching of isoproturon from the Wick soil. For the Hodnet lysimeters, a 35% increase in flow between the same treatments increased herbicide loss by 325%.

Influence of southern oscillation on autumn rainfall in Iran (1951-2011)

NASA Astrophysics Data System (ADS)

Roghani, Rabbaneh; Soltani, Saeid; Bashari, Hossein

2016-04-01

This study aimed to investigate the relationships between southern oscillation and autumn (October-December) rainfall in Iran. It also sought to identify the possible physical mechanisms involved in the mentioned relationships by analyzing observational atmospheric data. Analyses were based on monthly rainfall data from 50 synoptic stations with at least 35 years of records up to the end of 2011. Autumn rainfall time series were grouped by the average Southern Oscillation Index (SOI) and SOI phase methods. Significant differences between rainfall groups in each method were assessed by Kruskal-Wallis and Kolmogorov-Smirnov non-parametric tests. Their relationships were also validated using the linear error in probability space (LEPS) test. The results showed that average SOI and SOI phases during July-September were related with autumn rainfall in some regions located in the west and northwest of Iran, west coasts of the Caspian Sea and southern Alborz Mountains. The El Niño (negative) and La Niña (positive) phases were associated with increased and decreased autumn rainfall, respectively. Our findings also demonstrated the persistence of Southern Pacific Ocean's pressure signals on autumn rainfall in Iran. Geopotential height patterns were totally different in the selected El Niño and La Niña years over Iran. During the El Niño years, a cyclone was formed over the north of Iran and an anticyclone existed over the Mediterranean Sea. During La Niña years, the cyclone shifted towards the Mediterranean Sea and an anticyclone developed over Iran. While these El Niño conditions increased autumn rainfall in Iran, the opposite conditions during the La Niña phase decreased rainfall in the country. In conclusion, development of rainfall prediction models based on the SOI can facilitate agricultural and water resources management in Iran.

Weather model performance on extreme rainfall events simulation's over Western Iberian Peninsula

NASA Astrophysics Data System (ADS)

Pereira, S. C.; Carvalho, A. C.; Ferreira, J.; Nunes, J. P.; Kaiser, J. J.; Rocha, A.

2012-08-01

This study evaluates the performance of the WRF-ARW numerical weather model in simulating the spatial and temporal patterns of an extreme rainfall period over a complex orographic region in north-central Portugal. The analysis was performed for the December month of 2009, during the Portugal Mainland rainy season. The heavy rainfall to extreme heavy rainfall periods were due to several low surface pressure's systems associated with frontal surfaces. The total amount of precipitation for December exceeded, in average, the climatological mean for the 1971-2000 time period in +89 mm, varying from 190 mm (south part of the country) to 1175 mm (north part of the country). Three model runs were conducted to assess possible improvements in model performance: (1) the WRF-ARW is forced with the initial fields from a global domain model (RunRef); (2) data assimilation for a specific location (RunObsN) is included; (3) nudging is used to adjust the analysis field (RunGridN). Model performance was evaluated against an observed hourly precipitation dataset of 15 rainfall stations using several statistical parameters. The WRF-ARW model reproduced well the temporal rainfall patterns but tended to overestimate precipitation amounts. The RunGridN simulation provided the best results but model performance of the other two runs was good too, so that the selected extreme rainfall episode was successfully reproduced.

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...

Mapping monthly rainfall erosivity in Europe.

PubMed

Ballabio, Cristiano; Borrelli, Pasquale; Spinoni, Jonathan; Meusburger, Katrin; Michaelides, Silas; Beguería, Santiago; Klik, Andreas; Petan, Sašo; Janeček, Miloslav; Olsen, Preben; Aalto, Juha; Lakatos, Mónika; Rymszewicz, Anna; Dumitrescu, Alexandru; Tadić, Melita Perčec; Diodato, Nazzareno; Kostalova, Julia; Rousseva, Svetla; Banasik, Kazimierz; Alewell, Christine; Panagos, Panos

2017-02-01

Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315MJmmha -1 h -1 ) compared to winter (87MJmmha -1 h -1 ). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R 2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. 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. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

Interannual variability of Indian monsoon rainfall

NASA Technical Reports Server (NTRS)

Paolino, D. A.; Shukla, J.

1984-01-01

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

Downscaling of global climate change estimates to regional scales: An application to Iberian rainfall in wintertime

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

von Storch, H.; Zorita, E.; Cubasch, U.

A statistical strategy to deduct regional-scale features from climate general circulation model (GCM) simulations has been designed and tested. The main idea is to interrelate the characteristic patterns of observed simultaneous variations of regional climate parameters and of large-scale atmospheric flow using the canonical correlation technique. The large-scale North Atlantic sea level pressure (SLP) is related to the regional, variable, winter (DJF) mean Iberian Peninsula rainfall. The skill of the resulting statistical model is shown by reproducing, to a good approximation, the winter mean Iberian rainfall from 1900 to present from the observed North Atlantic mean SLP distributions. It ismore » shown that this observed relationship between these two variables is not well reproduced in the output of a general circulation model (GCM). The implications for Iberian rainfall changes as the response to increasing atmospheric greenhouse-gas concentrations simulated by two GCM experiments are examined with the proposed statistical model. In an instantaneous [open quotes]2 CO[sub 2][close quotes] doubling experiment, using the simulated change of the mean North Atlantic SLP field to predict Iberian rainfall yields, there is an insignificant increase of area-averaged rainfall of I mm/month, with maximum values of 4 mm/month in the northwest of the peninsula. In contrast, for the four GCM grid points representing the lberian Peninsula, the change is - 10 mm/month, with a minimum of - 19 mm/month in the southwest. In the second experiment, with the IPCC scenario A ([open quotes]business as usual[close quotes]) increase of CO[sub 2], the statistical-model results partially differ from the directly simulated rainfall changes: in the experimental range of 100 years, the area-averaged rainfall decreases by 7 mm/month (statistical model), and by 9 mm/month (GCM); at the same time the amplitude of the interdecadal variability is quite different. 17 refs., 10 figs.« less

Relationship of climatic conditions to fecal corticosterone levels of captive cheetahs reared in Japan.

PubMed

Uetake, Katsuji; Une, Yumi; Ito, Shu; Yamabe, Marino; Toyoda, Hideto; Tanaka, Toshio

2014-10-01

To assess the stress level of cheetahs reared in Japan and to identify the prime components of the climatic conditions that affect their thermal stress, fecal corticosterone was monitored for 8 months from May to the following January. A total of 203 fecal samples were gathered in the morning from seven adult cheetahs that were kept at a zoological garden in Wakayama, Japan. Cheetahs were on exhibit singly or together with a harmonious conspecific during the day, but housed singly at night. Although the monthly fluctuation in corticosterone concentrations was not significant, the concentrations were relatively low during the summer season. Individual differences among cheetahs and the interaction effect between individual and month on the corticosterone concentrations were significant. Whereas the corticosterone concentrations negatively correlated with air temperature, they were positively correlated with the amount of rainfall. The highest air temperature and the amount of rainfall were extracted as the prime factors affecting corticosterone concentrations. These results suggest that cheetahs reared in Japan are somewhat subjected to thermal stress, particularly on cooler and/or rainy days. © 2014 Japanese Society of Animal Science.

Prediction of monthly rainfall in Victoria, Australia: Clusterwise linear regression approach

NASA Astrophysics Data System (ADS)

Bagirov, Adil M.; Mahmood, Arshad; Barton, Andrew

2017-05-01

This paper develops the Clusterwise Linear Regression (CLR) technique for prediction of monthly rainfall. The CLR is a combination of clustering and regression techniques. It is formulated as an optimization problem and an incremental algorithm is designed to solve it. The algorithm is applied to predict monthly rainfall in Victoria, Australia using rainfall data with five input meteorological variables over the period of 1889-2014 from eight geographically diverse weather stations. The prediction performance of the CLR method is evaluated by comparing observed and predicted rainfall values using four measures of forecast accuracy. The proposed method is also compared with the CLR using the maximum likelihood framework by the expectation-maximization algorithm, multiple linear regression, artificial neural networks and the support vector machines for regression models using computational results. The results demonstrate that the proposed algorithm outperforms other methods in most locations.

Hurricane Katrina: Influence on the Male-to-Female Birth Ratio.

PubMed

Grech, Victor; Scherb, Hagen

2015-01-01

This study was carried out in order to ascertain whether or not Hurricane Katrina and related factors (i.e. the amount of rainfall) influenced the male-to-female birth ratio (M/F). Monthly births by gender for the affected states (Alabama, Florida, Louisiana and Mississippi) for January 2003 to December 2012 were obtained from the Centers for Disease Control and Prevention (CDC Wonder, Atlanta, Ga., USA). Precipitation data was obtained from the US National Weather Service. Ordinary linear logistic regression was used for trend analysis. A p value ≤0.05 was taken to represent a statistically significant result. Of the total of 3,903,660 live births, 1,996,966 (51.16%) were male and 1,906,694 (48.84%) were female. Significant seasonal variation was noted (the maximum M/F in May was 1.055, the minimum M/F in September was 1.041, p = 0.0073). There was also a separate and significant rise in M/F 8-10 months after the storm (April to June 2006, peak M/F 1.078, p = 0.0074), which translated to an approximate deficit of 800 girls compared to 46,072 girls born in that period if the M/F increase was theoretically only due to a girls' deficit in the denominator of the ratio. This spike was only present in Alabama, Louisiana and Mississippi, all of which received heavy rainfall. Florida did not receive heavy rainfall and experienced no such M/F spike. In this study there was a dose-response relation between the amount of rainfall after Hurricane Katrina and the monthly sex ratio of live births in the US states of Alabama, Louisiana and Mississippi 8-10 months later. The well-known yet unexplained distinct sex ratio seasonality may be due to natural or man-made radiation contained in the rain. © 2015 S. Karger AG, Basel.

Hurricane Katrina: Influence on the Male-to-Female Birth Ratio

PubMed Central

Grech, Victor; Scherb, Hagen

2015-01-01

Objective This study was carried out in order to ascertain whether or not Hurricane Katrina and related factors (i.e. the amount of rainfall) influenced the male-to-female birth ratio (M/F). Materials and Methods Monthly births by gender for the affected states (Alabama, Florida, Louisiana and Mississippi) for January 2003 to December 2012 were obtained from the Centers for Disease Control and Prevention (CDC Wonder, Atlanta, Ga., USA). Precipitation data was obtained from the US National Weather Service. Ordinary linear logistic regression was used for trend analysis. A p value ≤0.05 was taken to represent a statistically significant result. Results Of the total of 3,903,660 live births, 1,996,966 (51.16%) were male and 1,906,694 (48.84%) were female. Significant seasonal variation was noted (the maximum M/F in May was 1.055, the minimum M/F in September was 1.041, p = 0.0073). There was also a separate and significant rise in M/F 8–10 months after the storm (April to June 2006, peak M/F 1.078, p = 0.0074), which translated to an approximate deficit of 800 girls compared to 46,072 girls born in that period if the M/F increase was theoretically only due to a girls' deficit in the denominator of the ratio. This spike was only present in Alabama, Louisiana and Mississippi, all of which received heavy rainfall. Florida did not receive heavy rainfall and experienced no such M/F spike. Conclusion In this study there was a dose-response relation between the amount of rainfall after Hurricane Katrina and the monthly sex ratio of live births in the US states of Alabama, Louisiana and Mississippi 8–10 months later. The well-known yet unexplained distinct sex ratio seasonality may be due to natural or man-made radiation contained in the rain. PMID:26139554

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.

Rainfall and temperature changes and variability in the Upper East Region of Ghana

NASA Astrophysics Data System (ADS)

Issahaku, Abdul-Rahaman; Campion, Benjamin Betey; Edziyie, Regina

2016-08-01

The aim of the research was to assess the current trend and variation in rainfall and temperature in the Upper East Region, Ghana, using time series moving average analysis and decomposition methods. Meteorological data obtained from the Ghana Meteorological Agency in Accra, Ghana, from 1954 to 2014 were used in the models. The additive decomposition model was used to analyze the rainfall because the seasonal variation was relatively constant over time, while the multiplicative model was used for both the daytime and nighttime temperatures because their seasonal variations increase over time. The monthly maximum and the minimum values for the entire period were as follows: rainfall 455.50 and 0.00 mm, nighttime temperature 29.10°C and 13.25°C and daytime temperature 41.10°C and 26.10°C, respectively. Also, while rainfall was decreasing, nighttime and daytime temperatures were increasing in decadal times. Since both the daytime and nighttime temperatures were increasing and rainfall was decreasing, climate extreme events such as droughts could result and affect agriculture in the region, which is predominantly rain fed. Also, rivers, dams, and dugouts are likely to dry up in the region. It was also observed that there was much variation in rainfall making prediction difficult. Day temperatures were generally high with the months of March and April have been the highest. The months of December recorded the lowest night temperature. Inhabitants are therefore advised to sleep in well-ventilated rooms during the warmest months and wear protective clothing during the cold months to avoid contracting climate-related diseases.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Persistence Characteristics of Australian Rainfall Anomalies

NASA Astrophysics Data System (ADS)

Simmonds, Ian; Hope, Pandora

1997-05-01

Using 79 years (1913-1991) of Australian monthly precipitation data we examined the nature of the persistence of rainfall anomalies. Analyses were performed for four climate regions covering the country, as well as for the entire Australian continent. We show that rainfall over these regions has high temporal variability and that annual rainfall amounts over all five sectors vary in phase and are, with the exception of the north-west region, significantly correlated with the Southern Oscillation Index (SOI). These relationships were particularly strong during the spring season.It is demonstrated that Australian rainfall exhibits statistically significant persistence on monthly, seasonal, and (to a limited extent) annual time-scales, up to lags of 3 months and one season and 1 year. The persistence showed strong seasonal dependence, with each of the five regions showing memory out to 4 or 5 months from winter and spring. Many aspects of climate in the Australasian region are known to have undergone considerable changes about 1950. We show this to be true for persistence also; its characteristics identified for the entire record were present during the 1951--1980 period, but virtually disappeared in the previous 30-year period.Much of the seasonal distribution of rainfall persistence on monthly time-scales, particularly in the east, is due to the influence of the SOI. However, most of the persistence identified in winter and spring in the north-west is independent of the ENSO phenomenon.Rainfall anomalies following extreme dry and wet months, seasons and years (lowest and highest two deciles) persisted more than would be expected by chance. For monthly extreme events this was more marked in the winter semester for the wet events, except in the south-east region. In general, less persistence was found for the extreme seasons. Although the persistence of dry years was less than would have been expected by chance, the wet years appear to display persistence.

Latitudinal variation in summer monsoon rainfall over Western Ghat of India and its association with global sea surface temperatures.

PubMed

Revadekar, J V; Varikoden, Hamza; Murumkar, P K; Ahmed, S A

2018-02-01

The Western Ghats (WG) of India are basically north-south oriented mountains having narrow zonal width with a steep rising western face. The summer monsoon winds during June to September passing over the Arabian Sea are obstructed by the WG and thus orographically uplift to produce moderate-to-heavy precipitation over the region. However, it is seen that characteristic features of rainfall distribution during the season vary from north to south. Also its correlation with all-India summer monsoon rainfall increases from south to north. In the present study, an attempt is also made to examine long-term as well as short-term trends and variability in summer monsoon rainfall over different subdivisions of WG using monthly rainfall data for the period 1871-2014. Konkan & Goa and Coastal Karnataka show increase in rainfall from 1871 to 2014 in all individual summer monsoon months. Short-term trend analysis based on 31-year sliding window indicates that the trends are not monotonous, but has epochal behavior. In recent epoch, magnitudes of negative trends are consistently decreasing and have changed its sign to positive during 1985-2014. It has been observed that Indian Ocean Dipole (IOD) plays a dominant positive role in rainfall over entire WG in all summer monsoon months, whereas role of Nino regions are asymmetric over WG rainfall. Indian summer monsoon is known for its negative relationship with Nino SST. Negative correlations are also seen for WG rainfall with Nino regions but only during onset and withdrawal phase. During peak monsoon months July and August subdivisions of WG mostly show positive correlation with Nino SST. Copyright © 2017 Elsevier B.V. All rights reserved.

On Rainfall Modification by Major Urban Areas. Part 1; Observations from Space-borne Rain Radar Aboard TRMM

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshell; Starr, David OC. (Technical Monitor)

2001-01-01

A novel approach is introduced to correlating urbanization and rainfall modification. This study represents one of the first published attempts (possibly the first) to identify and quantify rainfall modification by urban areas using satellite-based rainfall measurements. Previous investigations successfully used rain gauge networks and around-based radar to investigate this phenomenon but still encountered difficulties due to limited, specialized measurements and separation of topographic and other influences. Three years of mean monthly rainfall rates derived from the first space-based rainfall radar, Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of data at half-degree latitude resolution enables identification of rainfall patterns around major metropolitan areas of Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Preliminary results reveal an average increase of 5.6% in monthly rainfall rates (relative to a mean upwind CONTROL area) over the metropolis but an average increase of approx. 28%, in monthly rainfall rates within 30-60 kilometers downwind of the metropolis. Some portions of the downwind area exhibit increases as high as 51%. It was also found that maximum rainfall rates found in the downwind impact area exceeded the mean value in the upwind CONTROL area by 48%-116% and were generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are quite consistent studies of St. Louis (e.g' METROMEX) and Chicago almost two decades ago and more recent studies in the Atlanta and Mexico City areas.

Attribution of extreme precipitation in the lower reaches of the Yangtze River during May 2016

NASA Astrophysics Data System (ADS)

Li, Chunxiang; Tian, Qinhua; Yu, Rong; Zhou, Baiquan; Xia, Jiangjiang; Burke, Claire; Dong, Buwen; Tett, Simon F. B.; Freychet, Nicolas; Lott, Fraser; Ciavarella, Andrew

2018-01-01

May 2016 was the third wettest May on record since 1961 over central eastern China based on station observations, with total monthly rainfall 40% more than the climatological mean for 1961-2013. Accompanying disasters such as waterlogging, landslides and debris flow struck part of the lower reaches of the Yangtze River. Causal influence of anthropogenic forcings on this event is investigated using the newly updated Met Office Hadley Centre system for attribution of extreme weather and climate events. Results indicate that there is a significant increase in May 2016 rainfall in model simulations relative to the climatological period, but this increase is largely attributable to natural variability. El Niño years have been found to be correlated with extreme rainfall in the Yangtze River region in previous studies—the strong El Niño of 2015-2016 may account for the extreme precipitation event in 2016. However, on smaller spatial scales we find that anthropogenic forcing has likely played a role in increasing the risk of extreme rainfall to the north of the Yangtze and decreasing it to the south.

Comparison of Two Stochastic Daily Rainfall Models and their Ability to Preserve Multi-year Rainfall Variability

NASA Astrophysics Data System (ADS)

Kamal Chowdhury, AFM; Lockart, Natalie; Willgoose, Garry; Kuczera, George; Kiem, Anthony; Parana Manage, Nadeeka

2016-04-01

Stochastic simulation of rainfall is often required in the simulation of streamflow and reservoir levels for water security assessment. As reservoir water levels generally vary on monthly to multi-year timescales, it is important that these rainfall series accurately simulate the multi-year variability. However, the underestimation of multi-year variability is a well-known issue in daily rainfall simulation. Focusing on this issue, we developed a hierarchical Markov Chain (MC) model in a traditional two-part MC-Gamma Distribution modelling structure, but with a new parameterization technique. We used two parameters of first-order MC process (transition probabilities of wet-to-wet and dry-to-dry days) to simulate the wet and dry days, and two parameters of Gamma distribution (mean and standard deviation of wet day rainfall) to simulate wet day rainfall depths. We found that use of deterministic Gamma parameter values results in underestimation of multi-year variability of rainfall depths. Therefore, we calculated the Gamma parameters for each month of each year from the observed data. Then, for each month, we fitted a multi-variate normal distribution to the calculated Gamma parameter values. In the model, we stochastically sampled these two Gamma parameters from the multi-variate normal distribution for each month of each year and used them to generate rainfall depth in wet days using the Gamma distribution. In another study, Mehrotra and Sharma (2007) proposed a semi-parametric Markov model. They also used a first-order MC process for rainfall occurrence simulation. But, the MC parameters were modified by using an additional factor to incorporate the multi-year variability. Generally, the additional factor is analytically derived from the rainfall over a pre-specified past periods (e.g. last 30, 180, or 360 days). They used a non-parametric kernel density process to simulate the wet day rainfall depths. In this study, we have compared the performance of our hierarchical MC model with the semi-parametric model in preserving rainfall variability in daily, monthly, and multi-year scales. To calibrate the parameters of both models and assess their ability to preserve observed statistics, we have used ground based data from 15 raingauge stations around Australia, which consist a wide range of climate zones including coastal, monsoonal, and arid climate characteristics. In preliminary results, both models show comparative performances in preserving the multi-year variability of rainfall depth and occurrence. However, the semi-parametric model shows a tendency of overestimating the mean rainfall depth, while our model shows a tendency of overestimating the number of wet days. We will discuss further the relative merits of the both models for hydrology simulation in the presentation.

Rainfall in and near Lake County, Illinois, December 1989-September 1993

USGS Publications Warehouse

Duncker, James J.; Vail, Tracy J.; Robinson, Steven M.

1994-01-01

Rainfall quantity data for 23 rainfall-gaging stations located in and near Lake County, Ill., are presented. The rainfall data were collected from December 1989 through September 1993 as part of an on-going rainfall-runoff investigation. Station descriptions identify the location of and equipment installed at each rainfall-gaging station. Total daily rainfall is tabulated for each rainfall-gaging station for each water year. Periods of missing record and snow-affected precipitation totals are identified. The data are presented graphically using annual hyetographs and mass plots.

Applications of high resolution rainfall radar data to quantify water temperature dynamics in urban catchments

NASA Astrophysics Data System (ADS)

Croghan, Danny; Van Loon, Anne; Bradley, Chris; Sadler, Jon; Hannnah, David

2017-04-01

Studies relating rainfall events to river water quality are frequently hindered by the lack of high resolution rainfall data. Local studies are particularly vulnerable due to the spatial variability of precipitation, whilst studies in urban environments require precipitation data at high spatial and temporal resolutions. The use of point-source data makes identifying causal effects of storms on water quality problematic and can lead to erroneous interpretations. High spatial and temporal resolution rainfall radar data offers great potential to address these issues. Here we use rainfall radar data with a 1km spatial resolution and 5 minute temporal resolution sourced from the UK Met Office Nimrod system to study the effects of storm events on water temperature (WTemp) in Birmingham, UK. 28 WTemp loggers were placed over 3 catchments on a rural-urban land use gradient to identify trends in WTemp during extreme events within urban environments. Using GIS, the catchment associated with each logger was estimated, and 5 min. rainfall totals and intensities were produced for each sub-catchment. Comparisons of rainfall radar data to meteorological stations in the same grid cell revealed the high accuracy of rainfall radar data in our catchments (<5% difference for studied months). The rainfall radar data revealed substantial differences in rainfall quantity between the three adjacent catchments. The most urban catchment generally received more rainfall, with this effect greatest in the highest intensity storms, suggesting the possibility of urban heat island effects on precipitation dynamics within the catchment. Rainfall radar data provided more accurate sub-catchment rainfall totals allowing better modelled estimates of storm flow, whilst spatial fluctuations in both discharge and WTemp can be simply related to precipitation intensity. Storm flow inputs for each sub-catchment were estimated and linked to changes in WTemp. WTemp showed substantial fluctuations (>1 °C) over short durations (<30 minutes) during storm events in urbanised sub-catchments, however WTemp recovery times were more prolonged. Use of the rainfall radar data allowed increased accuracy in estimates of storm flow timings and rainfall quantities at each sub-catchment, from which the impact of storm flow on WTemp could be quantified. We are currently using the radar data to derive thresholds for rainfall amount and intensity at which these storm deviations occur for each logger, from which the relative effects of land use and other catchment characteristics in each sub-catchment can be assessed. Our use of the rainfall radar data calls into question the validity of using station based data for small scale studies, particularly in urban areas, with high variation apparent in rainfall intensity both spatially and temporally. Variation was particularly high within the heavily urbanised catchment. For water quality studies, high resolution rainfall radar can be implemented to increase the reliability of interpretations of the response of water quality variables to storm water inputs in urban catchments.

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.

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.

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.

Some Precipitation Studies over Andhra Pradesh and the Bay of Bengal using TRMM and SSMI data

NASA Astrophysics Data System (ADS)

Rao, S. Ramalingeswara; Krishna, K. Muni; Kumar, Bhanu

2007-07-01

One of the most difficult issues in modeling the global atmosphere and climate by General Circulation Models is the simulation and initialization of precipitation processes and at the same time rainfall is most important meteorological parameter that effects India's economy. An attempt is made in the present study to evaluate diurnal variation of rain rates over the Bay of Bengal (BoB) for the months June through December during 1999-2002. TMI rainfall product of Wentz and Spencer and SSMI data sets were used in this study. Mean hourly rain rates were calculated over the BoB (10°-15° N and 85°-95°E) and discussed; this study highlights that maximum rain rates are observed in the afternoons during summer monsoon seasons. Secondly mean monthly annual cycle of rainfall is prepared using 3B42RT merged rain product and compared with mean monthly India Meteorological Department (IMD) data for the study period over Andhra Pradesh (A.P). Time series of daily variations of 3B42RT precipitation and observed real time rainfall data over A.P. for the study period is validated and the relationship between them is statistically significant at 1% level. Similarly mean monthly data prepared from the daily analysis and compared with the IMD mean monthly rainfall maps. The comparison suggests that even with only available real time data from 3B42RT and rain gauge, it is possible to construct usable large-scale rainfall maps on regular latitude-longitude grids. This analysis, which uses a high resolution and more local rain gauge data, is able to produce realistic details of Indian summer monsoon rainfall over the study period.

Spatio-temporal heterogeneity of malaria morbidity in Ghana: Analysis of routine health facility data

PubMed Central

Malm, Keziah; Peprah, Nana Yaw; Silal, Sheetal P.

2018-01-01

Background Malaria incidence is largely influenced by vector abundance. Among the many interconnected factors relating to malaria transmission, weather conditions such as rainfall and temperature are known to create suitable environmental conditions that sustain reproduction and propagation of anopheles mosquitoes and malaria parasites. In Ghana, climatic conditions vary across the country. Understanding the heterogeneity of malaria morbidity using data sourced from a recently setup data repository for routine health facility data could support planning. Methods Monthly aggregated confirmed uncomplicated malaria cases from the District Health Information Management System and average monthly rainfall and temperature records obtained from the Ghana Meteorological Agency from 2008 to 2016 were analysed. Univariate time series models were fitted to the malaria, rainfall and temperature data series. After pre-whitening the morbidity data, cross correlation analyses were performed. Subsequently, transfer function models were developed for the relationship between malaria morbidity and rainfall and temperature. Results Malaria morbidity patterns vary across zones. In the Guinea savannah, morbidity peaks once in the year and twice in both the Transitional forest and Coastal savannah, following similar patterns of rainfall at the zonal level. While the effects of rainfall on malaria morbidity are delayed by a month in the Guinea savannah and Transitional Forest zones those of temperature are delayed by two months in the Transitional forest zone. In the Coastal savannah however, incidence of malaria is significantly associated with two months lead in rainfall and temperature. Conclusion Data captured on the District Health Information Management System has been used to demonstrate heterogeneity in the dynamics of malaria morbidity across the country. Timing of these variations could guide the deployment of interventions such as indoor residual spraying, Seasonal Malaria Chemoprevention or vaccines to optimise effectiveness on zonal basis. PMID:29377908

Spatio-temporal heterogeneity of malaria morbidity in Ghana: Analysis of routine health facility data.

PubMed

Awine, Timothy; Malm, Keziah; Peprah, Nana Yaw; Silal, Sheetal P

2018-01-01

Malaria incidence is largely influenced by vector abundance. Among the many interconnected factors relating to malaria transmission, weather conditions such as rainfall and temperature are known to create suitable environmental conditions that sustain reproduction and propagation of anopheles mosquitoes and malaria parasites. In Ghana, climatic conditions vary across the country. Understanding the heterogeneity of malaria morbidity using data sourced from a recently setup data repository for routine health facility data could support planning. Monthly aggregated confirmed uncomplicated malaria cases from the District Health Information Management System and average monthly rainfall and temperature records obtained from the Ghana Meteorological Agency from 2008 to 2016 were analysed. Univariate time series models were fitted to the malaria, rainfall and temperature data series. After pre-whitening the morbidity data, cross correlation analyses were performed. Subsequently, transfer function models were developed for the relationship between malaria morbidity and rainfall and temperature. Malaria morbidity patterns vary across zones. In the Guinea savannah, morbidity peaks once in the year and twice in both the Transitional forest and Coastal savannah, following similar patterns of rainfall at the zonal level. While the effects of rainfall on malaria morbidity are delayed by a month in the Guinea savannah and Transitional Forest zones those of temperature are delayed by two months in the Transitional forest zone. In the Coastal savannah however, incidence of malaria is significantly associated with two months lead in rainfall and temperature. Data captured on the District Health Information Management System has been used to demonstrate heterogeneity in the dynamics of malaria morbidity across the country. Timing of these variations could guide the deployment of interventions such as indoor residual spraying, Seasonal Malaria Chemoprevention or vaccines to optimise effectiveness on zonal basis.

The climate impact on female acute pyelonephritis in Taiwan: A population-based study.

PubMed

Liu, Jui-Ming; Chang, Yu-Lung; Hsu, Ren-Jun; Su, Her-Young; Teng, Sen-Wen; Chang, Fung-Wei

2017-08-01

Urinary tract infection (UTI) is the main reason of community-acquired infection which causes large losses in social economy. The individual as well as climate factors make changes on the incidence. Acute pyelonephritis (APN) is one of the most serious UTI in female. The object of our study is to analyze whether climate factors will have effect on the incidence of female APN in Taiwan. This study consisted of 14,568 female patients with APN from 2001 to 2013 in Taiwan and patients with repeated APN were excluded. The monthly climate data was collected from the Central Weather Bureau. The available monthly climate data included highest, lowest, and average level of temperatures, humidity, rainfall, total rain days, and sunshine hours. The total incidence of female APN was 23.44 each 10,000 populations. The incidence of APN was positively correlated with temperature (r = 0.66), sunshine hours (r = 0.45), rainfall (r = 0.42), rain days (r = 0.29), and humidity (r = 0.23) per month. There is the strongest correlation between the average monthly temperature and the incidence of APN (β = 0.54). The correlation with the incidence of APN was also followed by rain days (β = 0.28) and humidity (β = 0.27). There is a significant expression on the incidence of female APN affected by seasonality and climate parameters. The monthly average temperature has the strongest correlation with female APN. The results of this research may facilitate the potential preventive strategies on female APN. Copyright © 2017. Published by Elsevier B.V.

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.

Multivariate analysis applied to monthly rainfall over Rio de Janeiro state, Brazil

NASA Astrophysics Data System (ADS)

Brito, Thábata T.; Oliveira-Júnior, José F.; Lyra, Gustavo B.; Gois, Givanildo; Zeri, Marcelo

2017-10-01

Spatial and temporal patterns of rainfall were identified over the state of Rio de Janeiro, southeast Brazil. The proximity to the coast and the complex topography create great diversity of rainfall over space and time. The dataset consisted of time series (1967-2013) of monthly rainfall over 100 meteorological stations. Clustering analysis made it possible to divide the stations into six groups (G1, G2, G3, G4, G5 and G6) with similar rainfall spatio-temporal patterns. A linear regression model was applied to a time series and a reference. The reference series was calculated from the average rainfall within a group, using nearby stations with higher correlation (Pearson). Based on t-test ( p < 0.05) all stations had a linear spatiotemporal trend. According to the clustering analysis, the first group (G1) contains stations located over the coastal lowlands and also over the ocean facing area of Serra do Mar (Sea ridge), a 1500 km long mountain range over the coastal Southeastern Brazil. The second group (G2) contains stations over all the state, from Serra da Mantiqueira (Mantiqueira Mountains) and Costa Verde (Green coast), to the south, up to stations in the Northern parts of the state. Group 3 (G3) contains stations in the highlands over the state (Serrana region), while group 4 (G4) has stations over the northern areas and the continent-facing side of Serra do Mar. The last two groups were formed with stations around Paraíba River (G5) and the metropolitan area of the city of Rio de Janeiro (G6). The driest months in all regions were June, July and August, while November, December and January were the rainiest months. Sharp transitions occurred when considering monthly accumulated rainfall: from January to February, and from February to March, likely associated with episodes of "veranicos", i.e., periods of 4-15 days of duration with no rainfall.

Trends of rainfall regime in Peninsular Malaysia during northeast and southwest monsoons

NASA Astrophysics Data System (ADS)

Chooi Tan, Kok

2018-04-01

The trends of rainfall regime in Peninsular Malaysia is mainly affected by the seasonal monsoon. The aim of this study is to investigate the impact of northeast and southwest monsoons on the monthly rainfall patterns over Badenoch Estate, Kedah. In addition, the synoptic maps of wind vector also being developed to identify the wind pattern over Peninsular Malaysia from 2007 – 2016. On the other hand, the archived daily rainfall data is acquired from Malaysian Meteorological Department. The temporal and trends of the monthly and annual rainfall over the study area have been analysed from 2007 to 2016. Overall, the average annual precipitation over the study area from 2007 to 2016 recorded by rain gauge is 2562.35 mm per year.

Physical Validation of TRMM TMI and PR Monthly Rain Products Over Oklahoma

NASA Technical Reports Server (NTRS)

Fisher, Brad L.

2004-01-01

The Tropical Rainfall Measuring Mission (TRMM) provides monthly rainfall estimates using data collected by the TRMM satellite. These estimates cover a substantial fraction of the earth's surface. The physical validation of TRMM estimates involves corroborating the accuracy of spaceborne estimates of areal rainfall by inferring errors and biases from ground-based rain estimates. The TRMM error budget consists of two major sources of error: retrieval and sampling. Sampling errors are intrinsic to the process of estimating monthly rainfall and occur because the satellite extrapolates monthly rainfall from a small subset of measurements collected only during satellite overpasses. Retrieval errors, on the other hand, are related to the process of collecting measurements while the satellite is overhead. One of the big challenges confronting the TRMM validation effort is how to best estimate these two main components of the TRMM error budget, which are not easily decoupled. This four-year study computed bulk sampling and retrieval errors for the TRMM microwave imager (TMI) and the precipitation radar (PR) by applying a technique that sub-samples gauge data at TRMM overpass times. Gridded monthly rain estimates are then computed from the monthly bulk statistics of the collected samples, providing a sensor-dependent gauge rain estimate that is assumed to include a TRMM equivalent sampling error. The sub-sampled gauge rain estimates are then used in conjunction with the monthly satellite and gauge (without sub- sampling) estimates to decouple retrieval and sampling errors. The computed mean sampling errors for the TMI and PR were 5.9% and 7.796, respectively, in good agreement with theoretical predictions. The PR year-to-year retrieval biases exceeded corresponding TMI biases, but it was found that these differences were partially due to negative TMI biases during cold months and positive TMI biases during warm months.

Rainfall erosivity in subtropical catchments and implications for erosion and particle-bound contaminant transfer: a case-study of the Fukushima region

NASA Astrophysics Data System (ADS)

Laceby, J. P.; Chartin, C.; Evrard, O.; Onda, Y.; Garcia-Sanchez, L.; Cerdan, O.

2015-07-01

The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 resulted in a significant fallout of radiocesium over the Fukushima region. After reaching the soil surface, radiocesium is almost irreversibly bound to fine soil particles. Thereafter, rainfall and snow melt run-off events transfer particle-bound radiocesium downstream. Erosion models, such as the Universal Soil Loss Equation (USLE), depict a proportional relationship between rainfall and soil erosion. As radiocesium is tightly bound to fine soil and sediment particles, characterizing the rainfall regime of the fallout-impacted region is fundamental to modelling and predicting radiocesium migration. Accordingly, monthly and annual rainfall data from ~ 60 meteorological stations within a 100 km radius of the FDNPP were analysed. Monthly rainfall erosivity maps were developed for the Fukushima coastal catchments illustrating the spatial heterogeneity of rainfall erosivity in the region. The mean average rainfall in the Fukushima region was 1387 mm yr-1 (σ 230) with the mean rainfall erosivity being 2785 MJ mm ha-1 yr-1 (σ 1359). The results indicate that the majority of rainfall (60 %) and rainfall erosivity (86 %) occurs between June and October. During the year, rainfall erosivity evolves positively from northwest to southeast in the eastern part of the prefecture, whereas a positive gradient from north to south occurs in July and August, the most erosive months of the year. During the typhoon season, the coastal plain and eastern mountainous areas of the Fukushima prefecture, including a large part of the contamination plume, are most impacted by erosive events. Understanding these rainfall patterns, particularly their spatial and temporal variation, is fundamental to managing soil and particle-bound radiocesium transfers in the Fukushima region. Moreover, understanding the impact of typhoons is important for managing sediment transfers in subtropical regions impacted by cyclonic activity.

Universal inverse power-law distribution for temperature and rainfall in the UK region

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2014-06-01

Meteorological parameters, such as temperature, rainfall, pressure, etc., exhibit selfsimilar space-time fractal fluctuations generic to dynamical systems in nature such as fluid flows, spread of forest fires, earthquakes, etc. The power spectra of fractal fluctuations display inverse power-law form signifying long-range correlations. A general systems theory model predicts universal inverse power-law form incorporating the golden mean for the fractal fluctuations. The model predicted distribution was compared with observed distribution of fractal fluctuations of all size scales (small, large and extreme values) in the historic month-wise temperature (maximum and minimum) and total rainfall for the four stations Oxford, Armagh, Durham and Stornoway in the UK region, for data periods ranging from 92 years to 160 years. For each parameter, the two cumulative probability distributions, namely cmax and cmin starting from respectively maximum and minimum data value were used. The results of the study show that (i) temperature distributions (maximum and minimum) follow model predicted distribution except for Stornowy, minimum temperature cmin. (ii) Rainfall distribution for cmin follow model predicted distribution for all the four stations. (iii) Rainfall distribution for cmax follows model predicted distribution for the two stations Armagh and Stornoway. The present study suggests that fractal fluctuations result from the superimposition of eddy continuum fluctuations.

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.

Comparison of multi-monthly rainfall-based drought severity indices, with application to semi-arid Konya closed basin, Turkey

NASA Astrophysics Data System (ADS)

Dogan, Selim; Berktay, Ali; Singh, Vijay P.

2012-11-01

SummaryMany drought indices (DIs) have been introduced to monitor drought conditions. This study compares Percent of Normal (PN), Rainfall Decile based Drought Index (RDDI), statistical Z-Score, China-Z Index (CZI), Standardized Precipitation Index (SPI), and Effective Drought Index (EDI) to identify droughts in a semi-arid closed basin (Konya), Turkey. Comparison studies of DIs under different climatic conditions is always interesting and may be insightful. Employing and comparing 18 different timesteps, the objective of comparison is twofold: (1) to determine the effect of timestep for choosing an appropriate value, and (2) to determine the sensitivity of DI to timestep and the choice of a DI. Monthly rainfall data obtained from twelve spatially distributed stations was used to compare DIs for timesteps ranging from 1 month to 48 months. These DIs were evaluated through correlations for various timesteps. Surprisingly, in many earlier studies, only 1-month time step has been used. Results showed that the employment of median timesteps was essential for future studies, since 1-month timestep DIs were found as irrelevant to those for other timesteps in arid/semi-arid regions because seasonal rainfall deficiencies are common there. Comparing time series of various DI values (numerical values of drought severity) instead of drought classes was advantageous for drought monitoring. EDI was found to be best correlated with other DIs when considering all timesteps. Therefore, drought classes discerned by DIs were compared with EDI. PN and RDDI provided different results than did others. PN detected a decrease in drought percentage for increasing timestep, while RDDI overestimated droughts for all timesteps. SPI and CZI were more consistent in detecting droughts for different timesteps. The response of DI and timestep combination to the change of monthly and multi-monthly rainfall for a qualitative comparison of severities (drought classes) was investigated. Analyzing the 1973-1974 dry spell at Beysehir station, EDI was found sensitive to monthly rainfall changes with respect to cumulative rainfall changes, especially more sensitive than other DIs for shorter timesteps. Overall, EDI was consistent with DIs for various timesteps and was preferable for monitoring long-term droughts in arid/semi-arid regions. The use of various DIs for timesteps of 6, 9, and 12 months is essential for long term drought studies. 1-month DIs should not be used solely in comparison studies to present a DI, unless there is a specific reason. This investigation showed that the use of an appropriate timestep is as important as the type of DI used to identify drought severities.

Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length

NASA Astrophysics Data System (ADS)

Guan, Kaiyu; Good, Stephen P.; Caylor, Kelly K.; Medvigy, David; Pan, Ming; Wood, Eric F.; Sato, Hisashi; Biasutti, Michela; Chen, Min; Ahlström, Anders; Xu, Xiangtao

2018-02-01

There is growing evidence of ongoing changes in the statistics of intra-seasonal rainfall variability over large parts of the world. Changes in annual total rainfall may arise from shifts, either singly or in a combination, of distinctive intra-seasonal characteristics -i.e. rainfall frequency, rainfall intensity, and rainfall seasonality. Understanding how various ecosystems respond to the changes in intra-seasonal rainfall characteristics is critical for predictions of future biome shifts and ecosystem services under climate change, especially for arid and semi-arid ecosystems. Here, we use an advanced dynamic vegetation model (SEIB-DGVM) coupled with a stochastic rainfall/weather simulator to answer the following question: how does the productivity of ecosystems respond to a given percentage change in the total seasonal rainfall that is realized by varying only one of the three rainfall characteristics (rainfall frequency, intensity, and rainy season length)? We conducted ensemble simulations for continental Africa for a realistic range of changes (-20% ~ +20%) in total rainfall amount. We find that the simulated ecosystem productivity (measured by gross primary production, GPP) shows distinctive responses to the intra-seasonal rainfall characteristics. Specifically, increase in rainfall frequency can lead to 28% more GPP increase than the same percentage increase in rainfall intensity; in tropical woodlands, GPP sensitivity to changes in rainy season length is ~4 times larger than to the same percentage changes in rainfall frequency or intensity. In contrast, shifts in the simulated biome distribution are much less sensitive to intra-seasonal rainfall characteristics than they are to total rainfall amount. Our results reveal three major distinctive productivity responses to seasonal rainfall variability—‘chronic water stress’, ‘acute water stress’ and ‘minimum water stress’ - which are respectively associated with three broad spatial patterns of African ecosystem physiognomy, i.e. savannas, woodlands, and tropical forests.

Climate and Leishmaniasis in French Guiana

PubMed Central

Roger, Amaury; Nacher, Mathieu; Hanf, Matthieu; Drogoul, Anne Sophie; Adenis, Antoine; Basurko, Celia; Dufour, Julie; Sainte Marie, Dominique; Blanchet, Denis; Simon, Stephane; Carme, Bernard; Couppié, Pierre

2013-01-01

To study the link between climatic variables and the incidence of leishmaniasis a study was conducted in Cayenne, French Guiana. Patients infected between January 1994 and December 2010. Meteorological data were studied in relation to the incidence of leishmaniasis using an ARIMA model. In the final model, the infections were negatively correlated with rainfall (with a 2-month lag) and with the number of days with rainfall > 50 mm (lags of 4 and 7 months). The variables that were positively correlated were temperature and the Multivariate El Niño Southern Oscillation Index with lags of 8 and 4 months, respectively. Significantly greater correlations were observed in March for rainfall and in November for the Multivariate El Niño/Southern Oscillation Index. Climate thus seems to be a non-negligible explanatory variable for the fluctuations of leishmaniasis. A decrease in rainfall is linked to increased cases 2 months later. This easily perceptible point could lead to an interesting prevention message. PMID:23939706

Organization of vertical shear of wind and daily variability of monsoon rainfall

NASA Astrophysics Data System (ADS)

Gouda, K. C.; Goswami, P.

2016-10-01

Very little is known about the mechanisms that govern the day to day variability of the Indian summer monsoon (ISM) rainfall; in the current dominant view, the daily rainfall is essentially a result of chaotic dynamics. Most studies in the past have thus considered monsoon in terms of its seasonal (June-September) or monthly rainfall. We show here that the daily rainfall in June is associated with vertical shear of horizontal winds at specific scales. While vertical shear had been used in the past to investigate interannual variability of seasonal rainfall, rarely any effort has been made to examine daily rainfall. Our work shows that, at least during June, the daily rainfall variability of ISM rainfall is associated with a large scale dynamical coherence in the sense that the vertical shear averaged over large spatial extents are significantly correlated with area-averaged daily rainfall. An important finding from our work is the existence of a clearly delineated monsoon shear domain (MSD) with strong coherence between area-averaged shear and area-averaged daily rainfall in June; this association of daily rainfall is not significant with shear over only MSD. Another important feature is that the association between daily rainfall and vertical shear is present only during the month of June. Thus while ISM (June-September) is a single seasonal system, it is important to consider the dynamics and variation of June independently of the seasonal ISM rainfall. The association between large-scale organization of circulation and daily rainfall is suggested as a basis for attempting prediction of daily rainfall by ensuring accurate simulation of wind shear.

Determination of mean rainfall from the Special Sensor Microwave/Imager (SSM/I) using a mixed lognormal distribution

NASA Technical Reports Server (NTRS)

Berg, Wesley; Chase, Robert

1992-01-01

Global estimates of monthly, seasonal, and annual oceanic rainfall are computed for a period of one year using data from the Special Sensor Microwave/Imager (SSM/I). Instantaneous rainfall estimates are derived from brightness temperature values obtained from the satellite data using the Hughes D-matrix algorithm. The instantaneous rainfall estimates are stored in 1 deg square bins over the global oceans for each month. A mixed probability distribution combining a lognormal distribution describing the positive rainfall values and a spike at zero describing the observations indicating no rainfall is used to compute mean values. The resulting data for the period of interest are fitted to a lognormal distribution by using a maximum-likelihood. Mean values are computed for the mixed distribution and qualitative comparisons with published historical results as well as quantitative comparisons with corresponding in situ raingage data are performed.

Rainfall Data Simulation

Treesearch

T.L. Rogerson

1980-01-01

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

A national-scale seasonal hydrological forecast system: development and evaluation over Britain

NASA Astrophysics Data System (ADS)

Bell, Victoria A.; Davies, Helen N.; Kay, Alison L.; Brookshaw, Anca; Scaife, Adam A.

2017-09-01

Skilful winter seasonal predictions for the North Atlantic circulation and northern Europe have now been demonstrated and the potential for seasonal hydrological forecasting in the UK is now being explored. One of the techniques being used combines seasonal rainfall forecasts provided by operational weather forecast systems with hydrological modelling tools to provide estimates of seasonal mean river flows up to a few months ahead. The work presented here shows how spatial information contained in a distributed hydrological model typically requiring high-resolution (daily or better) rainfall data can be used to provide an initial condition for a much simpler forecast model tailored to use low-resolution monthly rainfall forecasts. Rainfall forecasts (hindcasts) from the GloSea5 model (1996 to 2009) are used to provide the first assessment of skill in these national-scale flow forecasts. The skill in the combined modelling system is assessed for different seasons and regions of Britain, and compared to what might be achieved using other approaches such as use of an ensemble of historical rainfall in a hydrological model, or a simple flow persistence forecast. The analysis indicates that only limited forecast skill is achievable for Spring and Summer seasonal hydrological forecasts; however, Autumn and Winter flows can be reasonably well forecast using (ensemble mean) rainfall forecasts based on either GloSea5 forecasts or historical rainfall (the preferred type of forecast depends on the region). Flow forecasts using ensemble mean GloSea5 rainfall perform most consistently well across Britain, and provide the most skilful forecasts overall at the 3-month lead time. Much of the skill (64 %) in the 1-month ahead seasonal flow forecasts can be attributed to the hydrological initial condition (particularly in regions with a significant groundwater contribution to flows), whereas for the 3-month ahead lead time, GloSea5 forecasts account for ˜ 70 % of the forecast skill (mostly in areas of high rainfall to the north and west) and only 30 % of the skill arises from hydrological memory (typically groundwater-dominated areas). Given the high spatial heterogeneity in typical patterns of UK rainfall and evaporation, future development of skilful spatially distributed seasonal forecasts could lead to substantial improvements in seasonal flow forecast capability, potentially benefitting practitioners interested in predicting hydrological extremes, not only in the UK but also across Europe.

Monthly variability and possible sources of nitrate in ground water beneath mixed agricultural land use, Suwannee and Lafayette Counties, Florida

USGS Publications Warehouse

Katz, Brian G.; Böhlke, J.K.

2000-01-01

In an area of mixed agricultural land use in Suwannee and Lafayette Counties of northern Florida, water samples were collected monthly from 14 wells tapping the Upper Floridan aquifer during July 1998 through June 1999 to assess hydrologic and land-use factors affecting the variability in nitrate concentrations in ground water. Unusually high amounts of rainfall in September and October 1998 (43.5 centimeters total for both months) resulted in an increase in water levels in all wells in October 1998. This was followed by unusually low amounts of rainfall during November 1998 through May 1999, when rainfall was 40.7 centimeters below 30-year mean monthly values. The presence of karst features (sinkholes, springs, solution conduits) and the highly permeable sands that overlie the Upper Floridan aquifer provide for rapid movement of water containing elevated nitrate concentrations to the aquifer. Nitrate was the dominant form of nitrogen in ground water collected at all sites and nitrate concentrations ranged from less than 0.02 to 22 milligrams per liter (mg/L), as nitrogen. Water samples from most wells showed substantial monthly or seasonal fluctuations in nitrate concentrations. Generally, water samples from wells with nitrate concentrations higher than 10 mg/L showed the greatest amount of monthly fluctuation. For example, water samples from six of eight wells had monthly nitrate concentrations that varied by at least 5 mg/L during the study period. Water from most wells with lower nitrate concentrations (less than 6 mg/L) also showed large monthly fluctuations. For instance, nitrate concentrations in water from four sites showed monthly variations of more than 50 percent. Large fluctuations in nitrate concentrations likely result from seasonal agricultural practices (fertilizer application and animal waste spreading) at a particular site. For example, an increase in nitrate concentrations observed in water samples from seven sites in February or March 1999 most likely results from application of synthetic fertilizers during the late winter months. Lower nitrate concentrations were detected in water samples from five of eight wells sampled during high-flow conditions for the Suwannee River in March 1998 compared to low-flow conditions in November 1998. Evidence for reduction of nitrate due to denitrification reactions was observed at one site (AC-1), as indicated by elevated concentrations of nitrogen gas and a corresponding increase in nitrogen isotope (d15N-NO3) values with a decrease in nitrate concentrations. Denitrification is unlikely at other sites based on the presence of dissolved oxygen concentrations greater than 2 mg/L in ground water and no observed trend between nitrate concentrations and values d15N-NO3 values. Nitrate was the dominant nitrogen species in most monthly rainfall samples; however, ammonium concentrations were similar or greater than nitrate during November and December 1998. During February through May 1999, both nitrate and ammonium concentrations were substantially higher in monthly rainfall samples collected at the study area compared to mean monthly concentrations at the Bradford Forest site located east of the study area, which is part of the National Atmospheric Deposition Program/National Trends Network. Also, higher nitrogen deposition rates in the study area compared to those at Bradford Forest could indicate that substantial amounts of ammonia are volatilized from fertilizers and animal wastes, released to the atmosphere, and incorporated as nitrate and ammonium in rainfall deposited in the middle Suwannee River Basin. Ground-water samples from most sites had d15N-NO3 values that indicated a mixture of inorganic and organic sources of nitrogen, which corresponded to multiple land uses where both synthetic fertilizers and manure are used on fields near these sites. Distinct d15N-NO3 signatures, however, were observed at some sites. For example, water samples from areas of row-crop farmin

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.

[Epiphytic algae from Bajo Pepito, Isla Mujeres, Quintana Roo, Mexico].

PubMed

Quan-Young, L I; Díaz-Martín, M A; Espinoza-Avalos, J

2006-06-01

A total of 96 epiphytic algae species were identified from Bajo Pepito, Quintana Roo, México. 60.4% (58) belonged to the Rhodophyta, 19.79% (19) to the Phaeophyta, 16.6% (16) to the Chlorophyta and 3.1% (3) to the Cyanophyta; 49 species (50.5%) were found only in one month, while Heterosiphonia crispella was found in all of the sampled months. That species provided the largest contribution to the biomass of epiphytes. During January we registered the greater biommass and richness of epiphytes species, coincidently with high values of host species cover and rainfall.

Water resources of the Yap Islands

USGS Publications Warehouse

Van der Brug, Otto

1984-01-01

The Yap Islands consist of four major islands, Yap, Gagil-Tamil, Maap, and Rumung. Of these, Yap Island has more than half the total land area, most of the population, and almost all of the economic development. The islands of Maap and Rumung together compose only 15 percent of the land area and population. Average annual rainfall over the Yap Islands amounts to 122 inches. Rainfall-runoff comparisons indicate that about half of the annual rainfall runs off to the ocean on Yap Island and Gagil-Tamil. Streams on Gagil-Tamil are perennial but streams on Yap Island are dry an average of 3 months per year due to geologic differences. Analyses of water samples from 23 sources show the good quality and the chemical similarity of surface and ground water. This report summarizes the hydrologic data collected and provides interpretations that can be used by the planning and public works officials of Yap to make decisions concerning development and management of their water resources.

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

USGS Publications Warehouse

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

2015-01-01

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

Seasonal distribution of gastrointestinal nematode infections in sheep in a semiarid region, northeastern Brazil.

PubMed

de Souza, Maria de Fátima; Pimentel-Neto, Manoel; de Pinho, André Luís Santos; da Silva, Rízia Maria; Farias, Albeísa Cleyse Batista; Guimarães, Marcos Pezzi

2013-01-01

The objective of this study was to determine the seasonal distribution and gastrointestinal nematode parasite load in crossbred Santa Inês tracer lambs, and to correlate the rainfall during the study period with occurrences of parasitic infections. Sixty-four male tracer lambs between the ages of four and eight months were used in the study. Two tracer lambs were inserted into the herd every 28 days to determine the pattern of infective larvae available in the environment. Variation in the fecal egg count (FEC) of nematodes was observed at the study site, with many samples containing undetectable parasite loads during the dry season. The larvae identified in coprocultures were Haemonchus sp., Trichostrongylus sp., Cooperia sp., Strongyloides sp. and Oesophagostomum sp. The nematodes recovered at necropsy were Haemonchus contortus, Trichostrongylus colubriformis, Cooperia punctata, C. pectinata, Trichuris sp., Oesophagostomum sp. and Skrajabinema ovis. The total number of larvae and the total number of immature and adult forms recovered from the tracers showed seasonal distributions that significantly correlated with the amount of rainfall received that month (p value ≅ 0.000 in all cases ). The species H. contortus was predominant in the herd and should be considered to be main pathogenic nematode species in these hosts under these conditions.

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments

NASA Astrophysics Data System (ADS)

Schepen, Andrew; Zhao, Tongtiegang; Wang, Quan J.; Robertson, David E.

2018-03-01

Rainfall forecasts are an integral part of hydrological forecasting systems at sub-seasonal to seasonal timescales. In seasonal forecasting, global climate models (GCMs) are now the go-to source for rainfall forecasts. For hydrological applications however, GCM forecasts are often biased and unreliable in uncertainty spread, and calibration is therefore required before use. There are sophisticated statistical techniques for calibrating monthly and seasonal aggregations of the forecasts. However, calibration of seasonal forecasts at the daily time step typically uses very simple statistical methods or climate analogue methods. These methods generally lack the sophistication to achieve unbiased, reliable and coherent forecasts of daily amounts and seasonal accumulated totals. In this study, we propose and evaluate a Rainfall Post-Processing method for Seasonal forecasts (RPP-S), which is based on the Bayesian joint probability modelling approach for calibrating daily forecasts and the Schaake Shuffle for connecting the daily ensemble members of different lead times. We apply the method to post-process ACCESS-S forecasts for 12 perennial and ephemeral catchments across Australia and for 12 initialisation dates. RPP-S significantly reduces bias in raw forecasts and improves both skill and reliability. RPP-S forecasts are also more skilful and reliable than forecasts derived from ACCESS-S forecasts that have been post-processed using quantile mapping, especially for monthly and seasonal accumulations. Several opportunities to improve the robustness and skill of RPP-S are identified. The new RPP-S post-processed forecasts will be used in ensemble sub-seasonal to seasonal streamflow applications.

Relationships between High Impact Tropical Rainfall Events and Environmental Conditions

NASA Astrophysics Data System (ADS)

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

2017-12-01

While rainfall increases as moisture and vertical motion increase, relationships between regional environmental conditions and rainfall event characteristics remain more uncertain. Of particular importance are long duration, heavy rain rate, and significant accumulation events that contribute sizable fractions of overall precipitation over short time periods. This study seeks to establish relationships between observed rainfall event properties and environmental conditions. Event duration, rain rate, and rainfall accumulation are derived using the Tropical Rainfall Measuring Mission (TRMM) 3B42 3-hourly, 0.25° resolution rainfall retrieval from 2002-2013 between 10°N and 10°S. Events are accumulated into 2.5° grid boxes and matched to monthly mean total column water vapor (TCWV) and 500-hPa vertical motion (omega) in each 2.5° grid box, retrieved from ERA-interim reanalysis. Only months with greater than 3 mm/day rainfall are included to ensure sufficient sampling. 90th and 99th percentile oceanic events last more than 20% longer and have rain rates more than 20% lower than those over land for a given TCWV-omega condition. Event duration and accumulation are more sensitive to omega than TCWV over oceans, but more sensitive to TCWV than omega over land, suggesting system size, propagation speed, and/or forcing mechanism differences for land and ocean regions. Sensitivities of duration, rain rate, and accumulation to TCWV and omega increase with increasing event extremity. For 3B42 and ERA-Interim relationships, the 90th percentile oceanic event accumulation increases by 0.93 mm for every 1 Pa/min change in rising motion, but this increases to 3.7 mm for every 1 Pa/min for the 99th percentile. Over land, the 90th percentile event accumulation increases by 0.55 mm for every 1 mm increase in TCWV, whereas the 99th percentile increases by 0.90 mm for every 1 mm increase in TCWV. These changes in event accumulation are highly correlated with changes in event duration. Relationships between 3B42 event properties and ERA-Interim environmental conditions are currently being evaluated using the MERRA-2 reanalysis and two years of 30-minute, 0.1° Integrated Multi-satellitE Retrievals for GPM (IMERG) data. If results remain consistent, they may be valuable for evaluating weather and climate models.

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.

Rainfall variability over the tropical Pacific from July 1987 through December 1991 as inferred via monthly estimates from SSM/I

NASA Technical Reports Server (NTRS)

Berg, Wesley; Avery, Susan K.

1994-01-01

Estimates of monthly rainfall have been computed over the tropical Pacific using passive microwave satellite observations from the Special Sensor Microwave/Imager (SSM/I) for the preiod from July 1987 through December 1991. The monthly estimates were calibrated using measurements from a network of Pacific atoll rain gauges and compared to other satellite-based rainfall estimation techniques. Based on these monthly estimates, an analysis of the variability of large-scale features over intraseasonal to interannual timescales has been performed. While the major precipitation features as well as the seasonal variability distributions show good agreement with expected values, the presence of a moderately intense El Nino during 1986-87 and an intense La Nina during 1988-89 highlights this time period.

Hurricane Impact on Seepage Water in Larga Cave, Puerto Rico

NASA Astrophysics Data System (ADS)

Vieten, Rolf; Warken, Sophie; Winter, Amos; Schröder-Ritzrau, Andrea; Scholz, Denis; Spötl, Christoph

2018-03-01

Hurricane-induced rainfall over Puerto Rico has characteristic δ18O values which are more negative than local rainfall events. Thus, hurricanes may be recorded in speleothems from Larga cave, Puerto Rico, as characteristic oxygen isotope excursions. Samples of 84 local rainfall events between 2012 and 2013 ranged from -6.2 to +0.3‰, whereas nine rainfall samples belonging to a rainband of hurricane Isaac (23-24 August 2012) ranged from -11.8 to -7.1‰. Cave monitoring covered the hurricane season of 2014 and investigated the impact of hurricane rainfall on drip water chemistry. δ18O values were measured in cumulative monthly rainwater samples above the cave. Inside the cave, δ18O values of instantaneous drip water samples were analyzed and drip rates were recorded at six drip sites. Most effective recharge appears to occur during the wet months (April-May and August-November). δ18O values of instantaneous drip water samples ranged from -3.5 to -2.4‰. In April 2014 and April 2015 some drip sites showed more negative δ18O values than the effective rainfall (-2.9‰), implying an influence of hurricane rainfall reaching the cave via stratified seepage flow months to years after the event. Speleothems from these drip sites in Larga cave have a high potential for paleotempestology studies.

Response of transpiration to rain pulses for two tree species in a semiarid plantation.

PubMed

Chen, Lixin; Zhang, Zhiqiang; Zeppel, Melanie; Liu, Caifeng; Guo, Junting; Zhu, Jinzhao; Zhang, Xuepei; Zhang, Jianjun; Zha, Tonggang

2014-09-01

Responses of transpiration (Ec) to rain pulses are presented for two semiarid tree species in a stand of Pinus tabulaeformis and Robinia pseudoacacia. Our objectives are to investigate (1) the environmental control over the stand transpiration after rainfall by analyzing the effect of vapor pressure deficit (VPD), soil water condition, and rainfall on the post-rainfall Ec development and recovery rate, and (2) the species responses to rain pulses and implications on vegetation coverage under a changing rainfall regime. Results showed that the sensitivity of canopy conductance (Gc) to VPD varied under different incident radiation and soil water conditions, and the two species exhibited the same hydraulic control (-dG c/dlnVPD to Gcref ratio) over transpiration. Strengthened physiological control and low sapwood area of the stand contributed to low Ec. VPD after rainfall significantly influenced the magnitude and time series of post-rainfall stand Ec. The fluctuation of post-rainfall VPD in comparison with the pre-rainfall influenced the Ec recovery. Further, the stand Ec was significantly related to monthly rainfall, but the recovery was independent of the rainfall event size. Ec enhanced with cumulative soil moisture change (ΔVWC) within each dry-wet cycle, yet still was limited in large rainfall months. The two species had different response patterns of post-rainfall Ec recovery. Ec recovery of P. tabulaeformis was influenced by the pre- and post-rainfall VPD differences and the duration of rainless interval. R. pseudoacacia showed a larger immediate post-rainfall Ec increase than P. tabulaeformis did. We, therefore, concluded that concentrated rainfall events do not trigger significant increase of transpiration unless large events penetrate the deep soil and the species differences of Ec in response to pulses of rain may shape the composition of semiarid woodlands under future rainfall regimes.

Rainfall erosivity factor estimation in Republic of Moldova

NASA Astrophysics Data System (ADS)

Castraveš, Tudor; Kuhn, Nikolaus

2017-04-01

Rainfall erosivity represents a measure of the erosive force of rainfall. Typically, it is expressed as variable such as the R factor in the Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1965, 1978) or its derivates. The rainfall erosivity index for a rainfall event (EI30) is calculated from the total kinetic energy and maximum 30 minutes intensity of individual events. However, these data are often unavailable for wide regions and countries. Usually, there are three issues regarding precipitation data: low temporal resolution, low spatial density and limited access to the data. This is especially true for some of postsoviet countries from Eastern Europe, such as Republic of Moldova, where soil erosion is a real and persistent problem (Summer, 2003) and where soils represents the main natural resource of the country. Consequently, researching and managing soil erosion is particularly important. The purpose of this study is to develop a model based on commonly available rainfall data, such as event, daily or monthly amounts, to calculate rainfall erosivity for the territory of Republic of Moldova. Rainfall data collected during 1994-2015 period at 15 meteorological stations in the Republic of Moldova, with 10 minutes temporal resolution, were used to develop and calibrate a model to generate an erosivity map of Moldova. References 1. Summer, W., (2003). Soil erosion in the Republic of Moldova — the importance of institutional arrangements. Erosion Prediction in Ungauged Basins: Integrating Methods and Techniques (Proceedings of symposium HS01 held during IUGG2003 at Sapporo. July 2003). IAHS Publ. no. 279. 2. Wischmeier, W.H., and Smith, D.D. (1965). Predicting rainfall-erosion losses from cropland east of the Rocky Mountains. Agr. Handbook No. 282, U.S. Dept. Agr., Washington, DC 3. Wischmeier, W.H., and Smith, D.D. (1978). Predicting rainfall erosion losses. Agr. handbook No. 537, U.S. Dept. of Agr., Science and Education Administration.

Pollen Concentration in the Atmosphere of Abha City, Saudi Arabia and its Relationship with Meteorological Parameters

NASA Astrophysics Data System (ADS)

Alwadie, Hussein M.

A qualitative and quantitative evaluation of pollen concentration in the atmosphere of Abha city, Saudi Arabia with the relation to meteorological parameters is presented. Investigations were undertaken from January to December 2006 using a Burkard 7 day volumetric spore trap. A total of 6,492 pollen grains m-3 belonging to 50 pollen taxa was detected. Poaceae represented 55.1% of total pollen, Leguminosae (11.7%), Compositae (6.1%), Solanaceae (4.6%) and Cupressaceae (4.2%). Pollen grains were found throughout the year. July represented the highest peak of pollen number and also the highest pollen taxa. The monthly variation of pollen taxa and their relationship to meteorological parameters were investigated. It was found that the pollen concentration is positively correlated with temperature and negatively correlated with rainfall, relative humidity and wind velocity. May-September represented the months of highest pollen number (95% of total pollen).

Hydrologic and water-quality data, Honey Creek State Natural Area, Comal County, Texas, August 2001-September 2003

USGS Publications Warehouse

Slattery, Richard N.; Furlow, Allen L.; Ockerman, Darwin J.

2006-01-01

The U.S. Geological Survey collected rainfall, streamflow, evapotranspiration, and rainfall and stormflow water-quality data from seven sites in two adjacent watersheds in the Honey Creek State Natural Area, Comal County, Texas, during August 2001–September 2003, in cooperation with the U.S. Department of Agriculture, Natural Resources Conservation Service, and the San Antonio Water System. Data collected during this period represent baseline hydrologic and water-quality conditions before proposed removal of ashe juniper (Juniperus ashei) from one of the two watersheds. Juniper removal is intended as a best-management practice to increase water quantity (aquifer recharge and streamflow) and to protect water quality. Continuous (5-minute interval) rainfall data are collected at four sites; continuous (5-minute interval) streamflow data are collected at three sites. Fifteen-minute averages of meteorological and solar-energy-related data recorded at two sites are used to compute moving 30-minute evapotranspiration values on the basis of the energy-balance Bowen ratio method. Periodic rainfall water-quality data are collected at one site and stormflow water-quality data at three sites. Daily rainfall, streamflow, and evapotranspiration totals are presented in tables; detailed data are listed in an appendix. Results of analyses of the periodic rainfall and stormflow water-quality samples collected during runoff events are summarized in the appendix; not all data types were collected at all sites nor were all data types collected during the entire 26-month period.

Prescribed fires effects on physico-chemical properties and quantity of runoff and soil erosion in a Mediterranean forest

NASA Astrophysics Data System (ADS)

Esteban Lucas-Borja, Manuel; Plaza Alvaréz, Pedro Antonio; Sagra, Javier; Alfaro Sánchez, Raquel; Moya, Daniel; Ferrandiz Gotor, Pablo; De las Heras Ibañez, Jorge

2017-04-01

Wildfires have an important influence in forest ecosystems. Contrary to high severity fire, which may have negative impacts on the ecosystems, low severity induce small changes on soil properties. Thus and in order to reduce fire risk, low-severity prescribed fires have been widely used as a fuel reduction tool and silvicultural treatment in Mediterranean forest ecosystems. However, fire may alter microsite conditions and little is known about the impact of prescribed burning on the physico-chemical properties of runoff. In this study, we compared the effects of prescribed burning on physico-chemical properties and quantity of runoff and soil erosion during twelve months after a low severity prescribed fire applied in twelve 16 m2 plot (6 burned plots and 6 control plots used for comparison) set up in the Lezuza forest (Albacete, central-eastern Spain). Physico-chemical properties and quantity of runoff and soil losses were monitored after each rainfall event (five rainfall events in total). Also, different forest stand characteristics (slope, tree density, basal area and shrub/herbal cover) affecting each plot were measured. Results showed that forest stand characteristics were very similar in all used plots. Also, physico-chemical runoff properties were highly modified after the prescribed fire, increasing water pH, carbonates, bicarbonates, total dissolved solids and organic matter content dissolved in water. Electrical conductivity, calcium, sodium, chloride and magnesium were not affected by prescribed fire. Soil losses were highly related to precipitation intensity and tree interception. Tree intercepted the rainfall and significantly reduced soil losses and also runoff quantity. In conclusion and after the first six-month experiment, the influence of prescribed fires on physico-chemical runoff properties should be taken into account for developing proper prescribed burnings guidelines.

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

Romney, E.M.; Wallace, A.; Hunter, R.B.

New Artemisia seedlings are not established each year. Many that are established fail to survive because of unfavorable rainfall in succeeding years. A total of 184 young plants was examined for the number of annual growth rings to ascertain the year of establishment after all vegetation had been killed near the time of a nuclear test event in 1965. The three most important recent years for establishment and survival of new seedlings (as of 1976 and based on a sample of 184 plants) were 1966 (9 percent), 1969 (29%), and 1973 (36%). A total of 27% was established in themore » other years from 1965 to 1976. These three years were also the years with high rainfall input during preceding winter and spring months. If old plants are killed, seeds germinate with much lower inputs of precipitation. Many seedlings germinated in 1968 at a site where old ones had been burned off even though the rainfall was not favorable. Plants of a given age varied greatly in size according to their competition. Seedlings germinating in old stands grew little in comparison with those germinating in areas where old plants had been killed. One exception was an area where intense competition occurred due to large numbers of new plants, resulting in growth restriction on all plants.« less

Global warming and South Indian monsoon rainfall-lessons from the Mid-Miocene.

PubMed

Reuter, Markus; Kern, Andrea K; Harzhauser, Mathias; Kroh, Andreas; Piller, Werner E

2013-04-01

Precipitation over India is driven by the Indian monsoon. Although changes in this atmospheric circulation are caused by the differential seasonal diabatic heating of Asia and the Indo-Pacific Ocean, it is so far unknown how global warming influences the monsoon rainfalls regionally. Herein, we present a Miocene pollen flora as the first direct proxy for monsoon over southern India during the Middle Miocene Climate Optimum. To identify climatic key parameters, such as mean annual temperature, warmest month temperature, coldest month temperature, mean annual precipitation, mean precipitation during the driest month, mean precipitation during the wettest month and mean precipitation during the warmest month the Coexistence Approach is applied. Irrespective of a ~ 3-4 °C higher global temperature during the Middle Miocene Climate Optimum, the results indicate a modern-like monsoonal precipitation pattern contrasting marine proxies which point to a strong decline of Indian monsoon in the Himalaya at this time. Therefore, the strength of monsoon rainfall in tropical India appears neither to be related to global warming nor to be linked with the atmospheric conditions over the Tibetan Plateau. For the future it implies that increased global warming does not necessarily entail changes in the South Indian monsoon rainfall.

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.

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.

Historical analysis of interannual rainfall variability and trends in southeastern Brazil based on observational and remotely sensed data

NASA Astrophysics Data System (ADS)

Vásquez P., Isela L.; de Araujo, Lígia Maria Nascimento; Molion, Luiz Carlos Baldicero; de Araujo Abdalad, Mariana; Moreira, Daniel Medeiros; Sanchez, Arturo; Barbosa, Humberto Alves; Rotunno Filho, Otto Corrêa

2018-02-01

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

Analysis and prediction of rainfall trends over Bangladesh using Mann-Kendall, Spearman's rho tests and ARIMA model

NASA Astrophysics Data System (ADS)

Rahman, Mohammad Atiqur; Yunsheng, Lou; Sultana, Nahid

2017-08-01

In this study, 60-year monthly rainfall data of Bangladesh were analysed to detect trends. Modified Mann-Kendall, Spearman's rho tests and Sen's slope estimators were applied to find the long-term annual, dry season and monthly trends. Sequential Mann-Kendall analysis was applied to detect the potential trend turning points. Spatial variations of the trends were examined using inverse distance weighting (IDW) interpolation. AutoRegressive integrated moving average (ARIMA) model was used for the country mean rainfall and for other two stations data which depicted the highest and the lowest trend in the Mann-Kendall and Spearman's rho tests. Results showed that there is no significant trend in annual rainfall pattern except increasing trends for Cox's Bazar, Khulna, Satkhira and decreasing trend for Srimagal areas. For the dry season, only Bogra area represented significant decreasing trend. Long-term monthly trends demonstrated a mixed pattern; both negative and positive changes were found from February to September. Comilla area showed a significant decreasing trend for consecutive 3 months while Rangpur and Khulna stations confirmed the significant rising trends for three different months in month-wise trends analysis. Rangpur station data gave a maximum increasing trend in April whereas a maximum decreasing trend was found in August for Comilla station. ARIMA models predict +3.26, +8.6 and -2.30 mm rainfall per year for the country, Cox's Bazar and Srimangal areas, respectively. However, all the test results and predictions revealed a good agreement among them in the study.

Soil moisture status in a set of rain-fed cereal fields: application of the DR2 model at monthly scale

NASA Astrophysics Data System (ADS)

López-Vicente, M.; Navas, A.

2012-04-01

One important issue in agricultural management and hydrological research is the assessment of water stored during a rainfall event. In this study, the new Distributed Rainfall-Runoff (DR2) model (López-Vicente and Navas, 2012) is used to estimate the volume of actual available water (Waa) and the soil moisture status (SMS) in a set of rain-fed cereal fields (65 ha) located in the Central Spanish Pre-Pyrenees. This model makes the most of GIS techniques (ArcMapTM 10.0) and distinguishes five configurations of the upslope contributing area, infiltration processes and climatic parameters. Results are presented on a monthly basis. The study site has a relatively long history (since the 10th century) of human occupation, agricultural practices and water management. The landscape is representative of the typical former rain-fed Mediterranean agro-ecosystem where small patches of natural and anthropogenic areas are heterogeneously distributed. Climate is continental Mediterranean with a dry summer with rainfall events of high intensity (I30max, higher than 30 mm / h between May and October). Average annual precipitation was 520 mm for the reference period (1961-1990), whereas the average precipitation during the last ten years (2001-2010) was 16% lower (439 mm). Measured antecedent topsoil moisture presented the highest values in autumn (18.3 vol.%) and the lowest in summer (11.2 vol.%). Values of potential overland flow per raster cell (Q0) during maximum rainfall intensity varied notably in terms of time and space. When rainfall intensity is high (May, August, September and October), potential runoff was predicted along the surface of the crops and variability of Q0 was very low, whereas areas with no runoff production appeared when rainfall intensity was low and variability of Q0 values was high. A variance components analysis shows that values of Q0 are mainly explained by variations in the values of saturated hydraulic conductivity (76% of the variability of Q0) and, to a lesser extent, by the values of the antecedent topsoil moisture (23%) and the volumetric content of water of the soil at saturation (1%). Maps of monthly actual available water after maximum rainfall intensity presented a significant spatial variability, though values varied as a function of total rainfall depth and infiltration, and the five different scenarios of cumulative processes considered on the DR2 model. The minimum value of Waa for each month was well correlated with the average values of precipitation (Pearson's r = 0.86), whereas the mean values of Waa showed a close correlation with the values of maximum rainfall intensity (Pearson's r = 0.92). Maps of SMS and their values were reclassified in seven wetness-dryness categories. Predominant wet conditions occurred in May, September, October, November and December, whereas dry conditions appeared in February, March and July. Drying-up conditions were identified in January and June and wetting-up conditions occurred in April and August. The new DR2 model seems to be of interest to monitor humidity variations and trends in time and space in Mediterranean agricultural systems and can provide valuable information for sustainable soil and water resource management in agro-climatic analysis.

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.

Long-term flow forecasts based on climate and hydrologic modeling: Uruguay River basin

NASA Astrophysics Data System (ADS)

Tucci, Carlos Eduardo Morelli; Clarke, Robin Thomas; Collischonn, Walter; da Silva Dias, Pedro Leite; de Oliveira, Gilvan Sampaio

2003-07-01

This paper describes a procedure for predicting seasonal flow in the Rio Uruguay drainage basin (area 75,000 km2, lying in Brazilian territory), using sequences of future daily rainfall given by the global climate model (GCM) of the Brazilian agency for climate prediction (Centro de Previsão de Tempo e Clima, or CPTEC). Sequences of future daily rainfall given by this model were used as input to a rainfall-runoff model appropriate for large drainage basins. Forecasts of flow in the Rio Uruguay were made for the period 1995-2001 of the full record, which began in 1940. Analysis showed that GCM forecasts underestimated rainfall over almost all the basin, particularly in winter, although interannual variability in regional rainfall was reproduced relatively well. A statistical procedure was used to correct for the underestimation of rainfall. When the corrected rainfall sequences were transformed to flow by the hydrologic model, forecasts of flow in the Rio Uruguay basin were better than forecasts based on historic mean or median flows by 37% for monthly flows and by 54% for 3-monthly flows.

Predicting monthly precipitation along coastal Ecuador: ENSO and transfer function models

NASA Astrophysics Data System (ADS)

de Guenni, Lelys B.; García, Mariangel; Muñoz, Ángel G.; Santos, José L.; Cedeño, Alexandra; Perugachi, Carlos; Castillo, José

2017-08-01

It is well known that El Niño-Southern Oscillation (ENSO) modifies precipitation patterns in several parts of the world. One of the most impacted areas is the western coast of South America, where Ecuador is located. El Niño events that occurred in 1982-1983, 1987-1988, 1991-1992, and 1997-1998 produced important positive rainfall anomalies in the coastal zone of Ecuador, bringing considerable damage to livelihoods, agriculture, and infrastructure. Operational climate forecasts in the region provide only seasonal scale (e.g., 3-month averages) information, but during ENSO events it is key for decision-makers to use reliable sub-seasonal scale forecasts, which at the present time are still non-existent in most parts of the world. This study analyzes the potential predictability of coastal Ecuador rainfall at monthly scale. Instead of the discrete approach that considers training models using only particular seasons, continuous (i.e., all available months are used) transfer function models are built using standard ENSO indices to explore rainfall forecast skill along the Ecuadorian coast and Galápagos Islands. The modeling approach considers a large-scale contribution, represented by the role of a sea-surface temperature index, and a local-scale contribution represented here via the use of previous precipitation observed in the same station. The study found that the Niño3 index is the best ENSO predictor of monthly coastal rainfall, with a lagged response varying from 0 months (simultaneous) for Galápagos up to 3 months for the continental locations considered. Model validation indicates that the skill is similar to the one obtained using principal component regression models for the same kind of experiments. It is suggested that the proposed approach could provide skillful rainfall forecasts at monthly scale for up to a few months in advance.

Variations in Precipitation Parameters between Drought and Nondrought Periods in Texas and Some Implications for Cloud Seeding.

NASA Astrophysics Data System (ADS)

Flynn, Michael S.; Griffiths, John F.

1980-12-01

An analysis of the possible differences among various rainfall parameters during drought and nondrought periods was undertaken for 12 Texas stations. The division of monthly rainfall amounts into quintiles served as the rainfall classification. Rainfall amounts, number of rains and rainfall intensities were calculated for each quintile for four thresholds of rainfall 0.0254, 0.2540, 0.5080 and 1.2700 cm. The thresholds were applied on a daily and hourly basis. At low rainfall thresholds in nearly every case, numbers of rains in very dry periods proved to be <100% of normal.The possible differences in persistence of rainfall during Very Dry and Very Wet periods were examined by calculating runs of rains of 0.0254 cm or more per hour. Medians of runs of rain hours in Very Dry periods were found to be less than those in Very Wet periods except at Corpus Christi in April and at Waco in February. Probabilities that a run of rain hours would extend to a given length were determined. During Very Dry periods a probability >0.5 that a rain will extend into a second hour during a month of key importance to agriculture (June, July and August) occurs only at Amarillo, Lovelady, Port Arthur and Waco. The probability that a rain will extend into a third hour is never above 0.5 during the key months in Very Dry periods for any of the stations studied.The implications of these findings are discussed in relation to feasibility of cloud seeding and to irrigation management during severe drought.

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.

Comparison of TOPMODEL streamflow simulations using NEXRAD-based and measured rainfall data, McTier Creek watershed, South Carolina

USGS Publications Warehouse

Feaster, Toby D.; Westcott, Nancy E.; Hudson, Robert J.M.; Conrads, Paul; Bradley, Paul M.

2012-01-01

Rainfall is an important forcing function in most watershed models. As part of a previous investigation to assess interactions among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations in the Edisto River Basin, the topography-based hydrological model (TOPMODEL) was applied in the McTier Creek watershed in Aiken County, South Carolina. Measured rainfall data from six National Weather Service (NWS) Cooperative (COOP) stations surrounding the McTier Creek watershed were used to calibrate the McTier Creek TOPMODEL. Since the 1990s, the next generation weather radar (NEXRAD) has provided rainfall estimates at a finer spatial and temporal resolution than the NWS COOP network. For this investigation, NEXRAD-based rainfall data were generated at the NWS COOP stations and compared with measured rainfall data for the period June 13, 2007, to September 30, 2009. Likewise, these NEXRAD-based rainfall data were used with TOPMODEL to simulate streamflow in the McTier Creek watershed and then compared with the simulations made using measured rainfall data. NEXRAD-based rainfall data for non-zero rainfall days were lower than measured rainfall data at all six NWS COOP locations. The total number of concurrent days for which both measured and NEXRAD-based data were available at the COOP stations ranged from 501 to 833, the number of non-zero days ranged from 139 to 209, and the total difference in rainfall ranged from -1.3 to -21.6 inches. With the calibrated TOPMODEL, simulations using NEXRAD-based rainfall data and those using measured rainfall data produce similar results with respect to matching the timing and shape of the hydrographs. Comparison of the bias, which is the mean of the residuals between observed and simulated streamflow, however, reveals that simulations using NEXRAD-based rainfall tended to underpredict streamflow overall. Given that the total NEXRAD-based rainfall data for the simulation period is lower than the total measured rainfall at the NWS COOP locations, this bias would be expected. Therefore, to better assess the use of NEXRAD-based rainfall estimates as compared to NWS COOP rainfall data on the hydrologic simulations, TOPMODEL was recalibrated and updated simulations were made using the NEXRAD-based rainfall data. Comparisons of observed and simulated streamflow show that the TOPMODEL results using measured rainfall data and NEXRAD-based rainfall are comparable. Nonetheless, TOPMODEL simulations using NEXRAD-based rainfall still tended to underpredict total streamflow volume, although the magnitude of differences were similar to the simulations using measured rainfall. The McTier Creek watershed was subdivided into 12 subwatersheds and NEXRAD-based rainfall data were generated for each subwatershed. Simulations of streamflow were generated for each subwatershed using NEXRAD-based rainfall and compared with subwatershed simulations using measured rainfall data, which unlike the NEXRAD-based rainfall were the same data for all subwatersheds (derived from a weighted average of the six NWS COOP stations surrounding the basin). For the two simulations, subwatershed streamflow were summed and compared to streamflow simulations at two U.S. Geological Survey streamgages. The percentage differences at the gage near Monetta, South Carolina, were the same for simulations using measured rainfall data and NEXRAD-based rainfall. At the gage near New Holland, South Carolina, the percentage differences using the NEXRAD-based rainfall were twice as much as those using the measured rainfall. Single-mass curve comparisons showed an increase in the total volume of rainfall from north to south. Similar comparisons of the measured rainfall at the NWS COOP stations showed similar percentage differences, but the NEXRAD-based rainfall variations occurred over a much smaller distance than the measured rainfall. Nonetheless, it was concluded that in some cases, using NEXRAD-based rainfall data in TOPMODEL streamflow simulations may provide an effective alternative to using measured rainfall data. For this investigation, however, TOPMODEL streamflow simulations using NEXRAD-based rainfall data for both calibration and simulations did not show significant improvements with respect to matching observed streamflow over simulations generated using measured rainfall data.

Climatological Processing of Radar Data for the TRMM Ground Validation Program

NASA Technical Reports Server (NTRS)

Kulie, Mark; Marks, David; Robinson, Michael; Silberstein, David; Wolff, David; Ferrier, Brad; Amitai, Eyal; Fisher, Brad; Wang, Jian-Xin; Augustine, David;

Rainfall Type as a Dominant Control of the Isotopic Composition of Precipitation in the South Central United States

NASA Astrophysics Data System (ADS)

Sun, C.; Shanahan, T. M.; Partin, J. W.

2017-12-01

The processes that control the isotopic composition of precipitation in the mid-latitudes are understudied compared to the high and low latitudes, but are critical for interpreting paleo records using isotope proxies. To better understand these processes, we investigated changes of isotopic composition of rainwater in Central Texas using 20 months of event-based rainwater collection. We find that in both the event-based data and the monthly data from the Waco GNIP station, the dominant control on the isotopic composition of precipitation is the proportion that is derived from convective systems. This finding is consistent with previously reported data largely from tropical localities (Aggarwal et al., 2016), where large organized convective systems lead to high rainfall amounts and isotopically depleted precipitation. Although there are seasonal differences in the dominant rainfall types over the South Central US, with winter precipitation almost entirely stratiform, seasonality plays very little role in the net isotopic composition of precipitation because the total contribution during winter is small compared with spring, summer and fall. We also find that changes of source have little effect on the isotopic composition of rainfall, as the majority of the moisture is derived from the Gulf of Mexico with little influence of reevaporation or mixing. The majority of the warm season precipitation in the South Central US occurs in association with mesoscale convective systems (MCSs) and the development of these systems plays a critical role in the overall isotopic signature of precipitation. MCSs are characterized by a combination of intense, organized convection at their leading edges and trailing stratiform precipitation. Larger MCSs tend to contain higher proportions of stratiform rainfall and as a result, have isotopically depleted values. Proxy records from this region displaying more negative isotope values in the past should therefore be interpreted with caution as they could reflect either increases in cool versus warm season precipitation or changes in the intensity of warm season MCSs.

Improving rainfall representation for large-scale hydrological modelling of tropical mountain basins

NASA Astrophysics Data System (ADS)

Zulkafli, Zed; Buytaert, Wouter; Onof, Christian; Lavado, Waldo; Guyot, Jean-Loup

2013-04-01

Errors in the forcing data are sometimes overlooked in hydrological studies even when they could be the most important source of uncertainty. The latter particularly holds true in tropical countries with short historical records of rainfall monitoring and remote areas with sparse rain gauge network. In such instances, alternative data such as the remotely sensed precipitation from the TRMM (Tropical Rainfall Measuring Mission) satellite have been used. These provide a good spatial representation of rainfall processes but have been established in the literature to contain volumetric biases that may impair the results of hydrological modelling or worse, are compensated during model calibration. In this study, we analysed precipitation time series from the TMPA (TRMM Multiple Precipitation Algorithm, version 6) against measurements from over 300 gauges in the Andes and Amazon regions of Peru and Ecuador. We found moderately good monthly correlation between the pixel and gauge pairs but a severe underestimation of rainfall amounts and wet days. The discrepancy between the time series pairs is particularly visible over the east side of the Andes and may be attributed to localized and orographic-driven high intensity rainfall, which the satellite product may have limited skills at capturing due to technical and scale issues. This consequently results in a low bias in the simulated streamflow volumes further downstream. In comparison, with the recently released TMPA, version 7, the biases reduce. This work further explores several approaches to merge the two sources of rainfall measurements, each of a different spatial and temporal support, with the objective of improving the representation of rainfall in hydrological simulations. The methods used are (1) mean bias correction (2) data assimilation using Kalman filter Bayesian updating. The results are evaluated by means of (1) a comparison of runoff ratios (the ratio of the total runoff and the total precipitation over an extended period) in multiple basins, and (2) a comparison of the outcome of hydrological modelling using the distributed JULES (Joint-UK Land Environment Simulator) land surface model. First results indicate an improvement in the water balance that directly translates into an increased hydrological performance. The more interesting aspect of the study, however, will be the insights into the nature of satellite precipitation errors in this extreme environment and the optimal means of improving the data to generate increased confidence in hydrological predictions.

Characterization and disaggregation of daily rainfall in the Upper Blue Nile Basin in Ethiopia

NASA Astrophysics Data System (ADS)

Engida, Agizew N.; Esteves, Michel

2011-03-01

SummaryIn Ethiopia, available rainfall records are mainly limited to daily time steps. Though rainfall data at shorter time steps are important for various purposes like modeling of erosion processes and flood hydrographs, they are hardly available in Ethiopia. The objectives of this study were (i) to study the temporal characteristics of daily rains at two stations in the region of the Upper Blue Nile Basin (UBNB) and (ii) to calibrate and evaluate a daily rainfall disaggregation model. The analysis was based on rainfall data of Bahir Dar and Gonder Meteorological Stations. The disaggregation model used was the Modified Bartlett-Lewis Rectangular Pulse Model (MBLRPM). The mean daily rainfall intensity varied from about 4 mm in the dry season to 17 mm in the wet season with corresponding variation in raindays of 0.4-26 days. The observed maximum daily rainfall varied from 13 mm in the dry month to 200 mm in the wet month. The average wet/dry spell length varied from 1/21 days in the dry season to 6/1 days in the rainy season. Most of the rainfall occurs in the afternoon and evening periods of the day. Daily rainfall disaggregation using the MBLRPM alone resulted in poor match between the disaggregated and observed hourly rainfalls. Stochastic redistribution of the outputs of the model using Beta probability distribution function improved the agreement between observed and calculated hourly rain intensities. In areas where convective rainfall is dominant, the outputs of MBLRPM should be redistributed using relevant probability distributions to simulate the diurnal rainfall pattern.

Drought Analysis for Kuwait Using Standardized Precipitation Index

PubMed Central

2014-01-01

Implementation of adequate measures to assess and monitor droughts is recognized as a major matter challenging researchers involved in water resources management. The objective of this study is to assess the hydrologic drought characteristics from the historical rainfall records of Kuwait with arid environment by employing the criterion of Standardized Precipitation Index (SPI). A wide range of monthly total precipitation data from January 1967 to December 2009 is used for the assessment. The computation of the SPI series is performed for intermediate- and long-time scales of 3, 6, 12, and 24 months. The drought severity and duration are also estimated. The bivariate probability distribution for these two drought characteristics is constructed by using Clayton copula. It has been shown that the drought SPI series for the time scales examined have no systematic trend component but a seasonal pattern related to rainfall data. The results are used to perform univariate and bivariate frequency analyses for the drought events. The study will help evaluating the risk of future droughts in the region, assessing their consequences on economy, environment, and society, and adopting measures for mitigating the effect of droughts. PMID:25386598

Flood risk reduction and flow buffering as ecosystem services - Part 2: Land use and rainfall intensity effects in Southeast Asia

NASA Astrophysics Data System (ADS)

van Noordwijk, Meine; Tanika, Lisa; Lusiana, Betha

2017-05-01

Watersheds buffer the temporal pattern of river flow relative to the temporal pattern of rainfall. This ecosystem service is inherent to geology and climate, but buffering also responds to human use and misuse of the landscape. Buffering can be part of management feedback loops if salient, credible and legitimate indicators are used. The flow persistence parameter Fp in a parsimonious recursive model of river flow (Part 1, van Noordwijk et al., 2017) couples the transmission of extreme rainfall events (1 - Fp), to the annual base-flow fraction of a watershed (Fp). Here we compare Fp estimates from four meso-scale watersheds in Indonesia (Cidanau, Way Besai and Bialo) and Thailand (Mae Chaem), with varying climate, geology and land cover history, at a decadal timescale. The likely response in each of these four to variation in rainfall properties (including the maximum hourly rainfall intensity) and land cover (comparing scenarios with either more or less forest and tree cover than the current situation) was explored through a basic daily water-balance model, GenRiver. This model was calibrated for each site on existing data, before being used for alternative land cover and rainfall parameter settings. In both data and model runs, the wet-season (3-monthly) Fp values were consistently lower than dry-season values for all four sites. Across the four catchments Fp values decreased with increasing annual rainfall, but specific aspects of watersheds, such as the riparian swamp (peat soils) in Cidanau reduced effects of land use change in the upper watershed. Increasing the mean rainfall intensity (at constant monthly totals for rainfall) around the values considered typical for each landscape was predicted to cause a decrease in Fp values by between 0.047 (Bialo) and 0.261 (Mae Chaem). Sensitivity of Fp to changes in land use change plus changes in rainfall intensity depends on other characteristics of the watersheds, and generalisations made on the basis of one or two case studies may not hold, even within the same climatic zone. A wet-season Fp value above 0.7 was achievable in forest-agroforestry mosaic case studies. Inter-annual variability in Fp is large relative to effects of land cover change. Multiple (5-10) years of paired-plot data would generally be needed to reject no-change null hypotheses on the effects of land use change (degradation and restoration). Fp trends over time serve as a holistic scale-dependent performance indicator of degrading/recovering watershed health and can be tested for acceptability and acceptance in a wider social-ecological context.

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

USGS Publications Warehouse

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

2002-01-01

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

Regional rainfall-runoff relations for simulation of streamflow for watersheds in Du Page County, Illinois

USGS Publications Warehouse

Duncker, James J.; Melching, Charles S.

1998-01-01

Rainfall and streamflow data collected from July 1986 through September 1993 were utilized to calibrate and verify a continuous-simulation rainfall-runoff model for three watersheds (11.8--18.0 square miles in area) in Du Page County. Classification of land cover into three categories of pervious (grassland, forest/wetland, and agricultural land) and one category of impervious subareas was sufficient to accurately simulate the rainfall-runoff relations for the three watersheds. Regional parameter sets were obtained by calibrating jointly all parameters except fraction of ground-water inflow that goes to inactive ground water (DEEPFR), interflow recession constant (IRC), and infiltration (INFILT) for runoff from all three watersheds. DEEPFR and IRC varied among the watersheds because of physical differences among the watersheds. Two values of INFILT were obtained: one representing the rainfall-runoff process on the silty and clayey soils on the uplands and lake plains that characterize Sawmill Creek, St. Joseph Creek, and eastern Du Page County; and one representing the rainfall-runoff process on the silty soils on uplands that characterize Kress Creek and parts of western Du Page County. Regional rainfall-runoff relations, defined through joint calibration of the rainfall-runoff model and verified for independent periods, presented in this report, allow estimation of runoff for watersheds in Du Page County with an error in the total water balance less than 4.0 percent; an average absolute error in the annual-flow estimates of 17.1 percent with the error rarely exceeding 25 percent for annual flows; and correlation coefficients and coefficients of model-fit efficiency for monthly flows of at least 87 and 76 percent, respectively. Close reproduction of the runoff-volume duration curves was obtained. A frequency analysis of storm-runoff volume indicates a tendency of the model to undersimulate large storms, which may result from underestimation of the amount of impervious land cover in the watershed and errors in measuring rainfall for convective storms. Overall, the results of regional calibration and verification of the rainfall-runoff model indicate the simulated rainfall-runoff relations are adequate for stormwater-management planning and design for watersheds in Du Page County.

Predictable patterns of the May-June rainfall anomaly over East Asia

NASA Astrophysics Data System (ADS)

Xing, Wen; Wang, Bin; Yim, So-Young; Ha, Kyung-Ja

2017-02-01

During early summer (May-June, MJ), East Asia (EA) subtropical front is a defining feature of Asian monsoon, which produces the most prominent precipitation band in the global subtropics. Here we show that dynamical prediction of early summer EA (20°N-45°N, 100°E-130°E) rainfall made by four coupled climate models' ensemble hindcast (1979-2010) yields only a moderate skill and cannot be used to estimate predictability. The present study uses an alternative, empirical orthogonal function (EOF)-based physical-empirical (P-E) model approach to predict rainfall anomaly pattern and estimate its potential predictability. The first three leading modes are physically meaningful and can be, respectively, attributed to (a) the interaction between the anomalous western North Pacific subtropical high and underlying Indo-Pacific warm ocean, (b) the forcing associated with North Pacific sea surface temperature (SST) anomaly, and (c) the development of equatorial central Pacific SST anomalies. A suite of P-E models is established to forecast the first three leading principal components. All predictors are 0 month ahead of May, so the prediction here is named as a 0 month lead prediction. The cross-validated hindcast results demonstrate that these modes may be predicted with significant temporal correlation skills (0.48-0.72). Using the predicted principal components and the corresponding EOF patterns, the total MJ rainfall anomaly was hindcasted for the period of 1979-2015. The time-mean pattern correlation coefficient (PCC) score reaches 0.38, which is significantly higher than dynamical models' multimodel ensemble skill (0.21). The estimated potential maximum attainable PCC is around 0.65, suggesting that the dynamical prediction models may have large rooms to improve. Limitations and future work are discussed.

Response of transpiration to rain pulses for two tree species in a semiarid plantation

NASA Astrophysics Data System (ADS)

Chen, Lixin; Zhang, Zhiqiang; Zeppel, Melanie; Liu, Caifeng; Guo, Junting; Zhu, Jinzhao; Zhang, Xuepei; Zhang, Jianjun; Zha, Tonggang

2014-09-01

Responses of transpiration ( E c) to rain pulses are presented for two semiarid tree species in a stand of Pinus tabulaeformis and Robinia pseudoacacia. Our objectives are to investigate (1) the environmental control over the stand transpiration after rainfall by analyzing the effect of vapor pressure deficit (VPD), soil water condition, and rainfall on the post-rainfall E c development and recovery rate, and (2) the species responses to rain pulses and implications on vegetation coverage under a changing rainfall regime. Results showed that the sensitivity of canopy conductance ( G c) to VPD varied under different incident radiation and soil water conditions, and the two species exhibited the same hydraulic control (-d G c/dlnVPD to G cref ratio) over transpiration. Strengthened physiological control and low sapwood area of the stand contributed to low E c. VPD after rainfall significantly influenced the magnitude and time series of post-rainfall stand E c. The fluctuation of post-rainfall VPD in comparison with the pre-rainfall influenced the E c recovery. Further, the stand E c was significantly related to monthly rainfall, but the recovery was independent of the rainfall event size. E c enhanced with cumulative soil moisture change (ΔVWC) within each dry-wet cycle, yet still was limited in large rainfall months. The two species had different response patterns of post-rainfall E c recovery. E c recovery of P. tabulaeformis was influenced by the pre- and post-rainfall VPD differences and the duration of rainless interval. R. pseudoacacia showed a larger immediate post-rainfall E c increase than P. tabulaeformis did. We, therefore, concluded that concentrated rainfall events do not trigger significant increase of transpiration unless large events penetrate the deep soil and the species differences of E c in response to pulses of rain may shape the composition of semiarid woodlands under future rainfall regimes.

Could Malaria Control Programmes be Timed to Coincide with Onset of Rainfall?

PubMed

Komen, Kibii

2017-06-01

Malaria cases in South Africa's Northern Province of Limpopo have surpassed known endemic KwaZulu Natal and Mpumalanga Provinces. This paper applies statistical methods: regression analysis and impulse response function to understand the timing of impact and the length that such impacts last. Climate data (rainfall and temperature) are obtained from South African Weather Services (SAWs); global data from the European Centre for Medium-Range Weather Forecasts (ECMWF), while clinical malaria data came from Malaria Control Centre in Tzaneen (Limpopo Province). Data collected span from January 1998 to July 2007. Signs of the coefficients are positive for rainfall and temperature and negative for their exponents. Three out of five independent variables consistently maintain a very high statistical level of significance. The coefficients for climate variables describe an inverted u-shape: parameters for the exponents of rainfall (-0.02, -0.01, -0.02, -0.00) and temperature (-46.61, -47.46, -48.14, -36.04) are both negative. A one standard deviation rise in rainfall (rainfall onset) increases malaria cases, and the effects become sustained for at least 3 months and conclude that onset of rainfall therefore triggers a 'malaria season'. Malaria control programme and early warning system should be intensified in the first 3 months following the onset of rainfall.

Impact of Climatic Variability on Hydropower Reservoirs in the Paraiba Basin, Southeast of Brazil

NASA Astrophysics Data System (ADS)

Barros, A.; simoes, s

2002-05-01

During 2000/2001, a severe drought greatly reduced the volume of water available to Brazilian hydropower plants and lead to a national water rationing plan. To undestand the potential for climatic change in hydrological regimes and its impact on hydropower we chose the Paraiba Basin located in Southeast Brazil. Three important regional multi-purpose reservoirs are operating in this basin. Moreover, the Paraiba River is of great economic and environmental importance and also constitutes a major corridor connecting the two cities of Sao Paulo and Rio de Janeiro. We analyzed monthly and daily records for rainfall, streamflow and temperature using regression and variance analysis. Rainfall records do not show any significant trend since the 1930s/1940s. By contrast, analysis of seasonal patterns show that in the last twenty years rainfall has increased during autumn and winter (dry season) and decreased during spring and summer (rainy season). Comparison between rainfall and streaflow, from small catchment without man-made influences, shows a more pronounced deficit in streamflow when compared with rainfall. The shifts in seasonal rainfall could indicate a tendency towards a more uniform rainfall pattern and could serve to reduce the streamflow. However, the largest upward trends in temperature were found in the driest months (JJA). The increase in rainfall would not be sufficient to overcome increased of evaporation expect to the same period. Instead, such increase in evaporation could create an over more pronounced streamflow deficit. Climatic variability could be reducing water availability in these reservoirs especially in the driest months. To reduce the uncertainties in hydrological predictions, planners need to incorporate climatic variability, at the catchment scale, in order to accomodate the new conditions resulting from these changes.

Evolution of a rainfall induced landslide in Porciles, Asturias (North of Spain)

NASA Astrophysics Data System (ADS)

José Domínguez-Cuesta, María; Quintana, Luis; Alonso, Juan Luis; García Cortés, Silverio

2017-04-01

Asturias is a province of the Northern Spain, characterized by an abrupt relief (15° average slope), humid climate (960 mm/yr. rainfall) and a varied substratum mainly composed of sedimentary rocks (mostly limestones, sandstones and lutites). Landslide events, frequently linked to rainfall, are widely extended all around the region, affecting both infrastructures and people, which are largely scattered on it. The 6th of March of 2016 one of these instability events took place near the Porciles village (43°24'N 06°18'W), moving more than 10,000 m3 of land down, totally occupying the N-634 road. The main conditioning factors of this gravity movement were the modified geometry of the slope during the construction of the N-634 road and the lithology (mainly lutites and unconsolidated colluvial deposits). The rainfall is considered as the triggering factor. More than 4 months elapsed between the landslide occurrence and the initiation of the destabilized mass removal, after having stabilized the crown area. A landslide evolution study carried out during that period is presented in this work. The study is based on i) weekly oblique photographs taken from several fixed points, ii) three DTM constructed: one from previous topographic data and two LIDAR models obtained from drone flights and iii) rainfall data collected from the closest gauges to the landslide, including pre-sliding data. Several straight infrastructures affected by the landslide (an auxiliary road, some ditches and fences, among other elements) have been used as references. In this study we analyze, mainly, the relationship between the rainfall data and the evolution of the slide.

Forecasting malaria cases using climatic factors in delhi, India: a time series analysis.

PubMed

Kumar, Varun; Mangal, Abha; Panesar, Sanjeet; Yadav, Geeta; Talwar, Richa; Raut, Deepak; Singh, Saudan

2014-01-01

Background. Malaria still remains a public health problem in developing countries and changing environmental and climatic factors pose the biggest challenge in fighting against the scourge of malaria. Therefore, the study was designed to forecast malaria cases using climatic factors as predictors in Delhi, India. Methods. The total number of monthly cases of malaria slide positives occurring from January 2006 to December 2013 was taken from the register maintained at the malaria clinic at Rural Health Training Centre (RHTC), Najafgarh, Delhi. Climatic data of monthly mean rainfall, relative humidity, and mean maximum temperature were taken from Regional Meteorological Centre, Delhi. Expert modeler of SPSS ver. 21 was used for analyzing the time series data. Results. Autoregressive integrated moving average, ARIMA (0,1,1) (0,1,0)(12), was the best fit model and it could explain 72.5% variability in the time series data. Rainfall (P value = 0.004) and relative humidity (P value = 0.001) were found to be significant predictors for malaria transmission in the study area. Seasonal adjusted factor (SAF) for malaria cases shows peak during the months of August and September. Conclusion. ARIMA models of time series analysis is a simple and reliable tool for producing reliable forecasts for malaria in Delhi, India.

Implications of a decrease in the precipitation area for the past and the future

NASA Astrophysics Data System (ADS)

Benestad, Rasmus E.

2018-04-01

The total area with 24 hrs precipitation has shrunk by 7% between 50°S–50°N over the period 1998–2016, according to the satellite-based Tropical Rain Measurement Mission data. A decrease in the daily precipitation area is an indication of profound changes in the hydrological cycle, where the global rate of precipitation is balanced by the global rate of evaporation. This decrease was accompanied by increases in total precipitation, evaporation, and wet-day mean precipitation. If these trends are real, then they suggest increased drought frequencies and more intense rainfall. Satellite records, however, may be inhomogeneous because they are synthesised from a number of individual missions with improved technology over time. A linear dependency was also found between the global mean temperature and the 50°S–50°N daily precipitation area with a slope value of ‑17 × 106 km 2/°C. This dependency was used with climate model simulations to make future projections which suggested a continued decrease that will strengthen in the future. The precipitation area evolves differently when the precipitation is accumulated over short and long time scales, however, and there has been a slight increase in the monthly precipitation area while the daily precipitation area decreased. An increase on monthly scale may indicate more pronounced variations in the rainfall patterns due to migrating rain-producing phenomena.

Modelling soil erosion at European scale: the importance of management practices and the future climate and land use scenarios

NASA Astrophysics Data System (ADS)

Panagos, Panos; Ballabio, Cristiano; Meusburger, Katrin; Poesen, Jean; Lugato, Emanuele; Montanarella, Luca; Alewell, Christine; Borrelli, Pasquale

2017-04-01

The implementation of RUSLE2015 for modelling soil loss by water erosion at European scale has introduced important aspects related to management practices. The policy measurements such as reduced tillage, crop residues, cover crops, grass margins, stone walls and contouring have been incorporated in the RUSLE2015 modelling platform. The recent policy interventions introduced in Good Agricultural Environmental Conditions of Common Agricultural Policy have reduced the rate of soil loss in the EU by an average of 9.5% overall, and by 20% for arable lands (NATURE, 526, 195). However, further economic and political action should rebrand the value of soil as part of ecosystem services, increase the income of rural land owners, involve young farmers and organize regional services for licensing land use changes (Land Degradation and Development, 27 (6): 1547-1551). RUSLE2015 is combining the future policy scenarios and land use changes introduced by predictions of LUISA Territorial Modelling Platform. Latest developments in RUSLE2015 allow also incorporating the climate change scenarios and the forthcoming intensification of rainfall in North and Central Europe contrary to mixed trends in Mediterranean basin. The rainfall erosivity predictions estimate a mean increase by 18% in European Union by 2050. Recently, a module of CENTURY model was coupled with the RUSLE2015 for estimating the effect of erosion in current carbon balance in European agricultural lands (Global Change Biology, 22(5), 1976-1984; 2016). Finally, the monthly erosivity datasets (Science of the Total Environment, 579: 1298-1315) introduce a dynamic component in RUSLE2015 and it is a step towards spatio-temporal soil erosion mapping at continental scale. The monthly mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should apply in different seasons of the year. In the future, the soil erosion-modelling platform will incorporate the land use intra-annual variability, sediment transport and economic assessments of land degradation. Panagos, P., Borrelli, P., Robinson, D.A. 2015. Common Agricultural Policy: Tackling soil loss across Europe. Nature 526: 195 Panagos, P., Imeson, A., Meusburger, K., Borrelli, P., Poesen, J., Alewell, C. 2016. Soil Conservation in Europe: Wish or Reality? Land Degradation and Development, 27(6): 1547-1551 Lugato, E., Paustian, K., Panagos, P. et al. 2016. Quantifying the erosion effect on current carbon budget of European agricultural soils at high spatial resolution. Global Change Biology. 22(5): 1976-1984 Ballabio, C., Borrelli, P. et al. 2017. Mapping monthly rainfall erosivity in Europe. Science of the Total Environment, 579: 1298-1315

Vegetation response to rainfall seasonality and interannual variability in tropical dry forests

NASA Astrophysics Data System (ADS)

Feng, X.; Silva Souza, R. M.; Souza, E.; Antonino, A.; Montenegro, S.; Porporato, A. M.

2015-12-01

We analyzed the response of tropical dry forests to seasonal and interannual rainfall variability, focusing on the caatinga biome in semi-arid in Northeast Brazil. We selected four sites across a gradient of rainfall amount and seasonality and analyzed daily rainfall and biweekly Normalized Difference Vegetation Index (NDVI) in the period 2000-2014. The seasonal and interannual rainfall statistics were characterized using recently developed metrics describing duration, location, and intensity of wet season and compared them with those of NDVI time series and modelled soil moisture. A model of NDVI was also developed and forced by different rainfall scenarios (combination amount of rainfall and duration of wet season). The results show that the caatinga tends to have a more stable response characterized by longer and less variable growing seasons (of duration 3.1±0.1 months) compared to the rainfall wet seasons (2.0±0.5 months). Even for more extreme rainfall conditions, the ecosystem shows very little sensitivity to duration of wet season in relation to the amount of rainfall, however the duration of wet season is most evident for wetter sites. This ability of the ecosystem in buffering the interannual variability of rainfall is corroborated by the stability of the centroid location of the growing season compared to the wet season for all sites. The maximal biomass production was observed at intermediate levels of seasonality, suggesting a possible interesting trade-off in the effects of intensity (i.e., amount) and duration of the wet season on vegetation growth.

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...

Prediction of kharif rice yield at Kharagpur using disaggregated extended range rainfall forecasts

NASA Astrophysics Data System (ADS)

Dhekale, B. S.; Nageswararao, M. M.; Nair, Archana; Mohanty, U. C.; Swain, D. K.; Singh, K. K.; Arunbabu, T.

2017-08-01

The Extended Range Forecasts System (ERFS) has been generating monthly and seasonal forecasts on real-time basis throughout the year over India since 2009. India is one of the major rice producer and consumer in South Asia; more than 50% of the Indian population depends on rice as staple food. Rice is mainly grown in kharif season, which contributed 84% of the total annual rice production of the country. Rice cultivation in India is rainfed, which depends largely on rains, so reliability of the rainfall forecast plays a crucial role for planning the kharif rice crop. In the present study, an attempt has been made to test the reliability of seasonal and sub-seasonal ERFS summer monsoon rainfall forecasts for kharif rice yield predictions at Kharagpur, West Bengal by using CERES-Rice (DSSATv4.5) model. These ERFS forecasts are produced as monthly and seasonal mean values and are converted into daily sequences with stochastic weather generators for use with crop growth models. The daily sequences are generated from ERFS seasonal (June-September) and sub-seasonal (July-September, August-September, and September) summer monsoon (June to September) rainfall forecasts which are considered as input in CERES-rice crop simulation model for the crop yield prediction for hindcast (1985-2008) and real-time mode (2009-2015). The yield simulated using India Meteorological Department (IMD) observed daily rainfall data is considered as baseline yield for evaluating the performance of predicted yields using the ERFS forecasts. The findings revealed that the stochastic disaggregation can be used to disaggregate the monthly/seasonal ERFS forecasts into daily sequences. The year to year variability in rice yield at Kharagpur is efficiently predicted by using the ERFS forecast products in hindcast as well as real time, and significant enhancement in the prediction skill is noticed with advancement in the season due to incorporation of observed weather data which reduces uncertainty of yield prediction. The findings also recommend that the normal and above normal yields are predicted well in advance using the ERFS forecasts. The outcomes of this study are useful to farmers for taking appropriate decisions well in advance for climate risk management in rice production during different stages of the crop growing season at Kharagpur.

Rainfall erosivity estimation based on rainfall data collected over a range of temporal resolutions

USDA-ARS?s Scientific Manuscript database

Rainfall erosivity is the power of rainfall to cause soil erosion by water. The rainfall erosivity index for a rainfall event, EI30, is calculated from the total kinetic energy and maximum 30 minute intensity of individual events. However, these data are often unavailable in many areas of the worl...

Determining the precipitable water vapor with ground-based GPS and comparing its yearly variation to rainfall over Taiwan

NASA Astrophysics Data System (ADS)

Yeh, Ta-Kang; Hong, Jing-Shan; Wang, Chuan-Sheng; Chen, Chieh-Hung; Chen, Kwo-Hwa; Fong, Chin-Tzu

2016-06-01

Water vapor plays an important role in weather prediction. Thus, it would be helpful to use precipitable water vapor (PWV) data from Global Positioning System (GPS) signals to understand weather phenomena. Approximately 100 ground GPS stations that cooperate with approximately 500 ground weather stations were used in this study. The relationship between the PWV and rainfall was investigated by analyzing the amplitude and phase that resulted from harmonic analyses. The results indicated that the maximum PWV amplitudes were between 10.98 and 13.10 mm and always occurred at the end of July. The magnitudes of the PWV growth rate were between 0.65 and 0.81 mm/yr. These rates increased from 9.2% to 13.0% between 2006 and 2011. The largest peak PWV amplitude occurred in the Western region. However, the largest rainfall amplitude occurred in the Southern region. The presented peak rainfall time agreed with the peak PWV time in the Western, Southern, and Central Mountain regions. Although rainfall decreased with time in Taiwan, this decrease was not large. The greatest rainfall consistently occurred during the months in which typhoons occurred, and the greatest PWV values occurred at the end of July. Although the end of July had the greatest monthly average PWV values, the rainfall magnitude during this period was smaller than that during the typhoons, which only occurred for a few days; the PWV also increased during typhoons. Because this effect was short-term, it did not significantly contribute to the PWV monthly average.

Impact of La Niña and La Niña Modoki on Indonesia rainfall variability

NASA Astrophysics Data System (ADS)

Hidayat, R.; Juniarti, MD; Ma’rufah, U.

2018-05-01

La Niña events are indicated by cooling SST in central and eastern equatorial Pacific. While La Niña Modoki occurrences are indicated by cooling SST in central Pacific and warming SST in western and eastern equatorial Pacific. These two events are influencing rainfall variability in several regions including Indonesia. The objective of this study is to analyse the impact of La Niña and La Niña Modoki on Indonesian rainfall variability. We found the Nino 3.4 index is highly correlated (r = -0.95) with Indonesian rainfall. Positive rainfall anomalies up to 200 mm/month occurred mostly in Indonesian region during La Niña events, but in DJF several areas of Sumatera, Kalimantan and eastern Indonesia tend to have negative rainfall. During La Niña Modoki events, positive rainfall anomaly (up to 50 mm/month) occurred in Sumatera Island, Kalimantan, Java and eastern Indonesia in DJF and up to 175 mm/month occurred only in Java Island in MAM season. La Niña events have strong cooling SST in central and eastern equatorial Pacific (-1.5°C) in DJF. While La Niña Modoki events warming SST occurred in western and eastern equatorial Pacific (0.75°C) and cooling SST in central Pacific (- 0.75°C) in DJF and MAM. Walker circulation in La Niña Modoki events (on DJF and MAM) showed strong convergence in eastern Pacific, and weak convergence in western Pacific (Indonesia).

Characteristics of worst hour rainfall rate for radio wave propagation modelling in Nigeria

NASA Astrophysics Data System (ADS)

Osita, Ibe; Nymphas, E. F.

2017-10-01

Radio waves especially at the millimeter-wave band are known to be attenuated by rain. Radio engineers and designers need to be able to predict the time of the day when radio signal will be attenuated so as to provide measures to mitigate this effect. This is achieved by characterizing the rainfall intensity for a particular region of interest into worst month and worst hour of the day. This paper characterized rainfall in Nigeria into worst year, worst month, and worst hour. It is shown that for the period of study, 2008 and 2009 are the worst years, while September is the most frequent worst month in most of the stations. The evening time (LT) is the worst hours of the day in virtually all the stations.

Changes to Sub-daily Rainfall Patterns in a Future Climate

NASA Astrophysics Data System (ADS)

Westra, S.; Evans, J. P.; Mehrotra, R.; Sharma, A.

2012-12-01

An algorithm is developed for disaggregating daily rainfall into sub-daily rainfall 'fragments' (continuous high temporal-resolution rainfall sequences whose total depth sums to the daily rainfall amount) under a future, warmer climate. The basis of the algorithm is to re-sample sub-daily fragments from the historical record conditional on the total daily rainfall amount and a range of temperature-based atmospheric predictors. The logic is that as the atmosphere warms, future rainfall patterns will be more reflective of historical rainfall patterns which occurred on warmer days at the same location, or at locations which have an atmospheric temperature profile more representative of expected future atmospheric conditions. It was found that the daily to sub-daily scaling relationship varied significantly by season and by location, with rainfall patterns on warmer seasons or at warmer locations typically exhibiting higher rainfall intensity occurring over shorter periods within a day, compared with cooler seasons and locations. Importantly, by regressing against temperature-based atmospheric covariates, this effect was substantially reduced, suggesting that the approach also may be valid when extrapolating to a future climate. An adjusted method of fragments algorithm was then applied to nine stations around Australia, with the results showing that when holding total daily rainfall constant, the maximum intensity of short duration rainfall increased by a median of about 5% per degree for the maximum 6 minute burst, and 3.5% for the maximum one hour burst, whereas the fraction of the day with no rainfall increased by a median of 1.5%. This highlights that a large proportion of the change to the distribution of rainfall is likely to occur at sub-daily timescales, with significant implications for many hydrological systems.

Site-specific high-resolution models of the monsoon for Africa and Asia

NASA Astrophysics Data System (ADS)

Bryson, R. A.; Bryson, R. U.

2000-11-01

Using the macrophysical climate model of Bryson [Bryson, R.A., 1992. A macrophysical model of the Holocene intertropical convergence and jetstream positions and rainfall for the Saharan region. Meteorol. Atmos. Phys., 47, pp. 247-258], it is possible to calculate the monthly latitude of the jetstream and the latitude of the subtropical anticyclones. From these and modern climatic data, it is possible to model the two-century mean latitude of the intertropical convergence (ITC) month by month and estimate the monthly monsoon rainfall using the ITC-Rainfall model of Ilesanmi [Ilesanmi, O.O., 1971. An empirical formulation of an ITD rainfall model for the tropics — a case study of Nigeria. J. Appl. Meteorol., 10, pp. 882-891] and similar relationships. Input to this model is only calculated radiation and atmospheric optical depth estimated from a database of global volcanicity. Recent work has shown that it is possible to extend these estimates to both precipitation and temperature at specific sites, even in mountainous terrain. Testing of the model against archaeological records and climatic proxies is now underway, as well as refining the fundamental model. Preliminary indications are that the timing of fluctuations in the local climate is very well modeled. Especially well matched are the modeled Nile flood based on calculated rainfall on the Blue and White Nile watersheds and the level of Lake Moeris [Hassan, F., 1985. Holocene lakes and prehistoric settlements of the Western Faiyum, Egypt. J. Archaeol. Res., 13, pp. 483-501]. Modeled precipitation histories for specific sites in China, Thailand, the Arabian Peninsula, and North Africa will be presented and contrasted with the simulated rainfall history of Mesopotamia.

Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

NASA Astrophysics Data System (ADS)

Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

2017-12-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic precipitation, fed into a rainfall-runoff model to derive the flood frequency in the Tirolean Alps in Austria. Given the number of generated events, the simulation framework is able to generate a large variety of rainfall patterns, as well as reproduce the variograms of relevant extreme rainfall events in the region of interest.

Spatiotemporal trends in extreme rainfall and temperature indices over Upper Tapi Basin, India

NASA Astrophysics Data System (ADS)

Sharma, Priyank J.; Loliyana, V. D.; S. R., Resmi; Timbadiya, P. V.; Patel, P. L.

2017-12-01

The flood risk across the globe is intensified due to global warming and subsequent increase in extreme temperature and precipitation. The long-term trends in extreme rainfall (1944-2013) and temperature (1969-2012) indices have been investigated at annual, seasonal, and monthly time scales using nonparametric Mann-Kendall (MK), modified Mann-Kendall (MMK), and Sen's slope estimator tests. The extreme rainfall and temperature indices, recommended by the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI), have been analyzed at finer spatial scales for trend detection. The results of trend analyses indicate decreasing trend in annual total rainfall, significant decreasing trend in rainy days, and increasing trend in rainfall intensity over the basin. The seasonal rainfall has been found to decrease for all the seasons except postmonsoon, which could affect the rain-fed agriculture in the basin. The 1- and 5-day annual maximum rainfalls exhibit mixed trends, wherein part of the basin experiences increasing trend, while other parts experience a decreasing trend. The increase in dry spells and concurrent decrease in wet spells are also observed over the basin. The extreme temperature indices revealed increasing trends in hottest and coldest days, while decreasing trends in coldest night are found over most parts of the basin. Further, the diurnal temperature range is also found to increase due to warming tendency in maximum temperature (T max) at a faster rate compared to the minimum temperature (T min). The increase in frequency and magnitude of extreme rainfall in the basin has been attributed to the increasing trend in maximum and minimum temperatures, reducing forest cover, rapid pace of urbanization, increase in human population, and thereby increase in the aerosol content in the atmosphere. The findings of the present study would significantly help in sustainable water resource planning, better decision-making for policy framework, and setting up infrastructure against flood disasters in Upper Tapi Basin, India.

Mapping the world's tropical cyclone rainfall contribution over land using TRMM satellite data: precipitation budget and extreme rainfall

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2012-12-01

A study was performed to characterize over-land precipitation associated with tropical cyclones (TCs) for basins around the world gathered in the International Best Track Archive for Climate Stewardship (IBTrACS). From 1998 to 2010, rainfall data from TRMM 3B42, showed that TCs accounted for 8-, 11-, 7-, 10-, and 12-% of the annual over-land precipitation for North America, East Asia, Northern Indian Ocean, Australia, and South-West Indian Ocean respectively, and that TC-contribution decreased importantly within the first 150-km from the coast. At the local scale, TCs contributed on average to more than 40% and up to 77% of the annual precipitation budget over very different climatic areas with arid or tropical characteristics. The East Asia domain presented the higher and most constant TC-rain (170±23%-mm/yr) normalized over the area impacted, while the Southwest Indian domain presented the highest variability (130±48%-mm/yr), and the North American domain displayed the lowest average TC-rain (77±27%-mm/yr) despite a higher TC-activity. The maximum monthly TC-contribution (11-15%) was found later in the TC-season and was a conjunction between the peak of TC-activity, TC-rainfall, and the domain annual antagonism between dry and wet regimes if any. Furthermore, TC-days that accounted globally for 2±0.5% of all precipitation events for all basins, represented between 11-30% of rainfall extremes (>101.6mm/day). Locally, TC-rainfall was linked with the majority (>70%) or the quasi-totality (≈100%) of extreme rainfall. Finally, because of their importance in terms of rainfall amount, the contribution of tropical cyclones is provided for a selection of fifty urban areas experiencing cyclonic activity. Cases studies conducted at the regional scale will focus on the link between TC-activity, water resources, and hydrohazards such as floods and droughts.

Streamflow and Erosion Response to Prolonged Intense Rainfall of November 1-2, 2000, Island of Hawaii, Hawaii

USGS Publications Warehouse

Fontaine, Richard A.; Hill, Barry R.

2002-01-01

A combination of several meteorologic and topographic factors produced extreme rainfall over the eastern part of the island of Hawaii on November 1-2, 2000. Storm rainfall was concentrated in two distinct areas, the Waiakea and Kapapala areas, where maximum rainfall totals of 32.47 and 38.97 inches were recorded. Resultant flooding caused damages in excess of 70 million dollars, among the highest totals associated with flooding in the State's history. Storm rainfall had recurrence intervals that ranged from 10 years or less for maximum 1-hour totals to 100 years or more for maximum 24-hour totals As part of this study, peak flow and/or erosion data were collected at 41 sites. Analyses of these data indicated that peak discharges of record occurred at 6 of 12 sites where historic data were available. Peak flows with estimated recurrence intervals from 50 to over 100 years were recorded at 4 of 11 sites. Peak flows were poorly correlated with total storm rainfall. Critical rainfall durations associated with peak flows ranged from 1 to 12 hours and were about 3 hours at most sites. Rainfall-runoff computations and field observations indicated that infiltration-excess overland flow alone was not sufficient to have caused the observed flood peaks and therefore saturation-excess overland flow and subsurface flow probably contributed to peak flows at most sites Most hillslope erosion associated with the storm took place along or near the Kaoiki Pali in the Kapapala area. Hillslope erosion was predominately caused by overland flow.

Estimating nitrogen loading to ground water and assessing vulnerability to nitrate contamination in a large karstic springs Basin, Florida

USGS Publications Warehouse

Katz, B.G.; Sepulveda, A.A.; Verdi, R.J.

2009-01-01

A nitrogen (N) mass-balance budget was developed to assess the sources of N affecting increasing ground-water nitrate concentrations in the 960-km 2 karstic Ichetucknee Springs basin. This budget included direct measurements of N species in rainfall, ground water, and spring waters, along with estimates of N loading from fertilizers, septic tanks, animal wastes, and the land application of treated municipal wastewater and residual solids. Based on a range of N leaching estimates, N loads to ground water ranged from 262,000 to 1.3 million kg/year; and were similar to N export from the basin in spring waters (266,000 kg/year) when 80-90% N losses were assumed. Fertilizers applied to cropland, lawns, and pine stands contributed about 51% of the estimated total annual N load to ground water in the basin. Other sources contributed the following percentages of total N load to ground water: animal wastes, 27%; septic tanks, 12%; atmospheric deposition, 8%; and the land application of treated wastewater and biosolids, 2%. Due to below normal rainfall (97.3 cm) during the 12-month rainfall collection period, N inputs from rainfall likely were about 30% lower than estimates for normal annual rainfall (136 cm). Low N-isotope values for six spring waters (??15N-NO3 = 3.3 to 6.3???) and elevated potassium concentrations in ground water and spring waters were consistent with the large N contribution from fertilizers. Given ground-water residence times on the order of decades for spring waters, possible sinks for excess N inputs to the basin include N storage in the unsaturated zone and parts of the aquifer with relatively sluggish ground-water movement and denitrification. A geographical-based model of spatial loading from fertilizers indicated that areas most vulnerable to nitrate contamination were located in closed depressions containing sinkholes and other dissolution features in the southern half of the basin. ?? 2009 American Water Resources Association.

Herbicide and nitrate distribution in central Iowa rainfall

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

Hatfield, J.L.; Prueger, J.H.; Pfeiffer, R.L.

Herbicides are detected in rainfall; however, these are a small fraction of the total applied. This study was designed to evaluate monthly and annual variation in atrazine (6-chloro-N-ethyl-N{prime}-(1-methylethyl)-1,3,5-triazine-2,4-diamine), alachlor (2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)acetamide), metolachlor (2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide), and NO{sub 3}-N concentrations in rainfall over Walnut Creek watershed south of Ames, IA. The study began in 1991 and continued through 1994. Within the watershed, two wet/dry precipitation samplers were positioned 4 km apart. Detections varied during the year with >90% of the herbicide detections occurring in April through early July. Concentrations varied among events from nondetectable amounts to concentrations of 154 {mu}g L{sup {minus}1}, which occurredmore » when atrazine was applied during an extremely humid day immediately followed by rainfall of <10 mm that washed spray drift from the atmosphere. This was a local scale phenomenon, because the other collector had a more typical concentration of 1.7 {mu}g L{sup {minus}1} with an 8-mm rainfall. VAriation between the two collectors suggests that local scale meteorological processes affect herbicide movement. Yearly atrazine deposition totals were >100 {mu}g m{sup {minus}2} representing <0.1% of the amount applied. Nitrate-N concentrations in precipitation were uniformly distributed throughout the year and without annual variation in the concentrations. Deposition rates of NO{sub 3}-N were about 1.2 g m{sup {minus}2}. Annual loading onto the watershed was about 25% of the amount applied from all forms of N fertilizers. Movement and rates of deposition provide an understanding of the processes and magnitude of the impact of agriculture on the environment. 7 refs., 5 figs., 3 tabs.« less

Soil water sensor-based and evapotranspiration-based irrigation scheduling for soybean production on a Blackland Prairie soil in humid climate

USDA-ARS?s Scientific Manuscript database

In east-central Mississippi, annual rainfall was 1307 mm and reference evapotranspiration (ETo) was 1210 mm for the 120-year period from 1894 to 2014. From May to October, when major crops are typically grown in this area, monthly rainfall ranged from 72 to 118 mm, and monthly ETo from 94 to 146 mm ...

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.

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

NASA Astrophysics Data System (ADS)

Tolika, Konstantia; Maheras, Panagiotis; Anagnostopoulou, Christina

2018-05-01

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

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...

Correlation analysis of Standardized Precipitation Index (SPI) for the water debit and level of the Cisadane River during El Niño and La Niña years

NASA Astrophysics Data System (ADS)

Khoir, A. N.; Rohmah, M.; Nuryadi

2018-03-01

Hydrometeorological factor causes most disaster in Indonesia, and two of them are drought and flood. This study aims to correlate Standardized Precipitation Index (SPI) 3-monthly to water debit and water level in the Cisadane River. The monthly rainfall data from Serpong and Pasar Baru rain station from 2009 to 2011 when moderate El Niño and moderate La Niña happened. The correlation analysis between debit and water level to SPI 3-monthly used rain post of Serpong to represent the condition of the upstream area and rain post of Pasar Baru to represent the condition of the downstream area. The results showed that during La Niña year, the rainfall on the upstream area of the Cisadane River influenced the increase and the decrease in water debit and water level. Meanwhile, the rainfall on the downstream area of the river has an opposite effect on the increase and the decrease of debit and water level of the Pasar Baru. On the upstream area, the correlation between rainfall and water debit is 0.8, and the correlation between rainfall and water level is also 0.8. During El Niño year, the correlation was less than 0.5.

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.

High Resolution Monthly Oceanic Rainfall Based on Microwave Brightness Temperature Histograms

NASA Astrophysics Data System (ADS)

Shin, D.; Chiu, L. S.

2005-12-01

A statistical emission-based passive microwave retrieval algorithm has been developed by Wilheit, Chang and Chiu (1991) to estimate space/time oceanic rainfall. The algorithm has been applied to Special Sensor Microwave Imager (SSM/I) data taken on board the Defense Meteorological Satellite Program (DMSP) satellites to provide monthly oceanic rainfall over 2.5ox2.5o and 5ox5o latitude-longitude boxes by the Global Precipitation Climatology Project-Polar Satellite Precipitation Data Center (GPCP-PSPDC, URL: http://gpcp-pspdc.gmu.edu/) as part of NASA's contribution to the GPCP. The algorithm has been modified and applied to the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data to produce a TRMM Level 3 standard product (3A11) over 5ox5o latitude/longitude boxes. In this study, the algorithm code is modified to retrieve rain rates at 2.5ox2.5o and 1ox1o resolutions for TMI. Two months of TMI data have been tested and the results compared with the monthly mean rain rates derived from TRMM Level 2 TMI rain profile algorithm (2A12) and the original 5ox5o data from 3A11. The rainfall pattern is very similar to the monthly average of 2A12, although the intensity is slightly higher. Details in the rain pattern, such as rain shadow due to island blocking, which were not discernible from the low resolution products, are now easily discernible. The spatial average of the higher resolution rain rates are in general slightly higher than lower resolution rain rates, although a Student-t test shows no significant difference. This high resolution product will be useful for the calibration of IR rain estimates for the production of the GPCP merge rain product.

Seasonal forecasting of fire over Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Spessa, A. C.; Field, R. D.; Pappenberger, F.; Langner, A.; Englhart, S.; Weber, U.; Stockdale, T.; Siegert, F.; Kaiser, J. W.; Moore, J.

2015-03-01

Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean-atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Niño years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.

Stalling Tropical Cyclones over the Atlantic Basin

NASA Astrophysics Data System (ADS)

Nielsen-Gammon, J. W.; Emanuel, K.

2017-12-01

Hurricane Harvey produced massive amounts of rain over southeast Texas and southwest Louisiana. Average storm total rainfall amounts over a 10,000 square mile (26,000 square km) area exceeded 30 inches (750 mm). An important aspect of the storm that contributed to the large rainfall totals was its unusual motion. The storm stalled shortly after making landfall, then moved back offshore before once again making landfall five days later. This storm motion permitted heavy rainfall to occur in the same general area for an extended period of time. The unusual nature of this event motivates an investigation into the characteristics and potential climate change influences on stalled tropical cyclones in the Atlantic basin using the HURDAT 2 storm track database for 1866-2016 and downscaled tropical cyclones driven by simulations of present and future climate. The motion of cyclones is quantified as the size of a circle circumscribing all storm locations during a given length of time. For a three-day period, Harvey remained inside a circle with a radius of 123 km. This ranks within the top 0.6% of slowest-moving historical storm instances. Among the 2% of slowest-moving storm instances prior to Harvey, only 13 involved storms that stalled near the continental United States coast, where they may have produced substantial rainfall onshore while tapping into marine moisture. Only two such storms stalled in the month of September, in contrast to 20 September stalls out of the 36 storms that stalled over the nearby open Atlantic. Just four of the stalled coastal storms were hurricanes, implying a return frequency for such storms of much less than once per decade. The synoptic setting of these storms is examined for common features, and historical and projected trends in occurrences of stalled storms near the coast and farther offshore are investigated.

Characterization of urban runoff pollution between dissolved and particulate phases.

PubMed

Wei, Zhang; Simin, Li; Fengbing, Tang

2013-01-01

To develop urban stormwater management effectively, characterization of urban runoff pollution between dissolved and particulate phases was studied by 12 rainfall events monitored for five typical urban catchments. The average event mean concentration (AEMC) of runoff pollutants in different phases was evaluated. The AEMC values of runoff pollutants in different phases from urban roads were higher than the ones from urban roofs. The proportions of total dissolved solids, total dissolved nitrogen, and total dissolved phosphorus in total ones for all the catchments were 26.19%-30.91%, 83.29%-90.51%, and 61.54-68.09%, respectively. During rainfall events, the pollutant concentration at the initial stage of rainfall was high and then sharply decreased to a low value. Affected by catchments characterization and rainfall distribution, the highest concentration of road pollutants might appear in the later period of rainfall. Strong correlations were also found among runoffs pollutants in different phases. Total suspended solid could be considered as a surrogate for particulate matters in both road and roof runoff, while dissolved chemical oxygen demand could be regarded as a surrogate for dissolved matters in roof runoff.

Downstream aggradation owing to lava dome extrusion and rainfall runoff at Volcán Santiaguito, Guatemala

USGS Publications Warehouse

Harris, Andrew J. L.; Vallance, James W.; Kimberly, Paul; Rose, William I.; Matías, Otoniel; Bunzendahl, Elly; Flynn, Luke P.; Garbeil, Harold

2006-01-01

Persistent lava extrusion at the Santiaguito dome complex (Guatemala) results in continuous lahar activity and river bed aggradation downstream of the volcano. We present a simple method that uses vegetation indices extracted from Landsat Thematic Mapper (TM) data to map impacted zones. Application of this technique to a time series of 21 TM images acquired between 1987 and 2000 allow us to map, measure, and track temporal and spatial variations in the area of lahar impact and river aggradation.In the proximal zone of the fluvial system, these data show a positive correlation between extrusion rate at Santiaguito (E), aggradation area 12 months later (Aprox), and rainfall during the intervening 12 months (Rain12): Aprox=3.92+0.50 E+0.31 ln(Rain12) (r2=0.79). This describes a situation in which an increase in sediment supply (extrusion rate) and/or a means to mobilize this sediment (rainfall) results in an increase in lahar activity (aggraded area). Across the medial zone, we find a positive correlation between extrusion rate and/or area of proximal aggradation and medial aggradation area (Amed): Amed=18.84-0.05 Aprox - 6.15 Rain12 (r2=0.85). Here the correlation between rainfall and aggradation area is negative. This describes a situation in which increased sediment supply results in an increase in lahar activity but, because it is the zone of transport, an increase in rainfall serves to increase the transport efficiency of rivers flowing through this zone. Thus, increased rainfall flushes the medial zone of sediment.These quantitative data allow us to empirically define the links between sediment supply and mobilization in this fluvial system and to derive predictive relationships that use rainfall and extrusion rates to estimate aggradation area 12 months hence.

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

PubMed Central

Tao, Wanghai; Wu, Junhu; Wang, Quanjiu

2017-01-01

Rainfall erosion is a major cause of inducing soil degradation, and rainfall patterns have a significant influence on the process of sediment yield and nutrient loss. The mathematical models developed in this study were used to simulate the sediment and nutrient loss in surface runoff. Four rainfall patterns, each with a different rainfall intensity variation, were applied during the simulated rainfall experiments. These patterns were designated as: uniform-type, increasing-type, increasing- decreasing -type and decreasing-type. The results revealed that changes in the rainfall intensity can have an appreciable impact on the process of runoff generation, but only a slight effect on the total amount of runoff generated. Variations in the rainfall intensity in a rainfall event not only had a significant effect on the process of sediment yield and nutrient loss, but also the total amount of sediment and nutrient produced, and early high rainfall intensity may lead to the most severe erosion and nutrient loss. In this study, the calculated data concur with the measured values. The model can be used to predict the process of surface runoff, sediment transport and nutrient loss associated with different rainfall patterns. PMID:28272431

Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

NASA Astrophysics Data System (ADS)

Lucero, Omar A.; Rozas, Daniel

Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of this research could have further geographical validity.

Trend Analysis of Annual and Seasonal Rainfall in Kansas

NASA Astrophysics Data System (ADS)

Rahmani, V.; Hutchinson, S. L.; Hutchinson, J.; Anandhi, A.

2012-12-01

Precipitation has direct impacts on agricultural production, water resources management, and recreational activities, all of which have significant economic impacts. Thus developing a solid understanding of rainfall patterns and trends is important, and is particularly vital for regions with high climate variability like Kansas. In this study, the annual and seasonal rainfall trends were analyzed using daily precipitation data for four consecutive periods (1891-1920, 1921-1950, 1951-1980, and 1981-2010) and an overall data range of 1890 through 2011 from 23 stations in Kansas. The overall analysis showed that on average Kansas receives 714 mm of rain annually with a strong gradient from west (425 mm, Tribune) to east (1069 mm, Columbus). Due to this gradient, western and central Kansas require more irrigation water than eastern Kansas during the summer growing season to reach the plant water requirements and optimize yield. In addition, a gradual increase in total annual rainfall was found for 21 of 23 stations with a greater increase for recent years (1956 through 2011) and eastern part. The average trend slope for the state is 0.7 mm/yr with a minimum value of -0.8 mm/yr for Saint Francis in Northwest and a maximum value of 2 mm/yr for Independence in Southeast. Seasonal analysis showed that all stations received the most rain during the summer season (June, July, Aug) followed by Spring, Fall and Winter respectively. Investigating the number of dry days (days with rain less than or equal to 2.5 mm) showed that 17 of 23 had a decreasing trend from west to east and across time with the greatest decrease of -0.07 days/yr for Winfield in South and the greatest increase of 0.05 days/yr for Elkhart in Southwest. When assessing the number of dry days between rainfall events, it was found that the majority of the stations had a decreasing trend for most of the months from west to east and across time. These results indicate that Kansas is experiencing fewer dry days and more rainy days with an increasing trend of total rainfall, so the irrigation amount should be updated for each region, and crop and plant types can be modified. The increasing rainfall will also affect hydraulic structures like dams, culverts and channels that may result in more property loss and threat to human life. New rainfall patterns should be considered when designing stormwater management system to avoid poor (over or under sized) design.

Waters associated with an active basaltic volcano, Kilauea, Hawaii: Variation in solute sources, 1973-1991

USGS Publications Warehouse

Tilling, R.I.; Jones, B.F.

1996-01-01

Chemical and isotopic analyses of samples collected from a 1262-m-deep research borehole at the summit of Kilauea Volcano provide unique time-series data for composition of waters in the uppermost part of its hydrothermal system. These waters have a distinctive geochemical signature: a very low proportion of chloride relative to other anions compared with other Hawaiian wa-ters - thermal (???30 ??C) or nonthermal (<30 ??C) - and with most thermal waters of the world. Isotope data demonstrate that the borehole waters are of essentially meteoric origin, with minimal magmatic input. The water chemistry exhibits marked temporal variations, including pronounced short-term (days to weeks) effects of rainfall dilution and longer term (months to years) decline of total solutes. The 1973-1974 samples are Na-sulfate-dominant, but samples collected after July 1975 are (Mg + Ca)-bicarbonate-dominant. This compositional shift, probably abrupt, was associated with an increase in the partial pressure of CO2 (PCO2) related to volcanic degassing of CO2 accompanying a large eruption (December 31, 1974) and associated intense seismicity. Following the initial sharp increase, the PCO2 then decreased, approaching preemption values in April 1976. Beginning in mid-1975, solute concentrations of the borehole waters decreased substantially, from ???45 meq/L to <25 meq/L in only eight months; by 1991, total solute concentrations were <17 meq/L. This decline in solutes cannot be attributed to rainfall dilution and is inferred to reflect the decreasing availability with time of the easily leachable salts of alkali metals and sulfate, which originated in sublimates and fumarolic encrustations in fractures and cavities of rocks along the hydrologic flow paths. The overall chemistry of the summit-borehole waters is largely determined by hydrolysis reactions associated with normal weathering of host tholeiitic basalts on a geologic time scale, despite short-term perturbations in composition caused by rainfall dilution or volcanic activity.

Characterizing response of total suspended solids and total phosphorus loading to weather and watershed characteristics for rainfall and snowmelt events in agricultural watersheds

USGS Publications Warehouse

Danz, Mari E.; Corsi, Steven; Brooks, Wesley R.; Bannerman, Roger T.

2013-01-01

Understanding the response of total suspended solids (TSS) and total phosphorus (TP) to influential weather and watershed variables is critical in the development of sediment and nutrient reduction plans. In this study, rainfall and snowmelt event loadings of TSS and TP were analyzed for eight agricultural watersheds in Wisconsin, with areas ranging from 14 to 110 km2 and having four to twelve years of data available. The data showed that a small number of rainfall and snowmelt runoff events accounted for the majority of total event loading. The largest 10% of the loading events for each watershed accounted for 73–97% of the total TSS load and 64–88% of the total TP load. More than half of the total annual TSS load was transported during a single event for each watershed at least one of the monitored years. Rainfall and snowmelt events were both influential contributors of TSS and TP loading. TSS loading contributions were greater from rainfall events at five watersheds, from snowmelt events at two watersheds, and nearly equal at one watershed. The TP loading contributions were greater from rainfall events at three watersheds, from snowmelt events at two watersheds and nearly equal at three watersheds. Stepwise multivariate regression models for TSS and TP event loadings were developed separately for rainfall and snowmelt runoff events for each individual watershed and for all watersheds combined by using a suite of precipitation, melt, temperature, seasonality, and watershed characteristics as predictors. All individual models and the combined model for rainfall events resulted in two common predictors as most influential for TSS and TP. These included rainfall depth and the antecedent baseflow. Using these two predictors alone resulted in an R2 greater than 0.7 in all but three individual models and 0.61 or greater for all individual models. The combined model yielded an R2 of 0.66 for TSS and 0.59 for TP. Neither the individual nor the combined models were substantially improved by using additional predictors. Snowmelt event models were statistically significant for individual and combined watershed models, but the model fits were not all as good as those for rainfall events (R2 between 0.19 and 0.87). Predictor selection varied from watershed to watershed, and the common variables that were selected were not always selected in the same order. Influential variables were commonly direct measures of moisture in the watershed such as snowmelt, rainfall + snowmelt, and antecedent baseflow, or measures of potential snowmelt volume in the watershed such as air temperature.

Temporal and spatial changes of rainfall and streamflow in the Upper Tekezē-Atbara river basin, Ethiopia

NASA Astrophysics Data System (ADS)

Gebremicael, Tesfay G.; Mohamed, Yasir A.; Zaag, Pieter v.; Hagos, Eyasu Y.

2017-04-01

The Upper Tekezē-Atbara river sub-basin, part of the Nile Basin, is characterized by high temporal and spatial variability of rainfall and streamflow. In spite of its importance for sustainable water use and food security, the changing patterns of streamflow and its association with climate change is not well understood. This study aims to improve the understanding of the linkages between rainfall and streamflow trends and identify possible drivers of streamflow variabilities in the basin. Trend analyses and change-point detections of rainfall and streamflow were analysed using Mann-Kendall and Pettitt tests, respectively, using data records for 21 rainfall and 9 streamflow stations. The nature of changes and linkages between rainfall and streamflow were carefully examined for monthly, seasonal and annual flows, as well as indicators of hydrologic alteration (IHA). The trend and change-point analyses found that 19 of the tested 21 rainfall stations did not show statistically significant changes. In contrast, trend analyses on the streamflow showed both significant increasing and decreasing patterns. A decreasing trend in the dry season (October to February), short season (March to May), main rainy season (June to September) and annual totals is dominant in six out of the nine stations. Only one out of nine gauging stations experienced significant increasing flow in the dry and short rainy seasons, attributed to the construction of Tekezē hydropower dam upstream this station in 2009. Overall, streamflow trends and change-point timings were found to be inconsistent among the stations. Changes in streamflow without significant change in rainfall suggests factors other than rainfall drive the change. Most likely the observed changes in streamflow regimes could be due to changes in catchment characteristics of the basin. Further studies are needed to verify and quantify the hydrological changes shown in statistical tests by identifying the physical mechanisms behind those changes. The findings from this study are useful as a prerequisite for studying the effects of catchment management dynamics on the hydrological variabilities in the basin.

Rainfall prediction of Cimanuk watershed regions with canonical correlation analysis (CCA)

NASA Astrophysics Data System (ADS)

Rustiana, Shailla; Nurani Ruchjana, Budi; Setiawan Abdullah, Atje; Hermawan, Eddy; Berliana Sipayung, Sinta; Gede Nyoman Mindra Jaya, I.; Krismianto

2017-10-01

Rainfall prediction in Indonesia is very influential on various development sectors, such as agriculture, fisheries, water resources, industry, and other sectors. The inaccurate predictions can lead to negative effects. Cimanuk watershed is one of the main pillar of water resources in West Java. This watersheds divided into three parts, which is a headwater of Cimanuk sub-watershed, Middle of Cimanuk sub-watershed and downstream of Cimanuk sub- watershed. The flow of this watershed will flow through the Jatigede reservoir and will supply water to the north-coast area in the next few years. So, the reliable model of rainfall prediction is very needed in this watershed. Rainfall prediction conducted with Canonical Correlation Analysis (CCA) method using Climate Predictability Tool (CPT) software. The prediction is every 3months on 2016 (after January) based on Climate Hazards group Infrared Precipitation with Stations (CHIRPS) data over West Java. Predictors used in CPT were the monthly data index of Nino3.4, Dipole Mode (DMI), and Monsoon Index (AUSMI-ISMI-WNPMI-WYMI) with initial condition January. The initial condition is chosen by the last data update. While, the predictant were monthly rainfall data CHIRPS region of West Java. The results of prediction rainfall showed by skill map from Pearson Correlation. High correlation of skill map are on MAM (Mar-Apr-May), AMJ (Apr-May-Jun), and JJA (Jun-Jul-Aug) which means the model is reliable to forecast rainfall distribution over Cimanuk watersheds region (over West Java) on those seasons. CCA score over those season prediction mostly over 0.7. The accuracy of the model CPT also indicated by the Relative Operating Characteristic (ROC) curve of the results of Pearson correlation 3 representative point of sub-watershed (Sumedang, Majalengka, and Cirebon), were mostly located in the top line of non-skill, and evidenced by the same of rainfall patterns between observation and forecast. So, the model of CPT with CCA method is reliable to use.

Evaluating spatial and temporal variations of rainfall erosivity, case of Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Meshesha, Derege Tsegaye; Tsunekawa, Atsushi; Tsubo, Mitsuru; Haregeweyn, Nigussie; Adgo, Enyew

2015-02-01

Land degradation in many Ethiopian highlands occurs mainly due to high rainfall erosivity and poor soil conservation practices. Rainfall erosivity is an indicator of the precipitation energy and ability to cause soil erosion. In Central Rift Valley (CRV) of Ethiopia, where the climate is characterized as arid and semiarid, rainfall is the main driver of soil erosion that in turn causes a serious expansion in land degradation. In order to evaluate the spatial and temporal variability of rainfall erosivity and its impact on soil erosion, long-term rainfall data (1980-2010) was used, and the monthly Fournier index (FI) and the annual modified Fournier index (MFI) were applied. Student's t test analysis was performed particularly to examine statistical significances of differences in average monthly and annual erosivity values. The result indicated that, in a similar spatial pattern with elevation and rainfall amount, average annual erosivity is also found being higher in western highlands of the valley and gradually decreased towards the east. The long-term average annual erosivity (MFI) showed a general decreasing trend in recent 10 years (2000-2010) as compared to previous 20 years (1980-1999). In most of the stations, average erosivity of main rainy months (May, June, July, and August) showed a decreasing trend, whereby some of them (about 33.3 %) are statically significant at 90 and 95 % confidence intervals but with high variation in spatial pattern of changes. The overall result of the study showed that rainfall aggression (erosivity) in the region has a general decreasing trend in the recent decade as compared to previous decades, especially in the western highlands of the valley. Hence, it implies that anthropogenic factors such as land use change being coupled with topography (steep slope) have largely contributed to increased soil erosion rate in the region.

Characterizing Congo Basin rainfall and climate using Tropical Rainfall Measuring Mission (TRMM) satellite data and limited rain gauge ground observations

USGS Publications Warehouse

Munzimi, Yolande A.; Hansen, Matthew C.; Adusei, Bernard; Senay, Gabriel B.

2015-01-01

Quantitative understanding of Congo River basin hydrological behavior is poor because of the basin’s limited hydrometeorological observation network. In cases such as the Congo basin where ground data are scarce, satellite-based estimates of rainfall, such as those from the joint NASA/JAXA Tropical Rainfall Measuring Mission (TRMM), can be used to quantify rainfall patterns. This study tests and reports the use of limited rainfall gauge data within the Democratic Republic of Congo (DRC) to recalibrate a TRMM science product (TRMM 3B42, version 6) in characterizing precipitation and climate in the Congo basin. Rainfall estimates from TRMM 3B42, version 6, are compared and adjusted using ground precipitation data from 12 DRC meteorological stations from 1998 to 2007. Adjustment is achieved on a monthly scale by using a regression-tree algorithm. The output is a new, basin-specific estimate of monthly and annual rainfall and climate types across the Congo basin. This new product and the latest version-7 TRMM 3B43 science product are validated by using an independent long-term dataset of historical isohyets. Standard errors of the estimate, root-mean-square errors, and regression coefficients r were slightly and uniformly better with the recalibration from this study when compared with the 3B43 product (mean monthly standard errors of 31 and 40 mm of precipitation and mean r2 of 0.85 and 0.82, respectively), but the 3B43 product was slightly better in terms of bias estimation (1.02 and 1.00). Despite reasonable doubts that have been expressed in studies of other tropical regions, within the Congo basin the TRMM science product (3B43) performed in a manner that is comparable to the performance of the recalibrated product that is described in this study.

Precipitation forecasts for rainfall runoff predictions. A case study in poorly gauged Ribb and Gumara catchments, upper Blue Nile, Ethiopia

NASA Astrophysics Data System (ADS)

Seyoum, Mesgana; van Andel, Schalk Jan; Xuan, Yunqing; Amare, Kibreab

Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5 forecasts with a spatial resolution of 2 km; the Maximum, Mean and Minimum members (MaxEPS, MeanEPS and MinEPS where EPS stands for Ensemble Prediction System) of the fixed, low resolution (2.5 by 2.5 degrees) National Oceanic and Atmospheric Administration Global Forecast System (NOAA GFS) ensemble forecasts were used. Both the MM5 and the EPS were not calibrated (bias correction, downscaling (for EPS), etc.). In addition, zero forecasts assuming no rainfall in the coming days, and monthly average forecasts assuming average monthly rainfall in the coming days, were used. These rainfall forecasts were then used to drive the Hydrologic Engineering Center’s-Hydrologic Modeling System, HEC-HMS, hydrologic model for flow predictions. The results show that flow predictions using MaxEPS and MM5 precipitation forecasts over-predicted the peak flow for most of the seven events analyzed, whereas under-predicted peak flow was found using zero- and monthly average rainfall. The comparison of observed and predicted flow hydrographs shows that MM5, MaxEPS and MeanEPS precipitation forecasts were able to capture the rainfall signal that caused peak flows. Flow predictions based on MaxEPS and MeanEPS gave results that were quantitatively close to the observed flow for most events, whereas flow predictions based on MM5 resulted in large overestimations for some events. In follow-up research for this particular case study, calibration of the MM5 model will be performed. The overall analysis shows that freely available atmospheric forecasting products can provide additional information on upcoming rainfall and peak flow events in areas where only base-line forecasts such as no-rainfall or climatology are available.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

DOE PAGES

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; ...

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-04-01

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ˜25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present‐Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

PubMed Central

Pritchard, Michael S.; O'Brien, Travis A.; Timmermans, Ben W.

2018-01-01

Abstract Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ∼25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderate rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large‐scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large‐scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large‐scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large‐scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale‐aware parameterizations, but also reveal unrecognized trade‐offs from the entanglement of precipitation frequency and total amount. PMID:29861837

Rainfall From Resolved Rather Than Parameterized Processes Better Represents the Present-Day and Climate Change Response of Moderate Rates in the Community Atmosphere Model

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

Kooperman, Gabriel J.; Pritchard, Michael S.; O'Brien, Travis A.

Deficiencies in the parameterizations of convection used in global climate models often lead to a distorted representation of the simulated rainfall intensity distribution (i.e., too much rainfall from weak rain rates). While encouraging improvements in high percentile rainfall intensity have been found as the horizontal resolution of the Community Atmosphere Model is increased to ~25 km, we demonstrate no corresponding improvement in the moderate rain rates that generate the majority of accumulated rainfall. Using a statistical framework designed to emphasize links between precipitation intensity and accumulated rainfall beyond just the frequency distribution, we show that CAM cannot realistically simulate moderatemore » rain rates, and cannot capture their intensification with climate change, even as resolution is increased. However, by separating the parameterized convective and large-scale resolved contributions to total rainfall, we find that the intensity, geographic pattern, and climate change response of CAM's large-scale rain rates are more consistent with observations (TRMM 3B42), superparameterization, and theoretical expectations, despite issues with parameterized convection. Increasing CAM's horizontal resolution does improve the representation of total rainfall intensity, but not due to changes in the intensity of large-scale rain rates, which are surprisingly insensitive to horizontal resolution. Rather, improvements occur through an increase in the relative contribution of the large-scale component to the total amount of accumulated rainfall. Analysis of sensitivities to convective timescale and entrainment rate confirm the importance of these parameters in the possible development of scale-aware parameterizations, but also reveal unrecognized trade-offs from the entanglement of precipitation frequency and total amount.« less

Impact of an intense rainfall event on soil properties following a wildfire in a Mediterranean environment (North-East Spain).

PubMed

Francos, Marcos; Pereira, Paulo; Alcañiz, Meritxell; Mataix-Solera, Jorge; Úbeda, Xavier

2016-12-01

Intense rainfall events after severe wildfires can have an impact on soil properties, above all in the Mediterranean environment. This study seeks to examine the immediate impact and the effect after a year of an intense rainfall event on a Mediterranean forest affected by a high severity wildfire. The work analyses the following soil properties: soil aggregate stability, total nitrogen, total carbon, organic and inorganic carbon, the C/N ratio, carbonates, pH, electrical conductivity, extractable calcium, magnesium, sodium, potassium, available phosphorous and the sodium and potassium adsorption ratio (SPAR). We sampled soils in the burned area before, immediately after and one year after the rainfall event. The results showed that the intense rainfall event did not have an immediate impact on soil aggregate stability, but a significant difference was recorded one year after. The intense precipitation did not result in any significant changes in soil total nitrogen, total carbon, inorganic carbon, the C/N ratio and carbonates during the study period. Differences were only registered in soil organic carbon. The soil organic carbon content was significantly higher after the rainfall than in the other sampling dates. The rainfall event did increase soil pH, electrical conductivity, major cations, available phosphorous and the SPAR. One year after the fire, a significant decrease in soil aggregate stability was observed that can be attributed to high SPAR levels and human intervention, while the reduction in extractable elements can be attributed to soil leaching and vegetation consumption. Overall, the intense rainfall event, other post-fire rainfall events and human intervention did not have a detrimental impact on soil properties in all probability owing to the flat plot topography. Copyright © 2016 Elsevier B.V. All rights reserved.

Influence of preonset land atmospheric conditions on the Indian summer monsoon rainfall variability

NASA Astrophysics Data System (ADS)

Rai, Archana; Saha, Subodh K.; Pokhrel, Samir; Sujith, K.; Halder, Subhadeep

2015-05-01

A possible link between preonset land atmospheric conditions and the Indian summer monsoon rainfall (ISMR) is explored. It is shown that, the preonset positive (negative) rainfall anomaly over northwest India, Pakistan, Afghanistan, and Iran is associated with decrease (increase) in ISMR, primarily in the months of June and July, which in turn affects the seasonal mean. ISMR in the months of June and July is also strongly linked with the preonset 2 m air temperature over the same regions. The preonset rainfall/2 m air temperature variability is linked with stationary Rossby wave response, which is clearly evident in the wave activity flux diagnostics. As the predictability of Indian summer monsoon relies mainly on the El Niño-Southern Oscillation (ENSO), the found link may further enhance our ability to predict the monsoon, particularly during a non-ENSO year.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Hydrogeologic reconnaissance of Poro Point and vicinity, Luzon Island, Philippines

USGS Publications Warehouse

Worts, George Frank

1964-01-01

In 1961 a reconnaissance of the geology and ground-water hydrology of Poro Point, on the west coast of Luzon Island, Philippines, was made on behalf of the U.S. Department of the Navy. Poro Point, which marks the northern end of Lingayen Gulf, is about half a mile wide and projects northwestward about 2 miles into the China Sea. The point is underlain by coralline limestone of probable Pleistocene age. The aquifer system consists of a fresh-water lens floating on salt water within the coralline limestone. Several tube wells obtain fresh water from the lens, but in May, at the end of the 6-month dry season during which rainfall totals only 40 inches, the water becomes brackish. 'Skimming wells' are considered the best method of obtaining fresh water from the lens, whose annual range in average thickness is probably 25 to 40 feet. Recharge is about 2,000-3,000 acre-feet per year and is derived wholly from precipitation during the 6-month wet season in which rainfall totals about 92 inches. The approximate amount of ground water stored in the fresh-water lens ranges from about 3,000 acre-feet at the end of the dry season to about 5,000 acre-feet at the end of the wet season. Most of the ground water is discharged through seeps and submarine springs around Poro Point; pumpage in 1961 was only about 100 acre-feet.

Mixed forest plantations can efficiently filter rainfall deposits of sulfur and chlorine in Western China

PubMed Central

Zhao, Hairong; Yang, Wanqin; Wu, Fuzhong; Tan, Bo

2017-01-01

Forest filtering is a well-known and efficient method for diminishing atmospheric pollutant (such as SO42− and Cl−) inputs to soil and water; however, the filtering efficiencies of forests vary depending on the regional vegetation and climate. The rainy area of West China has suffered from heavy rainfall and human activity, which has potentially resulted in large amounts of sulfur and chlorine deposition, but little information is available regarding the filtering effects of typical plantations. Therefore, the migration of SO42− and Cl− from rainfall to throughfall, stemflow and runoff were investigated in a camphor (Cinnamomum camphora) plantation, a cryptomeria (Cryptomeria fortunei) plantation and a mixed plantation in a 9-month forest hydrology experiment. The results indicated the following: (i) The total SO42− and Cl− deposition was 43.05 kg ha−1 and 5.25 kg ha−1, respectively. (ii) The cover layer had the highest interception rate (60.08%), followed by the soil layer (16.02%) and canopy layer (12.85%). (iii) The mixed plantation resulted in the highest SO42− (37.23%) and Cl− (51.91%) interception rates at the forest ecosystem scale, and the interception rate increased with increasing rainfall. These results indicate that mixed plantations can effectively filter SO42− and Cl− in this area and in similar areas. PMID:28134356

Spatial and temporal heterogeneity of water soil erosion in a Mediterranean rain-fed crop

NASA Astrophysics Data System (ADS)

López-Vicente, M.; Quijano, L.; Gaspar, L.; Machín, J.; Navas, A.

2012-04-01

Fertile soil loss by raindrop impact and runoff processes in croplands presents significant variations at temporal and spatial scales. The combined use of advanced GIS techniques and detailed databases allows high resolution mapping of runoff and soil erosion processes. In this study the monthly values of soil loss are calculated in a medium size field of rain-fed winter barley and its drainage area located in the Central Spanish Pre-Pyrenees. The field is surrounded by narrow strips of dense Mediterranean vegetation (mainly holm oaks) and grass. Man-made infrastructures (paved trails and drainage ditches) modify the overland flow pathways and the study site appears hydrologically closed in its northern and western boundaries. This area has a continental Mediterranean climate with two humid periods, one in spring and a second in autumn and a dry summer with rainfall events of high intensity from July to October. The average annual rainfall is 495 mm and the average monthly rainfall intensity ranges from 1.1 mm / h in January to 7.4 mm / h in July. The predicted rates were obtained after running the RMMF model (Morgan, 2001) with the enhancements made to this model by Morgan and Duzant (2008) to the topographic module, and by López-Vicente and Navas (2010) to the hydrological module. A total of 613 soil samples were collected and all input and output maps were generated at high spatial resolution (1 x 1 m of cell size) with ArcMapTM 10.0. A map of effective cumulative runoff was calculated for each month of the year with a weighted multiple flow algorithm and four sub-catchments were distinguished within the field. The average soil erosion in the cultivated area is 1.32 Mg / ha yr and the corresponding map shows a high spatial variability (s.d. = 7.52 Mg / ha yr). The highest values of soil erosion appear in those areas where overland flow is concentrated and slope steepness is higher. The unpaved trail present the highest values of soil erosion with an average value of 72.23 Mg / ha yr, whereas the grass and forested areas have annual rates lower than 0.1 Mg / ha yr. The highest values of soil erosion appear in March, April, May, October and November showing a very good correlation with the depth of monthly rainfall (Pearson's r = 0.97) and a good correlation with the number of rainy days per month (Pearson's r = 0.76). However, no correlation was obtained with the values of monthly rainfall intensity. The availability of a detailed database of soil properties, weather values and a high resolution DEM allows mapping and calculating the spatial and temporal variations of the soil erosion processes within the cultivated area and the area surrounding the crop. Thus, the application of soil erosion models at high spatial and temporal resolution improves their predicting capability due to the complexity and large number of relevant interactions between the different sub-factors.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Effects of the 1998 Drought on the Freshwater Lens in the Laura Area, Majuro Atoll, Republic of the Marshall Islands

USGS Publications Warehouse

Presley, Todd K.

2005-01-01

Lower than average rainfall during late 1997 and early 1998 in Majuro Atoll, Republic of the Marshall Islands, caused a drought and severe drinking-water shortage. Majuro depends on a public rainfall catchment system, which uses an airport runway and storage reservoirs. The storage reservoirs can supply water for about 30 to 50 days without replenishment. In February 1998, after a few months with less than one inch of rainfall per month, a drought-related disaster was declared. Reverse-osmosis water-purification systems were brought to Majuro to help alleviate the water shortage. Concurrent with the water-purification program, ground water from a freshwater lens in the Laura area of the atoll was pumped at increased rates. Of the total consumed water during this period, ground water from Laura supplied between 90 percent (March 1998) and 64 percent (May 1998) of the drinking water. Due to public concern, a study was initiated to determine the effects of the drought on the freshwater lens. The areal extent of the freshwater lens is about 350 acres. A monitoring-well network, consisting of multiple wells driven to varying depths at 11 sites, was installed to determine the thickness of the freshwater lens. Similar locations relative to an earlier study were chosen so that the data from this study could be compared to 1984-85 data. At the end of the drought in June 1998, the freshwater near the middle of the lens was about 45 feet thick; and at the north and south ends, the freshwater was about 25 to 38 feet thick, respectively. Monitoring of the freshwater lens was continued through the wet season following the drought. The lens increased in thickness by 1 to 8 feet after 7 months of rainfall. Greater increases in lens thickness were measured on the lagoon side than on the ocean side of the freshwater lens. Lens thickness during August 1998, and seasonal variation of lens thickness in 1998, were compared to data collected in 1984-85. Comparison of lens thickness from the different years yielded an inconsistent result; the lens was not uniformly thicker in 1984-85 despite more rainfall and little or no pumpage during this time. Seasonal variation in 1998-99 was greater than seasonal variation in 1984-85 due to differences in seasonal rainfall and pumpage. The change in lens thickness suggested by the comparison between 1998-99 and 1984-85 data was complicated by effects due to different well locations, different wells, and assumed small-scale variability in the thickness of fine and coarse calcareous sediments. This result suggests that a monitoring program that uses the same wells through time is needed to adequately describe long-term variability in lens thickness.

Impact of tapping and soil water status on fine root dynamics in a rubber tree plantation in Thailand

PubMed Central

Chairungsee, Naruenat; Gay, Frederic; Thaler, Philippe; Kasemsap, Poonpipope; Thanisawanyangkura, Sornprach; Chantuma, Arak; Jourdan, Christophe

2013-01-01

Fine roots (FR) play a major role in the water and nutrient uptake of plants and contribute significantly to the carbon and nutrient cycles of ecosystems through their annual production and turnover. FR growth dynamics were studied to understand the endogenous and exogenous factors driving these processes in a 14-year-old plantation of rubber trees located in eastern Thailand. FR dynamics were observed using field rhizotrons from October 2007 to October 2009. This period covered two complete dry seasons (November to March) and two complete rainy seasons (April to October), allowing us to study the effect of rainfall seasonality on FR dynamics. Rainfall and its distribution during the two successive years showed strong differences with 1500 and 950 mm in 2008 and 2009, respectively. FR production (FRP) completely stopped during the dry seasons and resumed quickly after the first rains. During the rainy seasons, FRP and the daily root elongation rate (RER) were highly variable and exhibited strong annual variations with a total FRP of 139.8 and 40.4 mm-2 and an average RER of 0.16 and 0.12 cm day-1 in 2008 and 2009, respectively. The significant positive correlations found between FRP, RER, the appearance of new roots, and rainfall at monthly intervals revealed the impact of rainfall seasonality on FR dynamics. However, the rainfall patterns failed to explain the weekly variations of FR dynamics observed particularly during the rainy seasons. At this time step, FRP, RER, and the appearance of new FR were negatively correlated to the average soil matric potential measured at a depth of between 30 and 60 cm. In addition, our study revealed a significant negative correlation between FR dynamics and the monthly production of dry rubber. Consequently, latex harvesting might disturb carbon dynamics in the whole tree, far beyond the trunk where the tapping was performed. These results exhibit the impact of climatic conditions and tapping system in the carbon budget of rubber plantations. PMID:24400016

Modelling runoff and soil water content with the DR2-2013© SAGA v1.1 model at catchment scale under Mediterranean conditions (NE Spain)

NASA Astrophysics Data System (ADS)

López-Vicente, Manuel, , Dr.; Palazón, M. Sc. Leticia; Quijano, M. Sc. Laura; Gaspar, Leticia, , Dr.; Navas, Ana, , Dr.

2015-04-01

Hydrological and soil erosion models allow mapping and quantifying spatially distributed rates of runoff depth and soil redistribution for different land uses, management and tillage practices and climatic scenarios. The different temporal and spatial [very small (< 1 km2), small (1-5 km2), medium (5-50 km2) and large catchments (50-1000 km2) or river basins (>1000 km2)] scales of numerical simulations make model selection specific to each range of scales. Additionally, the spatial resolution of the inputs is in agreement with the size of the study area. In this study, we run the GIS-based water balance DR2-2013© SAGA v1.1 model (freely downloaded as executable file at http://digital.csic.es/handle/10261/93543), in the Vandunchil stream catchment (23 km2; Ebro river basin, NE Spain). All input maps are generated at 5 x 5 m of cell size (924,573 pixels per map) allowing sound parameterization. Simulation is run at monthly scale with average climatic values. This catchment is an open hydrological system and it has a long history of human occupation, agricultural practices and water management. Numerous manmade infrastructures or landscape linear elements (LLEs: paved and unpaved trails, rock mounds in non-cultivated areas, disperse and small settlements, shallow and long drainage ditches, stone walls, small rock dams, fences and vegetation strips) appear throughout the hillslopes and streams and modify the natural runoff pathways and thus the hydrological and sediment connectivity. Rain-fed cereal fields occupy one third of the catchment area, 1% corresponds to sealed soils, and the remaining area is covered with Mediterranean forest, scrubland, pine afforestation and meadow. The parent material corresponds to Miocene sandstones and lutites and Holocene colluvial and alluvial deposits. The climate is continental Mediterranean with two humid periods, one in spring and a second in autumn that summarizes 63% of the total annual precipitation. We created a synthetic weather station (WS) from the Caseda and Uncastillo WS. The effective rainfall that reaches the soils (after canopy interception and slope correction) was 85% on average from the total rainfall depth (556 mm yr-1) and the average initial runoff, before overland flow processes, was 320 mm yr-1. The simulated effective runoff (CQeff) ranged from 0 until 29,960 mm yr-1 and the corresponding map showed the typical spatial pattern of overland flow pathways though numerous disruptions appeared along the hillslopes and the main streams due to the presence of LLEs. The total depth of annual runoff corresponds to 37.8% of the total effective rainfall (TER) and 32.0% of the total rainfall depth (TR). The remaining volume of water, the soil water content (Waa) associated with the runoff and rainfall events, meant 62.2% and 52.7% of the TER and TR, respectively. The map of the Waa presented a different spatial pattern where the land uses play a more important role than the processes of cumulative overland flow. Significant variations in the monthly values of CQeff and Waa were described. This study proves the ability of the DR2-2013© SAGA v1.1 model to simulate the hydrological response of the soils at catchment scale.

Validation of new satellite rainfall products over the Upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Tesfaye Ayehu, Getachew; Tadesse, Tsegaye; Gessesse, Berhan; Dinku, Tufa

2018-04-01

Accurate measurement of rainfall is vital to analyze the spatial and temporal patterns of precipitation at various scales. However, the conventional rain gauge observations in many parts of the world such as Ethiopia are sparse and unevenly distributed. An alternative to traditional rain gauge observations could be satellite-based rainfall estimates. Satellite rainfall estimates could be used as a sole product (e.g., in areas with no (or poor) ground observations) or through integrating with rain gauge measurements. In this study, the potential of a newly available Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall product has been evaluated in comparison to rain gauge data over the Upper Blue Nile basin in Ethiopia for the period of 2000 to 2015. In addition, the Tropical Applications of Meteorology using SATellite and ground-based observations (TAMSAT 3) and the African Rainfall Climatology (ARC 2) products have been used as a benchmark and compared with CHIRPS. From the overall analysis at dekadal (10 days) and monthly temporal scale, CHIRPS exhibited better performance in comparison to TAMSAT 3 and ARC 2 products. An evaluation based on categorical/volumetric and continuous statistics indicated that CHIRPS has the greatest skills in detecting rainfall events (POD = 0.99, 1.00) and measure of volumetric rainfall (VHI = 1.00, 1.00), the highest correlation coefficients (r = 0.81, 0.88), better bias values (0.96, 0.96), and the lowest RMSE (28.45 mm dekad-1, 59.03 mm month-1) than TAMSAT 3 and ARC 2 products at dekadal and monthly analysis, respectively. CHIRPS overestimates the frequency of rainfall occurrence (up to 31 % at dekadal scale), although the volume of rainfall recorded during those events was very small. Indeed, TAMSAT 3 has shown a comparable performance with that of the CHIRPS product, mainly with regard to bias. The ARC 2 product was found to have the weakest performance underestimating rain gauge observed rainfall by about 24 %. In addition, the skill of CHIRPS is less affected by variation in elevation in comparison to TAMSAT 3 and ARC 2 products. CHIRPS resulted in average biases of 1.11, 0.99, and 1.00 at lower (< 1000 m a.s.l.), medium (1000 to 2000 m a.s.l.), and higher elevation (> 2000 m a.s.l.), respectively. Overall, the finding of this validation study shows the potentials of the CHIRPS product to be used for various operational applications such as rainfall pattern and variability study in the Upper Blue Nile basin in Ethiopia.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Use of eddy-covariance methods to "calibrate" simple estimators of evapotranspiration

USGS Publications Warehouse

Sumner, David M.; Geurink, Jeffrey S.; Swancar, Amy

2017-01-01

Direct measurement of actual evapotranspiration (ET) provides quantification of this large component of the hydrologic budget, but typically requires long periods of record and large instrumentation and labor costs. Simple surrogate methods of estimating ET, if “calibrated” to direct measurements of ET, provide a reliable means to quantify ET. Eddy-covariance measurements of ET were made for 12 years (2004-2015) at an unimproved bahiagrass (Paspalum notatum) pasture in Florida. These measurements were compared to annual rainfall derived from rain gage data and monthly potential ET (PET) obtained from a long-term (since 1995) U.S. Geological Survey (USGS) statewide, 2-kilometer, daily PET product. The annual proportion of ET to rainfall indicates a strong correlation (r2=0.86) to annual rainfall; the ratio increases linearly with decreasing rainfall. Monthly ET rates correlated closely (r2=0.84) to the USGS PET product. The results indicate that simple surrogate methods of estimating actual ET show positive potential in the humid Florida climate given the ready availability of historical rainfall and PET.

Characterization of Urban Runoff Pollution between Dissolved and Particulate Phases

PubMed Central

Wei, Zhang; Simin, Li; Fengbing, Tang

2013-01-01

To develop urban stormwater management effectively, characterization of urban runoff pollution between dissolved and particulate phases was studied by 12 rainfall events monitored for five typical urban catchments. The average event mean concentration (AEMC) of runoff pollutants in different phases was evaluated. The AEMC values of runoff pollutants in different phases from urban roads were higher than the ones from urban roofs. The proportions of total dissolved solids, total dissolved nitrogen, and total dissolved phosphorus in total ones for all the catchments were 26.19%–30.91%, 83.29%–90.51%, and 61.54–68.09%, respectively. During rainfall events, the pollutant concentration at the initial stage of rainfall was high and then sharply decreased to a low value. Affected by catchments characterization and rainfall distribution, the highest concentration of road pollutants might appear in the later period of rainfall. Strong correlations were also found among runoffs pollutants in different phases. Total suspended solid could be considered as a surrogate for particulate matters in both road and roof runoff, while dissolved chemical oxygen demand could be regarded as a surrogate for dissolved matters in roof runoff. PMID:23935444

Climate variables as predictors for seasonal forecast of dengue occurrence in Chennai, Tamil Nadu

NASA Astrophysics Data System (ADS)

Subash Kumar, D. D.; Andimuthu, R.

2013-12-01

Background Dengue is a recently emerging vector borne diseases in Chennai. As per the WHO report in 2011 dengue is one of eight climate sensitive disease of this century. Objective Therefore an attempt has been made to explore the influence of climate parameters on dengue occurrence and use for forecasting. Methodology Time series analysis has been applied to predict the number of dengue cases in Chennai, a metropolitan city which is the capital of Tamil Nadu, India. Cross correlation of the climate variables with dengue cases revealed that the most influential parameters were monthly relative humidity, minimum temperature at 4 months lag and rainfall at one month lag (Table 1). However due to intercorrelation of relative humidity and rainfall was high and therefore for predictive purpose the rainfall at one month lag was used for the model development. Autoregressive Integrated Moving Average (ARIMA) models have been applied to forecast the occurrence of dengue. Results and Discussion The best fit model was ARIMA (1,0,1). It was seen that the monthly minimum temperature at four months lag (β= 3.612, p = 0.02) and rainfall at one month lag (β= 0.032, p = 0.017) were associated with dengue occurrence and they had a very significant effect. Mean Relative Humidity had a directly significant positive correlation at 99% confidence level, but the lagged effect was not prominent. The model predicted dengue cases showed significantly high correlation of 0.814(Figure 1) with the observed cases. The RMSE of the model was 18.564 and MAE was 12.114. The model is limited by the scarcity of the dataset. Inclusion of socioeconomic conditions and population offset are further needed to be incorporated for effective results. Conclusion Thus it could be claimed that the change in climatic parameters is definitely influential in increasing the number of dengue occurrence in Chennai. The climate variables therefore can be used for seasonal forecasting of dengue with rise in minimum temperature and rainfall at a city level. Table 1. Cross correlation of climate variables with dengue cases in Chennai ** p<0.01,*p<0.05

Effect of Dam operation on monthly and annual trends of flow discharge in the Qom Rood Watershed, Iran

NASA Astrophysics Data System (ADS)

Yaghmaei, Hiva; Sadeghi, Seyed Hamidreza; Moradi, Hamidreza; Gholamalifard, Mehdi

2018-02-01

Trends in flow discharge, temperature and rainfall from the Qom Rood Watershed, Iran, for a period of 1979-2016 were analyzed at monthly and annual time scales. Trend analyses were conducted using the Mann-Kendall test, the double-mass curve of mean annual discharge versus rainfall, and rainfall-runoff relationship before and after the 15 Khordad Dam operation. Multiple regression of flow discharge against rainfall and temperature was used to determine the residual trend at four meteorological and hydrological stations located upstream and downstream of the Qom Rood Watershed. Results showed that the temperature at the upstream and downstream stations did not have any significant trend, but a significant decreasing trend (P < .05) in rainfall was detected only in May (z = -1.66) at the downstream stations. There was a significant positive trend (P < .05) in rainfall in February (z = 2.22) and July (z = 2.15) at the upstream stations, and in October (z = 2.3) and November (z = 1.8) at the downstream stations. However, there was a noticeable decrease in monthly and annual flow discharge, and residual trend at 99% significance level at the downstream stations. At the upstream stations, the flow discharges had significant (P < .05) declining trend in all months, but annual flow discharge did not change significantly. Analysis of double mass curve between runoff and rainfall at the downstream stations showed an inconsistency in the line slope concordant with the time of 15 Khordad Dam operation. Annual mean discharge at the upstream stations did not show a significant change before and after 15 Khordad Dam operation. However, annual flow magnitude decreased significantly by 87.5 and 81.7% in Shad Abad and KoohSefid, respectively. These results confirmed that natural driving forces did not affect flow discharge changes and the observed decreasing tendency in flow discharge at the downstream stations was due to 15 Khordad Dam, and at the upstream stations due to diversion/storage dams. These findings highlighted the role of human interference in changing the hydrologic regime in the study area based on which appropriate adaptive decisions can be made.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

NASA Technical Reports Server (NTRS)

Negri, A. J.; Xu, L.; Adler, R. F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The development of a satellite infrared technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall in Amazonia are presented. The Convective-Stratiform. Technique, calibrated by coincident, physically retrieved rain rates from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI), is applied during January to April 1999 over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. Results compare well (a one-hour lag) with the diurnal cycle derived from Tropical Ocean-Global Atmosphere (TOGA) radar-estimated rainfall in Rondonia. The satellite estimates reveal that the convective rain constitutes, in the mean, 24% of the rain area while accounting for 67% of the rain volume. The effects of geography (rivers, lakes, coasts) and topography on the diurnal cycle of convection are examined. In particular, the Amazon River, downstream of Manaus, is shown to both enhance early morning rainfall and inhibit afternoon convection. Monthly estimates from this technique, dubbed CST/TMI, are verified over a dense rain gage network in the state of Ceara, in northeast Brazil. The CST/TMI showed a high bias equal to +33% of the gage mean, indicating that possibly the TMI estimates alone are also high. The root mean square difference (after removal of the bias) equaled 36.6% of the gage mean. The correlation coefficient was 0.77 based on 72 station-months.

Assessing the statistical relationships among water-derived climate variables, rainfall, and remotely sensed features of vegetation: implications for evaluating the habitat of ticks.

PubMed

Alonso-Carné, J; García-Martín, A; Estrada-Peña, A

2015-01-01

Ticks are sensitive to changes in relative humidity and saturation deficit at the microclimate scale. Trends and changes in rainfall are commonly used as descriptors of field observations of tick populations, to capture the climate niche of ticks or to predict the climate suitability for ticks under future climate scenarios. We evaluated daily and monthly relationships between rainfall, relative humidity and saturation deficit over different ecosystems in Europe using daily climate values from 177 stations over a period of 10 years. We demonstrate that rainfall is poorly correlated with both relative humidity and saturation deficit in any of the ecological domains studied. We conclude that the amount of rainfall recorded in 1 day does not correlate with the values of humidity or saturation deficit recorded 24 h later: rainfall is not an adequate surrogate for evaluating the physiological processes of ticks at regional scales. We compared the Normalized Difference Vegetation Index (NDVI), a descriptor of photosynthetic activity, at a spatial resolution of 0.05°, with monthly averages of relative humidity and saturation deficit and also determined a lack of significant correlation. With the limitations of spatial scale and habitat coverage of this study, we suggest that the rainfall or NDVI cannot replace relative humidity or saturation deficit as descriptors of tick processes.

Disaggregating from daily to sub-daily rainfall under a future climate

NASA Astrophysics Data System (ADS)

Westra, S.; Evans, J.; Mehrotra, R.; Sharma, A.

2012-04-01

We describe an algorithm for disaggregating daily rainfall into sub-daily rainfall 'fragments' (continuous fine-resolution rainfall sequences whose total depth sums to the daily rainfall amount) under a future, warmer climate. The basis of the algorithm is re-sample sub-daily fragments from the historical record conditional on the total daily rainfall amount and a range of atmospheric predictors representative of the future climate. The logic is that as the atmosphere warms, future rainfall patterns will be more reflective of historical rainfall patterns which occurred on warmer days at the same location, or at locations which have an atmospheric profile more reflective of expected future conditions. When looking at the scaling from daily to sub-daily rainfall over the historical record, it was found that the relationship varied significantly by season and by location, with rainfall patterns on warmer seasons or at warmer locations typically showing more intense rain falling over shorter periods compared with cooler seasons and stations. Importantly, by regressing against atmospheric covariates such as temperature this effect was almost entirely eliminated, providing a basis for suggesting the approach may be valid when extrapolating sub-daily sequences to a future climate. The method of fragments algorithm was then applied to nine stations around Australia, and showed that when holding the total daily rainfall constant, the maximum intensity of a short duration (6 minute) rainfall increased by between 4.1% and 13.4% per degree change in temperature for the maximum six minute burst, between 3.1% and 6.8% for the maximum one hour burst, and between 1.5% and 3.5% for the fraction of the day with no rainfall. This highlights that a large proportion of the change to the distribution of precipitation in the future is likely to occur at sub-daily timescales, with significant implications for many hydrological systems.

Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2017-03-01

The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the total flow variability in the response of the urban drainage systems to heavy rainfall events.

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

PubMed

Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

2012-07-01

To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

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.

A Simple Lightning Assimilation Technique For Improving Retrospective WRF Simulations

EPA Science Inventory

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain...

A simple lightning assimilation technique for improving retrospective WRF simulations.

EPA Science Inventory

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-F...

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.

Analysis of spatial and temporal rainfall trends in Sicily during the 1921-2012 period

NASA Astrophysics Data System (ADS)

Liuzzo, Lorena; Bono, Enrico; Sammartano, Vincenzo; Freni, Gabriele

2016-10-01

Precipitation patterns worldwide are changing under the effects of global warming. The impacts of these changes could dramatically affect the hydrological cycle and, consequently, the availability of water resources. In order to improve the quality and reliability of forecasting models, it is important to analyse historical precipitation data to account for possible future changes. For these reasons, a large number of studies have recently been carried out with the aim of investigating the existence of statistically significant trends in precipitation at different spatial and temporal scales. In this paper, the existence of statistically significant trends in rainfall from observational datasets, which were measured by 245 rain gauges over Sicily (Italy) during the 1921-2012 period, was investigated. Annual, seasonal and monthly time series were examined using the Mann-Kendall non-parametric statistical test to detect statistically significant trends at local and regional scales, and their significance levels were assessed. Prior to the application of the Mann-Kendall test, the historical dataset was completed using a geostatistical spatial interpolation technique, the residual ordinary kriging, and then processed to remove the influence of serial correlation on the test results, applying the procedure of trend-free pre-whitening. Once the trends at each site were identified, the spatial patterns of the detected trends were examined using spatial interpolation techniques. Furthermore, focusing on the 30 years from 1981 to 2012, the trend analysis was repeated with the aim of detecting short-term trends or possible changes in the direction of the trends. Finally, the effect of climate change on the seasonal distribution of rainfall during the year was investigated by analysing the trend in the precipitation concentration index. The application of the Mann-Kendall test to the rainfall data provided evidence of a general decrease in precipitation in Sicily during the 1921-2012 period. Downward trends frequently occurred during the autumn and winter months. However, an increase in total annual precipitation was detected during the period from 1981 to 2012.

Improving the performance of streamflow forecasting model using data-preprocessing technique in Dungun River Basin

NASA Astrophysics Data System (ADS)

Khai Tiu, Ervin Shan; Huang, Yuk Feng; Ling, Lloyd

2018-03-01

An accurate streamflow forecasting model is important for the development of flood mitigation plan as to ensure sustainable development for a river basin. This study adopted Variational Mode Decomposition (VMD) data-preprocessing technique to process and denoise the rainfall data before putting into the Support Vector Machine (SVM) streamflow forecasting model in order to improve the performance of the selected model. Rainfall data and river water level data for the period of 1996-2016 were used for this purpose. Homogeneity tests (Standard Normal Homogeneity Test, the Buishand Range Test, the Pettitt Test and the Von Neumann Ratio Test) and normality tests (Shapiro-Wilk Test, Anderson-Darling Test, Lilliefors Test and Jarque-Bera Test) had been carried out on the rainfall series. Homogenous and non-normally distributed data were found in all the stations, respectively. From the recorded rainfall data, it was observed that Dungun River Basin possessed higher monthly rainfall from November to February, which was during the Northeast Monsoon. Thus, the monthly and seasonal rainfall series of this monsoon would be the main focus for this research as floods usually happen during the Northeast Monsoon period. The predicted water levels from SVM model were assessed with the observed water level using non-parametric statistical tests (Biased Method, Kendall's Tau B Test and Spearman's Rho Test).

Assessing operative natural and anthropogenic forcing factors from long-term climate time series of Uttarakhand (India) in the backdrop of recurring extreme rainfall events over northwest Himalaya

NASA Astrophysics Data System (ADS)

Agnihotri, Rajesh; Dimri, A. P.; Joshi, H. M.; Verma, N. K.; Sharma, C.; Singh, J.; Sundriyal, Y. P.

2017-05-01

The entire Indo-Himalayan region from northwest (Kashmir) to northeast (Assam) is facing prevalence of floods and landslides in recent years causing massive loss of property, human and animal lives, infrastructure, and eventually threatening tourist activities substantially. Extremely intense rainfall event of 2013 C.E. (between 15 and 17 June) kicked off mammoth flash floods in the Kedarnath area of Uttarakhand state, resulting in huge socioeconomic losses to the state and country. Uttarakhand is an important hilly region attracting thousands of tourists every year owing to numerous shrines and forested mountainous tourist spots. Though recent studies indicate a plausible weakening of Indian summer monsoon rainfall overall, recurrent anomalous high rainfall events over northwest Himalaya (e.g. -2010, 2013, and 2016) point out the need for a thorough reassessment of long-term time series data of regional rainfall and ambient temperatures in order to trace signatures of a shifting pattern in regional meteorology, if any. Accordingly, here we investigate 100-year-long monthly rainfall and air temperature time series data for a selected grid (28.5°N, 31.25°N; 78.75°E, 81.25°E) covering most parts of Uttarakhand state. We also examined temporal variance in interrelationships among regional meteorological data (temperature and precipitation) and key global climate variability indices using advance statistical methods. Major findings are (i) significant increase in pre-monsoon air temperature over Uttarakhand after 1997, (ii) increasing upward trend in June-July rainfall and its relationship with regional May temperatures (iii) monsoonal rainfall (June, July, August, and September; JJAS) showing covariance with interannual variability in Eurasian snow cover (ESC) extent during the month of March, and (iv) enhancing tendency of anomalous high rainfall events during negative phases of Arctic Oscillation. Obtained results indicate that under warming scenario, JJ rainfall (over AS) may further increase with occasional extreme rainfall spells when AO index (March) is negative.

Effect of spatial variability of storm on the optimal placement of best management practices (BMPs).

PubMed

Chang, C L; Chiueh, P T; Lo, S L

2007-12-01

It is significant to design best management practices (BMPs) and determine the proper BMPs placement for the purpose that can not only satisfy the water quantity and water quality standard, but also lower the total cost of BMPs. The spatial rainfall variability can have much effect on its relative runoff and non-point source pollution (NPSP). Meantime, the optimal design and placement of BMPs would be different as well. The objective of this study was to discuss the relationship between the spatial variability of rainfall and the optimal BMPs placements. Three synthetic rainfall storms with varied spatial distributions, including uniform rainfall, downstream rainfall and upstream rainfall, were designed. WinVAST model was applied to predict runoff and NPSP. Additionally, detention pond and swale were selected for being structural BMPs. Scatter search was applied to find the optimal BMPs placement. The results show that mostly the total cost of BMPs is higher in downstream rainfall than in upstream rainfall or uniform rainfall. Moreover, the cost of detention pond is much higher than swale. Thus, even though detention pond has larger efficiency for lowering peak flow and pollutant exports, it is not always the determined set in each subbasin.

The collaborative historical African rainfall model: description and evaluation

USGS Publications Warehouse

Funk, Christopher C.; Michaelsen, Joel C.; Verdin, James P.; Artan, Guleid A.; Husak, Gregory; Senay, Gabriel B.; Gadain, Hussein; Magadazire, Tamuka

2003-01-01

In Africa the variability of rainfall in space and time is high, and the general availability of historical gauge data is low. This makes many food security and hydrologic preparedness activities difficult. In order to help overcome this limitation, we have created the Collaborative Historical African Rainfall Model (CHARM). CHARM combines three sources of information: climatologically aided interpolated (CAI) rainfall grids (monthly/0.5° ), National Centers for Environmental Prediction reanalysis precipitation fields (daily/1.875° ) and orographic enhancement estimates (daily/0.1° ). The first set of weights scales the daily reanalysis precipitation fields to match the gridded CAI monthly rainfall time series. This produces data with a daily/0.5° resolution. A diagnostic model of orographic precipitation, VDELB—based on the dot-product of the surface wind V and terrain gradient (DEL) and atmospheric buoyancy B—is then used to estimate the precipitation enhancement produced by complex terrain. Although the data are produced on 0.1° grids to facilitate integration with satellite-based rainfall estimates, the ‘true’ resolution of the data will be less than this value, and varies with station density, topography, and precipitation dynamics. The CHARM is best suited, therefore, to applications that integrate rainfall or rainfall-driven model results over large regions. The CHARM time series is compared with three independent datasets: dekadal satellite-based rainfall estimates across the continent, dekadal interpolated gauge data in Mali, and daily interpolated gauge data in western Kenya. These comparisons suggest reasonable accuracies (standard errors of about half a standard deviation) when data are aggregated to regional scales, even at daily time steps. Thus constrained, numerical weather prediction precipitation fields do a reasonable job of representing large-scale diurnal variations.

Merging gauge and satellite rainfall with specification of associated uncertainty across Australia

NASA Astrophysics Data System (ADS)

Woldemeskel, Fitsum M.; Sivakumar, Bellie; Sharma, Ashish

2013-08-01

Accurate estimation of spatial rainfall is crucial for modelling hydrological systems and planning and management of water resources. While spatial rainfall can be estimated either using rain gauge-based measurements or using satellite-based measurements, such estimates are subject to uncertainties due to various sources of errors in either case, including interpolation and retrieval errors. The purpose of the present study is twofold: (1) to investigate the benefit of merging rain gauge measurements and satellite rainfall data for Australian conditions and (2) to produce a database of retrospective rainfall along with a new uncertainty metric for each grid location at any timestep. The analysis involves four steps: First, a comparison of rain gauge measurements and the Tropical Rainfall Measuring Mission (TRMM) 3B42 data at such rain gauge locations is carried out. Second, gridded monthly rain gauge rainfall is determined using thin plate smoothing splines (TPSS) and modified inverse distance weight (MIDW) method. Third, the gridded rain gauge rainfall is merged with the monthly accumulated TRMM 3B42 using a linearised weighting procedure, the weights at each grid being calculated based on the error variances of each dataset. Finally, cross validation (CV) errors at rain gauge locations and standard errors at gridded locations for each timestep are estimated. The CV error statistics indicate that merging of the two datasets improves the estimation of spatial rainfall, and more so where the rain gauge network is sparse. The provision of spatio-temporal standard errors with the retrospective dataset is particularly useful for subsequent modelling applications where input error knowledge can help reduce the uncertainty associated with modelling outcomes.

A 305 year monthly rainfall series for the Island of Ireland (1711-2016)

NASA Astrophysics Data System (ADS)

Murphy, Conor; Burt, Tim P.; Broderick, Ciaran; Duffy, Catriona; Macdonald, Neil; Matthews, Tom; McCarthy, Mark P.; Mullan, Donal; Noone, Simon; Ryan, Ciara; Thorne, Peter; Walsh, Seamus; Wilby, Robert L.

2017-04-01

This paper derives a continuous 305-year monthly rainfall series for the Island of Ireland (IoI) for the period 1711-2016. Two key data sources are employed: i) a previously unpublished UK Met Office Note which compiled annual rainfall anomalies and corresponding monthly per mille amounts from weather diaries and early observational records for the period 1711-1977; and ii) a long-term, homogenised monthly IoI rainfall series for the period 1850-2016. Using estimates of long-term average precipitation sampled from the quality assured series, the full record is reconstituted and insights drawn regarding notable periods and the range of climate variability and change experienced. Consistency with other long records for the region is examined, including: the England and Wales Precipitation series (EWP; 1766-2016); the early EWP Glasspoole series (1716-1765) and the Central England Temperature series (CET; 1711-2016). Strong correspondence between all records is noted from 1780 onwards. While disparities are evident between the early EWP and Ireland series, the latter shows strong decadal consistency with CET throughout the record. In addition, independent, early observations from Cork and Dublin, along with available documentary sources, corroborate the derived series and add confidence to our reconstruction. The new IoI rainfall record reveals that the wettest decades occurred in the early 18th Century, despite the fact that IoI has experienced a long-term winter wetting trend consistent with climate model projections. These exceptionally wet winters of the 1720s and 1730s were concurrent with almost unprecedented warmth in the CET, glacial advance throughout Scandinavia, and glacial retreat in West Greenland, consistent with a wintertime NAO-type forcing. Our study therefore demonstrates the value of long-term observational records for providing insight to the natural climate variability of the North Atlantic region.

Is convective precipitation increasing? The case of Catalonia

NASA Astrophysics Data System (ADS)

Llasat, M. C.; Marcos, R.; Turco, M.

2012-04-01

A recent work (Turco and Llasat, 2011) has been performed to analyse the trends of the ETCCDI (Expert Team on Climate Change Detection and Indices) precipitation indices in Catalonia (NE Iberian Peninsula) from 1951 to 2003, calculated from a interpolated dataset of daily precipitation, namely SPAIN02, regular at 0.2° horizontal resolution. This work has showed that no general trends at a regional scale have been observed, considering the annual and the seasonal regional values, and only the consecutive dry days index (CDD) at annual scale shows a locally coherent spatial trend pattern. Simultaneously, Llasat et al (2009, 2010) have showed an important increase of flash-flood events in the same region. Although aspects related with vulnerability, exposure and changes in uses of soil have been found as the main responsible of this increase, a major knowledge on the evolution of high rainfall events is mandatory. Heavy precipitation is usually associated to convective precipitation and therefore the analysis of the latter is a good indicator of it. Particularly, in Catalonia, funding was raised to define a parameter, designated as β, related with the greater or lesser convective character of the precipitation (Llasat, 2001). This parameter estimates the contribution of convective precipitation to total precipitation using 1-min or 5-min rainfall intensities usually estimated by rain gauges and it can be also analysed by means of the meteorological radar (Llasat et al, 2007). Its monthly distribution shows a maximum in August, followed by September, which are the months with the major number of flash-floods in Catalonia. This parameter also allows distinguishing between different kinds of precipitation events taking into account the degree of convective contribution. The main problem is the lack of long rainfall rate series that allow analysing trends in convective precipitation. The second one is related with its heterogeneous spatial and temporal distribution. To deal with both questions the 1-min rainfall intensity provided by the Jardí pluviograph (Barcelona, Spain) and the 5-min rainfall intensity from the SAIH network have been used. The first is situated in the Fabra observatory, at an altitude of 414 ma.s.l. and at a distance of 7.5 km from the sea, inland from the city of Barcelona. It started functioning in 1921 (Jardí, 1921), although only the series corresponding to the period 1927-1979 can be considered reliable (Burgueño et al, 1987), for this reason this series will be completed with information from other rain agues. The SAIH network from the Internal Basins of Catalonia is constituted by 126 rain gauges and provides information since 1996 (Llasat et al, 2007). Thanks to this information is possible to see that more than 70% of the population of Catalonia lives in regions where the convective contribution to the total rainfall between May and November is above 50%. Consequently, any change in its distribution can have an important social impact.

Spatial structure of monthly rainfall measurements average over 25 years and trends of the hourly variability of a current rainy day in Rwanda.

NASA Astrophysics Data System (ADS)

Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

2013-04-01

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

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

PubMed Central

Botai, Joel O.; Rautenbach, Hannes; Ncongwane, Katlego P.; Botai, Christina M.

2017-01-01

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease’s transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998–2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables’ and malaria cases’ time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature (R2 = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention. PMID:29117114

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

PubMed

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

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

PubMed

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

2016-11-18

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

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.

Changes in abundance of heterotrophic and coliform bacteria resident in stored water bodies in relation to incoming bacterial loads following rain events.

PubMed

Martin, Anthony Richard; Coombes, Peter John; Harrison, Tracey Lee; Hugh Dunstan, R

2010-01-01

Microbial properties of harvested rainwater were assessed at two study sites at Newcastle on the east coast of Australia. The investigation monitored daily counts of heterotrophic bacteria (HPC), total coliforms and E. coli during a mid-winter month (July). Immediately after a major rainfall event, increases in bacterial loads were observed at both sites, followed by gradual reductions in numbers to prior baseline levels within 7 days. Baseline HPC levels ranged from 500-1000 cfu/mL for the sites evaluated, and the loads following rain peaked at 3590-6690 cfu/mL. Baseline levels of total coliforms ranged from 0-100 cfu/100 mL and peaked at 480-1200 cfu/100 mL following rain. At Site 1, there was no evidence of E. coli loading associated with the rain events assessed, and Site 2 had no detectable E.coli colonies at baseline, with a peak load of 17 cfu/100 mL following rain which again diminished to baseline levels. It was concluded that rainfall events contributed to the bacterial load in rainwater storage systems, but processes within the rainwater storage ensured these incoming loads were not sustained.

NASA Tropical Rainfall Measurement Mission (TRMM): Effects of tropical rainfall on upper ocean dynamics, air-sea coupling and hydrologic cycle

NASA Technical Reports Server (NTRS)

Lagerloef, Gary; Busalacchi, Antonio J.; Liu, W. Timothy; Lukas, Roger B.; Niiler, Pern P.; Swift, Calvin T.

1995-01-01

This was a Tropical Rainfall Measurement Mission (TRMM) modeling, analysis and applications research project. Our broad scientific goals addressed three of the seven TRMM Priority Science Questions, specifically: What is the monthly average rainfall over the tropical ocean areas of about 10(exp 5) sq km, and how does this rain and its variability affect the structure and circulation of the tropical oceans? What is the relationship between precipitation and changes in the boundary conditions at the Earth's surface (e.g., sea surface temperature, soil properties, vegetation)? How can improved documentation of rainfall improve understanding of the hydrological cycle in the tropics?

The cumulative impacts of repeated heavy rainfall, flooding and altered water quality on the high-latitude coral reefs of Hervey Bay, Queensland, Australia.

PubMed

Butler, I R; Sommer, B; Zann, M; Zhao, J-X; Pandolfi, J M

2015-07-15

Terrestrial runoff and flooding have resulted in major impacts on coral communities worldwide, but we lack detailed understanding of flood plume conditions and their ecological effects. Over the course of repeated flooding between 2010 and 2013, we measured coral cover and water quality on the high-latitude coral reefs of Hervey Bay, Queensland, Australia. In 2013, salinity, total suspended solids, total nitrogen and total phosphorus were altered for up to six months post-flooding. Submarine groundwater caused hypo-saline conditions for a further four months. Despite the greater magnitude of flooding in 2013, declines in coral abundance (∼28%) from these floods were lower than the 2011 flood (∼40%), which occurred immediately after a decade of severe drought. There was an overall cumulative decrease of coral by ∼56% from 2010 to 2013. Our study highlights the need for local scale monitoring and research to facilitate informed management and conservation of catchments and marine environments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Transmission dynamics of Fasciola hepatica in the Plateau Region of Mexico. Effect of weather and treatment of mammals under current farm management.

PubMed

Cruz-Mendoza, Irene; Quiroz-Romero, Héctor; Correa, Dolores; Gómez-Espinoza, Guillermo

2011-01-10

The aim of the present work was to study the dynamics of Fasciola hepatica natural infection in ovines, caprines, bovines and two mollusc species, Lymnaea (Fossaria) humilis and Lymnaea (F.) bulimoides, from 2004 to mid 2007 under normal farm management conditions, and the relation to climate changes. The study was performed in a research centre in the plateau of Mexico. Temperature and rainfall were registered every month, as well as the number and intensity of infection in livestock and molluscs, as determined by coprology and direct observation/cercariae release, respectively. The first two years mammals were treated with clorsulon/ivermectin because the animals were harbouring concomitant intestinal nematode infections and this was the available drug combination. During the second period treatment was with triclabendazole. The temperature ranged from around cero to 30 °C, except during September 2005 to January 2006, when a cold climate prevailed. The rainfall augmented every year in July-August, and slightly in April, 2006. Lymneid snails appeared during or immediately after the rainfall peaks of 2004 and 2006, while few L. humilis and no L. bulimoides were present during the same period of 2005, probably because it was cold. A total of 15564 cercariae were released from molluscs during the wet time of 2004, 76 during 2005 and 368 in 2006. Several peaks of infection in mammals were observed, most occurring up to 4 months after the snails had disappeared. As expected, the weather had strong impact on snails and then on livestock infection. Also, treatment given to livestock was related to reduced cercarieae release five months later. Therefore, the combination of treatment and inspection of snails in the biotopes where the livestock graze may facilitate control of fasciolosis under current farm management. Copyright © 2010 Elsevier B.V. All rights reserved.

Assessment of an ensemble seasonal streamflow forecasting system for Australia

NASA Astrophysics Data System (ADS)

Bennett, James C.; Wang, Quan J.; Robertson, David E.; Schepen, Andrew; Li, Ming; Michael, Kelvin

2017-11-01

Despite an increasing availability of skilful long-range streamflow forecasts, many water agencies still rely on simple resampled historical inflow sequences (stochastic scenarios) to plan operations over the coming year. We assess a recently developed forecasting system called forecast guided stochastic scenarios (FoGSS) as a skilful alternative to standard stochastic scenarios for the Australian continent. FoGSS uses climate forecasts from a coupled ocean-land-atmosphere prediction system, post-processed with the method of calibration, bridging and merging. Ensemble rainfall forecasts force a monthly rainfall-runoff model, while a staged hydrological error model quantifies and propagates hydrological forecast uncertainty through forecast lead times. FoGSS is able to generate ensemble streamflow forecasts in the form of monthly time series to a 12-month forecast horizon. FoGSS is tested on 63 Australian catchments that cover a wide range of climates, including 21 ephemeral rivers. In all perennial and many ephemeral catchments, FoGSS provides an effective alternative to resampled historical inflow sequences. FoGSS generally produces skilful forecasts at shorter lead times ( < 4 months), and transits to climatology-like forecasts at longer lead times. Forecasts are generally reliable and unbiased. However, FoGSS does not perform well in very dry catchments (catchments that experience zero flows more than half the time in some months), sometimes producing strongly negative forecast skill and poor reliability. We attempt to improve forecasts through the use of (i) ESP rainfall forcings, (ii) different rainfall-runoff models, and (iii) a Bayesian prior to encourage the error model to return climatology forecasts in months when the rainfall-runoff model performs poorly. Of these, the use of the prior offers the clearest benefit in very dry catchments, where it moderates strongly negative forecast skill and reduces bias in some instances. However, the prior does not remedy poor reliability in very dry catchments. Overall, FoGSS is an attractive alternative to historical inflow sequences in all but the driest catchments. We discuss ways in which forecast reliability in very dry catchments could be improved in future work.

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.

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

NASA Astrophysics Data System (ADS)

Pan, Huali; Hu, Mingjian; Ou, Guoqiang

2017-04-01

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

Status of ground-water resources at U.S. Navy Support Facility, Diego Garcia; summary of hydrologic and climatic data, January 1992 through December 1994

USGS Publications Warehouse

Torikai, J.D.

1995-01-01

This report contains hydrologic and climatic data that describe the status of ground-water resources at U.S. Navy Support Facility, Diego Garcia. Data presented are from January 1992 through December 1994. This report concentrates on data from October through December 1994, and references previous data from 1992 through 1994. Cumulative rainfall for October through December 1994 was 55 inches which is higher than the mean cumulative rainfall of about 31 inches for the same 3 months. Total rainfall for 1994 was 131 inches which is 24 percent higher than the mean annual rainfall of 106 inches. In com- parison, total rainfall in 1992 and 1993 were 93 inches and 95 inches, respectively. Ground-water withdrawal during October through December 1994 averaged 903,000 gallons per day, while the annual withdrawal in 1994 was 942,700 gallons per day. Annual withdrawals in 1992 and 1993 averaged 935,900 gallons per day and 953,800 gallons per day, respectively. At the end of December 1994, the chloride concentration of the composite water supply was 28 milligrams per liter, well below the 250 milligrams per liter secondary drinking-water standard established by the U.S. Environmental Protection Agency. Chloride concentrations of the composite water supply from October through December 1994 ranged between 28 and 86 milligrams per liter. Chloride concentration of ground water in monitoring wells at Cantonment and Air Operations decreased in November and December, and seems to have leveled off by the end of the year. Although chloride concen- trations have decreased during the fourth quarter of 1994, there has been a general trend of increasing chloride concentrations in the deeper monitoring wells since the 1992 dry season, which began in March 1992. A fuel leak at Air Operations caused the shutdown of ten wells in May 1991. Four of the wells resumed pumping for water-supply purposes in April 1992. The remaining six wells are being used to hydraulically contain and divert fuel migration by recirculating 150,000 gallons of water each day.

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

Entropy of stable seasonal rainfall distribution in Kelantan

NASA Astrophysics Data System (ADS)

Azman, Muhammad Az-zuhri; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Radi, Noor Fadhilah Ahmad

2017-05-01

Investigating the rainfall variability is vital for any planning and management in many fields related to water resources. Climate change can gives an impact of water availability and may aggravate water scarcity in the future. Two statistics measurements which have been used by many researchers to measure the rainfall variability are variance and coefficient of variation. However, these two measurements are insufficient since rainfall distribution in Malaysia especially in the East Coast of Peninsular Malaysia is not symmetric instead it is positively skewed. In this study, the entropy concept is used as a tool to measure the seasonal rainfall variability in Kelantan and ten rainfall stations were selected. In previous studies, entropy of stable rainfall (ESR) and apportionment entropy (AE) were used to describe the rainfall amount variability during years for Australian rainfall data. In this study, the entropy of stable seasonal rainfall (ESSR) is suggested to model rainfall amount variability during northeast monsoon (NEM) and southwest monsoon (SWM) seasons in Kelantan. The ESSR is defined to measure the long-term average seasonal rainfall amount variability within a given year (1960-2012). On the other hand, the AE measures the rainfall amounts variability across the months. The results of ESSR and AE values show that stations in east coastline are more variable as compared to other stations inland for Kelantan rainfall. The contour maps of ESSR for Kelantan rainfall stations are also presented.

Correlation between total precipitable water and precipitation over East Asia

NASA Astrophysics Data System (ADS)

Keum, Wangho; Lim, Gyu-Ho

2017-04-01

The precipitation rate(PR) and the total precipitable water(TPW) interact with various physical mechanisms. The correlation of two variables changes with difference of domain resolution and characteristics of the region. This poster analyzes the correlation between PR and TPW over East Asia using Cyclostationary Empirical Orthogonal Function(CSEOF) which is one of the PCA analysis. The CSEOF is useful to search a periodic pattern of the data. The anomalies which is subtracted climatological mean from the original data are used to represent annual cycles. Two variances of ERA-Interim Monthly Total Column Water vapor and GPCP monthly precipitation amounts with 372 time since January, 1984 to December, 2014 are decomposed into several modes separately. The first mode which explain largest variance are used in analysis. PC of both PR and TPW increase recently on mean value and amplitude, and they show considerable correlation on phase. The correlation coefficient of PR and TPW is 0.61 and maintains the same values by month. The result of harmonic analysis shows 2 to 6 year oscillations. As result of decomposed modes of two variables, there is the relationship between TPW PC series and horizontal moisture gradient. The Horizontal moist gradient can change affect moisture flux convergence which is one of important variable of rainfall events.

Inter-Comparison of CHARM Data and WSR-88D Storm Integrated Rainfall

NASA Technical Reports Server (NTRS)

Jedlovec, Gary J.; Meyer, Paul J.; Guillory, Anthony R.; Stellman, Keith; Limaye, Ashutosh; Arnold, James E. (Technical Monitor)

2002-01-01

A localized precipitation network has been established over a 4000 sq km region of northern Alabama in support of local weather and climate research at the Global Hydrology and Climate Center (GHCC) in Huntsville. This Cooperative Huntsville-Area Rainfall Measurement (CHARM) network is comprised of over 80 volunteers who manually take daily rainfall measurements from 85 sites. The network also incorporates 20 automated gauges that report data at 1-5 minute intervals on a 24 h a day basis. The average spacing of the gauges in the network is about 6 kin, however coverage in some regions benefit from gauges every 1-2 km. The 24 h rainfall totals from the CHARM network have been used to validate Stage III rainfall estimates of daily and storm totals derived from the WSR-88D radars that cover northern Alabama. The Stage III rainfall product is produced by the Lower Mississippi River Forecast Center (LMRFC) in support of their daily forecast operations. The intercomparisons between the local rain gauge and the radar estimates have been useful to understand the accuracy and utility of the Stage III data. Recently, the Stage III and CHARM rainfall measurements have been combined to produce an hourly rainfall dataset at each CHARM observation site. The procedure matches each CHARM site with a time sequence of Stage III radar estimates of precipitation. Hourly stage III rainfall estimates were used to partition the rain gauge values to the time interval over which they occurred. The new hourly rain gauge dataset is validated at selected points where 1-5 minute rainfall measurements have been made. This procedure greatly enhances the utility of the CHARM data for local weather and hydrologic modeling studies. The conference paper will present highlights of the Stage III intercomparison and some examples of the combined radar / rain gauge product demonstrating its accuracy and utility in deriving an hourly rainfall product from the 24 h CHARM totals.

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

NASA Technical Reports Server (NTRS)

White, Cary B.; Houser, Paul R.; Arain, Altaf M.; Yang, Zong-Liang; Syed, Kamran; Shuttleworth, W. James

1997-01-01

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

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

PubMed

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

2012-09-01

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

Conditional flood frequency and catchment state: a simulation approach

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Forecasting paediatric malaria admissions on the Kenya Coast using rainfall.

PubMed

Karuri, Stella Wanjugu; Snow, Robert W

2016-01-01

Malaria is a vector-borne disease which, despite recent scaled-up efforts to achieve control in Africa, continues to pose a major threat to child survival. The disease is caused by the protozoan parasite Plasmodium and requires mosquitoes and humans for transmission. Rainfall is a major factor in seasonal and secular patterns of malaria transmission along the East African coast. The goal of the study was to develop a model to reliably forecast incidences of paediatric malaria admissions to Kilifi District Hospital (KDH). In this article, we apply several statistical models to look at the temporal association between monthly paediatric malaria hospital admissions, rainfall, and Indian Ocean sea surface temperatures. Trend and seasonally adjusted, marginal and multivariate, time-series models for hospital admissions were applied to a unique data set to examine the role of climate, seasonality, and long-term anomalies in predicting malaria hospital admission rates and whether these might become more or less predictable with increasing vector control. The proportion of paediatric admissions to KDH that have malaria as a cause of admission can be forecast by a model which depends on the proportion of malaria admissions in the previous 2 months. This model is improved by incorporating either the previous month's Indian Ocean Dipole information or the previous 2 months' rainfall. Surveillance data can help build time-series prediction models which can be used to anticipate seasonal variations in clinical burdens of malaria in stable transmission areas and aid the timing of malaria vector control.

Dissipation dynamics of terbuthylazine in soil during the maize growing season.

PubMed

Stipičević, Sanja; Mendaš, Gordana; Dvoršćak, Marija; Fingler, Sanja; Galzina, Natalija; Barić, Klara

2017-12-20

Ever since terbuthylazine (TBA) replaced atrazine in herbicide crop treatment, its much greater persistence has raised considerable environmental concern. The aim of our field experiment was to establish the dissipation dynamics of TBA and its degradation product desethylterbuthylazine (DET) in soil over five months of maize growth. We applied TBA as part of pre-emergent treatment in the regular and double-the-regular amounts. Soil samples were collected periodically at the following depths: 0-10 cm, 10-20 cm, 20-30 cm, and 30-50 cm. For TBA and DET soil residue analysis we used microwave-assisted extraction with methanol, followed by HPLC-UV/DAD. Regardless of the application rate, more than 80 % of the applied TBA dissipated from the first 50 cm of soil in the two months after herbicide application and 120 mm of rainfall. Three months later (at maize harvest), less than 4 % of total TBA remained in the soil, mostly in the top 20 cm rich with organic carbon on which TBA is likelier to adsorb. The loss of TBA from soil coincided with the rise in DET, especially the top soil layers, during the periods of low rainfall and highest soil temperatures. This points to biodegradation as the main route of TBA dissipation in humic soils. The applied amount had no significant effect on TBA dissipation in the top (humic) layers, but in the layers with less than 1 % of organic carbon, it was higher when the doublethe- regular dose was applied.

Research on the semi-distributed monthly rainfall runoff model at the Lancang River basin based on DEM

NASA Astrophysics Data System (ADS)

Liu, Gang; Zhao, Rong; Liu, Jiping; Zhang, Qingpu

2007-06-01

The Lancang River Basin is so narrow and its hydrological and meteorological information are so flexible. The Rainfall, evaporation, glacial melt water and groundwater affect the runoff whose replenishment forms changing notable with the season in different areas at the basin. Characters of different kind of distributed model and conceptual hydrological model are analyzed. A semi-distributed hydrological model of relation between monthly runoff and rainfall, temperate and soil type has been built in Changdu County based on Visual Basic and ArcObject. The way of discretization of distributed hydrological model was used in the model, and principles of conceptual model are taken into account. The sub-catchment of Changdu is divided into regular cells, and all kinds of hydrological and meteorological information and land use classes and slope extracted from 1:250000 digital elevation models are distributed in each cell. The model does not think of the rainfall-runoff hydro-physical process but use the conceptual model to simulate the whole contributes to the runoff of the area. The affection of evapotranspiration loss and underground water is taken into account at the same time. The spatial distribute characteristics of the monthly runoff in the area are simulated and analyzed with a few parameters.

Convective and nonconvective rainfall partitioning over a mixed Sudanian Savanna Agriculture Catchment: Use of a distributed sensor network

NASA Astrophysics Data System (ADS)

Ceperley, N. C.; Mande, T.; Barrenetxea, G.; Repetti, A.; Yacouba, H.; Tyler, S. W.; Parlange, M. B.

2011-12-01

A hydro-meteorological field campaign (joint EPFL-2iE) in a mixed agricultural and forest region in the southern Burkina Faso Savanna aims to identify and understand convective rainfall processes and the link to soil moisture. A simple slab Mixed Layer and Lifting Condensation Level model is implemented to separate convective and nonconvective rainfall. Data for this research were acquired during the 2010 rainy season using an array of wireless weather stations (SensorScope) as well as surface energy balance stations that based upon eddy correlation heat flux measurements. The precipitation was found to be variable over the basin with some 200 mm of difference in total seasonal rainfall between agricultural fields and savanna forest. Convective rainfall represents more than 30% of the total rainfall. The convective rainfall events are short (less than hour), intense (greater than 3 mm/minute) and occur both in the early morning and in the afternoons. These events can have an important impact on soil erosion, which we discuss in more detail along with seasonal stream-aquifer interactions.

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

PubMed Central

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

2001-01-01

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

Tropical Rainfall Measurement Mission (TRMM) Operation Summary

NASA Technical Reports Server (NTRS)

Nio, Tomomi; Saito, Susumu; Stocker, Erich; Pawloski, James H.; Murayama, Yoshifumi; Ohata, Takeshi

2015-01-01

The Tropical Rainfall Measurement Mission (TRMM) is a joint U.S. and Japan mission to observe tropical rainfall, which was launched by H-II No. 6 from Tanegashima in Japan at 6:27 JST on November 28, 1997. After the two-month commissioning of TRMM satellite and instruments, the original nominal mission lifetime was three years. In fact, the operations has continued for approximately 17.5 years. This paper provides a summary of the long term operations of TRMM.

Projections of West African summer monsoon rainfall extremes from two CORDEX models

NASA Astrophysics Data System (ADS)

Akinsanola, A. A.; Zhou, Wen

2018-05-01

Global warming has a profound impact on the vulnerable environment of West Africa; hence, robust climate projection, especially of rainfall extremes, is quite important. Based on two representative concentration pathway (RCP) scenarios, projected changes in extreme summer rainfall events over West Africa were investigated using data from the Coordinated Regional Climate Downscaling Experiment models. Eight (8) extreme rainfall indices (CDD, CWD, r10mm, r20mm, PRCPTOT, R95pTOT, rx5day, and sdii) defined by the Expert Team on Climate Change Detection and Indices were used in the study. The performance of the regional climate model (RCM) simulations was validated by comparing with GPCP and TRMM observation data sets. Results show that the RCMs reasonably reproduced the observed pattern of extreme rainfall over the region and further added significant value to the driven GCMs over some grids. Compared to the baseline period 1976-2005, future changes (2070-2099) in summer rainfall extremes under the RCP4.5 and RCP8.5 scenarios show statistically significant decreasing total rainfall (PRCPTOT), while consecutive dry days and extreme rainfall events (R95pTOT) are projected to increase significantly. There are obvious indications that simple rainfall intensity (sdii) will increase in the future. This does not amount to an increase in total rainfall but suggests a likelihood of greater intensity of rainfall events. Overall, our results project that West Africa may suffer more natural disasters such as droughts and floods in the future.

Characterizing the interaction of groundwater and surface water in the karst aquifer of Fangshan, Beijing (China)

NASA Astrophysics Data System (ADS)

Chu, Haibo; Wei, Jiahua; Wang, Rong; Xin, Baodong

2017-03-01

Correct understanding of groundwater/surface-water (GW-SW) interaction in karst systems is of greatest importance for managing the water resources. A typical karst region, Fangshan in northern China, was selected as a case study. Groundwater levels and hydrochemistry analyses, together with isotope data based on hydrogeological field investigations, were used to assess the GW-SW interaction. Chemistry data reveal that water type and the concentration of cations in the groundwater are consistent with those of the surface water. Stable isotope ratios of all samples are close to the local meteoric water line, and the 3H concentrations of surface water and groundwater samples are close to that of rainfall, so isotopes also confirm that karst groundwater is recharged by rainfall. Cross-correlation analysis reveals that rainfall leads to a rise in groundwater level with a lag time of 2 months and groundwater exploitation leads to a fall within 1 month. Spectral analysis also reveals that groundwater level, groundwater exploitation and rainfall have significantly similar response periods, indicating their possible inter-relationship. Furthermore, a multiple nonlinear regression model indicates that groundwater level can be negatively correlated with groundwater exploitation, and positively correlated with rainfall. The overall results revealed that groundwater level has a close correlation with groundwater exploitation and rainfall, and they are indicative of a close hydraulic connection and interaction between surface water and groundwater in this karst system.

Use of microwave satellite data to study variations in rainfall over the Indian Ocean

NASA Technical Reports Server (NTRS)

Hinton, Barry B.; Martin, David W.; Auvine, Brian; Olson, William S.

1990-01-01

The University of Wisconsin Space Science and Engineering Center mapped rainfall over the Indian Ocean using a newly developed Scanning Multichannel Microwave Radiometer (SMMR) rain-retrieval algorithm. The short-range objective was to characterize the distribution and variability of Indian Ocean rainfall on seasonal and annual scales. In the long-range, the objective is to clarify differences between land and marine regimes of monsoon rain. Researchers developed a semi-empirical algorithm for retrieving Indian Ocean rainfall. Tools for this development have come from radiative transfer and cloud liquid water models. Where possible, ground truth information from available radars was used in development and testing. SMMR rainfalls were also compared with Indian Ocean gauge rainfalls. Final Indian Ocean maps were produced for months, seasons, and years and interpreted in terms of historical analysis over the sub-continent.

Prediction of Meiyu rainfall in Taiwan by multi-lead physical-empirical models

NASA Astrophysics Data System (ADS)

Yim, So-Young; Wang, Bin; Xing, Wen; Lu, Mong-Ming

2015-06-01

Taiwan is located at the dividing point of the tropical and subtropical monsoons over East Asia. Taiwan has double rainy seasons, the Meiyu in May-June and the Typhoon rains in August-September. To predict the amount of Meiyu rainfall is of profound importance to disaster preparedness and water resource management. The seasonal forecast of May-June Meiyu rainfall has been a challenge to current dynamical models and the factors controlling Taiwan Meiyu variability has eluded climate scientists for decades. Here we investigate the physical processes that are possibly important for leading to significant fluctuation of the Taiwan Meiyu rainfall. Based on this understanding, we develop a physical-empirical model to predict Taiwan Meiyu rainfall at a lead time of 0- (end of April), 1-, and 2-month, respectively. Three physically consequential and complementary predictors are used: (1) a contrasting sea surface temperature (SST) tendency in the Indo-Pacific warm pool, (2) the tripolar SST tendency in North Atlantic that is associated with North Atlantic Oscillation, and (3) a surface warming tendency in northeast Asia. These precursors foreshadow an enhanced Philippine Sea anticyclonic anomalies and the anomalous cyclone near the southeastern China in the ensuing summer, which together favor increasing Taiwan Meiyu rainfall. Note that the identified precursors at various lead-times represent essentially the same physical processes, suggesting the robustness of the predictors. The physical empirical model made by these predictors is capable of capturing the Taiwan rainfall variability with a significant cross-validated temporal correlation coefficient skill of 0.75, 0.64, and 0.61 for 1979-2012 at the 0-, 1-, and 2-month lead time, respectively. The physical-empirical model concept used here can be extended to summer monsoon rainfall prediction over the Southeast Asia and other regions.

Selection of meteorological parameters affecting rainfall estimation using neuro-fuzzy computing methodology

NASA Astrophysics Data System (ADS)

Hashim, Roslan; Roy, Chandrabhushan; Motamedi, Shervin; Shamshirband, Shahaboddin; Petković, Dalibor; Gocic, Milan; Lee, Siew Cheng

2016-05-01

Rainfall is a complex atmospheric process that varies over time and space. Researchers have used various empirical and numerical methods to enhance estimation of rainfall intensity. We developed a novel prediction model in this study, with the emphasis on accuracy to identify the most significant meteorological parameters having effect on rainfall. For this, we used five input parameters: wet day frequency (dwet), vapor pressure (e̅a), and maximum and minimum air temperatures (Tmax and Tmin) as well as cloud cover (cc). The data were obtained from the Indian Meteorological Department for the Patna city, Bihar, India. Further, a type of soft-computing method, known as the adaptive-neuro-fuzzy inference system (ANFIS), was applied to the available data. In this respect, the observation data from 1901 to 2000 were employed for testing, validating, and estimating monthly rainfall via the simulated model. In addition, the ANFIS process for variable selection was implemented to detect the predominant variables affecting the rainfall prediction. Finally, the performance of the model was compared to other soft-computing approaches, including the artificial neural network (ANN), support vector machine (SVM), extreme learning machine (ELM), and genetic programming (GP). The results revealed that ANN, ELM, ANFIS, SVM, and GP had R2 of 0.9531, 0.9572, 0.9764, 0.9525, and 0.9526, respectively. Therefore, we conclude that the ANFIS is the best method among all to predict monthly rainfall. Moreover, dwet was found to be the most influential parameter for rainfall prediction, and the best predictor of accuracy. This study also identified sets of two and three meteorological parameters that show the best predictions.

Simulation of precipitation by weather pattern and frontal analysis

NASA Astrophysics Data System (ADS)

Wilby, Robert

1995-12-01

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

TRMM Fire Algorithm, Product and Applications

NASA Technical Reports Server (NTRS)

Ji, Yi-Min; Stocker, Erich

2003-01-01

Land fires are frequent menaces to human lives and property. They also change the state of the vegetation and contribute to the climate forcing by releasing large amount of aerosols and greenhouse gases into the atmosphere. This paper summarizes methodologies of detecting global land fires from the Tropical Rainfall Measuring Mission (TRMM) Visible Infrared Scanner FIRS) measurements. The TRMM Science Data and Information System (TSDIS) fire products include global images of daily hot spots and monthly fire counts at 0.5 deg. x 0.5 deg. resolution, as well as text fiies that details necessary information of all fire pixels. The information includes date, orbit number, pixel number, local time, solar zenith angle, latitude, longitude, reflectance of visible/near infrared channels, brightness temperatures of infrared channels, as well as background brightness temperatures of infrared channels. These products have been archived since January 1998. The TSDIS fire products are compared with the coincidental European Commission (EC) Joint Research Center (JRC) 1 km AVHRR fire products. Analyses of the TSDIS monthly fire products during the period from 1998 to 2003 manifested seasonal cycles of biomass fires over Southeast Asia, Africa, North America and South America. The data also showed interannual variations associated with the 98/99 ENS0 cycle in Central America and the Indonesian region. In order to understand the variability of global land fires and their effects on the distribution of atmospheric aerosols, statistical methods were applied to the TSDIS fire products as well as to the Total Ozone Mapping Spectrometer (TOMS) aerosol index products for a period of five years from January 1998 to December 2002. The variability of global atmospheric aerosol is consistent with the fire variations over these regions during this period. The correlation between fire count and TOMS aerosol index is about 0.55 for fire pixels in Southeast Asia, Indonesia, and Africa. Parallel statistical analyses such as Empirical Orthogonal Function (EOF) analysis and Singular Spectrum Analysis (SSA) methods were applied to pentad TRMM fire data and TOMS aerosol data. The EOF analyses showed contrast between North and South hemispheres and also inter- continental transitions in Africa and America. EOF and SSA analyses also identified 25-60 day intra-seasonal oscillations that were superimposed on the annual cycles of both fire and aerosol data. The intra-seasonal variability of fires showed similarity of tropical rainfall oscillation modes. The TRMM fire products were also compared to the coincident TRMh4 rainfall and other rainfall products to investigate the interaction between rainfall and fire. The results indicate that the annual, interannual and intraseasonal variability of fire are dominated by global rainfall variations. However, the feedback of fire to the rainfall occurrence at regional scale for certain regions is also evident.

Meteorological influences on algal bloom potential in a nutrient-rich blackwater river

EPA Science Inventory

The effect of variability in rainfall on the potential for algal blooms was examined for the St. Johns River in northeast Florida. Water chemistry and phytoplankton data were collected at selected sites monthly from 1993 through 2003. Information on rainfall and estimates ofw at...

Effects of rainfall patterns and land cover on the subsurface flow generation of sloping Ferralsols in southern China

PubMed Central

Yang, Jie; Tang, Chongjun; Chen, Lihua; Liu, Yaojun; Wang, Lingyun

2017-01-01

Rainfall patterns and land cover are two important factors that affect the runoff generation process. To determine the surface and subsurface flows associated with different rainfall patterns on sloping Ferralsols under different land cover types, observational data related to surface and subsurface flows from 5 m × 15 m plots were collected from 2010 to 2012. The experiment was conducted to assess three land cover types (grass, litter cover and bare land) in the Jiangxi Provincial Soil and Water Conservation Ecological Park. During the study period, 114 natural rainfall events produced subsurface flow and were divided into four groups using k-means clustering according to rainfall duration, rainfall depth and maximum 30-min rainfall intensity. The results showed that the total runoff and surface flow values were highest for bare land under all four rainfall patterns and lowest for the covered plots. However, covered plots generated higher subsurface flow values than bare land. Moreover, the surface and subsurface flows associated with the three land cover types differed significantly under different rainfall patterns. Rainfall patterns with low intensities and long durations created more subsurface flow in the grass and litter cover types, whereas rainfall patterns with high intensities and short durations resulted in greater surface flow over bare land. Rainfall pattern I had the highest surface and subsurface flow values for the grass cover and litter cover types. The highest surface flow value and lowest subsurface flow value for bare land occurred under rainfall pattern IV. Rainfall pattern II generated the highest subsurface flow value for bare land. Therefore, grass or litter cover are able to convert more surface flow into subsurface flow under different rainfall patterns. The rainfall patterns studied had greater effects on subsurface flow than on total runoff and surface flow for covered surfaces, as well as a greater effect on surface flows associated with bare land. PMID:28792507

Application of spatial Poisson process models to air mass thunderstorm rainfall

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.

1987-01-01

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).

PubMed

Yan, Long; Wang, Hong; Zhang, Xuan; Li, Ming-Yue; He, Juan

2017-01-01

Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model. A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970-2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE). Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004-0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009-0.037) displayed the highest prediction accuracy. The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.

Monthly variations of diurnal rainfall in north coast of West Java Indonesia during boreal winter periods

NASA Astrophysics Data System (ADS)

Yulihastin, E.; Trismidianto

2018-05-01

Diurnal rainfall during the active monsoon period is usually associated with the highest convective activity that often triggers extreme rainfall. Investigating diurnal rainfall behavior in the north coast of West Java is important to recognize the behavioral trends of data leading to such extreme events in strategic West Java because the city of Jakarta is located in this region. Variability of diurnal rainfall during the period of active monsoon on December-January-February (DJF) composite during the 2000-2016 period was investigated using hourly rainfall data from Tropical Rainfall Measuring Mission (TRMM) 3B41RT dataset. Through the Empirical Mode Decomposition method was appears that the diurnal rain cycle during February has increased significantly in its amplitude and frequency. It is simultaneously shows that the indication of extreme rainfall events is related to diurnal rain divergences during February shown through phase shifts. The diurnal, semidiurnal, and terdiurnal cycles appear on the characteristics of the DJF composite rainfall data during the 2000-2016 period.The significant increases in amplitude occurred during February are the diurnal (IMF 3) and terdiurnal (IMF 1) of rainfall cycles.

Evolving Improvements to TRMM Ground Validation Rainfall Estimates

NASA Technical Reports Server (NTRS)

Robinson, M.; Kulie, M. S.; Marks, D. A.; Wolff, D. B.; Ferrier, B. S.; Amitai, E.; Silberstein, D. S.; Fisher, B. L.; Wang, J.; Einaudi, Franco (Technical Monitor)

2000-01-01

The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. Since the successful 1997 launch of the TRMM satellite, GV rainfall estimates have demonstrated systematic improvements directly related to improved radar and rain gauge data, modified science techniques, and software revisions. Improved rainfall estimates have resulted in higher quality GV rainfall products and subsequently, much improved evaluation products for the satellite-based precipitation estimates from TRMM. This presentation will demonstrate how TRMM GV rainfall products created in a semi-automated, operational environment have evolved and improved through successive generations. Monthly rainfall maps and rainfall accumulation statistics for each primary site will be presented for each stage of GV product development. Contributions from individual product modifications involving radar reflectivity (Ze)-rain rate (R) relationship refinements, improvements in rain gauge bulk-adjustment and data quality control processes, and improved radar and gauge data will be discussed. Finally, it will be demonstrated that as GV rainfall products have improved, rainfall estimation comparisons between GV and satellite have converged, lending confidence to the satellite-derived precipitation measurements from TRMM.

Geochemical Indicators of Nitrogen flow in a Check-Dam Catchment in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Wang, Y.; Chen, S.; Huang, Y.; Gao, Y.

2017-12-01

The increasingly fragile ecological environment and associative nitrogen (N) biogeochemical cycle have become critical environmental and ecological issues in China's Loess Plateau. However, N flow and N source for typical catchments remains poorly understood in the Loess Plateau. In this study, we measured concentrations and isotopic signatures of N, hydrogen (H), and oxygen (O) in both rainfall and river water. Results showed that baseflow variation in total nitrogen (TN) concentrations ranged from 0.16 to 32.70 mg·L-1. Monthly TN deposition and monthly N wet deposition concentrations to river water were from 0.05 to 2.91 kg·hm-2 and from 0.28 to 11.26 kg, respectively, with significant variations between rainy and dry seasons. The range of variation in δ2H values for rainfall and baseflow were from -90.0‰ to +19.8‰ and from -67.2‰ to -38.4‰, respectively, while δ18O-H2O values ranged from -12.1‰ to +2.7‰ and from -9.3‰ to -3.6‰, respectively. Furthermore, NO3- δ15N and δ18O values in baseflow ranged from -2.0‰ to +20.5‰ and from +8.0‰ to +15.6‰, respectively. The results indicated that rainfall was affected by below-cloud secondary evaporation and caused strong isotopic kinetic fractionation to occur during the falling process. The NO3-in runoff mainly derived from the nitrification of soil organic matter (SOM), for which the proportion of manure or sewage was from 50.5% to 83%.

The potential of urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam

NASA Astrophysics Data System (ADS)

de Vos, Lotte; Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

2017-02-01

The high density of built-up areas and resulting imperviousness of the land surface makes urban areas vulnerable to extreme rainfall, which can lead to considerable damage. In order to design and manage cities to be able to deal with the growing number of extreme rainfall events, rainfall data are required at higher temporal and spatial resolutions than those needed for rural catchments. However, the density of operational rainfall monitoring networks managed by local or national authorities is typically low in urban areas. A growing number of automatic personal weather stations (PWSs) link rainfall measurements to online platforms. Here, we examine the potential of such crowdsourced datasets for obtaining the desired resolution and quality of rainfall measurements for the capital of the Netherlands. Data from 63 stations in Amsterdam (˜ 575 km2) that measure rainfall over at least 4 months in a 17-month period are evaluated. In addition, a detailed assessment is made of three Netatmo stations, the largest contributor to this dataset, in an experimental setup. The sensor performance in the experimental setup and the density of the PWS network are promising. However, features in the online platforms, like rounding and thresholds, cause changes from the original time series, resulting in considerable errors in the datasets obtained. These errors are especially large during low-intensity rainfall, although they can be reduced by accumulating rainfall over longer intervals. Accumulation improves the correlation coefficient with gauge-adjusted radar data from 0.48 at 5 min intervals to 0.60 at hourly intervals. Spatial rainfall correlation functions derived from PWS data show much more small-scale variability than those based on gauge-adjusted radar data and those found in similar research using dedicated rain gauge networks. This can largely be attributed to the noise in the PWS data resulting from both the measurement setup and the processes occurring in the data transfer to the online PWS platform. A double mass comparison with gauge-adjusted radar data shows that the median of the stations resembles the rainfall reference better than the real-time (unadjusted) radar product. Averaging nearby raw PWS measurements further improves the match with gauge-adjusted radar data in that area. These results confirm that the growing number of internet-connected PWSs could successfully be used for urban rainfall monitoring.

Urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam

NASA Astrophysics Data System (ADS)

de Vos, Lotte; Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko

2017-04-01

The high density of built-up areas and resulting imperviousness of the land surface makes urban areas vulnerable to extreme rainfall, which can lead to considerable damage. In order to design and manage cities to be able to deal with the growing number of extreme rainfall events, rainfall data is required at higher temporal and spatial resolutions than those needed for rural catchments. However, the density of operational rainfall monitoring networks managed by local or national authorities is typically low in urban areas. A growing number of automatic personal weather stations (PWSs) link rainfall measurements to online platforms. Here, we examine the potential of such crowdsourced datasets for obtaining the desired resolution and quality of rainfall measurements for the capital of the Netherlands. Data from 63 stations in Amsterdam (˜575 km2}) that measure rainfall over at least 4 months in a 17-month period are evaluated. In addition, a detailed assessment is made of three Netatmo stations, the largest contributor to this dataset, in an experimental set-up. The sensor performance in the experimental set-up and the density of the PWS-network are promising. However, features in the online platforms, like rounding and thresholds, cause changes from the original time series, resulting in considerable errors in the datasets obtained. These errors are especially large during low intensity rainfall, although they can be reduced by accumulating rainfall over longer intervals. Accumulation improves the correlation coefficient with gauge-adjusted radar data from 0.48 at 5 min intervals to 0.60 at hourly intervals. Spatial rainfall correlation functions derived from PWS data show much more small-scale variability than those based on gauge-adjusted radar data and those found in similar research using dedicated rain gauge networks. This can largely be attributed to the noise in the PWS data resulting from both the measurement setup and the processes occurring in the data transfer to the online PWS-platform. A double mass comparison with gauge-adjusted radar data shows that the median of the stations resembles the rainfall reference better than the real-time (unadjusted) radar product. Averaging nearby raw PWS measurements further improves the match with gauge-adjusted radar data in that area. These results confirm that the growing number of internet-connected PWSs could successfully be used for urban rainfall monitoring.

Climate impact on malaria in northern Burkina Faso.

PubMed

Tourre, Yves M; Vignolles, Cécile; Viel, Christian; Mounier, Flore

2017-11-27

The Paluclim project managed by the French Centre National d'Etudes Spatiales (CNES) found that total rainfall for a 3-month period is a confounding factor for the density of malaria vectors in the region of Nouna in the Sahel administrative territory of northern Burkina Faso. Following the models introduced in 1999 by Craig et al. and in 2003 by Tanser et al., a climate impact model for malaria risk (using different climate indices) was created. Several predictions of this risk at different temporal scales (i.e. seasonal, inter-annual and low-frequency) were assessed using this climate model. The main result of this investigation was the discovery of a significant link between malaria risk and low-frequency rainfall variability related to the Atlantic Multi-decadal Oscillation (AMO). This result is critical for the health information systems in this region. Knowledge of the AMO phases would help local authorities to organise preparedness and prevention of malaria, which is of particular importance in the climate change context.

Acid rain monitoring in East-Central Florida from 1977 to present

NASA Technical Reports Server (NTRS)

Madsen, B. C.; Kheoh, T.; Hinkle, C. R.; Dreschel, T. W.

1990-01-01

Rainfall has been collected on the University of Central Florida campus and at the Kennedy Space Center over a 12 year period. The chemical composition has been determined and summarized by monthly, annual periods, and for the entire 12 year period at both locations. The weighted average pH at each site is 4.58; however, annual weighted average pH has been equal to or above the 12 year average during six of the past eight years. Nitrate concentrations have increased slightly during recent years while excess sulfate concentrations have remained below the 12 year weighted average during six of the past seven years. Stepwise regression suggests that sulfate, nitrate, ammonium ion and calcium play major roles in the description of rainwater acidity. Annual acid deposition and annual rainfall have varied from 20 to 50 meg/(m(exp 2) year) and 100 to 180 cm/year, respectively. Sea salt comprises at least 25 percent of the total ionic composition.

The Amazon forest-rainfall feedback: the roles of transpiration and interception

NASA Astrophysics Data System (ADS)

Dekker, Stefan; Staal, Arie; Tuinenburg, Obbe

2017-04-01

In the Amazon, deep-rooted trees increase local transpiration and high tree cover increase local interception evaporation. These increased local evapotranspiration fluxes to the atmosphere have both positive effects on forests down-wind, as they stimulate rainfall. Although important for the functioning of the Amazon, we have an inadequate assessment on the strength and the timing of these forest-rainfall feedbacks. In this study we (i) estimate local forest transpiration and local interception evaporation, (ii) simulate the trajectories of these moisture flows through the atmosphere and (iii) quantify their contributions to the forest-rainfall feedback for the whole Amazon basin. To determine the atmospheric moisture flows in tropical South America we use a Lagrangian moisture tracking algorithm on 0.25° (c. 25 km) resolution with eight atmospheric layers on a monthly basis for the period 2003-2015. With our approach we account for multiple re-evaporation cycles of this moisture. We also calculate for each month the potential effects of forest loss on evapotranspiration. Combined, these calculations allow us to simulate the effects of land-cover changes on rainfall in downwind areas and estimate the effect on the forest. We found large regional and temporal differences in the importance how forest contribute to rainfall. The transpiration-rainfall feedback is highly important during the dry season. Between September-November, when large parts of the Amazon are at the end of the dry season, more than 50% of the rainfall is caused by the forests upstream. This means that droughts in the Amazon are alleviated by the forest. Furthermore, we found that much moisture cycles several times during its trajectory over the Amazon. After one evapotranspiration-rainfall cycle, more than 40% of the moisture is re-evaporated again. The interception-evaporation feedback is less important during droughts. Finally from our analysis, we show that the forest-rainfall feedback is essential for the resilience of the south-western and northern parts of the Amazon forest. Without the forest-rainfall feedbacks, these forest wouldn't exist.

Tree Carbohydrate Dynamics Across a Rainfall Gradient in Panama During the 2016 ENSO

NASA Astrophysics Data System (ADS)

Dickman, L. T.; Xu, C.; Behar, H.; McDowell, N.

2017-12-01

Non-structural carbohydrates (NSC) provide a measure of the carbon supply available to support respiration, growth, and defense. Support for a role of carbon starvation - or depletion of NSC stores - in drought induced tree mortality is varied without consensus for the tropics. The 2016 ENSO drought provided a unique opportunity to capture drought impacts on tropical forest carbohydrate dynamics. To quantify these impacts, we collected monthly NSC samples across a rainfall gradient in Panama for the duration of the ENSO. We observed high variability in foliar NSC among species within sites. Foliage contained very little starch, indicating that total NSC dynamics are driven by soluble sugars. Foliar NSC depletion did not progress with drought duration as predicted, but showed little variation over course of the ENSO. Foliar NSC did, however, increase with rainfall, suggesting NSC depletion may occur with longer-term drought. These results suggest that, while short-term droughts like the 2016 ENSO may not have a significant impact on carbon dynamics, we may observe greater impacts as drought progresses over longer timescales. These results will be used to evaluate whether the current implementation of carbon starvation in climate models are capturing observed trends in tropical forest carbon allocation and mortality, and to tune model parameters for improved predictive capability.

Have Tropical Cyclones Been Feeding More Extreme Rainfall?

NASA Technical Reports Server (NTRS)

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

2008-01-01

We have conducted a study of the relationship between tropical cyclone (TC) and extreme rain events using GPCP and TRMM rainfall data, and storm track data for July through November (JASON) in the North Atlantic (NAT) and the western North Pacific (WNP). Extreme rain events are defined in terms of percentile rainrate, and TC-rain by rainfall associated with a named TC. Results show that climatologically, 8% of rain events and 17% of the total rain amount in NAT are accounted by TCs, compared to 9% of rain events and 21% of rain amount in WNP. The fractional contribution of accumulated TC-rain to total rain, Omega, increases nearly linearly as a function of rainrate. Extending the analyses using GPCP pentad data for 1979-2005, and for the post-SSM/I period (1988-2005), we find that while there is no significant trend in the total JASON rainfall over NAT or WNP, there is a positive significant trend in heavy rain over both basins for the 1979-2005 period, but not for the post-SSM/I period. Trend analyses of Omega for both periods indicate that TCs have been feeding increasingly more to rainfall extremes in NAT, where the expansion of the warm pool area can explain slight more than 50% of the change in observed trend in total TC rainfall. In WNP, trend signals for Omega are mixed, and the long-term relationship between TC rain and warm pool areas are strongly influenced by interannual and interdecadal variability.

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.

The Effects of Rainfall Inhomogeneity on Climate Variability of Rainfall Estimated from Passive Microwave Sensors

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Poyner, Philip; Berg, Wesley; Thomas-Stahle, Jody

2007-01-01

Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (T(sub b)) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km X 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global mean monthly errors introduced by not explicitly accounting for rainfall inhomogeneity do not exceed 0.5% if the beam-filling error is allowed to be a function of rainfall rate and freezing level and does not exceed 2% if a universal beam-filling correction is applied that depends only upon the freezing level. Monthly regional errors can be significantly larger. Over the Indian Ocean, errors as large as 8% were found if the beam-filling correction is allowed to vary with rainfall rate and freezing level while errors of 15% were found if a universal correction is used.

Characterization of rainfall-runoff response and estimation of the effect of wetland restoration on runoff, Heron Lake Basin, southwestern Minnesota, 1991-97

USGS Publications Warehouse

Jones, Perry M.; Winterstein, Thomas A.

2000-01-01

The U.S. Geological Survey (USGS), in cooperation with the Minnesota Department of Natural Resources and the Heron Lake Watershed District, conducted a study to characterize the rainfall-runoff response and to examine the effects of wetland restoration on the rainfall-runoff response within the Heron Lake Basin in southwestern Minnesota. About 93 percent of the land cover in the Heron Lake Basin consists of agricultural lands, consisting almost entirely of row crops, with less than one percent consisting of wetlands. The Hydrological Simulation Program – Fortran (HSPF), Version 10, was calibrated to continuous discharge data and used to characterize rainfall-runoff responses in the Heron Lake Basin between May 1991 and August 1997. Simulation of the Heron Lake Basin was done as a two-step process: (1) simulations of five small subbasins using data from August 1995 through August 1997, and (2) simulations of the two large basins, Jack and Okabena Creek Basins, using data from May 1991 through September 1996. Simulations of the five small subbasins was done to determine basin parameters for the land segments and assess rainfall-runoff response variability in the basin. Simulations of the two larger basins were done to verify the basin parameters and assess rainfall-runoff responses over a larger area and for a longer time period. Best-fit calibrations of the five subbasin simulations indicate that the rainfall-runoff response is uniform throughout the Heron Lake Basin, and 48 percent of the total rainfall for storms becomes direct (surface and interflow) runoff. Rainfall-runoff response variations result from variations in the distribution, intensity, timing, and duration of rainfall; soil moisture; evapotranspiration rates; and the presence of lakes in the basin. In the spring, the amount and distribution of rainfall tends to govern the runoff response. High evapotranspiration rates in the summer result in a depletion of moisture from the soils, substantially affecting the rainfall-runoff relation. Five wetland restoration simulations were run for each of five subbasins using data from August 1995 through August 1997, and for the two larger basins, Jack and Okabena Creek Basins, using data from May 1991 through September 1996. Results from linear regression analysis of total simulated direct runoff and total rainfall data for simulated storms in the wetland-restoration simulations indicate that the portion of total rainfall that becomes runoff will be reduced by 46 percent if 45 percent of current cropland is converted to wetland. The addition of wetlands reduced peak runoff in most of the simulations, but the reduction varied with antecedent soil moisture, the magnitude of the peak flow, and the presence of current wetlands and lakes. Reductions in the simulated total and peak runoff from the Jack Creek Basin for most of the simulated storms were greatest when additional wetlands were simulated in the North Branch Jack Creek or the Upper Jack Creek Subbasins. In the Okabena Creek Basin, reductions in simulated peak runoff for most of the storms were greatest when additional wetlands were simulated in the Lower Okabena Creek Subbasin.

Detection of the diurnal cycle in rainfall from the TRMM satellite

NASA Technical Reports Server (NTRS)

Bell, Thomas L.

1989-01-01

Consideration is given to the process of detecting the diurnal cycle from data that will be collected by the Tropical Rainfall Measuring Mission satellite. The analysis of data for the diurnal cycle is discussed, accounting for the fact that satellite visits will be irregularly spaced in time. The accuracy with which the first few harmonics of the diurnal cycle can be detected from several months of satellite data is estimated using rainfall statistics observed during the GARP Atlantic Tropical Experiment.

Analysis of the influence of rainfall variables on urban effluents concentrations and fluxes in wet weather

NASA Astrophysics Data System (ADS)

Gooré Bi, Eustache; Monette, Frédéric; Gasperi, Johnny

2015-04-01

Urban rainfall runoff has been a topic of increasing importance over the past years, a result of both the increase in impervious land area arising from constant urban growth and the effects of climate change on urban drainage. The main goal of the present study is to assess and analyze the correlations between rainfall variables and common indicators of urban water quality, namely event mean concentrations (EMCs) and event fluxes (EFs), in order to identify and explain the impacts of each of the main rainfall variables on the generation process of urban pollutants during wet periods. To perform this analysis, runoff from eight summer rainfall events that resulted in combined sewer overflow (CSO) was sampled simultaneously from two distinct catchment areas in order to quantify discharges at the respective outfalls. Pearson statistical analysis of total suspended solids (TSS), chemical oxygen demand (COD), carbonaceous biochemical oxygen demand at 5 days (CBOD5), total phosphorus (Ptot) and total kedjal nitrogen (N-TKN) showed significant correlations (ρ = 0.05) between dry antecedent time (DAT) and EMCs on one hand, and between total rainfall (TR) and the volume discharged (VD) during EFs, on the other. These results show that individual rainfall variables strongly affect either EMCs or EFs and are good predictors to consider when selecting variables for statistical modeling of urban runoff quality. The results also show that in a combined sewer network, there is a linear relationship between TSS event fluxes and COD, CBOD5, Ptot, and N-TKN event fluxes; this explains 97% of the variability of these pollutants which adsorb onto TSS during wet weather, which therefore act as tracers. Consequently, the technological solution selected for TSS removal will also lead to a reduction of these pollutants. Given the huge volumes involved, urban runoffs contribute substantially to pollutant levels in receiving water bodies, a situation which, in a climate change context, may get much worse as a result of more frequent, shorter, but more intense rainfall events.

Historical Contingencies in Microbial Responses to Drought

NASA Astrophysics Data System (ADS)

Hawkes, C.; Waring, B.; Rocca, J.; Kivlin, S.; Giauque, H.; Averill, C.

2014-12-01

Although water is a primary controller of microbial function and we expect climate change to alter water availability in the future, our understanding of how microbial communities respond to a change in moisture and what that means for soil carbon cycling remain poorly understood. In part, this uncertainty arises from a lack of understanding of microbial response mechanisms and how those lead to aggregate soil function. Environmental tracking would be facilitated if microbial communities respond to new climatic conditions via rapid physiological acclimatization, shifts in community composition, or adaptation. In contrast, historical contingencies could be created by dispersal limitation or local adaptation to previous conditions. To address environmental tracking vs. legacies, we examined how soil microbial communities were affected by precipitation at multiple scales and asked whether rainfall was a primary driver of the observed responses. We leveraged a local steep rainfall gradient with field surveys, lab incubations, reciprocal transplants, and rainfall manipulations to approach this problem. Across a steep rainfall gradient, we found that soil microbial communities were strongly associated with historical rainfall, with two-thirds of the variation in community composition explained by mean annual precipitation. In 12-month experimental lab manipulations of soil moisture, soil functional responses were constrained by historical rainfall, with greater activity in soils subjected to their original moisture condition. The constraints of historical rainfall held even after 18 months in reciprocal transplant common gardens along the rainfall gradient and with manipulated dispersal of regional microbial communities. Yet, when water was manipulated at a single site over 4 years, legacies did not develop. Overall, these findings are consistent with long-term rainfall acting as a strong habitat filter and resulting in a legacy of both microbial community composition and physiological capacity that can affect soil carbon cycling. Placing the ecological and evolutionary dynamics of microbial communities in the context of historical and future environmental variation may thus provide us with a framework for improving prediction of ecosystem responses to climate change.

The Southern Oscillation and Prediction of `Der' Season Rainfall in Somalia.

NASA Astrophysics Data System (ADS)

Hutchinson, P.

1992-05-01

Somalia survives in semiarid to arid conditions, with annual rainfall totals rarely exceeding 700 mm, which are divided between two seasons. Many areas are arid, with negligible precipitation. Seasonal totals are highly variable. Thus, any seasonal rainfall forecast would be of significant importance to both the agricultural and animal husbandry communities. An investigation was carried out to determine whether there is a relationship between the Southern Oscillation and seasonal rainfall. No relationship exists between the Southern Oscillation and rainfall during the midyear `Gu' season, but it is shown that the year-end `Der' season precipitation is attected by the Southern Oscillation in southern and central areas of Somalia. Three techniques were used: correlation, regression, and simple contingency tables. Correlations between the SOI (Southern Oscillation index) and seasonal rainfall vary from zero up to about 0.8, with higher correlations in the south, both for individual stations and for area-averaged rainfall. Regression provides some predictive capacity, but the `explanation' of the variation in rainfall is not particularly high. The contingency tables revealed that there were very few occasions of both high SOI and high seasonal rainfall, although there was a wide scatter of seasonal rainfall associated with a low SOI.It is concluded that the SOI would be useful for planners, governments, and agencies as one tool in food/famine early warning but that the relationships are not strong enough for the average farmer to place much reliance on forecasts produced solely using the SOI.

[Monitoring and analysis on evolution process of rainfall runoff water quality in urban area].

PubMed

Dong, Wen; Li, Huai-En; Li, Jia-Ke

2013-02-01

In order to find the water quality evolution law and pollution characteristics of the rainfall runoff from undisturbed to the neighborhood exit, 6 times evolution process of rainfall runoff water quality were monitored and analyzed from July to October in 2011, and contrasted the clarification efficiency of the grassland to the roof runoff rudimentarily at the same time. The research showed: 1. the results of the comparison from "undisturbed, rainfall-roof, rainfall runoff-road, rainfall-runoff the neighborhood exit runoff " showed that the water quality of the undisturbed rain was better than that from the roof and the neighborhood exist, but the road rainfall runoff water quality was the worst; 2. the average concentrations of the parameters such as COD, ammonia nitrogen and total nitrogen all exceeded the Fifth Class of the Surface Water Quality Standard except for the soluble total phosphorus from undisturbed rainfall to the neighborhood exit; 3. the runoff water quality of the short early fine days was better than that of long early fine days, and the last runoff water quality was better than that of the initial runoff in the same rainfall process; 4. the concentration reduction of the grassland was notable, and the reduction rate of the grassland which is 1.0 meter wide of the roof runoff pollutants such as COD and nitrogen reached 30%.

Geographic Information System and Remote Sensing Approach with Hydrologic Rational Model for Flood Event Analysis in Jakarta

NASA Astrophysics Data System (ADS)

Aditya, M. R.; Hernina, R.; Rokhmatuloh

2017-12-01

Rapid development in Jakarta which generates more impervious surface has reduced the amount of rainfall infiltration into soil layer and increases run-off. In some events, continuous high rainfall intensity could create sudden flood in Jakarta City. This article used rainfall data of Jakarta during 10 February 2015 to compute rainfall intensity and then interpolate it with ordinary kriging technique. Spatial distribution of rainfall intensity then overlaid with run-off coefficient based on certain land use type of the study area. Peak run-off within each cell resulted from hydrologic rational model then summed for the whole study area to generate total peak run-off. For this study area, land use types consisted of 51.9 % industrial, 37.57% parks, and 10.54% residential with estimated total peak run-off 6.04 m3/sec, 0.39 m3/sec, and 0.31 m3/sec, respectively.

Effective application of optical sensing technology for sustainable liquid level sensing and rainfall measurement

NASA Astrophysics Data System (ADS)

Afzal, Muhammad Hassan Bin

2015-05-01

Rainfall measurement is performed on regular basis to facilitate effectively the weather stations and local inhabitants. Different types of rain gauges are available with different measuring principle for rainfall measurement. In this research work, a novel optical rain sensor is designed, which precisely calculate the rainfall level according to rainfall intensity. This proposed optical rain sensor model introduced in this paper, which is basically designed for remote sensing of rainfall and it designated as R-ORMS (Remote Optical Rainfall Measurement sensor). This sensor is combination of some improved method of tipping bucket rain gauge and most of the optical hydreon rain sensor's principle. This optical sensor can detect the starting time and ending time of rain, rain intensity and rainfall level. An infrared beam from Light Emitting Diode (LED) through powerful convex lens can accurately determines the diameter of each rain drops by total internal reflection principle. Calculations of these accumulative results determine the rain intensity and rainfall level. Accurate rainfall level is determined by internal optical LED based sensor which is embedded in bucket wall. This internal sensor is also following the total internal reflection (TIR) principle and the Fresnel's law. This is an entirely novel design of optical sensing principle based rain sensor and also suitable for remote sensing rainfall level. The performance of this proposed sensor has been comprehensively compared with other sensors with similar attributes and it showed better and sustainable result. Future related works have been proposed at the end of this paper, to provide improved and enhanced performance of proposed novel rain sensor.

The relationship of lightning activity and short-duration rainfall events during warm seasons over the Beijing metropolitan region

NASA Astrophysics Data System (ADS)

Wu, Fan; Cui, Xiaopeng; Zhang, Da-Lin; Qiao, Lin

2017-10-01

The relationship between lightning activity and rainfall associated with 2925 short-duration rainfall (SDR) events over the Beijing metropolitan region (BMR) is examined during the warm seasons of 2006-2007, using the cloud-to-ground (CG) and intracloud (IC) lightning data from Surveillance et Alerte Foudre par Interférometrie Radioélectrique (SAFIR)-3000 and 5-min rainfall data from automatic weather stations (AWSs). An optimal radius of 10 km around selected AWSs is used to determine the lightning-rainfall relationship. The lightning-rainfall correlations vary significantly, depending upon the intensity of SDR events. That is, correlation coefficient (R 0.7) for the short-duration heavy rainfall (SDHR, i.e., ≥ 20 mm h- 1) events is found higher than that (R 0.4) for the weak SDR (i.e., 5-10 mm h- 1) events, and lower percentage of the SDHR events (< 10%) than the weak SDR events (40-50%) are observed with few flashes. Significant time-lagged correlations between lightning and rainfall are also found. About 80% of the SDR events could reach their highest correlation coefficients when the associated lightning flashes shift at time lags of < 25 min before and after rainfall begins. Those events with lightning preceding rainfall account for 50-60% of the total SDR events. Better lightning-rainfall correlations can be attained when time lags are incorporated, with the use of total (CG and IC) lightning data. These results appear to have important implications for improving the nowcast of SDHR events.

Characterization and first flush analysis in road and roof runoff in Shenyang, China.

PubMed

Li, Chunlin; Liu, Miao; Hu, Yuanman; Gong, Jiping; Sun, Fengyun; Xu, Yanyan

2014-01-01

As urbanization increases, urban runoff is an increasingly important component of total urban non-point source pollution. In this study, the properties of urban runoff were examined in Shenyang, in northeastern China. Runoff samples from a tiled roof, a concrete roof and a main road were analyzed for key pollutants (total suspended solids (TSS), total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (COD), Pb, Cd, Cr, Cu, Ni, and Zn). The event mean concentration, site mean concentration, M(V) curves (dimensionless cumulative curve of pollutant load with runoff volume), and mass first flush ratio (MFF30) were used to analyze the characteristics of pollutant discharge and first flush (FF) effect. For all events, the pollutant concentration peaks occurred in the first half-hour after the runoff appeared and preceded the flow peaks. TN is the main pollutant in roof runoff. TSS, TN, TP, Pb, and Cr are the main pollutants in road runoff in Shenyang. There was a significant correlation between TSS and other pollutants except TN in runoff, which illustrated that TSS was an important carrier of organic matter and heavy metals. TN had strong positive correlations with total rainfall (Pearson's r = 0.927), average rainfall (Pearson's r = 0.995), and maximum rainfall intensity (Pearson's r = 0.991). TP had a strong correlation with rainfall intensity (Pearson's r = 0.940). A significant positive correlation between COD and rainfall duration (Pearson's r = 0.902, significance level = 0.05) was found. The order of FF intensity in different surfaces was concrete roof > tile roof > road. Rainfall duration and the length of the antecedent dry period were positively correlated with the FF. TN tended to exhibit strong flush for some events. Heavy metals showed a substantially stronger FF than other pollutant.

Mixing the Green-Ampt model and Curve Number method as an empirical tool for rainfall excess estimation in small ungauged catchments.

NASA Astrophysics Data System (ADS)

Grimaldi, S.; Petroselli, A.; Romano, N.

2012-04-01

The Soil Conservation Service - Curve Number (SCS-CN) method is a popular rainfall-runoff model that is widely used to estimate direct runoff from small and ungauged basins. The SCS-CN is a simple and valuable approach to estimate the total stream-flow volume generated by a storm rainfall, but it was developed to be used with daily rainfall data. To overcome this drawback, we propose to include the Green-Ampt (GA) infiltration model into a mixed procedure, which is referred to as CN4GA (Curve Number for Green-Ampt), aiming to distribute in time the information provided by the SCS-CN method so as to provide estimation of sub-daily incremental rainfall excess. For a given storm, the computed SCS-CN total net rainfall amount is used to calibrate the soil hydraulic conductivity parameter of the Green-Ampt model. The proposed procedure was evaluated by analyzing 100 rainfall-runoff events observed in four small catchments of varying size. CN4GA appears an encouraging tool for predicting the net rainfall peak and duration values and has shown, at least for the test cases considered in this study, a better agreement with observed hydrographs than that of the classic SCS-CN method.

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

NASA Astrophysics Data System (ADS)

Aronica, G. T.; Candela, A.

2007-12-01

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

A simple lightning assimilation technique for improving ...

EPA Pesticide Factsheets

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly averaged bias of 6 h accumulated rainfall is reduced from 0.54 to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF applications. The

A Simple Lightning Assimilation Technique For Improving ...

EPA Pesticide Factsheets

Convective rainfall is often a large source of error in retrospective modeling applications. In particular, positive rainfall biases commonly exist during summer months due to overactive convective parameterizations. In this study, lightning assimilation was applied in the Kain-Fritsch (KF) convective scheme to improve retrospective simulations using the Weather Research and Forecasting (WRF) model. The assimilation method has a straightforward approach: Force KF deep convection where lightning is observed and, optionally, suppress deep convection where lightning is absent. WRF simulations were made with and without lightning assimilation over the continental United States for July 2012, July 2013, and January 2013. The simulations were evaluated against NCEP stage-IV precipitation data and MADIS near-surface meteorological observations. In general, the use of lightning assimilation considerably improves the simulation of summertime rainfall. For example, the July 2012 monthly-averaged bias of 6-h accumulated rainfall is reduced from 0.54 mm to 0.07 mm and the spatial correlation is increased from 0.21 to 0.43 when lightning assimilation is used. Statistical measures of near-surface meteorological variables also are improved. Consistent improvements also are seen for the July 2013 case. These results suggest that this lightning assimilation technique has the potential to substantially improve simulation of warm-season rainfall in retrospective WRF appli

Rainfall-Runoff and Water-Balance Models for Management of the Fena Valley Reservoir, Guam

USGS Publications Warehouse

Yeung, Chiu W.

2005-01-01

The U.S. Geological Survey's Precipitation-Runoff Modeling System (PRMS) and a generalized water-balance model were calibrated and verified for use in estimating future availability of water in the Fena Valley Reservoir in response to various combinations of water withdrawal rates and rainfall conditions. Application of PRMS provides a physically based method for estimating runoff from the Fena Valley Watershed during the annual dry season, which extends from January through May. Runoff estimates from the PRMS are used as input to the water-balance model to estimate change in water levels and storage in the reservoir. A previously published model was calibrated for the Maulap and Imong River watersheds using rainfall data collected outside of the watershed. That model was applied to the Almagosa River watershed by transferring calibrated parameters and coefficients because information on daily diversions at the Almagosa Springs upstream of the gaging station was not available at the time. Runoff from the ungaged land area was not modeled. For this study, the availability of Almagosa Springs diversion data allowed the calibration of PRMS for the Almagosa River watershed. Rainfall data collected at the Almagosa rain gage since 1992 also provided better estimates of rainfall distribution in the watershed. In addition, the discontinuation of pan-evaporation data collection in 1998 required a change in the evapotranspiration estimation method used in the PRMS model. These reasons prompted the update of the PRMS for the Fena Valley Watershed. Simulated runoff volume from the PRMS compared reasonably with measured values for gaging stations on Maulap, Almagosa, and Imong Rivers, tributaries to the Fena Valley Reservoir. On the basis of monthly runoff simulation for the dry seasons included in the entire simulation period (1992-2001), the total volume of runoff can be predicted within -3.66 percent at Maulap River, within 5.37 percent at Almagosa River, and within 10.74 percent at Imong River. Month-end reservoir volumes simulated by the reservoir water-balance model for both calibration and verification periods compared closely with measured reservoir volumes. Errors for the calibration periods ranged from 4.51 percent [208.7 acre-feet (acre-ft) or 68.0 million gallons (Mgal)] to -5.90 percent (-317.8 acre-ft or -103.6 Mgal). For the verification periods, errors ranged from 1.69 percent (103.5 acre-ft or 33.7 Mgal) to -4.60 percent (-178.7 acre-ft or -58.2 Mgal). Monthly simulation bias ranged from -0.19 percent for the calibration period to -0.98 percent for the verification period; relative error ranged from -0.37 to -1.12 percent, respectively. Relatively small bias indicated that the model did not consistently overestimate or underestimate reservoir volume.

Validation of the TRMM Multi Satellite Rainfall Product 3B42 and estimation of scavenging coefficients for (131)I and (137)Cs using TRMM 3B42 rainfall data.

PubMed

Shrivastava, R; Dash, S K; Hegde, M N; Pradeepkumar, K S; Sharma, D N

2014-12-01

The TRMM rainfall product 3B42 is compared with rain gauge observations for Kaiga, India on monthly and seasonal time scales. This comparison is carried out for the years 2004-2007 spanning four monsoon seasons. A good correlation is obtained between the two data sets however; magnitude wise, the cumulative precipitation of the satellite product on monthly and seasonal time scales is deficient by almost 33-40% as compared to the rain gauge data. The satellite product is also compared with APHRODITE's Monsoon Asia data set on the same time scales. This comparison indicates a much better agreement since both these data sets represent an average precipitation over the same area. The scavenging coefficients for (131)I and (137)Cs are estimated using TRMM 3B42, rain gauge and APHRODITE data. The values obtained using TRMM 3B42 rainfall data compare very well with those obtained using rain gauge and APHRODITE data. Copyright © 2014 Elsevier Ltd. All rights reserved.

Status of ground-water resources at U.S. Navy Support Facility, Diego Garcia; summary of hydrologic and climatic data, January 1993 through June 1995

USGS Publications Warehouse

Torikai, J.D.

1995-01-01

This report contains hydrologic and climatic data that describe the status of ground-water resources at U.S. Navy Support Facility, Diego Garcia. Data presented are from January 1993 through June 1995, although the report focuses on hydrologic events from April through June 1995. Cumulative rainfall for April through June 1995 was about 14 inches which is 70 percent of the mean cumulative rainfall of about 20 inches for the same 3 months in a year. April through June is within the annual dry season. Rainfall for each month was below average from the respective mean monthly rainfall. All mean rainfall values are calculated for the fixed base period 1951-90. Ground-water withdrawal during April through June 1995 averaged 833,700 gallons per day. Withdrawal for the same 3 months in 1994 averaged 950,000 gallons per day. At the end of June 1995, the chloride concentration of the composite water supply was 57 milligrams per liter, well below the 250 milligrams per liter secondary drinking-water standard established by the U.S. Environmental Protection Agency. Chloride concentrations of the composite water supply from April through June 1995 ranged between 26 and 62 milligrams per liter. Chloride concentration of ground water in monitoring wells at Cantonment and Air Operations increased since April 1995, with water from the deepest monitoring wells increasing in chloride concentra- tion by about 1000 milligrams per liter. A fuel leak at Air Operations caused the shutdown of ten wells in May 1991. Four of the wells resumed pumping for water-supply purposes in April 1992. The remaining six wells are being used to hydraulically contain and divert fuel migration away from water-supply wells by recirculating about 150,000 gallons of water each day.

Seasonal abundance of soil arthropods in relation to meteorological and edaphic factors in the agroecosystems of Faisalabad, Punjab, Pakistan

NASA Astrophysics Data System (ADS)

Shakir, Muhammad Mussadiq; Ahmed, Sohail

2015-05-01

Soil arthropods are an important component of agroecosystems, contributing significantly to their biodiversity and functioning. However, seasonal patterns, population dynamics, and significant roles of these soil arthropods in improvement of soil structures and functions are influenced by many factors. The objective of the current study was to investigate soil arthropod abundance in relation to a blend of meteorological and edaphic factors and to find out the difference in abundance among various crops (sugarcane, cotton, wheat, alfalfa fodder, and citrus orchards). The arthropod sampling was done by pitfall traps and Tullgren extractions on fortnightly intervals. Soil temperature and relative humidity were noted on the field sites while analysis for soil pH, organic matter, and soil moisture contents were done in the laboratory. The rainfall data was obtained from an observatory. Results showed that significant differences were found in soil arthropod abundance across different sampling months and crops. Out of total 13,673 soil arthropods sampled, 38 % belonged to Collembola, followed by 15 % Hymenoptera, 15 % Acarina, 11 % Myriapods, 6 % Coleoptera, 5 % Orthoptera, and 5 % Araneae. Mean abundance per sample was highest in summer months as compared to winter. Overall abundance per sample was significantly different between all crops ( p < 0.05). Cluster analysis revealed four categories of soil arthropods according to abundance, i.e., highly abundant (Collembola, Acarina, Myripoda, Hymenoptera), moderately abundant (Orthoptera, Aranae, Coleoptera), least abundant (Dermaptera, Hemiptera, Diptera), and rare (Blattaria, Isoptera, Diplura, Lepidoptera). Soil temperature and soil organic matter showed significant positive correlation with abundance, while relative humidity was significantly negatively correlated. Soil moisture and soil pH showed no significant correlations while no correlation was found with total rainfall. PCA analysis revealed that soil surface arthropods were the major contributors of variation in overall abundance in extreme temperature months while microarthropods in low-temperature months. CCA analysis revealed the occurrence of different arthropod groups in correspondence with different abiotic variables. Results are discussed in view of position of these arthropods as useful indicators under changing environmental conditions impacting agroecosystems in the study area.

Role of sea surface temperature anomalies in the tropical Indo-Pacific region in the northeast Asia severe drought in summer 2014: month-to-month perspective

NASA Astrophysics Data System (ADS)

Xu, Zhiqing; Fan, Ke; Wang, HuiJun

2017-09-01

The severe drought over northeast Asia in summer 2014 and the contribution to it by sea surface temperature (SST) anomalies in the tropical Indo-Pacific region were investigated from the month-to-month perspective. The severe drought was accompanied by weak lower-level summer monsoon flow and featured an obvious northward movement during summer. The mid-latitude Asian summer (MAS) pattern and East Asia/Pacific teleconnection (EAP) pattern, induced by the Indian summer monsoon (ISM) and western North Pacific summer monsoon (WNPSM) rainfall anomalies respectively, were two main bridges between the SST anomalies in the tropical Indo-Pacific region and the severe drought. Warming in the Arabian Sea induced reduced rainfall over northeast India and then triggered a negative MAS pattern favoring the severe drought in June 2014. In July 2014, warming in the tropical western North Pacific led to a strong WNPSM and increased rainfall over the Philippine Sea, triggering a positive EAP pattern. The equatorial eastern Pacific and local warming resulted in increased rainfall over the off-equatorial western Pacific and triggered an EAP-like pattern. The EAP pattern and EAP-like pattern contributed to the severe drought in July 2014. A negative Indian Ocean dipole induced an anomalous meridional circulation, and warming in the equatorial eastern Pacific induced an anomalous zonal circulation, in August 2014. The two anomalous cells led to a weak ISM and WNPSM, triggering the negative MAS and EAP patterns responsible for the severe drought. Two possible reasons for the northward movement of the drought were also proposed.

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

Temporal and spatial variations of rainfall erosivity in Southern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Ming-Hsi; Lin, Huan-Hsuan; Chu, Chun-Kuang

2014-05-01

Soil erosion models are essential in developing effective soil and water resource conservation strategies. Soil erosion is generally evaluated using the Universal Soil Loss Equation (USLE) with an appropriate regional scale description. Among factors in the USLE model, the rainfall erosivity index (R) provides one of the clearest indications of the effects of climate change. Accurate estimation of rainfall erosivity requires continuous rainfall data; however, such data rarely demonstrate good spatial and temporal coverage. The data set consisted of 9240 storm events for the period 1993 to 2011, monitored by 27 rainfall stations of the Central Weather Bureau (CWB) in southern Taiwan, was used to analyze the temporal-spatial variations of rainfall erosivity. The spatial distribution map was plotted based on rainfall erosivity by the Kriging interpolation method. Results indicated that rainfall erosivity is mainly concentrated in rainy season from June to November typically contributed 90% of the yearly R factor. The temporal variations of monthly rainfall erosivity during June to November and annual rainfall erosivity have increasing trend from 1993 to 2011. There is an increasing trend from southwest to northeast in spatial distribution of rainfall erosivity in southern Taiwan. The results further indicated that there is a higher relationship between elevation and rainfall erosivity. The method developed in this study may also be useful for sediment disasters on Climate Change.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

NASA Astrophysics Data System (ADS)

Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

2018-05-01

Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

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.

An exploratory study on occurrence and impact of climate change on agriculture in Tamil Nadu, India

NASA Astrophysics Data System (ADS)

Varadan, R. Jayakumara; Kumar, Pramod; Jha, Girish Kumar; Pal, Suresh; Singh, Rashmi

2017-02-01

This study has been undertaken to examine the occurrence of climate change in Tamil Nadu, the southernmost state of India and its impact on rainfall pattern which is a primary constraint for agricultural production. Among the five sample stations examined across the state, the minimum temperature has increased significantly in Coimbatore while the same has decreased significantly in Vellore whereas both minimum and maximum temperatures have increased significantly in Madurai since 1969 with climate change occurring between late 1980s and early 1990s. As a result, the south-west monsoon has been disturbed with August rainfall increasing with more dispersion while September rainfall decreasing with less dispersion. Thus, September, the peak rainfall month of south-west monsoon before climate change, has become the monsoon receding month after climate change. Though there has been no change in the trend of the north-east monsoon, the quantity of October and November rainfall has considerably increased with increased dispersion after climate change. On the whole, south-west monsoon has decreased with decreased dispersion while north-east monsoon has increased with increased dispersion. Consequently, the season window for south-west monsoon crops has shortened while the north-east monsoon crops are left to fend against flood risk during their initial stages. Further, the incoherence in warming, climate change and rainfall impact seen across the state necessitates devising different indigenous and institutional adaptation strategies for different regions to overcome the adverse impacts of climate change on agriculture.

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

Trends and Bioclimatic Assessment of Extreme Indices: Emerging Insights for Rainfall Derivative Crop Microinsurance in Central-West Nigeria

NASA Astrophysics Data System (ADS)

Awolala, D. O.

2015-12-01

Scientific predictions have forecasted increasing economic losses by which farming households will be forced to consider new adaptation pathways to close the food gap and be income secure. Pro-poor adaptation planning decisions therefore must rely on location-specific details from systematic assessment of extreme climate indices to provide template for most suitable financial adaptation instruments. This paper examined critical loss point to water stress in maize production and risk-averse behaviour to extreme local climate in Central West Nigeria. Trends of extreme indices and bio-climatic assessment based on RClimDex for numerical weather predictions were carried out using a 3-decade time series daily observational climate data of the sub-humid region. The study reveals that the flowering and seed formation stage was identified as the most critical loss point when seed formation is a function of per unit soil water available for uptake. The sub-humid has a bi-modal rainfall pattern but faces longer dry spell with a fast disappearing mild climate measured by budyko evaporation of 80.1%. Radiation index of dryness of 1.394 confirms the region is rapidly becoming drier at an evaporation rate of 949 mm/year and rainfall deficit of 366 mm/year. Net primary production from rainfall is fast declining by 1634 g(DM)/m2/year. These conditions influenced by monthly rainfall uncertainties are associated with losses of standing crops because farmers are uncertain of rainfall probability distribution especially during most important vegetative stage. In a simulated warmer climate, an absolute dryness of months was observed compared with 4 dry months in a normal climate which explains triggers of food deficits and income losses. Positive coefficients of tropical nights (TR20), warm nights (TN90P) and warm days (TX90P), and the negative coefficient of cold days (TX10P) with time are significant at P<0.05. The increasing gradient of warm spell indicator (WSDI), the decreasing gradients of cold nights (TN10P) and cold days (TX10P) are added evidence of aridity arising from increasing rainfall deficits. This paper recommends that the region needs rainfall-based index microinsurance adaptation financial instruments capable of sharing covariate shocks with farmers within an incentive-based risk sharing framework.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Hassan, Zulkarnain; Haidir, Ahmad; Saad, Farah Naemah Mohd; Ayob, Afizah; Rahim, Mustaqqim Abdul; Ghazaly, Zuhayr Md.

2018-03-01

The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

Use of the gamma distribution to represent monthly rainfall in Africa for drought monitoring applications

USGS Publications Warehouse

Husak, Gregory J.; Michaelsen, Joel C.; Funk, Christopher C.

2007-01-01

Evaluating a range of scenarios that accurately reflect precipitation variability is critical for water resource applications. Inputs to these applications can be provided using location- and interval-specific probability distributions. These distributions make it possible to estimate the likelihood of rainfall being within a specified range. In this paper, we demonstrate the feasibility of fitting cell-by-cell probability distributions to grids of monthly interpolated, continent-wide data. Future work will then detail applications of these grids to improved satellite-remote sensing of drought and interpretations of probabilistic climate outlook forum forecasts. The gamma distribution is well suited to these applications because it is fairly familiar to African scientists, and capable of representing a variety of distribution shapes. This study tests the goodness-of-fit using the Kolmogorov–Smirnov (KS) test, and compares these results against another distribution commonly used in rainfall events, the Weibull. The gamma distribution is suitable for roughly 98% of the locations over all months. The techniques and results presented in this study provide a foundation for use of the gamma distribution to generate drivers for various rain-related models. These models are used as decision support tools for the management of water and agricultural resources as well as food reserves by providing decision makers with ways to evaluate the likelihood of various rainfall accumulations and assess different scenarios in Africa. 

[Seasonality of rotavirus infection in Venezuela: relationship between monthly rotavirus incidence and rainfall rates].

PubMed

González Chávez, Rosabel

2015-09-01

In general, it has been reported that rotavirus infection was detected year round in tropical countries. However, studies in Venezuela and Brazil suggest a seasonal behavior of the infection. On the other hand, some studies link infection with climatic variables such as rainfall. This study analyzes the pattern of behavior of the rotavirus infection in Carabobo-Venezuela (2001-2005), associates the seasonality of the infection with rainfall, and according to the seasonal pattern, estimates the age of greatest risk for infection. The analysis of the rotavirus temporal series and accumulated precipitation was performed with the software SPSS. The infection showed two periods: high incidence (November-April) and low incidence (May-October). Accumulated precipitation presents an opposite behavior. The highest frequency of events (73.8% 573/779) for those born in the period with a low incidence of the virus was recorded at an earlier age (mean age 6.5 +/- 2.0 months) when compared with those born in the station of high incidence (63.5% 568/870, mean age 11.7 +/- 2.2 months). Seasonality of the infection and the inverse relationship between virus incidence and rainfall was demonstrated. In addition, it was found that the period of birth determines the age and risk of infection. This information generated during the preaccine period will be helpful to measure the impact of the vaccine against the rotavirus.

[Characteristics of Atmospheric Nitrogen Wet Deposition and Associated Impact on N Transport in the Watershed of Red Soil Area in Southern China].

PubMed

Hao, Zhuo; Gao, Yang; Zhang, Jin-zhong; Xu, Ya-juan; Yu, Gui-rui

2015-05-01

In this study, Qianyanzhou Xiangxi River Basin in the rainy season was monitored to measure different nitrogen form concentrations of rainfall and rainfall-runoff process, in order to explore the southern red soil region of nitrogen wet deposition characteristics and its influence on N output in watershed. The results showed that there were 27 times rainfall in the 2014 rainy season, wherein N wet deposition load reached 43.64-630.59 kg and N deposition flux were 0.44-6.43 kg · hm(-2), which presented a great seasonal variability. We selected three rainfall events to make dynamic analysis. The rainfall in three rainfall events ranged from 8 to 14mm, and the deposition load in the watershed were from 18.03 to 41.16 kg and its flux reached 0.18 to 0.42 kg · hm(-2). Meanwhile, this three rainfall events led to 4189.38 m3 of the total runoff discharge, 16.72 kg of total nitrogen (TN) load and 4.64 kg · hm(-2) of flux, wherein dissolved total nitrogen (DTN) were 9.64 kg and 2.68 kg · hm(-2), ammonium-nitrogen (NH(4+)-N) were 2.93 kg and 0.81 kg · hm(-2), nitrate-nitrogen (NO(3-)-N) were 5.60 kg and 1.56 kg · hm(-2). The contribution rate of N wet deposition to N output from watershed reached 56%-94% , implying that the rainfall-runoff had tremendous contribution to N loss in this small watershed. The concentrations of TN in water had exceeded 1.5 mg · L(-1) of eutrophication threshold, which existed an eutrophication potential.

Detecting the hydrological impacts of forest cover change in tropical mountain areas: need for detrending time series of rainfall and streamflow data.

NASA Astrophysics Data System (ADS)

Molina, A.; Vanacker, V.; Brisson, E.; Balthazar, V.

2012-04-01

Interactions between human activities and the physical environment have increasingly transformed the hydrological functioning of Andean ecosystems. In these human-modified landscapes, land use/-cover change may have a profound effect on riverine water and sediment fluxes. The hydrological impacts of land use/-cover change are diverse, as changes in vegetation affect the various components of the hydrological cycle including evapotranspiration, infiltration and surface runoff. Quantitative data for tropical mountain regions are scarce, as few long time series on rainfall, water discharge and land use are available. Furthermore, time series of rainfall and streamflow data in tropical mountains are often highly influenced by large inter- and intra-annual variability. In this paper, we analyse the hydrological response to complex forest cover change for a catchment of 280 km2 located in the Ecuadorian Andes. Forest cover change in the Pangor catchment was reconstructed based on airphotos (1963, 1977), LANDSAT TM (1991) and ETM+ data (2001, 2009). From 1963, natural vegetation was converted to agricultural land and pine plantations: forests decreased by a factor 2, and paramo decreased by 20 km2 between 1963 and 2009. For this catchment, there exists an exceptionally long record of rainfall and streamflow data that dates back from the '70s till now, but large variability in hydrometeorological data exists that is partly related to ENSO events. Given the nonstationary and nonlinear character of the ENSO-related changes in rainfall, we used the Hilbert-Huang transformation to detrend the time series of the river flow data from inter- and intra-annual fluctuations in rainfall. After applying adaptive data analysis based on empirical model decomposition techniques, it becomes apparent that the long-term trend in streamflow is different from the long-term trend in rainfall data. While the streamflow data show a long-term decrease in monthly flow, the rainfall data have a trend of increasing and then decreasing precipitation amounts. These results suggest that the land use changes had an important impact on the total water yield of the catchment. Interestingly, the effect of reforestation in the upper part of the catchment with its associated decrease in water yield seems to be dominant over the effect of deforestation in the lower part of the basin.

Spatio-temporal modelling of dengue fever incidence in Malaysia

NASA Astrophysics Data System (ADS)

Che-Him, Norziha; Ghazali Kamardan, M.; Saifullah Rusiman, Mohd; Sufahani, Suliadi; Mohamad, Mahathir; @ Kamariah Kamaruddin, Nafisah

2018-04-01

Previous studies reported significant relationship between dengue incidence rate (DIR) and both climatic and non-climatic factors. Therefore, this study proposes a generalised additive model (GAM) framework for dengue risk in Malaysia by using both climatic and non-climatic factors. The data used is monthly DIR for 12 states of Malaysia from 2001 to 2009. In this study, we considered an annual trend, seasonal effects, population, population density and lagged DIR, rainfall, temperature, number of rainy days and El Niño-Southern Oscillation (ENSO). The population density is found to be positively related to monthly DIR. There are generally weak relationships between monthly DIR and climate variables. A negative binomial GAM shows that there are statistically significant relationships between DIR with climatic and non-climatic factors. These include mean rainfall and temperature, the number of rainy days, sea surface temperature and the interaction between mean temperature (lag 1 month) and sea surface temperature (lag 6 months). These also apply to DIR (lag 3 months) and population density.

Hydrological and hydrochemical impact studies in the urbanised Petrusse river basin (Luxembourg)

NASA Astrophysics Data System (ADS)

Pfister, L.; Iffly, J.; Guignard, C.; Krein, A.; Matgen, P.; Salvia-Castellvi, M.; van den Bos, R.; Tailliez, C.; Barnich, F.; Hofmmann, L.

2009-04-01

On the basis of ancient topographical maps, the growing urbanisation of the Petrusse river basin (42.9 km2) has been documented on 50-year time steps since 1770. While until the 1950's urban areas remained below 10% of total basin area, they are now close to 50%. This rapid change has consisted mainly in a change from cropland into built areas. As a direct consequence of these considerable changes in landuse, the basin presumably has undergone significant modifications of both its hydrological regime and the quality of the flowing surface waters. In the framework of a national monitoring programme, the Petrusse basin has been progressively equipped with 3 recording streamgauges between 1999 and 2003. Several meteorological stations are located in the immediate vicinity of the basin. The hydrological regime revealed by the 15-minute recordings of the streamgauges is very specific to heavily urbanised basins, i.e. characterised by quick reactions to incoming rainfall, as well as very limited contributions from sub-surface and groundwater reservoirs. A conceptual hydrological model has been used to evaluate roughly the impact of the progressive urbanisation of the Petrusse basin since 1770 on the rainfall-runoff relationship. Major changes were found for summer months, with significantly higher peak discharges and increasingly rapid reactions to rainfall events. However, the limitations of the spatial density of rainfall recordings (only 1 rainfall measurement site available between 1854 - 1949) cause severe shortcomings in the accuracy of the incoming rainfall estimations, especially in the case of convective rainfall events. This in turn also considerably reduces the accuracy of the historical rainfall-runoff simulations. Between 2002 and 2004, several monitoring campaigns have been carried out in the Petrusse basin in order to determine the impact of sewer system contributions from the urbanised areas to the water quality within the Petrusse. The investigations have shown a very strong so-called first-flush effect. During dry sequences, numerous deposits on roads and roofs (heavy metals, oils, etc.) accumulate, before being washed away during the first minutes of rainfall events and being ultimately being transported to the Petrusse river via the sewer systems, causing considerable pollution peaks. Current investigations target a reduction of this pollution. The involved volumes of polluted water are of such extent, that they cannot be dealt with by conventional waste water treatment systems. The currently existing rainfall measurement network around the city of Luxembourg has a spatial resolution that is still too low to capture accurately convective rainfall events. A new rainfall measurement approach will soon be tested to estimate spatio-temporal rainfall dynamics with a high resolution above the city of Luxembourg. Based on a combination of conventional raingauges, weather radar and microwave measurements (via cell-phone networks) this approach is supposed to provide data that might ultimately contribute to a real-time management of the first flush pollutions in the Petrusse river basin.

The saptio-temporal distribution of lightning over the southern Levant and its relation to the regional synoptic systems

NASA Astrophysics Data System (ADS)

Shalev, S.; Izsak, T.; Saaroni, H.; Yair, Y.; Ziv, B.

2010-09-01

The saptio-temporal distribution of lightning flashes over the southern Levant is derived from data obtained from the Lightning Positioning and Tracking System (LPATS) operated by the Israeli Electrical Company (IEC). The system has an aerial coverage in a range of ~ 500 Km around central Israel, including the southeastern Mediterranean Sea, Israel, Lebanon, western Syria and Jordan and the eastern part of Sinai Peninsula and the Red Sea. The study period includes 4 years. The spatial distribution of lightning flash density indicated the highest concentration over the sea, and is attributed to the contribution of sensible and latent heat fluxes. Other centers of high flash density appear along the coastal plain, expressing the friction effect of the coastline, and along orographic barriers, especially in northern Israel. The intra-annual distribution shows a complete absence of lightning in the eastern Mediterranean during the summer (JJA) which is due to the persistent existence of the subtropical high above the region. The vast majority of the lightning activity occurs during 7 months between October and April. Even though over 65% of the rainfall is obtained in the winter months (DJF) only 35% of the lightning is obtained in the winter and October is the richest month, with 40% of total annual number of lightning flashes. This is attributed mostly to tropical intrusions, i.e., Red Sea Trough (RST), which is characterized by high static instability. Cyprus lows are the synoptic system contributing the vast majority, >80%, of the rainfall in Israel, but only 42% of the lightning, whereas the RST, a minor contributor of rainfall, shares 48% of the lightning. However, during the winter 66% of the lightning flashes are associated with Cyprus lows and 25% with RST while during the autumn months the ratio is reversed: only 27% are associated with Cyprus lows and the majority (63%) occurs during RST. It was found that over 80% of the days defined as Cyprus lows were associated with lightning, indicating the instability associated with these cyclones over the region. During the RST, even though it is characterized by different weather conditions, 60% of the days were associated with lightning. The spatial distribution of lightning is further studied for positive and negative cloud-to-ground flashes separately. Positive lightning, being <10% of their total number, are concentrated eastward over the coast and inland compared to the negative flashes. This may be explained by the enhanced inclination of the thunder-cloud due to their encounter with the coastline, leading to a "tilted dipole" which is manifested in a larger percentage of positive flashes. Similar results are found in the west coast of Japan in the winter season.

Assessing acid rain and climate effects on the temporal variation of dissolved organic matter in the unsaturated zone of a karstic system from southern China

NASA Astrophysics Data System (ADS)

Liao, Jin; Hu, Chaoyong; Wang, Miao; Li, Xiuli; Ruan, Jiaoyang; Zhu, Ying; Fairchild, Ian J.; Hartland, Adam

2018-01-01

Acid rain has the potential to significantly impact the quantity and quality of dissolved organic matter (DOM) leached from soil to groundwater. Yet, to date, the effects of acid rain have not been investigated in karstic systems, which are expected to strongly buffer the pH of atmospheric rainfall. This study presents a nine-year DOM fluorescence dataset from a karst unsaturated zone collected from two drip sites (HS4, HS6) in Heshang Cave, southern China between 2005 and 2014. Cross-correlograms show that fluorescence intensity of both dripwaters lagged behind rainfall by ∼1 year (∼11 months lag for HS4, and ∼13 months for HS6), whereas drip rates responded quite quickly to rainfall (0 months lag for HS4, and ∼3 months for HS6), based on optimal correlation coefficients. The rapid response of drip rates to rainfall is related to the change of reservoir head pressure in summer, associated with higher rainfall. In winter, low rainfall has a limited effect on head pressure, and drip rates gradually slow to a constant value associated with base flow from the overlying reservoir- this effect being most evident on inter-annual timescales (R2 = 0.80 for HS4 and R2 = 0.86 for HS6, n = 9, p < 0.01). We ascribed the ∼1 year lag of fluorescence intensity to the effect of the soil moisture deficit and the karst process on delaying water and solute transport. After eliminating the one year lag, the congruent seasonal pacing and amplitude between fluorescence intensity and rainfall observed suggests that the seasonality of fluorescence intensity was mainly controlled by the monsoonal rains which can govern the output of DOM from the soil, as well as the residence time of water in the unsaturated zone. On inter-annual timescales, a robust linear relationship between fluorescence intensity and annual (effective) precipitation amount (R2 = 0.86 for HS4 and R2 = 0.77 for HS6, n = 9, p < 0.01) was identified, implying that annual (effective) precipitation is the main determinant of DOM concentration in the aquifer. Conversely, the insensitivity of fluorescence intensity and fluorescence wavelength maxima to variations in the pH of local rainfall suggests that acid rain over the study period (∼pH 5.6 to ∼ 4.5) had no discernable effect on the quantity and quality of DOM in karst soil and soil solution, likely being strongly buffered by soil carbonates. Therefore, despite large increases in anthropogenic acid rain in recent Chinese history, hydrologic forcing is the predominant factor driving variations in DOM in karst aquifers.

Characteristics of extreme rainfall events in northwestern Peru during the 1982-1983 El Nino period

NASA Technical Reports Server (NTRS)

Goldberg, R. A.; Tisnado, G. M.; Scofield, R. A.

1987-01-01

Histograms and contour maps describing the daily rainfall characteristics of a northwestern Peru area most severely affected by the 1982-1983 El Nino event were prepared from daily rainfall data obtained from 66 stations in this area during the El Nino event, and during the same 8-month intervals for the two years preceding and following the event. These data were analyzed, in conjunction with the anlysis of visible and IR satellite images, for cloud characteristics and structure. The results present a comparison of the rainfall characteristics as a function of elevation, geographic location, and the time of year for the El Nino and non-El Nino periods.

James Madison and a Shift in Precipitation Seasonality

NASA Astrophysics Data System (ADS)

Druckenbrod, D. L.; Mann, M. E.; Stahle, D. W.; Cleaveland, M. K.; Therrell, M. D.; Shugart, H. H.

2001-12-01

An eighteen-year meteorological diary and tree ring data from James Madison's Montpelier plantation provide a consistent reconstruction of early summer and prior fall rainfall for the 18th Century Virginia piedmont. The Madison meteorological diary suggests a seasonal shift in monthly rainfall towards an earlier wet season relative to 20th Century norms. Furthermore, dendroclimatic reconstructions of early summer and prior fall rainfall reflect this shift in the seasonality of summer rainfall. The most pronounced early summer drought during the Madison diary period is presented as a case study. This 1792 drought occurs during one of the strongest El Niño events on record and is highlighted in the correspondence of James Madison.

The use of simulated rainfall to study the discharge process and the influence factors of urban surface runoff pollution loads.

PubMed

Qinqin, Li; Qiao, Chen; Jiancai, Deng; Weiping, Hu

2015-01-01

An understanding of the characteristics of pollutants on impervious surfaces is essential to estimate pollution loads and to design methods to minimize the impacts of pollutants on the environment. In this study, simulated rainfall equipment was constructed to investigate the pollutant discharge process and the influence factors of urban surface runoff (USR). The results indicated that concentrations of total suspended solids (TSS), total nitrogen (TN), total phosphorus (TP) and chemical oxygen demand (COD) appeared to be higher in the early period and then decreased gradually with rainfall duration until finally stabilized. The capacity and particle size of surface dust, rainfall intensity and urban surface slopes affected runoff pollution loads to a variable extent. The loads of TP, TN and COD showed a positive relationship with the surface dust capacity, whereas the maximum TSS load appeared when the surface dust was 0.0317 g·cm⁻². Smaller particle sizes (<0.125 mm) of surface dust generated high TN, TP and COD loads. Increases in rainfall intensity and surface slope enhanced the pollution carrying capacity of runoff, leading to higher pollution loads. Knowledge of the influence factors could assist in the management of USR pollution loads.

Rain from Tropical Storm Noel

NASA Technical Reports Server (NTRS)

2007-01-01

Though not the most powerful storm of the 2007 Atlantic Hurricane season, Tropical Storm Noel was among the most deadly. Only Category 5 Hurricane Felix and its associated flooding had a higher toll. The slow-moving Tropical Storm Noel inundated the Dominican Republic, Haiti, Jamaica, Cuba, and the Bahamas with heavy rain between October 28 and November 1, 2007. The resulting floods and mudslides left at least 115 dead and thousands homeless throughout the Caribbean, reported the Associated Press on November 2, 2007. This image shows the distribution of the rainfall that made Noel a deadly storm. The image shows rainfall totals as measured by the Multi-satellite Precipitation Analysis (MPA) at NASA Goddard Space Flight Center from October 26 through November 1, 2007. The analysis is based on measurements taken by the Tropical Rainfall Measuring Mission (TRMM) satellite. The heaviest rainfall fell in the Dominican Republic and the Bahamas, northeast of Noel's center. Areas of dark red show that rainfall totals over the south-central Dominican Republic and parts of the Bahamas were over 551 millimeters (21 inches). Much of eastern Hispaniola, including both the Dominican Republic and Haiti received at least 200 mm (about 8 inches) of rain, shown in yellow. Rainfall totals over Haiti and Cuba were less, with a range of at least 50 mm (2 inches) to over 200 mm (8 inches).

The potential of lipopolysaccharide as a real-time biomarker of bacterial contamination in marine bathing water.

PubMed

Sattar, Anas A; Jackson, Simon K; Bradley, Graham

2014-03-01

The use of total lipopolysaccharide (LPS) as a rapid biomarker for bacterial pollution was investigated at a bathing and surfing beach during the UK bathing season. The levels of faecal indicator bacteria Escherichia coli (E. coli), the Gram-positive enterococci, and organisms commonly associated with faecal material, such as total coliforms and Bacteroides, were culturally monitored over four months to include a period of heavy rainfall and concomitant pollution. Endotoxin measurement was performed using a kinetic Limulus Amebocyte Lysate (LAL) assay and found to correlate well with all indicators. Levels of LPS in excess of 50 Endotoxin Units (EU) mL(-1) were found to correlate with water that was unsuitable for bathing under the current European regulations. Increases in total LPS, mainly from Gram-negative indicator bacteria, are thus a potential real-time, qualitative method for testing bacterial quality of bathing waters.

Rainfall and cave water isotopic relationships in two South-France sites

NASA Astrophysics Data System (ADS)

Genty, D.; Labuhn, I.; Hoffmann, G.; Danis, P. A.; Mestre, O.; Bourges, F.; Wainer, K.; Massault, M.; Van Exter, S.; Régnier, E.; Orengo, Ph.; Falourd, S.; Minster, B.

2014-04-01

This article presents isotopic measurements (δ18O and δD) of precipitation and cave drip water from two sites in southern France in order to investigate the link between rainfall and seepage water, and to characterize regional rainfall isotopic variability. These data, which are among the longest series in France, come from two rainfall stations in south-west France (Le Mas 1996-2012, and Villars 1998-2012; typically under Atlantic influence), and from one station in the south-east (Orgnac 2000-2012; under both Mediterranean and Atlantic influence). Rainfall isotopic composition is compared to drip water collected under stalactites from the same sites: Villars Cave (four drip stations 1999-2012) in the south-west, and Chauvet Cave (two drip stations 2000-2012) in the south-east, near Orgnac. The study of these isotopic data sets allows the following conclusions to be drawn about the rainfall/drip water relationships and about rainfall variability: (1) the cave drip water isotopic composition does not show any significant changes since the beginning of measurements; in order to explain its isotopic signature it is necessary to integrate weighted rainfall δ18O of all months during several years, which demonstrates that, even at shallow depths (10-50 m), cave drip water is a mixture of rain water integrated over relatively long periods, which give an apparent time residence from several months to up to several years. These results have important consequences on the interpretation of proxies like speleothem fluid inclusions and tree-ring cellulose isotopic composition, which are used for paleoclimatic studies; (2) in the Villars Cave, where drip stations at two different depths were studied, lower δ18O values were observed in the lower galleries, which might be due to winter season overflows during infiltration and/or to older rain water with a different isotopic composition that reaches the lower galleries after years; (3) local precipitation is characterized by local meteoric water lines, LMWL, with δ18O/δD slopes close to 7 in both areas, and correlations between air temperature and precipitation δ18O are low at both monthly and annual scales, even with temperature weighted by the amount of precipitation; (4) the mesoscale climate model REMOiso, equipped with a water isotope module, allows the direct comparison of modeled and observed long term water isotope records. The model slightly overestimates rainfall δ18O at the respective sampling stations. However, it simulates very well not only the seasonal rainfall isotopic signal but also some intra-seasonal patterns such as a typical double-peak δ18O pattern in winter time.

Rainfall influence on styles of mass movement

NASA Astrophysics Data System (ADS)

Anderson, S. P.; Rengers, F. K.; Foster, M. A.; Winchell, E. W.; Anderson, R. S.

2017-12-01

Precipitation characteristics influence whether hillslope materials move in rain-splash driven hops, shallow landslides, or in deep-seated failures. While one might expect a particular style of slope failure to dominate in a region, we report on multiple distinctive mass movements on a single ridge, each associated with different weather events. This suggests that understanding climate regulation of denudation rates and hillslope morphology requires quantifying both triggering hydro-climates, and the corresponding hillslope response to the full spectrum of events. We explore these connections on Dakota Ridge, a hogback at the eastern margin of the Colorado Front Range. The dipslope of Dakota Ridge has generated slumps, debris flows, and an earthflow over the last 4 years; Pleistocene-era deep-seated landslides are also evident. We document mass-movements along a 1 km long segment of Dakota Ridge. Weeklong precipitation and flooding in September 2013 produced slumps, each of which displaced 50-100 m3 of mobile regolith several meters downslope, and some of which triggered shallow, relatively non-erosive debris flows. By contrast, a similar precipitation total over the month of May 2015 mobilized an earthflow. The 10 m wide earthflow displaced mobile regolith downslope as much as 10 m over its 150 m length. These recent landslides are dwarfed by a 400 m wide deep-seated landslide that controls slope morphology from ridge crest to toe. Exposure ages (10Be) suggest a late-Pleistocene age for this feature. Although the September 2013 storm produced record-setting rainfall totals at daily, monthly and annual timescales (e.g., annual exceedance probability of <1/1000 for daily totals), the failures from that event, while numerous, were the smallest of all the landslides in the study area. These observations raise the question: what hydro-climatic conditions produce deep-seated, bedrock involved slope failures? Recent storms suggest that within mobile regolith, individual failure size increases with duration of the triggering weather event. Ridge-scale bedrock-involved failures presumably reflect a more persistently wet climate.

Depth distribution of radiocesium in Fukushima paddy fields and implications for ongoing decontamination works

NASA Astrophysics Data System (ADS)

Lepage, H.; Evrard, O.; Onda, Y.; Lefèvre, I.; Laceby, J. P.; Ayrault, S.

2014-09-01

Large quantities of radiocesium were deposited across a 3000 km2 area northwest of the Fukushima Dai-ichi nuclear power plant after the March 2011 accident. Although many studies have investigated the fate of radiocesium in soil in the months following the accident, the potential migration of this radioactive contaminant in rice paddy fields requires further examination after the typhoons that occurred in this region. Such investigations will help minimize potential human exposure in rice paddy fields or transfer of radioactive contaminants from soils to rice. Radionuclide activity concentrations and organic content were analysed in 10 soil cores sampled from paddy fields in November 2013, 20 km north of the Fukushima power plant. Our results demonstrate limited depth migration of radiocesium with the majority concentrated in the uppermost layers of soils (< 5 cm). More than 30 months after the accident, 81.5 to 99.7% of the total 137Cs inventories was still found within the < 5 cm of the soil surface, despite cumulative rainfall totalling 3300 mm. Furthermore, there were no significant correlations between radiocesium migration depth and total organic carbon content. We attributed the maximum depth penetration of 137Cs to maintenance (grass cutting - 97% of 137Cs in the upper 5 cm) and farming operations (tilling - 83% of 137Cs in the upper 5 cm). As this area is exposed to erosive events, ongoing decontamination works may increase soil erodibility. We therefore recommend the rapid removal of the uppermost - contaminated - layer of the soil after removing the vegetation to avoid erosion of contaminated material during the subsequent rainfall events. Remediation efforts should be concentrated on soils characterised by radiocesium activities > 10 000 Bq kg-1 to prevent the contamination of rice. Further analysis is required to clarify the redistribution of radiocesium eroded on river channels.

Passive microwave remote sensing of rainfall with SSM/I: Algorithm development and implementation

NASA Technical Reports Server (NTRS)

Ferriday, James G.; Avery, Susan K.

1994-01-01

A physically based algorithm sensitive to emission and scattering is used to estimate rainfall using the Special Sensor Microwave/Imager (SSM/I). The algorithm is derived from radiative transfer calculations through an atmospheric cloud model specifying vertical distributions of ice and liquid hydrometeors as a function of rain rate. The algorithm is structured in two parts: SSM/I brightness temperatures are screened to detect rainfall and are then used in rain-rate calculation. The screening process distinguishes between nonraining background conditions and emission and scattering associated with hydrometeors. Thermometric temperature and polarization thresholds determined from the radiative transfer calculations are used to detect rain, whereas the rain-rate calculation is based on a linear function fit to a linear combination of channels. Separate calculations for ocean and land account for different background conditions. The rain-rate calculation is constructed to respond to both emission and scattering, reduce extraneous atmospheric and surface effects, and to correct for beam filling. The resulting SSM/I rain-rate estimates are compared to three precipitation radars as well as to a dynamically simulated rainfall event. Global estimates from the SSM/I algorithm are also compared to continental and shipboard measurements over a 4-month period. The algorithm is found to accurately describe both localized instantaneous rainfall events and global monthly patterns over both land and ovean. Over land the 4-month mean difference between SSM/I and the Global Precipitation Climatology Center continental rain gauge database is less than 10%. Over the ocean, the mean difference between SSM/I and the Legates and Willmott global shipboard rain gauge climatology is less than 20%.

Models for short term malaria prediction in Sri Lanka

PubMed Central

Briët, Olivier JT; Vounatsou, Penelope; Gunawardena, Dissanayake M; Galappaththy, Gawrie NL; Amerasinghe, Priyanie H

2008-01-01

Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed. PMID:18460204

The effects of more extreme rainfall patterns on nitrogen leaching from a field crop system in the upper Midwest, USA

NASA Astrophysics Data System (ADS)

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

2016-12-01

As global surface temperatures rise, the proportion of total rainfall that falls in heavy storm events is increasing in many areas, in particular the US Midwest, a major agricultural region. These changes in rainfall patterns may have consequences for ecosystem nutrient losses, especially from agricultural ecosystems. We conducted a multi-year rainfall manipulation experiment to examine how more extreme rainfall patterns affect nitrogen (N) leaching from row-crop ecosystems in the upper Midwest, and to what extent tillage may moderate these effects. 5x5m rainout shelters were installed in April 2015 to impose control and extreme rainfall patterns in replicated plots under conventional tillage and no-till management at the Kellogg Biological Station LTER site. Plots exposed to the control rainfall treatment received ambient rainfall, and those exposed to the extreme rainfall treatment received the same total amount of water but applied once every 2 weeks, to simulate larger, less frequent storms. N leaching was calculated as the product of measured soil water N concentrations and modeled soil water drainage at 1.2m depth using HYDRUS-1D. Based on data to date, more N has been leached from both tilled and no-till soils exposed to the extreme rainfall treatment compared to the control rainfall treatment. Results thus far suggest that greater soil water drainage is a primary driver of this increase, and changes in within-system nitrogen cycling - such as net N mineralization and crop N uptake - may also play a role. The experiment is ongoing, and our results so far suggest that intensifying precipitation patterns may exacerbate N leaching from agricultural soils, with potentially negative consequences for receiving ground- and surface waters, as well as for farmers.

Role of meteorological conditions in reported chickenpox cases in Wuhan and Hong Kong, China.

PubMed

Chen, Banghua; Sumi, Ayako; Wang, Lei; Zhou, Wang; Kobayashi, Nobumichi

2017-08-03

Chickenpox is a common contagious disease that remains an important public health issue worldwide. Over 90% of unvaccinated individuals become infected, but infection occurs at different ages in different parts of the world. Many people have been infected by 20 to 30 years of age in China, and adults and pregnant women who become infected often develop severe infection. Furthermore, a mortality rate of 2-3 per 100,000 infected persons has been reported. In this study, we explore the temperature-dependent transition of patterns of reported chickenpox cases in two large subtropical climate cities, Wuhan and Hong Kong, China, to aid in the prediction of epidemics and preparation for the effects of climatic changes on epidemiology of chickenpox in China. We used a time series analysis comprising a spectral analysis based on the maximum entropy method in the frequency domain and the nonlinear least squares method in the time domain. Specifically, the following time series data were analyzed: data of reported chickenpox cases and meteorological data, including the mean temperature, relative humidity and total rainfall in Wuhan and Hong Kong from January 2008 to June 2015. The time series data of chickenpox for both Wuhan and Hong Kong have two peaks per year, one in winter and another in spring, indicating a bimodal cycle. To investigate the source of the bimodal cycle of the chickenpox data, we defined the contribution ratio of the 1-year cycle, Q 1 , and the 6-month cycle, Q 2 , as the contribution of the amplitude of a 1-year cycle and a 6-month cycle, respectively, to the entire amplitude of the time-series data. The Q 1 values of Wuhan and Hong Kong were positively correlated with the annual mean temperature and rainfall of each city. Conversely, the Q 2 values of Wuhan and Hong Kong were negatively correlated with the annual mean temperature and rainfall of Wuhan and Hong Kong. Our results showed that the mean temperature and rainfall have a significant influence on the incidence of chickenpox, and might be important predictors of chickenpox incidence in Wuhan and Hong Kong.

Stable isotope ratios in rainfall and water vapour at Bangalore, Southern India during the monsoon period of 2013

NASA Astrophysics Data System (ADS)

Peethambaran, Rahul; Ghosh, Prosenjit

2015-04-01

Rainwater and water vapour were collected during monsoon rainfall from Bangalore station to identifying the signature of moisture sources. Moisture responsible for the rainfall originates from Arabian Sea and Bay of Bengal and advected to the station together with vapour generated from the local . Total no of samples includes 72 for water vapour and 81 for rainwater respectively. The mean difference between water vapour and rainwater was found to be -13.27±2.5 ‰ for δ18O, -100±9 ‰ for δD, which was calculated from monthly mean values of water vapour and rainwater. The most enriched samples of rainwater and water vapour were found during the pre monsoon months which correspond to temperature maximum at the study location. Lighter isotopic ratios were recorded in samples collected during the starting of monsoon showers which goes to further depletion in δ18O during the period of post monsoon. This was mainly due to the change in the prevailing wind direction from southwest to northeast. Local Meteoric Water Line (LMWL) generated for rainwater (d = 7.49 δ 18O + 5.2555, R² = 0.93) equation suggesting enrichment due to evaporation. Local Vapour Line (LVL) (d = 7.5248 δ 18O + 6.6534,R² = 0.8957) indicates the dominance of vapor from local source. The time series of d-xcess of rainwater and water vapor reveals large variability, coinciding with the presence of transported and local sources. It was observed that rainwater and water vapor exhibits higher values indicating re-evaporation from the region. Repetition of this feature demonstrated pattern of moisture recycling in the atmosphere and the contribution of continental evaporation and transpiration. The sensitivity of isotopes to the sudden change in wind direction was documented by an abrupt variations in the isotope values. Such changes in wind patterns were mostly associated with the prevalence of low pressure depression systems during the monsoon periods. Detailed analysis on role of wind patterns and air parcel trajectories, atmospheric parameters such as rainfall, temperature and relative humidity and quantitative estimation of local source moisture source contributions will be discussed at the time of presentation.

The Fate of Pollutants in Porous Asphalt Pavements, Laboratory Experiments to Investigate Their Potential to Impact Environmental Health.

PubMed

Charlesworth, Susanne M; Beddow, Jamie; Nnadi, Ernest O

2017-06-21

Pervious Paving Systems (PPS) are part of a sustainable approach to drainage in which excess surface water is encouraged to infiltrate through their structure, during which potentially toxic elements, such as metals and hydrocarbons are treated by biodegradation and physical entrapment and storage. However, it is not known where in the PPS structure these contaminants accumulate, which has implications for environmental health, particularly during maintenance, as well as consequences for the recycling of material from the PPS at the end-of-life. A 1 m³ porous asphalt (PA) PPS test rig was monitored for 38 months after monthly additions of road sediment (RS) (367.5 g in total) and unused oil (430 mL in total), characteristic of urban loadings, were applied. Using a rainfall simulator, a typical UK rainfall rate of 15 mm/h was used to investigate its efficiency in dealing with contamination. Water quality of the effluent discharged from the rig was found to be suitable for discharge to most environments. On completion of the monitoring, a core was taken down through its surface, and samples of sediment and aggregate were taken. Analysis showed that most of the sediment remained in the surface course, with metal levels lower than the original RS, but higher than clean, unused aggregate or PA. However, even extrapolating these concentrations to 20 years' worth of in-service use (the projected life of PPS) did not suggest their accumulation would present an environmental pollution risk when carrying out maintenance of the pavement and also indicates that the material could be recycled at end-of-life.

The Fate of Pollutants in Porous Asphalt Pavements, Laboratory Experiments to Investigate Their Potential to Impact Environmental Health

PubMed Central

Charlesworth, Susanne M.; Beddow, Jamie; Nnadi, Ernest O.

2017-01-01

Pervious Paving Systems (PPS) are part of a sustainable approach to drainage in which excess surface water is encouraged to infiltrate through their structure, during which potentially toxic elements, such as metals and hydrocarbons are treated by biodegradation and physical entrapment and storage. However, it is not known where in the PPS structure these contaminants accumulate, which has implications for environmental health, particularly during maintenance, as well as consequences for the recycling of material from the PPS at the end-of-life. A 1 m3 porous asphalt (PA) PPS test rig was monitored for 38 months after monthly additions of road sediment (RS) (367.5 g in total) and unused oil (430 mL in total), characteristic of urban loadings, were applied. Using a rainfall simulator, a typical UK rainfall rate of 15 mm/h was used to investigate its efficiency in dealing with contamination. Water quality of the effluent discharged from the rig was found to be suitable for discharge to most environments. On completion of the monitoring, a core was taken down through its surface, and samples of sediment and aggregate were taken. Analysis showed that most of the sediment remained in the surface course, with metal levels lower than the original RS, but higher than clean, unused aggregate or PA. However, even extrapolating these concentrations to 20 years’ worth of in-service use (the projected life of PPS) did not suggest their accumulation would present an environmental pollution risk when carrying out maintenance of the pavement and also indicates that the material could be recycled at end-of-life. PMID:28635641

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.

Design of the primary and secondary Pre-TRMM and TRMM ground truth sites

NASA Technical Reports Server (NTRS)

Garstang, Michael; Austin, Geoffrey; Cosgrove, Claire

1991-01-01

Results generated over six months are covered in five manuscripts: (1) estimates of rain volume over the Peninsula of Florida during the summer season based upon the Manually Digitized Radar data; (2) the diurnal characteristics of rainfall over Florida and over the near shore waters; (3) convective rainfall as measured over the east coast of central Florida; (4) the spatial and temporal variability of rainfall over Florida; and (5) comparisons between the land based radar and an optical raingage onboard an anchored buoy 50 km offshore.

Potential Impact of Rainfall on the Air-Surface Exchange of Total Gaseous Mercury from Two Common Urban Ground Surfaces

EPA Science Inventory

The impact of rainfall on total gaseous mercury (TGM) flux from pavement and street dirt surfaces was investigated in an effort to determine the influence of wet weather events on mercury transport in urban watersheds. Street dirt and pavement are common urban ground surfaces tha...

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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.

Monsoon Rainfall and Landslides in Nepal

NASA Astrophysics Data System (ADS)

Dahal, R. K.; Hasegawa, S.; Bhandary, N. P.; Yatabe, R.

2009-12-01

A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of antecedent rainfall in triggering landslides. It is noticed that a moderate correlation exists between the antecedent rainfalls of 3 to 10 days and the daily rainfall at failure in the Nepal Himalaya. The rainfall thresholds are utilized to develop early warning systems. Taking reference of the intensity-duration threshold and normalized rainfall intensity threshold, two proto-type models of early warning systems (RIEWS and N-RIEWS) are proposed. Early warning models show less time for evacuation in the case of short duration and high intensity rainfall, whereas for long duration rainfall, warning time is enough and when warning information disseminate to the people, people will aware to possible landslide risk. In the meantime, they will be mentally ready to tackle with possible disaster of coming hours or days and will avoid the consequences. On the basis of coarse hydro-meteorological data of developing country like Nepal, this simple and rather easy model of early warning will certainly help to reduce fatalities from landslides.

The effects of hurricane Rita and subsequent drought on alligators in southwest Louisiana.

PubMed

Lance, Valentine A; Elsey, Ruth M; Butterstein, George; Trosclair, Phillip L; Merchant, Mark

2010-02-01

Hurricane Rita struck the coast of southwest Louisiana in September 2005. The storm generated an enormous tidal surge of approximately four meters in height that inundated many thousands of acres of the coastal marsh with full strength seawater. The initial surge resulted in the deaths of a number of alligators and severely stressed those who survived. In addition, a prolonged drought (the lowest rainfall in 111 years of recorded weather data) following the hurricane resulted in highly saline conditions that persisted in the marsh for several months. We had the opportunity to collect 11 blood samples from alligators located on Holly Beach less than a month after the hurricane, but were unable to collect samples from alligators on Rockefeller Wildlife Refuge until February 2006. Conditions at Rockefeller Refuge did not permit systematic sampling, but a total of 201 samples were collected on the refuge up through August 2006. The blood samples were analyzed for sodium, potassium, chloride, osmolality, and corticosterone. Blood samples from alligators sampled on Holly Beach in October 2005, showed a marked elevation in plasma osmolality, sodium, chloride, potassium, corticosterone, and an elevated heterophil/lymphocyte ratio. Blood samples from alligators on Rockefeller Refuge showed increasing levels of corticosterone as the drought persisted and elevated osmolality and electrolytes. After substantial rainfall in July and August, these indices of osmotic stress returned to within normal limits. (c) 2009 Wiley-Liss, Inc.

Rainfall-ground movement modelling for natural gas pipelines through landslide terrain

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

O`Neil, G.D.; Simmonds, G.R.; Grivas, D.A.

1996-12-31

Perhaps the greatest challenge to geotechnical engineers is to maintain the integrity of pipelines at river crossings where landslide terrain dominates the approach slopes. The current design process at NOVA Gas Transmission Ltd. (NGTL) has developed to the point where this impact can be reasonably estimated using in-house models of pipeline-soil interaction. To date, there has been no method to estimate ground movements within unexplored slopes at the outset of the design process. To address this problem, rainfall and slope instrumentation data have been processed to derive rainfall-ground movement relationships. Early results indicate that the ground movements exhibit two components:more » a steady, small rate of movement independent of the rainfall, and, increased rates over short periods of time following heavy amounts of rainfall. Evidence exists of a definite threshold value of rainfall which has to be exceeded before any incremental movement is induced. Additional evidence indicates a one-month lag between rainfall and ground movement. While these models are in the preliminary stage, results indicate a potential to estimate ground movements for both initial design and planned maintenance actions.« less

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

2012-01-01

Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

Vegetation responses to season of fire in an aseasonal, fire-prone fynbos shrubland

PubMed Central

Cowling, Richard M.; van Wilgen, Brian W.; Rikhotso, Diba R.; Difford, Mark

2017-01-01

Season of fire has marked effects on floristic composition in fire-prone Mediterranean-climate shrublands. In these winter-rainfall systems, summer-autumn fires lead to optimal recruitment of overstorey proteoid shrubs (non-sprouting, slow-maturing, serotinous Proteaceae) which are important to the conservation of floral diversity. We explored whether fire season has similar effects on early establishment of five proteoid species in the eastern coastal part of the Cape Floral Kingdom (South Africa) where rainfall occurs year-round and where weather conducive to fire and the actual incidence of fire are largely aseasonal. We surveyed recruitment success (ratio of post-fire recruits to pre-fire parents) of proteoids after fires in different seasons. We also planted proteoid seeds into exclosures, designed to prevent predation by small mammals and birds, in cleared (intended to simulate fire) fynbos shrublands at different sites in each of four seasons and monitored their germination and survival to one year post-planting (hereafter termed ‘recruitment’). Factors (in decreasing order of importance) affecting recruitment success in the post-fire surveys were species, pre-fire parent density, post-fire age of the vegetation at the time of assessment, and fire season, whereas rainfall (for six months post-fire) and fire return interval (>7 years) had little effect. In the seed-planting experiment, germination occurred during the cooler months and mostly within two months of planting, except for summer-plantings, which took 2–3 months longer to germinate. Although recruitment success differed significantly among planting seasons, sites and species, significant interactions occurred among the experimental factors. In both the post-fire surveys and seed planting experiment, recruitment success in relation to fire- or planting season varied greatly within and among species and sites. Results of these two datasets were furthermore inconsistent, suggesting that proteoid recruitment responses are not related to the season of fire. Germination appeared less rainfall-dependent than in winter-rainfall shrublands, suggesting that summer drought-avoiding dormancy is limited and has less influence on variation in recruitment success among fire seasons. The varied response of proteoid recruitment to fire season (or its simulation) implies that burning does not have to be restricted to particular seasons in eastern coastal fynbos, affording more flexibility for fire management than in shrublands associated with winter rainfall. PMID:28828239

Vegetation responses to season of fire in an aseasonal, fire-prone fynbos shrubland.

PubMed

Kraaij, Tineke; Cowling, Richard M; van Wilgen, Brian W; Rikhotso, Diba R; Difford, Mark

2017-01-01

Season of fire has marked effects on floristic composition in fire-prone Mediterranean-climate shrublands. In these winter-rainfall systems, summer-autumn fires lead to optimal recruitment of overstorey proteoid shrubs (non-sprouting, slow-maturing, serotinous Proteaceae) which are important to the conservation of floral diversity. We explored whether fire season has similar effects on early establishment of five proteoid species in the eastern coastal part of the Cape Floral Kingdom (South Africa) where rainfall occurs year-round and where weather conducive to fire and the actual incidence of fire are largely aseasonal. We surveyed recruitment success (ratio of post-fire recruits to pre-fire parents) of proteoids after fires in different seasons. We also planted proteoid seeds into exclosures, designed to prevent predation by small mammals and birds, in cleared (intended to simulate fire) fynbos shrublands at different sites in each of four seasons and monitored their germination and survival to one year post-planting (hereafter termed 'recruitment'). Factors (in decreasing order of importance) affecting recruitment success in the post-fire surveys were species, pre-fire parent density, post-fire age of the vegetation at the time of assessment, and fire season, whereas rainfall (for six months post-fire) and fire return interval (>7 years) had little effect. In the seed-planting experiment, germination occurred during the cooler months and mostly within two months of planting, except for summer-plantings, which took 2-3 months longer to germinate. Although recruitment success differed significantly among planting seasons, sites and species, significant interactions occurred among the experimental factors. In both the post-fire surveys and seed planting experiment, recruitment success in relation to fire- or planting season varied greatly within and among species and sites. Results of these two datasets were furthermore inconsistent, suggesting that proteoid recruitment responses are not related to the season of fire. Germination appeared less rainfall-dependent than in winter-rainfall shrublands, suggesting that summer drought-avoiding dormancy is limited and has less influence on variation in recruitment success among fire seasons. The varied response of proteoid recruitment to fire season (or its simulation) implies that burning does not have to be restricted to particular seasons in eastern coastal fynbos, affording more flexibility for fire management than in shrublands associated with winter rainfall.

Characteristics of occurrence of heavy rainfall events over Odisha during summer monsoon season

NASA Astrophysics Data System (ADS)

Swain, Madhusmita; Pattanayak, Sujata; Mohanty, U. C.

2018-06-01

During summer monsoon season heavy to very heavy rainfall events have been occurring over most part of India, routinely result in flooding over Indian Monsoon Region (IMR). It is worthwhile to mention that as per Geological Survey of India, Odisha is one of the most flood prone regions of India. The present study analyses the occurrence of very light (0-2.4 mm/day), light (2.5 - 15.5 mm/day), moderate (15.6 - 64.4 mm/day), heavy (64.5 - 115.4 mm/day), very heavy (115.5 - 204.4 mm/day) and extreme (≥ 204.5 mm/day) rainy days over Odisha during summer monsoon season for a period of 113 years (1901 - 2013) and a detailed study has been done for heavy-to-extreme rainy days. For this purpose, India Meteorological Department (IMD) gridded (0.25° × 0.25° lat/lon) rainfall data and the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-Interim) (0.125° × 0.125° lat/lon) datasets are used. The analysis reveals that the frequency of very light, light and moderate rainy days persists with almost constant trend, but the heavy, very heavy and extreme rainy days exhibit an increasing trend during the study period. It may be noted that more than 60% of heavy-to-extreme rainy days are observed in the month of July and August. Furthermore, during the recent period (1980-2013), there are a total of 150 extreme rainy days are observed over Odisha, out of which 47% are associated with monsoon depressions (MDs) and cyclonic storms, 41% are with lows, 2% are due to the presence of middle and upper tropospheric cyclonic circulations, 1% is due to monsoon trough and other 9% of extreme rainy days does not follow any of these synoptic conditions. Since a large (nearly half) percentage of extreme rainy days over Odisha is due to the presence of MDs, a detailed examination of MDs is illustrated in this study. Analysis reveals that there are a total of 91 MDs formed over the Bay of Bengal (BoB) during 1980 - 2013, and out of which 56 (61.5% of total MD) MDs crossed Odisha. Further spatial analysis of extreme rainfall days exhibits that the maximum frequency of extreme rainy days is present over the south west region of Odisha.

HOW STRONG IS THE RELATIONSHIP BETWEEN RAINFALL VARIABILITY AND CAATINGA PRODUCTIVITY? A CASE STUDY UNDER A CHANGING CLIMATE.

PubMed

Salimon, Cleber; Anderson, Liana

2017-05-22

Despite the knowledge of the influence of rainfall on vegetation dynamics in semiarid tropical Brazil, few studies address and explore quantitatively the various aspects of this relationship. Moreover, Northeast Brazil is expected to have its rainfall reduced by as much as 60% until the end of the 21st Century, under scenario AII of the IPCC Report 2010. We sampled and analyzed satellite-derived monthly rainfall and a vegetation index data for 40 sites with natural vegetation cover in Paraíba State, Brazil from 2001 to 2012. In addition, the anomalies for both variables were calculated. Rainfall variation explained as much as 50% of plant productivity, using the vegetation index as a proxy, and rainfall anomaly explained 80% of the vegetation productivity anomaly. In an extreme dry year (2012), with 65% less rainfall than average for the period 2001-2012, the vegetation index decreased by 25%. If such decrease persists in a long term trend in rainfall reduction, this could lead to a disruption in this ecosystem functioning and the dominant vegetation could become even more xeric or desert-like, bringing serious environmental, social and economical impacts.

Extreme Monsoon Rainfall Signatures Preserved in the Invasive Terrestrial Gastropod Lissachatina fulica

NASA Astrophysics Data System (ADS)

Ghosh, Prosenjit; Rangarajan, Ravi; Thirumalai, Kaustubh; Naggs, Fred

2017-11-01

Indian summer monsoon (ISM) rainfall lasts for a period of 4 months with large variations recorded in terms of rainfall intensity during its period between June and September. Proxy reconstructions of past ISM rainfall variability are required due to the paucity of long instrumental records. However, reconstructing subseasonal rainfall is extremely difficult using conventional hydroclimate proxies due to inadequate sample resolution. Here, we demonstrate the utility of the stable oxygen isotope composition of gastropod shells in reconstructing past rainfall on subseasonal timescales. We present a comparative isotopic study on present day rainwater and stable isotope ratios of precipitate found in the incremental growth bands of giant African land snail Lissachatina fulica (Bowdich) from modern day (2009) and in the historical past (1918). Isotopic signatures present in the growth bands allowed for the identification of ISM rainfall variability in terms of its active and dry spells in the modern as well as past gastropod record. Our results demonstrate the utility of gastropod growth band stable isotope ratios in semiquantitative reconstructions of seasonal rainfall patterns. High resolution climate records extracted from gastropod growth band stable isotopes (museum and archived specimens) can expand the scope for understanding past subseasonal-to-seasonal climate variability.

Detection of major climatic and environmental predictors of liver fluke exposure risk in Ireland using spatial cluster analysis.

PubMed

Selemetas, Nikolaos; de Waal, Theo

2015-04-30

Fasciolosis caused by Fasciola hepatica (liver fluke) can cause significant economic and production losses in dairy cow farms. The aim of the current study was to identify important weather and environmental predictors of the exposure risk to liver fluke by detecting clusters of fasciolosis in Ireland. During autumn 2012, bulk-tank milk samples from 4365 dairy farms were collected throughout Ireland. Using an in-house antibody-detection ELISA, the analysis of BTM samples showed that 83% (n=3602) of dairy farms had been exposed to liver fluke. The Getis-Ord Gi* statistic identified 74 high-risk and 130 low-risk significant (P<0.01) clusters of fasciolosis. The low-risk clusters were mostly located in the southern regions of Ireland, whereas the high-risk clusters were mainly situated in the western part. Several climatic variables (monthly and seasonal mean rainfall and temperatures, total wet days and rain days) and environmental datasets (soil types, enhanced vegetation index and normalised difference vegetation index) were used to investigate dissimilarities in the exposure to liver fluke between clusters. Rainfall, total wet days and rain days, and soil type were the significant classes of climatic and environmental variables explaining the differences between significant clusters. A discriminant function analysis was used to predict the exposure risk to liver fluke using 80% of data for modelling and the remaining subset of 20% for post hoc model validation. The most significant predictors of the model risk function were total rainfall in August and September and total wet days. The risk model presented 100% sensitivity and 91% specificity and an accuracy of 95% correctly classified cases. A risk map of exposure to liver fluke was constructed with higher probability of exposure in western and north-western regions. The results of this study identified differences between clusters of fasciolosis in Ireland regarding climatic and environmental variables and detected significant predictors of the exposure risk to liver fluke. Copyright © 2015 Elsevier B.V. All rights reserved.

Status of ground-water resources at U.S. Navy Support Facility, Diego Garcia; summary of hydrologic and climatic data, January 1993 through March 1995

USGS Publications Warehouse

Torikai, J.D.

1995-01-01

This report contains hydrologic and climatic data that describe the status of ground-water resources at U.S. Navy Support Facility, Diego Garcia. Data presented are from January 1993 through March 1995, although the report focuses on hydrologic events from January through March 1995. Cumulative rainfall for January through March 1995 was about 42 inches which is higher than the mean cumulative rainfall of about 33 inches for the same 3 months in a year. January and February are part of the annual wet season and March is the start of the annual dry season. Rainfall for each month was above average from the respective mean monthly rainfall. Ground- water withdrawal during January through March 1995 averaged 894,600 gallons per day. Withdrawal for the same 3 months in 1994 averaged 999,600 gallons per day. At the end of March 1995, the chloride concentration of the composite water supply was 26 milligrams per liter, well below the 250 milligrams per liter secondary drinking-water standard established by the U.S. Environmental Protection Agency. Chloride concentrations of the composite water supply from January through March 1995 ranged between 19 and 49 milligrams per liter. Chloride concentration of ground water in monitoring wells at Cantonment and Air Operations decreased since November 1994. The deepest monitoring wells show declines in chloride concentration by as much as 4,000 milligrams per liter. A fuel leak at Air Operations caused the shutdown of ten wells in May 1991. Four of the wells resumed pumping for water- supply purposes in April 1992. The remaining six wells are being used to hydraulically contain and divert fuel migration by recirculating about 150,000 gallons of water each day.

Large-scale precipitation estimation using Kalpana-1 IR measurements and its validation using GPCP and GPCC data

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mahesh, C.; Gairola, Rakesh M.

2011-12-01

Large-scale precipitation estimation is very important for climate science because precipitation is a major component of the earth's water and energy cycles. In the present study, the GOES precipitation index technique has been applied to the Kalpana-1 satellite infrared (IR) images of every three-hourly, i.e., of 0000, 0300, 0600,…., 2100 hours UTC, for rainfall estimation as a preparatory to the INSAT-3D. After the temperatures of all the pixels in a grid are known, they are distributed to generate a three-hourly 24-class histogram of brightness temperatures of IR (10.5-12.5 μm) images for a 1.0° × 1.0° latitude/longitude box. The daily, monthly, and seasonal rainfall have been estimated using these three-hourly rain estimates for the entire south-west monsoon period of 2009 in the present study. To investigate the potential of these rainfall estimates, the validation of monthly and seasonal rainfall estimates has been carried out using the Global Precipitation Climatology Project and Global Precipitation Climatology Centre data. The validation results show that the present technique works very well for the large-scale precipitation estimation qualitatively as well as quantitatively. The results also suggest that the simple IR-based estimation technique can be used to estimate rainfall for tropical areas at a larger temporal scale for climatological applications.

Diurnal variations of summer precipitation over the regions east to Tibetan Plateau

NASA Astrophysics Data System (ADS)

Wu, Yang; Huang, Anning; Huang, Danqing; Chen, Fei; Yang, Ben; Zhou, Yang; Fang, Dexian; Zhang, Lujun; Wen, Lijuan

2017-12-01

Based on the hourly gauge-satellite merged precipitation product with the horizontal resolution of 0.1° latitude/longitude during 2008-2014, diurnal variations of the summer precipitation amount (PA), frequency (PF), and intensity (PI) with different duration time over the regions east to Tibetan Plateau have been systematically revealed in this study. Results indicate that the eight typical precipitation diurnal patterns identified by the cluster analysis display pronounced regional features among the plateaus, basins, plains, hilly and coastal areas. The precipitation diurnal cycles are significantly affected by the sub-grid terrain fluctuations. The PA, PF and PI of the total rainfall show much more pronounced double diurnal peaks with the sub-grid topography standard deviation (SD) decreased. Meanwhile, the diurnal peaks of PA and PF (PI) strengthen (weaken) with the sub-grid topography SD enhanced. Over the elevated mountain ranges, southeastern hilly and coastal regions, the PA and PF diurnal patterns of the total rainfall generally show predominant late-afternoon peaks, which are closely associated with the short-duration (≤slant 3 h) rainfall. Along the Tibetan Plateau to its downstream, the diurnal peaks of PA, PF and PI for the total rainfall all exhibit obvious eastward phase time delay mainly due to the diurnal evolutions of long-duration (> 6 h) rainfall. However, the 4-6 h rainfall leads to the eastward phase time delay of the total rainfall along the Taihang Mountains to its downstream. Further mechanism analysis suggests that the midnight to morning diurnal evolution of the long-duration rainfall is closely associated with the diurnal variations of the upward branches of thermally driven mountain-plain solenoids and the water vapor transport associated with the accelerated nocturnal southwesterly winds. The late-afternoon peak of the short-duration PA over the southeastern hilly and coastal regions is ascribed to the strong local thermal convections due to the solar heating in afternoon, while the early-evening peak of the short-duration PA over the elevated mountain ranges is significantly contributed by the upward warm-moist wind from the surrounding low-lying basins or plains.

Vertical Profiles of Latent Heat Release Over the Global Tropics using TRMM Rainfall Products from December 1997 to November 2001

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Starr, David (Technical Monitor)

2002-01-01

NASA Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) derived rainfall information will be used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to November 2000. Rainfall, latent heating and radar reflectivity structures between El Nino (DJF 1997-98) and La Nina (DJF 1998-99) will be examined and compared. The seasonal variation of heating over various geographic locations (i.e., oceanic vs continental, Indian ocean vs west Pacific, Africa vs S. America) will also be analyzed. In addition, the relationship between rainfall, latent heating (maximum heating level), radar reflectivity and SST is examined and will be presented in the meeting. The impact of random error and bias in stratiform percentage estimates from PR on latent heating profiles is studied and will also be presented in the meeting. Additional information is included in the original extended abstract.

From TRMM to GPM: How well can heavy rainfall be detected from space?

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis K.; Pai, D. S.; AghaKouchak, Amir

2016-02-01

In this study, we investigate the capabilities of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and the recently released Integrated Multi-satellitE Retrievals for GPM (IMERG) in detecting and estimating heavy rainfall across India. First, the study analyzes TMPA data products over a 17-year period (1998-2014). While TMPA and reference gauge-based observations show similar mean monthly variations of conditional heavy rainfall events, the multi-satellite product systematically overestimates its inter-annual variations. Categorical as well as volumetric skill scores reveal that TMPA over-detects heavy rainfall events (above 75th percentile of reference data), but it shows reasonable performance in capturing the volume of heavy rain across the country. An initial assessment of the GPM-based multi-satellite IMERG precipitation estimates for the southwest monsoon season shows notable improvements over TMPA in capturing heavy rainfall over India. The recently released IMERG shows promising results to help improve modeling of hydrological extremes (e.g., floods and landslides) using satellite observations.

Modelling rainfall amounts using mixed-gamma model for Kuantan district

NASA Astrophysics Data System (ADS)

Zakaria, Roslinazairimah; Moslim, Nor Hafizah

2017-05-01

An efficient design of flood mitigation and construction of crop growth models depend upon good understanding of the rainfall process and characteristics. Gamma distribution is usually used to model nonzero rainfall amounts. In this study, the mixed-gamma model is applied to accommodate both zero and nonzero rainfall amounts. The mixed-gamma model presented is for the independent case. The formulae of mean and variance are derived for the sum of two and three independent mixed-gamma variables, respectively. Firstly, the gamma distribution is used to model the nonzero rainfall amounts and the parameters of the distribution (shape and scale) are estimated using the maximum likelihood estimation method. Then, the mixed-gamma model is defined for both zero and nonzero rainfall amounts simultaneously. The formulae of mean and variance for the sum of two and three independent mixed-gamma variables derived are tested using the monthly rainfall amounts from rainfall stations within Kuantan district in Pahang Malaysia. Based on the Kolmogorov-Smirnov goodness of fit test, the results demonstrate that the descriptive statistics of the observed sum of rainfall amounts is not significantly different at 5% significance level from the generated sum of independent mixed-gamma variables. The methodology and formulae demonstrated can be applied to find the sum of more than three independent mixed-gamma variables.

Evaluation of satellite and simulated rainfall products for hydrological applications in the Notwane catchment, Botswana

NASA Astrophysics Data System (ADS)

Kenabatho, P. K.; Parida, B. P.; Moalafhi, D. B.

2017-08-01

In semi-arid catchments, hydrological modeling, water resources planning and management are hampered by insufficient spatial rainfall data which is usually derived from limited rain gauge networks. Satellite products are potential candidates to augment the limited spatial rainfall data in these areas. In this paper, the utility of the Tropical Rainfall Measuring Mission (TRMM) product (3B42 v7) is evaluated using data from the Notwane catchment in Botswana. In addition, rainfall simulations obtained from a multi-site stochastic rainfall model based on the generalised linear models (GLMs) were used as additional spatial rainfall estimates. These rainfall products were compared to the observed rainfall data obtained from six (6) rainfall stations available in the catchment for the period 1998-2012. The results show that in general the two approaches produce reasonable spatial rainfall estimates. However, the TRMM products provided better spatial rainfall estimates compared to the GLM rainfall outputs on an average, as more than 90% of the monthly rainfall variations were explained by the TRMM compared to 80% from the GLMs. However, there is still uncertainty associated mainly with limited rainfall stations, and the inability of the two products to capture unusually high rainfall values in the data sets. Despite this observation, rainfall indices computed to further assess the daily rainfall products (i.e. rainfall occurrence and amounts, length of dry spells) were adequately represented by the TRMM data compared to the GLMs. Performance from the GLMs is expected to improve with addition of further rainfall predictors. A combination of these rainfall products allows for reasonable spatial rainfall estimates and temporal (short term future) rainfall simulations from the TRMM and GLMs, respectively. The results have significant implications on water resources planning and management in the catchment which has, for the past three years, been experiencing prolonged droughts as shown by the drying of Gaborone dam (currently at a record low of 1.6% full), which is the main source of water supply to the city of Gaborone and neighbouring townships in Botswana.

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

A Dramatic Regime Shift in Rainfall Predictability Related to the Ningaloo Niño/Niña in the Late 1990s

NASA Astrophysics Data System (ADS)

Doi, T.; Behera, S. K.; Yamagata, T.

2014-12-01

The global warming and the Interdecadal Pacific Oscillation (IPO) started influencing the coastal ocean off Western Australia, leading to a dramatic change in the regional climate predictability.　The warmed ocean started driving rainfall regionally there after the late 1990s. Because of this, rainfall predictability off Western Australia on a seasonal time scale was drastically enhanced in the late 1990s; it is significantly predictable 5 months ahead after the late 1990s. The high prediction skill of the rainfall in recent decades encourages development of an early warning system of Ningaloo Niño/Niña events to mitigate possible societal as well as agricultural impacts in the granary.

Spatial epidemiology of suspected clinical leptospirosis in Sri Lanka.

PubMed

Robertson, C; Nelson, T A; Stephen, C

2012-04-01

Leptospirosis is one of the most widespread zoonoses in the world. A large outbreak of suspected human leptospirosis began in Sri Lanka during 2008. This study investigated spatial variables associated with suspected leptospirosis risk during endemic and outbreak periods. Data were obtained for monthly numbers of reported cases of suspected clinical leptospirosis for 2005-2009 for all of Sri Lanka. Space-time scan statistics were combined with regression modelling to test associations during endemic and outbreak periods. The cross-correlation function was used to test association between rainfall and leptospirosis at four locations. During the endemic period (2005-2007), leptospirosis risk was positively associated with shorter average distance to rivers and with higher percentage of agriculture made up of farms <0·20 hectares. Temporal correlation analysis of suspected leptospirosis cases and rainfall revealed a 2-month lag in rainfall-case association during the baseline period. Outbreak locations in 2008 were characterized by shorter distance to rivers and higher population density. The analysis suggests the possibility of household transmission in densely populated semi-urban villages as a defining characteristic of the outbreak. The role of rainfall in the outbreak remains to be investigated, although analysis here suggests a more complex relationship than simple correlation.

Seasonality of Human Leptospirosis in Reunion Island (Indian Ocean) and Its Association with Meteorological Data

PubMed Central

Desvars, Amélie; Jégo, Sylvaine; Chiroleu, Frédéric; Bourhy, Pascale; Cardinale, Eric; Michault, Alain

2011-01-01

Background Leptospirosis is a disease which occurs worldwide but particularly affects tropical areas. Transmission of the disease is dependent on its excretion by reservoir animals and the presence of moist environment which allows the survival of the bacteria. Methods and Findings A retrospective study was undertaken to describe seasonal patterns of human leptospirosis cases reported by the Centre National de Références des Leptospiroses (CNRL, Pasteur Institute, Paris) between 1998 and 2008, to determine if there was an association between the occurrence of diagnosed cases and rainfall, temperature and global solar radiation (GSR). Meteorological data were recorded in the town of Saint-Benoît (Météo France “Beaufonds-Miria” station), located on the windward (East) coast. Time-series analysis was used to identify the variables that best described and predicted the occurrence of cases of leptospirosis on the island. Six hundred and thirteen cases were reported during the 11-year study period, and 359 cases (58.56%) were diagnosed between February and May. A significant correlation was identified between the number of cases in a given month and the associated cumulated rainfall as well as the mean monthly temperature recorded 2 months prior to diagnosis (r = 0.28 and r = 0.23 respectively). The predictive model includes the number of cases of leptospirosis recorded 1 month prior to diagnosis (b = 0.193), the cumulated monthly rainfall recorded 2 months prior to diagnosis (b = 0.145), the average monthly temperature recorded 0 month prior to diagnosis (b = 3.836), and the average monthly GSR recorded 0 month prior to diagnosis (b = −1.293). Conclusions Leptospirosis has a seasonal distribution in Reunion Island. Meteorological data can be used to predict the occurrence of the disease and our statistical model can help to implement seasonal prevention measures. PMID:21655257

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

A new eco-hydrological distributed model for the analysis of the climate change impact on water resources of Mediterranean ecosystems: the Flumendosa basin case study in Sardinia

NASA Astrophysics Data System (ADS)

Sarigu, Alessio; Cortis, Clorinda; Montaldo, Nicola

2014-05-01

In the last three decades, climate change and human activities increased desertification process in Mediterranean regions, with dramatic consequences for agriculture and water availability. For instance in the Flumendosa reservoir system in Sardinia the average annual runoff in the latter part of the 20th century was less than half the historic average rate, while the precipitation over the Flumendosa basin has decreased, but not at such a drastic rate as the discharge, suggesting a marked non-linear response of discharge to precipitation changes. With the objective of analyzing and looking for the reasons of the historical runoff decrease a new ecohydrological model is developed and tested for the main basin of the Sardinia island, the Flumendosa basin. The eco-hydrological model developed couples a distributed hydrological model and a vegetation dynamic model (VDM). The hydrological model estimates the soil water balance of each basin cell using the force-restore method and the Philips model for runoff estimate. Then it computes runoff propagation along the river network through a modified version of the Muskingum -Cunge method (Mancini et al., 2000; Montaldo et al., 2004). The VDM evaluates the changes in biomass over time from the difference between the rates of biomass production (photosynthesis) and loss (respiration and senescence), and provides LAI, which is then used by the hydrological model for evapotranspiration and rainfall interception estimates. Case study is the Flumendosa basin (Sardinia, basin area of about 1700 km2), which is characterized by a reservoir system that supplies water to the main city of Sardinia, Cagliari. Data are from 42 rain stations (1922-2008 period) over the entire basin and data of runoff are available for the same period. The model has been successfully calibrated for the 1922 - 2008 period for which rain, meteorological data and discharge data are available. We demonstrate that the hystorical strong decrease of runoff is due to a change of rainfall regime, with a decrease of rainfall during the winter months, and a little increase of rainfall during spring-summer months. Indeed, the higher Spring rainfall produced an increase of transpiration mainly, whithout any impact on runoff. Instead the decrease of rainfall in winter months produces a strong decrease of runoff. This trend impacts significantly on monthly runoff production, and, more important, on yearly runoff production, because most of the yearly runoff contribution comes from the winter months. Yearly runoff is more important in Sardinia water resources systems, because runoff is accumulated in dam reservoirs, and is the main water resources of the island. Hence, due to the change of rainfall regime in last decades we are observing a dramatic decrease of runoff, which is reaching to impact on the water availability of the Sardinian major city, Cagliari.

The relationship of lightning activity and short-duation rainfall events during warm seasons over the Beijing metropolitan region

NASA Astrophysics Data System (ADS)

Wu, F.; Cui, X.; Zhang, D. L.; Lin, Q.

2017-12-01

The relationship between lightning activity and rainfall associated with 2925 short-duration rainfall (SDR) events over the Beijing metropolitan region (BMR) is examined during the warm seasons of 2006-2007, using the cloud-to-ground (CG) and intracloud (IC) lightning data from Surveillance et Alerte Foudre par Interférometrie Radioélectrique (SAFIR)-3000 and 5-min rainfall data from automatic weather stations (AWSs). To facilitate the analysis of the rainfall-lightning correlations, the SDR events are categorized into six different intensity grades according to their hourly rainfall rates (HRRs), and an optimal radius of 10 km from individual AWSs for counting their associated lightning flashes is used. Results show that the lightning-rainfall correlations vary significantly with different intensity grades. Weak correlations (R 0.4) are found in the weak SDR events, and 40-50% of the events are no-flash ones. And moderate correlation (R 0.6) are found in the moderate SDR events, and > 10-20% of the events are no-flash ones. In contrast, high correlations (R 0.7) are obtained in the SDHR events, and < 10% of the events are no-flash ones. The results indicate that lightning activity is observed more frequently and correlated more robust with the rainfall in the SDHR events. Significant time lagged correlations between lightning and rainfall are also found. About 80% of the SDR events could reach their highest correlation coefficients when the associated lightning flashes shift at time lags of < 25 min before and after rainfall begins. The percentages of SDR events with CG or total lightning activity preceding, lagging or coinciding with rainfall shows that (i) in about 55% of the SDR events lightning flashes preceded rainfall; (ii) the SDR events with lightning flashes lagging behind rainfall accounted for about 30%; and (iii) the SDR events without any time shifts accounted for the remaining 15%. Better lightning-rainfall correlations can be attained when time lags are incorporated, with the use of total (CG and IC) lightning data. These results appear to have important implications to improving the nowcast of SDHR events.

Water-quality characteristics of urban runoff and estimates of annual loads in the Tampa Bay area, Florida, 1975-80

USGS Publications Warehouse

Lopez, M.A.; Giovannelli, R.F.

1984-01-01

Rainfall, runoff, and water quality data were collected at nine urban watersheds in the Tampa Bay area from 1975 to 1980. Watershed drainage area ranged from 0.34 to 0.45 sq mi. Land use was mixed. Development ranged from a mostly residential watershed with a 19% impervious surface, to a commercial-residential watershed with a 61% impervious surface. Average biochemical oxygen demand concentrations of base flow at two sites and of stormwater runoff at five sites exceeded treated sewage effluent standards. Average coliform concentrations of stormwater runoff at all sites were several orders of magnitude greater than standards for Florida Class III receiving water (for recreation or propagation and management of fish and wildlife). Average concentrations of lead and zinc in stormwater runoff were consistently higher than Class III standards. Stormwater-runoff loads and base-flow concentrations of biochemical oxygen demand, chemical oxygen demand, total nitrogen, total organic nitrogen, total phosphorus, and lead were related to runoff volume, land use, urban development, and antecedent daily rainfall by multiple linear regression. Stormwater-runoff volume was related to pervious area, hydraulically connected impervious surfaces, storm rainfall, and soil-infiltration index. Base-flow daily discharge was related to drainage area and antecedent daily rainfall. The flow regression equations of this report were used to compute 1979 water-year loads of biochemical oxygen demand, chemical oxygen demand, total nitrogen, total organic nitrogen, total phosphorus , and total lead for the nine Tampa Bay area urban watersheds. (Lantz-PTT)

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Validation of TRMM precipitation radar monthly rainfall estimates over Brazil

NASA Astrophysics Data System (ADS)

Franchito, Sergio H.; Rao, V. Brahmananda; Vasques, Ana C.; Santo, Clovis M. E.; Conforte, Jorge C.

2009-01-01

In an attempt to validate the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) over Brazil, TRMM PR estimates are compared with rain gauge station data from Agência Nacional de Energia Elétrica (ANEEL). The analysis is conducted on a seasonal basis and considers five geographic regions with different precipitation regimes. The results showed that TRMM PR seasonal rainfall is well correlated with ANEEL rainfall (correlation coefficients are significant at the 99% confidence level) over most of Brazil. The random and systematic errors of TRMM PR are sensitive to seasonal and regional differences. During December to February and March to May, TRMM PR rainfall is reliable over Brazil. In June to August (September to November) TRMM PR estimates are only reliable in the Amazonian and southern (Amazonian and southeastern) regions. In the other regions the relative RMS errors are larger than 50%, indicating that the random errors are high.

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.

Phlebotomus argentipes seasonal patterns in India and Nepal.

PubMed

Picado, Albert; Das, Murari Lal; Kumar, Vijay; Dinesh, Diwakar S; Rijal, Suman; Singh, Shri P; Das, Pradeep; Coosemans, Marc; Boelaert, Marleen; Davies, Clive

2010-03-01

The current control of Phebotomus argentipes (Annandale and Brunetti), the vector of Leishmania donovani (Laveran and Mesnil), on the Indian subcontinent is base on indoor residual spraying. The efficacy of this method depends, among other factors, on the timing and number of spraying rounds, which depend on the P. argentipes seasonality. To describe P. argentipes' seasonal patterns, six visceral leishmaniasis (VL) endemic villages, three in Muzaffarpur and three in Sunsari districts in India and Nepal, respectively, were selected based on accessibility and VL incidence. Ten houses per cluster with the highest P. argentipes density were monitored monthly for 15-16 mo using Center for Disease Control and Prevention light traps. Minimum and maximum temperature and rainfall data for the months January 2006 through December 2007 were collected from the nearest available weather stations. Backwards stepwise regression was used to generate the minimal adequate model for explaining the monthly variation in P. argentipes populations. The seasonality of P. argentipes is similar in India and Nepal, with two annual density peaks around May and October. Monthly P. argentipes density is positively associated with temperature and negatively associated with rainfall in both study sites. The multivariate climate model explained 57% of the monthly vectorial abundance. Vector control programs against P. argentipes (i.e., indoor residual spraying) should take into account the seasonal described here when implementing and monitoring interventions. Monitoring simple meteorological variables (i.e., temperature, rainfall) may allow prediction of VL epidemics on the Indian subcontinent.

[Runoff Pollution Experiments of Paddy Fields Under Different Irrigation Patterns].

PubMed

Zhou, Jing-wen; Su, Bao-lin; Huang, Ning-bo; Guan, Yu-tang; Zhao, Kun

2016-03-15

To study runoff and non-point source pollution of paddy fields and to provide a scientific basis for agricultural water management of paddy fields, paddy plots in the Jintan City and the Liyang City were chosen for experiments on non-point source pollution, and flood irrigation and intermittent irrigation patterns were adopted in this research. The surface water level and rainfall were observed during the growing season of paddies, and the runoff amount from paddy plots and loads of total nitrogen (TN) and total phosphorus (TP) were calculated by different methods. The results showed that only five rain events of totally 27 rainfalls and one artificially drainage formed non-point source pollution from flood irrigated paddy plot, which resulted in a TN export coefficient of 49.4 kg · hm⁻² and a TP export coefficient of 1.0 kg · hm⁻². No any runoff event occurred from the paddy plot with intermittent irrigation even in the case of maximum rainfall of 95.1 mm. Runoff from paddy fields was affected by water demands of paddies and irrigation or drainage management, which was directly correlated to surface water level, rainfall amount and the lowest ridge height of outlets. Compared with the flood irrigation, intermittent irrigation could significantly reduce non-point source pollution caused by rainfall or artificial drainage.

Tree-Ring Reconstruction of Wet Season Rainfall Totals in the Amazon

NASA Astrophysics Data System (ADS)

Stahle, D. W.; Lopez, L.; Granato-Souza, D.; Barbosa, A. C. M. C.; Torbenson, M.; Villalba, R.; Pereira, G. D. A.; Feng, S.; Schongart, J.; Cook, E. R.

2017-12-01

The Amazon Basin is a globally important center of deep atmospheric convection, energy balance, and biodiversity, but only a handful of weather stations in this vast Basin have recorded rainfall measurements for at least 50 years. The available rainfall and river level observations suggest that the hydrologic cycle in the Amazon may have become amplified in the last 40-years, with more extreme rainfall and streamflow seasonality, deeper droughts, and more severe flooding. These changes in the largest hydrological system on earth may be early evidence of the expected consequences of anthropogenic climate change and deforestation in the coming century. Placing these observed and simulated changes in the context of natural climate variability during the late Holocene is a significant challenge for high-resolution paleoclimatology. We have developed exactly dated and well-replicated annual tree-ring chronologies from two native Amazonian tree species (Cedrela sp and Centrolobium microchaete). These moisture sensitive chronologies have been used to compute two reconstructions of wet season rainfall totals, one in the southern Amazon based on Centrolobium and another in the eastern equatorial Amazon using Cedrela. Both reconstructions are over 200-years long and extend the available instrumental observations in each region by over 150-years. These reconstructions are well correlated with the same regional and large-scale climate dynamics that govern the inter-annual variability of the instrumental wet season rainfall totals. Increased multi-decadal variability is reconstructed after 1950 with the Centrolobium chronologies in the southern Amazon. The Cedrela reconstruction from the eastern Amazon exhibits changes in the spatial pattern of correlation with regional rainfall stations and the large-scale sea surface temperature field after 1990 that may be consistent with recent changes in the mean position of the Inter-Tropical Convergence Zone in March over the western Atlantic and South American sector.

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.

Landsliding and flooding event triggered by heavy rains in the Rize region

NASA Astrophysics Data System (ADS)

Yalcin, Ali; Kavurmaci, M. Murat

2013-04-01

Rize province has been significantly damaged by frequent landslides and floods which are caused by severe rainfalls and result in many casualties. The area is prone to landslides because of the climate conditions, geologic, and land cover characteristics of the region. The most recent landslide occurred on August 26, 2010 in Gundogdu town. The landslides have caused large numbers of casualties and huge economic losses in the region. Thirteen people died, twenty houses collapsed, more than a hundred houses damaged, and one hundred fifty vehicles were damaged in the Gundogdu landslide. Flood event is often seen in the region of Rize, due to continuous rainfall. Floods cause huge loss of life and property in this region. Rainfall is the most frequent landslide-triggering factor in East Black Sea region, Turkey, especially Rize region. Rize is the rainiest city of Turkey. Total annual precipitation is over 2300 mm, and precipitation is equally distributed in each month. However, in August 26, 166.5 mm precipitation rained within 24 hours in the region and this rainstorm caused great damage. The intensity rainfall periods were become as an indicator of landslide activity. It is very important that the presence of suitable lithologic units for occurring landslides. There are appropriate materials to contributed constitution of landslides in the study area; completely weathered dacite. In addition, intensity land cover types as tea plantations have been blocked surface flows and rainfall is able to quickly penetrate into the soil through open tension cracks that appear in the landslide head and in stretching zones. According to the results of the analysis, the study area has been overlaid tea garden 70 % percentage approximately. Furthermore, the landslide risks have increased by devastation of land cover in this region. In this region, over-steepened slopes, slope saturation in areas of heavy rainfall, and removal of slope vegetation can also increase landslide potential. The combination of all these effects have been affected to the settlement areas and living people in the study area. In this study, the effects of all the factors were separately examined on landslides.

Water Budget of East Maui, Hawaii

USGS Publications Warehouse

Shade, Patricia J.

1999-01-01

Ground-water recharge is estimated from six monthly water budgets calculated using long-term average rainfall and streamflow data, estimated pan-evaporation and fog-drip data, and soil characteristics. The water-budget components are defined seasonally, through the use of monthly data, and spatially by broad climatic and geohydrologic areas, through the use of a geographic information system model. The long-term average water budget for east Maui was estimated for natural land-use conditions. The average rainfall, fog-drip, runoff, evapotranspiration, and ground-water recharge volumes for the east Maui study area are 2,246 Mgal/d, 323 Mgal/d, 771 Mgal/d, 735 Mgal/d, and 1,064 Mgal/d, respectively.

Climate Assessment for 1997.

NASA Astrophysics Data System (ADS)

Bell, Gerald D.; Halpert, Michael S.

1998-05-01

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

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.

Factors governing the total rainfall yield from continental convective clouds

NASA Technical Reports Server (NTRS)

Rosenfeld, Daniel; Gagin, Abraham

1989-01-01

Several important factors that govern the total rainfall from continental convective clouds were investigated by tracking thousands of convective cells in Israel and South Africa. The rainfall volume yield (Rvol) of the individual cells that build convective rain systems has been shown to depend mainly on the cloud-top height. There is, however, considerable variability in this relationship. The following factors that influence the Rvol were parameterized and quantitatively analyzed: (1) cloud base temperature, (2)atmospheric instability, and (3) the extent of isolation of the cell. It is also shown that a strong low level forcing increases the duration of Rvol of clouds reaching the same vertical extent.

Population dynamics of earthworms in relation to soil physico-chemical parameters in agroforestry systems of Mizoram, India.

PubMed

Lalthanzara, H; Ramanujam, S N; Jha, L K

2011-09-01

Earthworm population dynamics was studied in two agroforestry systems in the tropical hilly terrain of Mizoram, north-east India, over a period of 24 months, from July 2002 to June 2004. Two sites of agroforestry situated at Sakawrtuichhun (SKT) and Pachhunga University College (PUC) campus, Aizawl, having pineapple as the main crop, were selected for detail studies on population dynamics. Five of the total twelve species of earthworm reported from the state were recorded in the study sites. The density of earthworm ranged from 6 to 243 ind.m(-2) and biomass from 3.2 - 677.64 g.m(-2) in SKT. Comparatively the density and biomass in PUC, which is at relatively higher altitude were lowerwith a range of 0 to 176 ind.m(-2) and biomass from 0 - 391.36 g.m(-2) respectively. Population dynamics of earthworm was significantly correlated with rainfall and physical characters of the soil. Earthworm biomass was significantly affected by rainfall and moisture content of the soil. The influence of chemical factors was relatively less.

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.

Effects of Increased Horizontal Resolution on Simulation of the North American Monsoon in the NCAR CAM3: An Evaluation based on Surface, Satellite, and Reanalysis Data

NASA Astrophysics Data System (ADS)

Collier, J. C.; Zhang, G. J.

2006-05-01

Simulation of the North American monsoon system by the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM3) is evaluated in its sensitivity to increasing horizontal resolution. For two resolutions, T42 and T85, rainfall is compared to TRMM satellite-derived and surface gauge-based rainfall rates over the U.S. and northern Mexico as well as rainfall accumulations in gauges of the North American Monsoon Experiment (NAME) Enhanced Rain Gauge Network (NERN) in the Sierra Madre Occidental mountains. Simulated upper-tropospheric mass and wind fields are compared to those from NCEP-NCAR reanalyses. The comparison presented herein demonstrates that tropospheric motions associated with the North American monsoon system are sensitive to increasing the horizontal resolution of the model. An increase in resolution from T42 to T85 results in changes to a region of large-scale mid-tropospheric descent found north and east of the monsoon anticyclone. Relative to its simulation at T42, this region extends farther south and west at T85. Additionally, at T85, the subsidence is stronger. Consistent with the differences in large-scale descent, the T85 simulation of CAM3 is anomalously dry over Texas and northeastern Mexico during the peak monsoon months. Meanwhile, the geographic distribution of rainfall over the Sierra Madre Occidental region of Mexico is more satisfactorily simulated at T85 than at T42 for July and August. Moisture import into this region is greater at T85 than at T42 during these months. A focused study of the Sierra Madre Occidental region in particular shows that, in the regional average sense, the timing of the peak of the monsoon is relatively insensitive to the horizontal resolution of the model, while a phase bias in the diurnal cycle of monsoon-season precipitation is somewhat reduced in the higher-resolution run. At both resolutions, CAM3 poorly simulates the month-to-month evolution of monsoon rainfall over extreme northwestern Mexico and Arizona, though biases are considerably improved at T85.

Rainfall recharge estimation on a nation-wide scale using satellite information in New Zealand

NASA Astrophysics Data System (ADS)

Westerhoff, Rogier; White, Paul; Moore, Catherine

2015-04-01

Models of rainfall recharge to groundwater are challenged by the need to combine uncertain estimates of rainfall, evapotranspiration, terrain slope, and unsaturated zone parameters (e.g., soil drainage and hydraulic conductivity of the subsurface). Therefore, rainfall recharge is easiest to estimate on a local scale in well-drained plains, where it is known that rainfall directly recharges groundwater. In New Zealand, this simplified approach works in the policy framework of regional councils, who manage water allocation at the aquifer and sub-catchment scales. However, a consistent overview of rainfall recharge is difficult to obtain at catchment and national scale: in addition to data uncertainties, data formats are inconsistent between catchments; the density of ground observations, where these exist, differs across regions; each region typically uses different local models for estimating recharge components; and different methods and ground observations are used for calibration and validation of these models. The research described in this paper therefore presents a nation-wide approach to estimate rainfall recharge in New Zealand. The method used is a soil water balance approach, with input data from national rainfall and soil and geology databases. Satellite data (i.e., evapotranspiration, soil moisture, and terrain) aid in the improved calculation of rainfall recharge, especially in data-sparse areas. A first version of the model has been implemented on a 1 km x 1 km and monthly scale between 2000 and 2013. A further version will include a quantification of recharge estimate uncertainty: with both "top down" input error propagation methods and catchment-wide "bottom up" assessments of integrated uncertainty being adopted. Using one nation-wide methodology opens up new possibilities: it can, for example, help in more consistent estimation of water budgets, groundwater fluxes, or other hydrological parameters. Since recharge is estimated for the entire land surface, and not only the known aquifers, the model also identifies other zones that could potentially recharge aquifers, including large areas (e.g., mountains) that are currently regarded as impervious. The resulting rainfall recharge data have also been downscaled in a 200 m x 200 m calculation of a national monthly water table. This will lead to better estimation of hydraulic conductivity, which holds considerable potential for further research in unconfined aquifers in New Zealand.

Atmospheric precursors and assessment of the extreme rainfall responsible for the Madeira flashfloods on 20 February 2010

NASA Astrophysics Data System (ADS)

Fragoso, M.; Trigo, R. M.; Lopes, S.; Lopes, A.; Magro, C.

2010-09-01

On February 20, 2010, the Madeira island (Portugal) was hit by torrential rains that triggered catastrophic flash floods, accounting for 43 deaths and 8 missing people. The regional authorities estimated that the total losses exceeded 1 billion of euros resulting from the destructive damages, which were very harmful in Funchal, the capital of the region, where 22 persons died. This paper aims to analyse and discuss two main issues related with the exceptionality of this event. The first part deals with the atmospheric context associated with the rainfall episode, which occurred embedded in a very rainy winter season on this subtropical Atlantic region. Large scale atmospheric controls will be analysed, taking into consideration the low phase conditions of the North Atlantic Oscillation (NAO) that remained overwhelmingly negative between late November 2009 and early April 2010. The role of positive sea surface temperatures anomalies in the subtropical Atlantic region during the prevous weeks will be also investigated. Furthermore, the discussion will be focused on the meteorological precursors of the 20 February rainstorm, using synoptic weather charts and sub-daily reanalysis data and analysing appropriate variables, such as, SLP, geopotential height, instability indices, precipitable water, and others atmospheric parameters. The second section of this work is devoted to the evaluation of the exceptionality of the rainfall records related with this event. In Funchal (Observatory station), the precipitation amount registered during February 2010 was 458 mm, exceeding by seven times (!) the average monthly precipitation, constituting the new absolute record, since 1865, when this meteorological station began its activity. The daily rainfall on 20 February in the same location was 132 mm, which is the highest daily amount since 1920. Return periods of this daily amount will be estimated for the two stations with the longest period available of daily precipitation, Funchal Observatory and mountain peek Areeiro. Daily, sub-daily, hourly and sub-hourly rainfall data will be also analysed using the available information from the modern automated raingauge network of the island. Among the several notable rainfall amounts, it should be highlighted the daily amounts between 300 and 350 mm reached in different locations on the southern flanks of the mountains above the 500 m height and six hours rainfall exceeding 200 mm at the upper parts of the slopes in the Funchal area.

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

NASA Astrophysics Data System (ADS)

Longobardi, Antonia; Diodato, Nazzareno; Mobilia, Mirka

2017-04-01

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

How Habitat Change and Rainfall Affect Dung Beetle Diversity in Caatinga, a Brazilian Semi-Arid Ecosystem

PubMed Central

Liberal, Carolina Nunes; de Farias, Ângela Maria Isidro; Meiado, Marcos Vinicius; Filgueiras, Bruno K. C.; Iannuzzi, Luciana

2011-01-01

The aim of the present study was to evaluate how dung beetle communities respond to both environment and rainfall in the Caatinga, a semi-arid ecosystem in northeastern Brazil. The communities were sampled monthly from May 2006 to April 2007 using pitfall traps baited with human feces in two environments denominated “land use area” and “undisturbed area.” Abundance and species richness were compared between the two environments and two seasons (dry and wet season) using a generalized linear model with a Poisson error distribution. Diversity was compared between the two environments (land use area and undisturbed area) and seasons (dry and wet) using the Two-Way ANOVA test. Non-metric multidimensional scaling was performed on the resemblance matrix of Bray-Curtis distances (with 1000 random restarts) to determine whether disturbance affected the abundance and species composition of the dung beetle communities. Spearman's correlation coefficient was used to determine whether rainfall was correlated with abundance and species richness. A total of 1097 specimens belonging to 13 species were collected. The most abundant and frequent species was Dichotomius geminatus Arrow (Coleoptera: Scarabaeidae). The environment exerted an influence over abundance. Abundance and diversity were affected by season, with an increase in abundance at the beginning of the wet season. The correlation coefficient values were high and significant for abundance and species richness, which were both correlated to rainfall. In conclusion, the restriction of species to some environments demonstrates the need to preserve these areas in order to avoid possible local extinction. Therefore, in extremely seasonable environments, such as the Caatinga, seasonal variation strongly affects dung beetle communities. PMID:22224924

How habitat change and rainfall affect dung beetle diversity in Caatinga, a Brazilian semi-arid ecosystem.

PubMed

Liberal, Carolina Nunes; de Farias, Ângela Maria Isidro; Meiado, Marcos Vinicius; Filgueiras, Bruno K C; Iannuzzi, Luciana

2011-01-01

The aim of the present study was to evaluate how dung beetle communities respond to both environment and rainfall in the Caatinga, a semi-arid ecosystem in northeastern Brazil. The communities were sampled monthly from May 2006 to April 2007 using pitfall traps baited with human feces in two environments denominated "land use area" and "undisturbed area." Abundance and species richness were compared between the two environments and two seasons (dry and wet season) using a generalized linear model with a Poisson error distribution. Diversity was compared between the two environments (land use area and undisturbed area) and seasons (dry and wet) using the Two-Way ANOVA test. Non-metric multidimensional scaling was performed on the resemblance matrix of Bray-Curtis distances (with 1000 random restarts) to determine whether disturbance affected the abundance and species composition of the dung beetle communities. Spearman's correlation coefficient was used to determine whether rainfall was correlated with abundance and species richness. A total of 1097 specimens belonging to 13 species were collected. The most abundant and frequent species was Dichotomius geminatus Arrow (Coleoptera: Scarabaeidae). The environment exerted an influence over abundance. Abundance and diversity were affected by season, with an increase in abundance at the beginning of the wet season. The correlation coefficient values were high and significant for abundance and species richness, which were both correlated to rainfall. In conclusion, the restriction of species to some environments demonstrates the need to preserve these areas in order to avoid possible local extinction. Therefore, in extremely seasonable environments, such as the Caatinga, seasonal variation strongly affects dung beetle communities.

The Potential Financial Costs of Climate Change on Health of Urban and Rural Citizens: A Case Study of Vibrio cholerae Infections at Bukavu Town, South Kivu Province, Eastern of Democratic Republic of Congo.

PubMed

Munyuli, Mb Théodore; Kavuvu, J-M Mbaka; Mulinganya, Guy; Bwinja, G Mulinganya

2013-01-01

Cholera epidemics have a recorded history in eastern Congo dating to 1971. A study was conducted to find out the linkage between climate variability/change and cholera outbreak and to assess the related economic cost in the management of cholera in Congo. This study integrates historical data (20 years) on temperature and rainfall with the burden of disease from cholera in South-Kivu province, eastern Congo. Analyses of precipitation and temperatures characteristics in South-Kivu provinces showed that cholera epidemics are closely associated with climatic factors variability. Peaks in Cholera new cases were in synchrony with peaks in rainfalls. Cholera infection cases declined significantly (P<0.05) with the rise in the average temperature. The monthly number of new Cholera cases oscillated between 5 and 450. For every rise of the average temperature by 0.35 °C to 0.75 °C degree Celsius, and for every change in the rainfall variability by 10-19%, it is likely cholera infection risks will increase by 17 to 25%. The medical cost of treatment of Cholera case infection was found to be of US$50 to 250 per capita. The total costs of Cholera attributable to climate change were found to fall in the range of 4 to 8% of the per capita in annual income in Bukavu town. It is likely that high rainfall favor multiplication of the bacteria and contamination of water sources by the bacteria (Vibrio cholerae). The consumption of polluted water, promiscuity, population density and lack of hygiene are determinants favoring spread and infection of the bacteria among human beings living in over-crowded environments.

Evaluation of remote hydrologic data-acquisition systems, west-central Florida

USGS Publications Warehouse

Turner, J.F.; Woodham, W.M.

1980-01-01

The study provides an evaluation of the hydrologic applications of a land-line and two satellite data-relay systems operated during 1977-78 in the Southwest Florida Water Management District. These systems were tested to evaluate operational and reliability characteristics. Telephone lines were used to relay data in the land-line system, and the Geostationary Operational Environmental Satellite (GOES) and Land satellite (Landsat) were used in the satellite system. The land-line system was tested for 15 months at a streamflow site. Accurate data were obtained 94% of the time during the test period. Data losses were attributed to telephone-line interference, low-battery voltage, and vandalism. The GOES system was tested at a rainfall site for 17 months. During this period, 79% of the transmissions received from the station were relayed by the GOES system to the U.S. Geological Survey computer, resulting in successful processing of 88% of all possible rainfall observations. On the average, seven data transmissions were completed each day. The Landsat system was tested at a rainfall site for about 17 months and for about 8 months at a streamflow site. During these periods of operation, only about 2% of all data observations for the stations were successfully relayed by the Landsat system to the U.S. Geological Survey computer. An average of about three data transmissions was completed each day for each site. (USGS).

Landslide database dominated by rainfall triggered events

NASA Astrophysics Data System (ADS)

Devoli, G.; Strauch, W.; Álvarez, A.

2009-04-01

A digital landslide database has been created for Nicaragua to provide the scientific community and national authorities with a tool for landslide hazard assessment. Valuable information on landslide events has been obtained from a great variety of sources. On the basis of the data stored in the database, preliminary analyses performed at national scale aimed to characterize landslides in terms of spatial and temporal distribution, types of slope movements, triggering mechanisms, number of casualties and damage to infrastructure. A total of about 17000 events spatially distributed in mountainous and volcanic terrains have been collected in the database. The events are temporally distributed between 1826 and 2003, but a large number of the records (62% of the total number) occurred during the disastrous Hurricane Mitch in October 1998. The results showed that debris flows are the most common types of landslides recorded in the database (66% of the total amount), but other types, including rockfalls and slides, have also been identified. Rainfall, also associated with tropical cyclones, is the most frequent triggering mechanism of landslides in Nicaragua, but also seismic and volcanic activities are important triggers or, especially, the combination of one of them with rainfall. Rainfall has caused all types of failures, but debris flows and translational shallow slides are more frequent types. Earthquakes have most frequently triggered rockfalls and slides, while volcanic eruptions rockfalls and debris flows. Landslides triggered by rainfall were limited in time to the wet season that lasts from May to October and an increase in the number of events is observed during the months of September and October, which is in accord with the period of the rainy season in the Pacific and Northern and Central regions and when the country has the highest probability of being impacted by hurricanes. Both Atlantic and Pacific tropical cyclones have triggered landslides. At the medium scale, the influence of topographic and lithologic parameters on the occurrence of landslides was also analyzed and the physical characterization of landslides was done to better understand the landslide dynamics and run-out distances in both volcanic and non-volcanic areas. Data from fairly well documented events in Nicaragua were compared with other similar events in Central America and elsewhere and treated statistically to search for possible correlations and empirical relationships to predict run-out distances for different types of landslides, knowing the height of fall or the volume. The empirical relationships showed that debris flows and debris avalanches at volcanoes have the highest mobility and reach longer distances compared to other types of landslides. Because of their characteristics and downstream behaviour (long run-out distances and large volumes) both types of landslides have produced the highest number of victims in the country being the most dangerous to life and property.

The Effects of More Extreme Rainfall Patterns on Infiltration and Nutrient Losses in Agricultural Soils

NASA Astrophysics Data System (ADS)

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

2015-12-01

In the coming century, the proportion of total rainfall that falls in heavy storm events is expected to increase in many areas, especially in the US Midwest, a major agricultural region. These changes in rainfall patterns may have consequences for hydrologic flow and nutrient losses, especially in agricultural soils, with potentially negative consequences for receiving ground- and surface waters. We used a tracer experiment to examine how more extreme rainfall patterns may affect the movement of water and solutes through an agricultural soil profile in the upper Midwest, and to what extent tillage may moderate these effects. Two rainfall patterns were created with 5m x 5m rainout shelters at the Kellogg Biological Station LTER site in replicated plots with either conventional tillage or no-till management. Control rainfall treatments received water 3x per week, and extreme rainfall treatments received the same total amount of water but once every two weeks, to simulate less frequent but larger storms. In April 2015, potassium bromide (KBr) was added as a conservative tracer of water flow to all plots, and Br- concentrations in soil water at 1.2m depth were measured weekly from April through July. Soil water Br- concentrations increased and peaked more quickly under the extreme rainfall treatment, suggesting increased infiltration and solute transfer to depth compared to soils exposed to control rainfall patterns. Soil water Br- also increased and peaked more quickly in no-till than in conventional tillage treatments, indicating differences in flow paths between management systems. Soil moisture measured every 15 minutes at 10, 40, and 100cm depths corroborates tracer experiment results: rainfall events simulated in extreme rainfall treatments led to large increases in deep soil moisture, while the smaller rainfall events simulated under control conditions did not. Deep soil moisture in no-till treatments also increased sooner after water application as compared to in conventional soils. Our results suggest that exposure to more extreme rainfall patterns will likely increase infiltration depth and nutrient losses in agricultural soils. In particular, soils under no-till management, which leads to development of preferential flow paths, may be particularly vulnerable to vertical nutrient losses.

Hydrological Components of a Young Loblolly Pine Plantation on a Sandy Soil with Estimates of Water Use and Loss

Treesearch

Deborah A. Abrahamson; Phillip M. Dougherty; Stanley J. Zarnoch

1998-01-01

Fertilizer and irrigation treatments were applied in a 7- to l0-year-old loblolly pine (Pinus taeda L.) plantation on a sandy soil near Laurinburg, North Carolina. Rainfall, throughfall, stemflow, and soil water content were measured throughout the study period. Monthly interception losses ranged from 4 to 15% of rainfall. Stemflow ranged from 0.2...

Tropical Cyclones Feed More Heavy Rain in a Warmer Climate

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Geo-statistical model of Rainfall erosivity by using high temporal resolution precipitation data in Europe

NASA Astrophysics Data System (ADS)

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

2015-04-01

Rainfall erosivity (R-factor) is among the 6 input factors in estimating soil erosion risk by using the empirical Revised Universal Soil Loss Equation (RUSLE). R-factor is a driving force for soil erosion modelling and potentially can be used in flood risk assessments, landslides susceptibility, post-fire damage assessment, application of agricultural management practices and climate change modelling. The rainfall erosivity is extremely difficult to model at large scale (national, European) due to lack of high temporal resolution precipitation data which cover long-time series. In most cases, R-factor is estimated based on empirical equations which take into account precipitation volume. The Rainfall Erosivity Database on the European Scale (REDES) is the output of an extensive data collection of high resolution precipitation data in the 28 Member States of the European Union plus Switzerland taking place during 2013-2014 in collaboration with national meteorological/environmental services. Due to different temporal resolutions of the data (5, 10, 15, 30, 60 minutes), conversion equations have been applied in order to homogenise the database at 30-minutes interval. The 1,541 stations included in REDES have been interpolated using the Gaussian Process Regression (GPR) model using as covariates the climatic data (monthly precipitation, monthly temperature, wettest/driest month) from WorldClim Database, Digital Elevation Model and latitude/longitude. GPR has been selected among other candidate models (GAM, Regression Kriging) due the best performance both in cross validation (R2=0.63) and in fitting dataset (R2=0.72). The highest uncertainty has been noticed in North-western Scotland, North Sweden and Finland due to limited number of stations in REDES. Also, in highlands such as Alpine arch and Pyrenees the diversity of environmental features forced relatively high uncertainty. The rainfall erosivity map of Europe available at 500m resolution plus the standard error and the erosivity density (Rainfall erosivity per mm of precipitation) are available in the European Soil Data Centre (ESDAC). The highest erosivity has been found in the mediterrean countries (Italy, Western Greece, Spain, Northern Portugal), South Austria, Slovenia, Croatia and Western United Kingdom.

Rain-fed fig yield as affected by rainfall distribution

NASA Astrophysics Data System (ADS)

Bagheri, Ensieh; Sepaskhah, Ali Reza

2014-08-01

Variable annual rainfall and its uneven distribution are the major uncontrolled inputs in rain-fed fig production and possibly the main cause of yield fluctuation in Istahban region of Fars Province, I.R. of Iran. This introduces a considerable risk in rain-fed fig production. The objective of this study was to find relationships between seasonal rainfall distribution and rain-fed fig production in Istahban region to determine the critical rainfall periods for rain-fed fig production and supplementary irrigation water application. Further, economic analysis for rain-fed fig production was considered in this region to control the risk of production. It is concluded that the monthly, seasonal and annual rainfall indices are able to show the effects of rainfall and its distribution on the rain-fed fig yield. Fig yield with frequent occurrence of 80 % is 374 kg ha-1. The internal rates of return for interest rate of 4, 8 and 12 % are 21, 58 and 146 %, respectively, that are economically feasible. It is concluded that the rainfall in spring especially in April and in December has negatively affected fig yield due to its interference with the life cycle of Blastophaga bees for pollination. Further, it is concluded that when the rainfall is limited, supplementary irrigation can be scheduled in March.

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.

Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

NASA Astrophysics Data System (ADS)

Varikoden, Hamza; Revadekar, J. V.

2018-03-01

Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.

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.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

Technical Report Series on Global Modeling and Data Assimilation. Volume 12; Comparison of Satellite Global Rainfall Algorithms

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Chang, Alfred T. C.; Chiu, Long S.

1997-01-01

Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates.

An interdecadal regime shift in rainfall predictability related to the Ningaloo Nino in the late 1990s

NASA Astrophysics Data System (ADS)

Doi, T.; Behera, S. K.; Yamagata, T.

2016-02-01

The global warming and the Interdecadal Pacific Oscillation (IPO) started influencing the coastal ocean off Western Australia, leading to a dramatic change in the regional climate predictability. The warmer ocean started driving rainfall variability regionally there after the late 1990s. Because of this, rainfall predictability near the coastal region of Western Australia on a seasonal time scale was drastically enhanced in the late 1990s; it is significantly predictable 5 months ahead after the late 1990s. The high prediction skill of the rainfall in recent decades is very encouraging and would help to develop an early warning system of Ningaloo Nino/Nina events to mitigate possible societal as well as agricultural impacts in the granary of Western Australia.

An interdecadal regime shift in rainfall predictability related to the Ningaloo Niño in the late 1990s

NASA Astrophysics Data System (ADS)

Doi, Takeshi; Behera, Swadhin K.; Yamagata, Toshio

2015-02-01

The global warming and the Interdecadal Pacific Oscillation (IPO) started influencing the coastal ocean off Western Australia, leading to a dramatic change in the regional climate predictability. The warmer ocean started driving rainfall variability regionally there after the late 1990s. Because of this, rainfall predictability near the coastal region of Western Australia on a seasonal time scale was drastically enhanced in the late 1990s; it is significantly predictable 5 months ahead after the late 1990s. The high prediction skill of the rainfall in recent decades is very encouraging and would help to develop an early warning system of Ningaloo Niño/Niña events to mitigate possible societal as well as agricultural impacts in the granary of Western Australia.

Precipitation Processes Derived from TRMM Satellite Data, Cloud Resolving Model and Field Campaigns

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Lang, S.; Simpson, J.; Meneghini, R.; Halverson, J.; Johnson, R.; Adler, R.; Einaudi, Franco (Technical Monitor)

2001-01-01

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. Present large-scale weather and climate models can simulate cloud latent heat release only crudely thus reducing their confidence in predictions on both global and regional scales. In this paper, NASA Tropical Rainfall Measuring (TRMM) precipitation radar (PR) derived rainfall information and the Goddard Convective and Stratiform Heating (CSH) algorithm used to estimate the four-dimensional structure of global monthly latent heating and rainfall profiles over the global tropics from December 1997 to October 2000. Rainfall latent heating and radar reflectively structure between ENSO (1997-1998 winter) and non-ENSO (1998-1999 winter) periods are examined and compared. The seasonal variation of heating over various geographic locations (i.e. Indian ocean vs west Pacific; Africa vs S. America) are also analyzed. In addition, the relationship between rainfall latent heating maximum heating level), radar reflectively and SST are examined.

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

PubMed

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

2012-06-15

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

Rainfall estimation from microwave links in São Paulo, Brazil.

NASA Astrophysics Data System (ADS)

Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

2017-04-01

Rainfall estimation from microwave link networks has been successfully demonstrated in countries such as the Netherlands, Israel and Germany. The path-averaged rainfall intensity can be computed from the signal attenuation between cell phone towers. Although this technique is still in development, it offers great opportunities to retrieve rainfall rates at high spatiotemporal resolutions very close to the ground surface. High spatiotemporal resolutions and closer-to-ground measurements are highly appreciated, especially in urban catchments where high-impact events such as flash-floods develop in short time scales. We evaluate here this rainfall measurement technique for a tropical climate, something that has hardly been done previously. This is highly relevant since many countries with few surface rainfall observations are located in the tropics. The test-bed is the Brazilian city of São Paulo. The performance of 16 microwave links was evaluated, from a network of 200 links, for the last 3 months of 2014. The open software package RAINLINK was employed to obtain link rainfall estimates. The evaluation was done through a dense automatic gauge network. Results are promising and encouraging, especially for short links for which a high correlation (> 0.9) and a low bias (< 5%) were obtained.

Recharge signal identification based on groundwater level observations.

PubMed

Yu, Hwa-Lung; Chu, Hone-Jay

2012-10-01

This study applied a method of the rotated empirical orthogonal functions to directly decompose the space-time groundwater level variations and determine the potential recharge zones by investigating the correlation between the identified groundwater signals and the observed local rainfall records. The approach is used to analyze the spatiotemporal process of piezometric heads estimated by Bayesian maximum entropy method from monthly observations of 45 wells in 1999-2007 located in the Pingtung Plain of Taiwan. From the results, the primary potential recharge area is located at the proximal fan areas where the recharge process accounts for 88% of the spatiotemporal variations of piezometric heads in the study area. The decomposition of groundwater levels associated with rainfall can provide information on the recharge process since rainfall is an important contributor to groundwater recharge in semi-arid regions. Correlation analysis shows that the identified recharge closely associates with the temporal variation of the local precipitation with a delay of 1-2 months in the study area.

Rainfall, Streamflow, and Water-Quality Data During Stormwater Monitoring, Halawa Stream Drainage Basin, Oahu, Hawaii, July 1, 2000 to June 30, 2001

USGS Publications Warehouse

Presley, Todd K.

2001-01-01

The State of Hawaii Department of Transportation Stormwater Monitoring Program was implemented on January 1, 2001. The program includes the collection of rainfall, streamflow, and water-quality data at selected sites in the Halawa Stream drainage basin. Rainfall and streamflow data were collected from July 1, 2000 to June 30, 2001. Few storms during the year met criteria for antecedent dry conditions or provided enough runoff to sample. The storm of June 5, 2001 was sufficiently large to cause runoff. On June 5, 2001, grab samples were collected at five sites along North Halawa and Halawa Streams. The five samples were later analyzed for nutrients, trace metals, oil and grease, total petroleum hydrocarbons, fecal coliform, biological and chemical oxygen demands, total suspended solids, and total dissolved solids.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Verification of the skill of numerical weather prediction models in forecasting rainfall from U.S. landfalling tropical cyclones

NASA Astrophysics Data System (ADS)

Luitel, Beda; Villarini, Gabriele; Vecchi, Gabriel A.

2018-01-01

The goal of this study is the evaluation of the skill of five state-of-the-art numerical weather prediction (NWP) systems [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)] in forecasting rainfall from North Atlantic tropical cyclones (TCs). Analyses focus on 15 North Atlantic TCs that made landfall along the U.S. coast over the 2007-2012 period. As reference data we use gridded rainfall provided by the Climate Prediction Center (CPC). We consider forecast lead-times up to five days. To benchmark the skill of these models, we consider rainfall estimates from one radar-based (Stage IV) and four satellite-based [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); the CPC MORPHing Technique (CMORPH)] rainfall products. Daily and storm total rainfall fields from each of these remote sensing products are compared to the reference data to obtain information about the range of errors we can expect from "observational data." The skill of the NWP models is quantified: (1) by visual examination of the distribution of the errors in storm total rainfall for the different lead-times, and numerical examination of the first three moments of the error distribution; (2) relative to climatology at the daily scale. Considering these skill metrics, we conclude that the NWP models can provide skillful forecasts of TC rainfall with lead-times up to 48 h, without a consistently best or worst NWP model.

What are the most important factors determining different vegetation types in the Chapada Diamantina, Brazil?

PubMed

Neves, S P S; Funch, R; Conceição, A A; Miranda, L A P; Funch, L S

2016-06-01

A transect was used to examine the environmental and biological descriptors of a compact vegetation mosaic in the Chapada Diamantina in northeastern Brazil, including the floristic composition, spectrum of plant life forms, rainfall, and soil properties that defined areas of cerrado (Brazilian savanna), caatinga (seasonally dry tropical forest thorny, deciduous shrub/arboreal vegetation) and cerrado-caatinga transition vegetation. The floristic survey was made monthly from April/2009 to March/2012. A dendrogram of similarity was generated using the Jaccard Index based on a matrix of the species that occurred in at least two of the vegetation types examined. The proportions of life forms in each vegetation type were compared using the chi-square test. Composite soil samples were analyzed by simple variance (ANOVA) to examine relationships between soil parameters of each vegetation type and the transition area. The monthly precipitation levels in each vegetation type were measured and compared using the chi-square test. A total of 323 species of angiosperms were collected distributed in 193 genera and 54 families. The dendrogram demonstrated strong difference between the floristic compositions of the cerrado and caatinga, sharing 2% similarity. The chi-square test did not demonstrate any significant statistical differences between the monthly values of recorded rainfall. The organic matter and clay contents of the soilsin the caatinga increased while sand decreased, and the proportions of therophyte, hemicryptophyte, and chamaephyte life forms decreased and phanerophytes increased. We can therefore conclude that the floristic composition and the spectrum of life forms combined to define the cerrado and caatinga vegetation along the transect examined, with soil being the principal conditioning factor determining the different vegetation types, independent of precipitation levels.

Forecasting Global Rainfall for Points Using ECMWF's Global Ensemble and Its Applications in Flood Forecasting

NASA Astrophysics Data System (ADS)

Pillosu, F. M.; Hewson, T.; Mazzetti, C.

2017-12-01

Prediction of local extreme rainfall has historically been the remit of nowcasting and high resolution limited area modelling, which represent only limited areas, may not be spatially accurate, give reasonable results only for limited lead times (<2 days) and become prohibitively expensive at global scale. ECMWF/EFAS/GLOFAS have developed a novel, cost-effective and physically-based statistical post-processing software ("ecPoint-Rainfall, ecPR", operational in 2017) that uses ECMWF Ensemble (ENS) output to deliver global probabilistic rainfall forecasts for points up to day 10. Firstly, ecPR applies a new notion of "remote calibration", which 1) allows us to replicate a multi-centennial training period using only one year of data, and 2) provides forecasts for anywhere in the world. Secondly, the software applies an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals, and of where biases in the model can be improved upon. A long-term verification has shown that the post-processed rainfall has better reliability and resolution at every lead time if compared with ENS, and for large totals, ecPR outputs have the same skill at day 5 that the raw ENS has at day 1 (ROC area metric). ecPR could be used as input for hydrological models if its probabilistic output is modified accordingly to the inputs requirements for hydrological models. Indeed, ecPR does not provide information on where the highest total is likely to occur inside the gridbox, nor on the spatial distribution of rainfall values nearby. "Scenario forecasts" could be a solution. They are derived from locating the rainfall peak in sensitive positions (e.g. urban areas), and then redistributing the remaining quantities in the gridbox modifying traditional spatial correlation characterization methodologies (e.g. variogram analysis) in order to take account, for instance, of the type of rainfall forecast (stratiform, convective). Such an approach could be a turning point in the field of medium-range global real-time riverine flood forecasts. This presentation will illustrate for ecPR 1) system calibration, 2) operational implementation, 3) long-term verification, 4) future developments, and 5) early ideas for the application of ecPR outputs in hydrological models.

Hydrogeological characterisation of groundwater over Brazil using remotely sensed and model products.

PubMed

Hu, Kexiang; Awange, Joseph L; Khandu; Forootan, Ehsan; Goncalves, Rodrigo Mikosz; Fleming, Kevin

2017-12-01

For Brazil, a country frequented by droughts and whose rural inhabitants largely depend on groundwater, reliance on isotope for its monitoring, though accurate, is expensive and limited in spatial coverage. We exploit total water storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE) satellites to analyse spatial-temporal groundwater changes in relation to geological characteristics. Large-scale groundwater changes are estimated using GRACE-derived TWS and altimetry observations in addition to GLDAS and WGHM model outputs. Additionally, TRMM precipitation data are used to infer impacts of climate variability on groundwater fluctuations. The results indicate that climate variability mainly controls groundwater change trends while geological properties control change rates, spatial distribution, and storage capacity. Granular rocks in the Amazon and Guarani aquifers are found to influence larger storage capability, higher permeability (>10 -4 m/s) and faster response to rainfall (1 to 3months' lag) compared to fractured rocks (permeability <10 -7 m/s and lags > 3months) found only in Bambui aquifer. Groundwater in the Amazon region is found to rely not only on precipitation but also on inflow from other regions. Areas beyond the northern and southern Amazon basin depict a 'dam-like' pattern, with high inflow and slow outflow rates (recharge slope > 0.75, discharge slope < 0.45). This is due to two impermeable rock layer-like 'walls' (permeability <10 -8 m/s) along the northern and southern Alter do Chão aquifer that help retain groundwater. The largest groundwater storage capacity in Brazil is the Amazon aquifer (with annual amplitudes of > 30cm). Amazon's groundwater declined between 2002 and 2008 due to below normal precipitation (wet seasons lasted for about 36 to 47% of the time). The Guarani aquifer and adjacent coastline areas rank second in terms of storage capacity, while the northeast and southeast coastal regions indicate the smallest storage capacity due to lack of rainfall (annual average is rainfall <10cm). Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial and temporal heterogeneity of Anopheles mosquitoes and Plasmodium falciparum transmission along the Kenyan coast.

PubMed

Mbogo, Charles M; Mwangangi, Joseph M; Nzovu, Joseph; Gu, Weidong; Yan, Guiyan; Gunter, James T; Swalm, Chris; Keating, Joseph; Regens, James L; Shililu, Josephat I; Githure, John I; Beier, John C

2003-06-01

The seasonal dynamics and spatial distributions of Anopheles mosquitoes and Plasmodium falciparum parasites were studied for one year at 30 villages in Malindi, Kilifi, and Kwale Districts along the coast of Kenya. Anopheline mosquitoes were sampled inside houses at each site once every two months and malaria parasite prevalence in local school children was determined at the end of the entomologic survey. A total of 5,476 Anopheles gambiae s.l. and 3,461 An. funestus were collected. Species in the An. gambiae complex, identified by a polymerase chain reaction, included 81.9% An. gambiae s.s., 12.8% An. arabiensis, and 5.3% An. merus. Anopheles gambiae s.s. contributed most to the transmission of P. falciparum along the coast as a whole, while An. funestus accounted for more than 50% of all transmission in Kwale District. Large spatial heterogeneity of transmission intensity (< 1 up to 120 infective bites per person per year) resulted in correspondingly large and significantly related variations in parasite prevalence (range = 38-83%). Thirty-two percent of the sites (7 of 22 sites) with malaria prevalences ranging from 38% to 70% had annual entomologic inoculation rates (EIR) less than five infective bites per person per year. Anopheles gambiae s.l. and An. funestus densities in Kwale were not significantly influenced by rainfall. However, both were positively correlated with rainfall one and three months previously in Malindi and Kilifi Districts, respectively. These unexpected variations in the relationship between mosquito populations and rainfall suggest environmental heterogeneity in the predominant aquatic habitats in each district. One important conclusion is that the highly non-linear relationship between EIRs and prevalence indicates that the consistent pattern of high prevalence might be governed by substantial variation in transmission intensity measured by entomologic surveys. The field-based estimate of entomologic parameters on a district level does not provide a sensitive indicator of transmission intensity in this study.

Hydrologic change in a coast redwood forest, Caspar Creek Experimental Watersheds: implications for salmonid survival

Treesearch

Elizabeth Keppeler

2016-01-01

The 52-year record of streamflow from the Caspar Creek Experimental Watersheds shows a trend toward decreasing rainfall and streamflow during the fall season when coho salmon (Oncorhynchus kisutch) migrate upstream to spawn. Rainfall records show a slight declining trend in fall totals and a slight increasing trend in spring totals since 1962, but only November shows a...

Influences of large-scale convection and moisture source on monthly precipitation isotope ratios observed in Thailand, Southeast Asia

NASA Astrophysics Data System (ADS)

Wei, Zhongwang; Lee, Xuhui; Liu, Zhongfang; Seeboonruang, Uma; Koike, Masahiro; Yoshimura, Kei

2018-04-01

Many paleoclimatic records in Southeast Asia rely on rainfall isotope ratios as proxies for past hydroclimatic variability. However, the physical processes controlling modern rainfall isotopic behaviors in the region is poorly constrained. Here, we combined isotopic measurements at six sites across Thailand with an isotope-incorporated atmospheric circulation model (IsoGSM) and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to investigate the factors that govern the variability of precipitation isotope ratios in this region. Results show that rainfall isotope ratios are both correlated with local rainfall amount and regional outgoing longwave radiation, suggesting that rainfall isotope ratios in this region are controlled not only by local rain amount (amount effect) but also by large-scale convection. As a transition zone between the Indian monsoon and the western North Pacific monsoon, the spatial difference of observed precipitation isotope among different sites are associated with moisture source. These results highlight the importance of regional processes in determining rainfall isotope ratios in the tropics and provide constraints on the interpretation of paleo-precipitation isotope records in the context of regional climate dynamics.

Satellite-based high-resolution mapping of rainfall over southern Africa

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Drönner, Johannes; Nauss, Thomas

2017-06-01

A spatially explicit mapping of rainfall is necessary for southern Africa for eco-climatological studies or nowcasting but accurate estimates are still a challenging task. This study presents a method to estimate hourly rainfall based on data from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Rainfall measurements from about 350 weather stations from 2010-2014 served as ground truth for calibration and validation. SEVIRI and weather station data were used to train neural networks that allowed the estimation of rainfall area and rainfall quantities over all times of the day. The results revealed that 60 % of recorded rainfall events were correctly classified by the model (probability of detection, POD). However, the false alarm ratio (FAR) was high (0.80), leading to a Heidke skill score (HSS) of 0.18. Estimated hourly rainfall quantities were estimated with an average hourly correlation of ρ = 0. 33 and a root mean square error (RMSE) of 0.72. The correlation increased with temporal aggregation to 0.52 (daily), 0.67 (weekly) and 0.71 (monthly). The main weakness was the overestimation of rainfall events. The model results were compared to the Integrated Multi-satellitE Retrievals for GPM (IMERG) of the Global Precipitation Measurement (GPM) mission. Despite being a comparably simple approach, the presented MSG-based rainfall retrieval outperformed GPM IMERG in terms of rainfall area detection: GPM IMERG had a considerably lower POD. The HSS was not significantly different compared to the MSG-based retrieval due to a lower FAR of GPM IMERG. There were no further significant differences between the MSG-based retrieval and GPM IMERG in terms of correlation with the observed rainfall quantities. The MSG-based retrieval, however, provides rainfall in a higher spatial resolution. Though estimating rainfall from satellite data remains challenging, especially at high temporal resolutions, this study showed promising results towards improved spatio-temporal estimates of rainfall over southern Africa.

Assessment of landslide hazards induced by extreme rainfall event in Jammu and Kashmir Himalaya, northwest India

NASA Astrophysics Data System (ADS)

Kumar, Amit; Asthana, AKL; Priyanka, Rao Singh; Jayangondaperumal, R.; Gupta, Anil K.; Bhakuni, SS

2017-05-01

In the Indian Himalayan region (IHR), landslide-driven hazards have intensified over the past several decades primarily caused by the occurrence of heavy and extreme rainfall. However, little attention has been given to determining the cause of events triggered during pre- and post-Indian Summer Monsoon (ISM) seasons. In the present research, detailed geological, meteorological, and remote sensing investigations have been carried out on an extreme rainfall landslide event that occurred in Sadal village, Udhampur district, Jammu and Kashmir Himalaya, during September 2014. Toward the receding phase of the ISM (i.e., in the month of September 2014), an unusual rainfall event of 488.2 mm rainfall in 24 h took place in Jammu and Kashmir Himalaya in contrast to the normal rainfall occurrence. Geological investigations suggest that a planar weakness in the affected region is caused by bedding planes that consist of an alternate sequence of hard, compact sandstone and weak claystone. During this extreme rainfall event, the Sadal village was completely buried under the rock slides, as failure occurred along the planar weakness that dips toward the valley slope. Rainfall data analysis from the Tropical Rainfall Measuring Mission (TRMM) for the preceding years homogeneous time series (July-September) indicates that the years 2005, 2009, 2011, 2012, and 2014 (i.e., closely spaced and clustering heavy rainfall events) received heavy rainfalls during the withdrawal of the ISM; whereas the heaviest rainfall was received in the years 2003 and 2013 at the onset of the ISM in the study region. This suggests that no characteristic cyclicity exists for extreme rainfall events. However, we observe that either toward the onset of the ISM or its retreat, the extreme rainfall facilitates landslides, rockfall, and slope failures in northwestern Himalaya. The spatiotemporal distribution of landslides caused by extreme rainfall events suggests its confinement toward the windward side of the Himalayan front.

Topical cyclone rainfall characteristics as determined from a satellite passive microwave radiometer

NASA Technical Reports Server (NTRS)

Rodgers, E. B.; Adler, R. F.

1979-01-01

Data from the Nimbus-5 Electrically Scanning Microwave Radiometer (ESMR-5) were used to calculate latent heat release and other rainfall parameters for over 70 satellite observations of 21 tropical cyclones in the tropical North Pacific Ocean. The results indicate that the ESMR-5 measurements can be useful in determining the rainfall characteristics of these storms and appear to be potentially useful in monitoring as well as predicting their intensity. The ESMR-5 derived total tropical cyclone rainfall estimates agree favorably with previous estimates for both the disturbance and typhoon stages. The mean typhoon rainfall rate (1.9 mm h(-1)) is approximately twice that of disturbances (1.1 mm h(-1)).

Extreme rainfall-induced landslide changes based on landslide susceptibility in China, 1998-2015

NASA Astrophysics Data System (ADS)

Li, Weiyue; Liu, Chun; Hong, Yang

2017-04-01

Nowadays, landslide has been one of the most frequent and seriously widespread natural hazards all over the world. Rainfall, especially heavy rainfall is a trigger to cause the landslide occurrence, by increasing soil pore water pressures. In China, rainfall-induced landslides have risen up over to 90% of the total number. Rainfall events sometimes generate a trend of extremelization named rainfall extremes that induce the slope failure suddenly and severely. This study shows a method to simulate the rainfall-induced landslide spatio-temporal distribution on the basis of the landslide susceptibility index. First, the study on landslide susceptibility in China is introduced. We set the values of the index to the range between 0 and 1. Second, we collected TRMM 3B42 precipitation products spanning the years 1998-2015 and extracted the daily rainfall events greater than 50mm/day as extreme rainfall. Most of the rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours. The combination of these two aspects can be exploited to simulate extreme rainfall-induced landslide distribution and illustrate the changes in 17 years. This study shows a useful tool to be part of rainfall-induced landslide simulation methodology for landslide early warning.

Rainfall variability and drought characteristics in two agro-climatic zones: An assessment of climate change challenges in Africa.

PubMed

Ayanlade, Ayansina; Radeny, Maren; Morton, John F; Muchaba, Tabitha

2018-07-15

This paper examines drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' climate change perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations. Consequently, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability (p) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62≤p≥0.8 in all the stations, though, the p-values for 10day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days <0.30, but less reliable in the months of March, August and October (CV-RD>0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided to farmers, at a subsidized price by the government, for them to cope with the current condition of climate change. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Effect of climatic variability on malaria trends in Baringo County, Kenya.

PubMed

Kipruto, Edwin K; Ochieng, Alfred O; Anyona, Douglas N; Mbalanya, Macrae; Mutua, Edna N; Onguru, Daniel; Nyamongo, Isaac K; Estambale, Benson B A

2017-05-25

Malaria transmission in arid and semi-arid regions of Kenya such as Baringo County, is seasonal and often influenced by climatic factors. Unravelling the relationship between climate variables and malaria transmission dynamics is therefore instrumental in developing effective malaria control strategies. The main aim of this study was to describe the effects of variability of rainfall, maximum temperature and vegetation indices on seasonal trends of malaria in selected health facilities within Baringo County, Kenya. Climate variables sourced from the International Research Institute (IRI)/Lamont-Doherty Earth Observatory (LDEO) climate database and malaria cases reported in 10 health facilities spread across four ecological zones (riverine, lowland, mid-altitude and highland) between 2004 and 2014 were subjected to a time series analysis. A negative binomial regression model with lagged climate variables was used to model long-term monthly malaria cases. The seasonal Mann-Kendall trend test was then used to detect overall monotonic trends in malaria cases. Malaria cases increased significantly in the highland and midland zones over the study period. Changes in malaria prevalence corresponded to variations in rainfall and maximum temperature. Rainfall at a time lag of 2 months resulted in an increase in malaria transmission across the four zones while an increase in temperature at time lags of 0 and 1 month resulted in an increase in malaria cases in the riverine and highland zones, respectively. Given the existence of a time lag between climatic variables more so rainfall and peak malaria transmission, appropriate control measures can be initiated at the onset of short and after long rains seasons.

Monitoring on The Quality and Quantity of DIY Rainwater Harvesting System

NASA Astrophysics Data System (ADS)

Kasmin, H.; Bakar, N. H.; Zubir, M. M.

2016-07-01

Rainwater harvesting is an alternative sources of water supply and can be used for potable and non-potable uses. It could helps to store treated rainwater for more beneficial use and also for flood mitigation. Sustainable approach for flooding problem reduction in urban areas is by slowing down the rate of surface runoff flows at source by providing more storage area/tank. In order to understand the performance of a rainwater harvesting system (RWH), a preliminary monitoring on a ‘do it yourself’ (DIY) RWH model with additional first -flush strategy for water quality treatment was done. The main concept behind first flush diversion is to prevent initial polluted rainwater from entering the storage tank. Based on seven rainfall events observed in Parit Raja, both quality and quantity of the rainfalls were analysed. For rainwater quality, the samples from first flush diverter and storage tank were taken to understand their performance based on pH, dissolved oxygen (DO), turbidity, total dissolved solid (TDS), total suspended solid (TSS), chemical oxygen demand (COD) and biochemical oxygen demand (BOD) parameters. While for rainwater quantity, hydrograph analysis were done based on the performance of total rainfall and runoff, peak flow of rainfall and runoff; and delayed time parameters. Based on Interim National Water Quality Standard (INWQS) and National Drinking Water Quality Standard (NDWQS), first flush diverter apparently helps on water quality improvement in storage tanks when pH, DO, TDS, TSS and turbidity were classified as Class I (INWQS) and is allowable for drinking; but BOD and COD parameters were classified as Class III (INWQS). Hence, it has potential to be used as potable usage but will need extensive treatment to reduce its poor microbial quality. Based on the maximum observed rainfall event which had total volume of 3195.5 liter, had peakflow reduction from 0.00071 m3/s to 0.00034 m3/s and delayed runoff between 5 and 10 minutes after rainfall started. It concludes that the performance of water retention could be due to total rainfall and the tank capacity. Therefore, RWH has a potential to be used as potable use and at the same time it also has a potential to reduce local urban flooding.

Climate change effects on landslides in southern B.C.

NASA Astrophysics Data System (ADS)

Jakob, M.

2009-04-01

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

Experimental drought induces short-term changes in soil functionality and microbial community structure after fire in a Mediterranean shrubland

NASA Astrophysics Data System (ADS)

Hinojosa, M. B.; Parra, A.; Laudicina, V. A.; Moreno, J. M.

2014-10-01

Fire is a major ecosystem driver, causing significant changes in soil nutrients and microbial community structure and functionality. Post-fire soil dynamics can vary depending on rainfall patterns, although variations in response to drought are poorly known. This is particularly important in areas with poor soils and limited rainfall, like arid and semiarid ones. Furthermore, climate change projections in many such areas anticipate reduced precipitation and longer drought, together with an increase in fire severity. The effects of experimental drought and fire were studied on soils in a Mediterranean Cistus-Erica shrubland in Central Spain. A replicated (n = 4) field experiment was carried out in which four levels of rainfall pattern were implemented by means of a rain-out shelters and irrigation system. The treatments were: environmental control (natural rainfall), historical control (long-term average rainfall, 2 months drought), moderate drought (25% reduction of historical control, 5 months drought) and severe drought (45% reduction, 7 months drought). After one growing season, the plots were burned with high fire intensity, except a set of unburned plots that served as control. Soils were collected seasonally during one year and variables related to soil nutrient availability and microbial community structure and functionality were studied. Burned soils increased nutrient availability (P, N, K) with respect to unburned ones, but drought reduced such an increase in P, while it further increased N and K. Such changes in available soil nutrients were short-lived. Drought caused a further decrease of enzyme activities, carbon mineralization rate and microbial biomass. Fire decreased the relative abundance of fungi and actinomycetes. However, fire and drought caused a further reduction in fungi, with bacteria becoming relatively more abundant. Arguably, increasing drought and fires due to climate change will likely shift soil recovery after fire.

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.

A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa

NASA Astrophysics Data System (ADS)

Maidment, Ross I.; Grimes, David; Black, Emily; Tarnavsky, Elena; Young, Matthew; Greatrex, Helen; Allan, Richard P.; Stein, Thorwald; Nkonde, Edson; Senkunda, Samuel; Alcántara, Edgar Misael Uribe

2017-05-01

Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets.

Interannual and intra-annual variability of rainfall in Haiti (1905-2005)

NASA Astrophysics Data System (ADS)

Moron, Vincent; Frelat, Romain; Jean-Jeune, Pierre Karly; Gaucherel, Cédric

2015-08-01

The interannual variability of annual and monthly rainfall in Haiti is examined from a database of 78 rain gauges in 1905-2005. The spatial coherence of annual rainfall is rather low, which is partly due to Haiti's rugged landscape, complex shoreline, and surrounding warm waters (mean sea surface temperatures >27 °C from May to December). The interannual variation of monthly rainfall is mostly shaped by the intensity of the low-level winds across the Caribbean Sea, leading to a drier- (or wetter-) than-average rainy season associated with easterly (or westerly) anomalies, increasing (or decreasing) winds. The varying speed of low-level easterlies across the Caribbean basin may reflect at least four different processes during the year: (1) an anomalous trough/ridge over the western edge of the Azores high from December to February, peaking in January; (2) a zonal pressure gradient between Eastern Pacific and the tropical Northern Atlantic from May/June to September, with a peak in August (i.e. lower-than-average rainfall in Haiti is associated with positive sea level pressure anomalies over the tropical North Atlantic and negative sea level pressure anomalies over the Eastern Pacific); (3) a local ocean-atmosphere coupling between the speed of the Caribbean Low Level Jet and the meridional sea surface temperature (SST) gradient across the Caribbean basin (i.e. colder-than-average SST in the southern Caribbean sea is associated with increased easterlies and below-average rainfall in Haiti). This coupling is triggered when the warmest Caribbean waters move northward toward the Gulf of Mexico; (4) in October/November, a drier- (or wetter-) than-usual rainy season is related to an almost closed anticyclonic (or cyclonic) anomaly located ENE of Haiti on the SW edge of the Azores high. This suggests a main control of the interannual variations of rainfall by intensity, track and/or recurrence of tropical depressions traveling northeast of Haiti. During this period, the teleconnection of Haitian rainfall with synchronous Atlantic and Eastern Pacific SST is at a minimum.

Vegetative and reproductive phenology of a floodplain tree species Barringtonia acutangula from North East India.

PubMed

Nath, Shikhasmita; Nath, Arun Jyoti; Das, Ashesh Kumar

2016-03-01

Vegetative and reproductive phenology of Barringtonia acutangula, a floodplain tree species was studied at Chatla floodplain, Assam North East India with the aim to investigate vegetative and reproductive phenology under stressful environment of seasonal submergence and to assess the impact of environmental variables (temperature and precipitation) on tree phenophases. Quantitative assessment was made at 15 day interval for all the phenophases (leaf initiation, leaf-fall, flowering and fruiting) by tagging 40 (forty) trees over aperiod of two years (2012-14).To test seasonal influence on the phenology of Barringtonia acutangula different phenophases were correlated with environmental variables and statistical spearman's rank correlation coefficient was employed. Aridity index was computed that delineate influence of rainfall and temperature together on any phenophases. Leaf initiation showed positively significant correlation with temperature (r(s) = 0.601, p = < .05) during the year 2012-2013 whereas it was significantly correlated with rainfall (r(s) = 0.583, p = < .05) and aridity index (r(s) = 0.583, p = < .05) during the year 2013-2014. Leaf-fall was significant negatively correlated with temperature (r(s) = -0.623, p = < .05), rainfall (r(s) = -0.730, p = < .01) and aridity index (r(s) = -0.730, p = < .01) for both the studied years. Flowering was significantly influenced by temperature (r(s) = 0.639, p = < .05), rainfall (r(s) = 0.890, p = < .01) and aridity index (r(s) = 0.890, p = < .01) while in one month lag flowering was significantly correlated with rainfall (r(s) = 0.678, p = < .01) in 2012-13. Fruiting was also positively significant with temperature (r(s) = 0.795, P < .05), rainfall (r(s) = 0.835, P < .01) and aridity index (r(s) = 0.835, P < .01) for both the years. During one month lag period fruiting was positively correlated with temperature, rainfall and aridity index in both the years. Temperature, rainfall and aridity index were major determinants of the various vegetative and reproductive phenology of B. acutangula and any changes in these variables in future due to climate change, might have profound effect on phenophases of this tree species.

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

PubMed

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

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

A simple stochastic rainstorm generator for simulating spatially and temporally varying rainfall

NASA Astrophysics Data System (ADS)

Singer, M. B.; Michaelides, K.; Nichols, M.; Nearing, M. A.

2016-12-01

In semi-arid to arid drainage basins, rainstorms often control both water supply and flood risk to marginal communities of people. They also govern the availability of water to vegetation and other ecological communities, as well as spatial patterns of sediment, nutrient, and contaminant transport and deposition on local to basin scales. All of these landscape responses are sensitive to changes in climate that are projected to occur throughout western North America. Thus, it is important to improve characterization of rainstorms in a manner that enables statistical assessment of rainfall at spatial scales below that of existing gauging networks and the prediction of plausible manifestations of climate change. Here we present a simple, stochastic rainstorm generator that was created using data from a rich and dense network of rain gauges at the Walnut Gulch Experimental Watershed (WGEW) in SE Arizona, but which is applicable anywhere. We describe our methods for assembling pdfs of relevant rainstorm characteristics including total annual rainfall, storm area, storm center location, and storm duration. We also generate five fitted intensity-duration curves and apply a spatial rainfall gradient to generate precipitation at spatial scales below gauge spacing. The model then runs by Monte Carlo simulation in which a total annual rainfall is selected before we generate rainstorms until the annual precipitation total is reached. The procedure continues for decadal simulations. Thus, we keep track of the hydrologic impact of individual storms and the integral of precipitation over multiple decades. We first test the model using ensemble predictions until we reach statistical similarity to the input data from WGEW. We then employ the model to assess decadal precipitation under simulations of climate change in which we separately vary the distribution of total annual rainfall (trend in moisture) and the intensity-duration curves used for simulation (trends in storminess). We demonstrate the model output through spatial maps of rainfall and through statistical comparisons of relevant parameters and distributions. Finally, discuss how the model can be used to understand basin-scale hydrology in terms of soil moisture, runoff, and erosion.

Rainfall Product Evaluation for the TRMM Ground Validation Program

NASA Technical Reports Server (NTRS)

Amitai, E.; Wolff, D. B.; Robinson, M.; Silberstein, D. S.; Marks, D. A.; Kulie, M. S.; Fisher, B.; Einaudi, Franco (Technical Monitor)

2000-01-01

Evaluation of the Tropical Rainfall Measuring Mission (TRMM) satellite observations is conducted through a comprehensive Ground Validation (GV) Program. Standardized instantaneous and monthly rainfall products are routinely generated using quality-controlled ground based radar data from four primary GV sites. As part of the TRMM GV program, effort is being made to evaluate these GV products and to determine the uncertainties of the rainfall estimates. The evaluation effort is based on comparison to rain gauge data. The variance between the gauge measurement and the true averaged rain amount within the radar pixel is a limiting factor in the evaluation process. While monthly estimates are relatively simple to evaluate, the evaluation of the instantaneous products are much more of a challenge. Scattegrams of point comparisons between radar and rain gauges are extremely noisy for several reasons (e.g. sample volume discrepancies, timing and navigation mismatches, variability of Z(sub e)-R relationships), and therefore useless for evaluating the estimates. Several alternative methods, such as the analysis of the distribution of rain volume by rain rate as derived from gauge intensities and from reflectivities above the gauge network will be presented. Alternative procedures to increase the accuracy of the estimates and to reduce their uncertainties also will be discussed.

Longitudinal study on the temporal and micro-spatial distribution of Galba truncatula in four farms in Belgium as a base for small-scale risk mapping of Fasciola hepatica.

PubMed

Charlier, Johannes; Soenen, Karen; De Roeck, Els; Hantson, Wouter; Ducheyne, Els; Van Coillie, Frieke; De Wulf, Robert; Hendrickx, Guy; Vercruysse, Jozef

2014-11-26

The trematode parasite Fasciola hepatica causes important economic losses in ruminants worldwide. Current spatial distribution models do not provide sufficient detail to support farm-specific control strategies. A technology to reliably assess the spatial distribution of intermediate host snail habitats on farms would be a major step forward to this respect. The aim of this study was to conduct a longitudinal field survey in Flanders (Belgium) to (i) characterise suitable small water bodies (SWB) for Galba truncatula and (ii) describe the population dynamics of G. truncatula. Four F. hepatica-infected farms from two distinct agricultural regions were examined for the abundance of G. truncatula from the beginning (April 2012) until the end (November 2012) of the grazing season. Per farm, 12 to 18 SWB were selected for monthly examination, using a 10 m transect analysis. Observations on G. truncatula abundance were coupled with meteorological and (micro-)environmental factors and the within-herd prevalence of F. hepatica using simple comparison or negative binomial regression models. A total of 54 examined SWB were classified as a pond, ditch, trench, furrow or moist area. G. truncatula abundance was significantly associated with SWB-type, region and total monthly precipitation, but not with monthly temperature. The clear differences in G. truncatula abundance between the 2 studied regions did not result in comparable differences in F. hepatica prevalence in the cattle. Exploration of the relationship of G. truncatula abundance with (micro)-environmental variables revealed a positive association with soil and water pH and the occurrence of Ranunculus sp. and a negative association with mowed pastures, water temperature and presence of reed-like plant species. Farm-level predictions of G. truncatula risk and subsequent risk for F. hepatica occurrence would require a rainfall, soil type (representing the agricultural region) and SWB layer in a geographic information system. While rainfall and soil type information is easily accessible, the recent advances in very high spatial resolution cameras carried on board of satellites, planes or drones should allow the delineation of SWBs in the future.

Bayesian Spatiotemporal Analysis of Socio-Ecologic Drivers of Ross River Virus Transmission in Queensland, Australia

PubMed Central

Hu, Wenbiao; Clements, Archie; Williams, Gail; Tong, Shilu; Mengersen, Kerrie

2010-01-01

This study aims to examine the impact of socio-ecologic factors on the transmission of Ross River virus (RRV) infection and to identify areas prone to social and ecologic-driven epidemics in Queensland, Australia. We used a Bayesian spatiotemporal conditional autoregressive model to quantify the relationship between monthly variation of RRV incidence and socio-ecologic factors and to determine spatiotemporal patterns. Our results show that the average increase in monthly RRV incidence was 2.4% (95% credible interval (CrI): 0.1–4.5%) and 2.0% (95% CrI: 1.6–2.3%) for a 1°C increase in monthly average maximum temperature and a 10 mm increase in monthly average rainfall, respectively. A significant spatiotemporal variation and interactive effect between temperature and rainfall on RRV incidence were found. No association between Socio-economic Index for Areas (SEIFA) and RRV was observed. The transmission of RRV in Queensland, Australia appeared to be primarily driven by ecologic variables rather than social factors. PMID:20810846

Eddy-induced salinity pattern in the North Pacific

NASA Astrophysics Data System (ADS)

Abe, H.; Ebuchi, N.; Ueno, H.; Ishiyama, H.; Matsumura, Y.

2017-12-01

This research examines spatio-temporal behavior of sea surface salinity (SSS) after intense rainfall events using observed data from Aquarius. Aquarius SSS in the North Pacific reveals one notable event in which SSS is locally freshened by intense rainfall. Although SSS pattern shortly after the rainfall reflects atmospheric pattern, its final form reflects ocean dynamic structure; an anticyclonic eddy. Since this anticyclonic eddy was located at SSS front created by precipitation, this eddy stirs the water in a clockwise direction. This eddy stirring was visible for several months. It is expected horizontal transport by mesoscale eddies would play significant role in determining upper ocean salinity structure.

Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

NASA Astrophysics Data System (ADS)

Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

2017-04-01

Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze these datasets to better understand their similarities and differences in characterizing rainfall patterns across Chile. Monthly analysis showed that all satellite products highly overestimated rainfall in the arid North zone. However, there were no major difference between all three products from North to South-Central zones. Though, in the South zone, PERSIANN-CDR shows the lowest fit with high underestimation, while CHIRPS 2.0 and TMPA 3B43 v7 had better agreement with in situ measurements. The accuracy of satellite products were highly dependent on the amount of monthly rainfall with the best results found during winter seasons and in zones (Central to South) with higher amounts of precipitation. PERSIANN-CDR and CHIRPS 2.0 were used to derive SPI at time-scale of 1, 3 and 6 months, both satellite products presented similar results when it was compared in situ against satellite SPI's. Because of its higher spatial resolution that allows better characterizing of spatial variation in precipitation pattern, the CHIRPS 2.0 was used to mapping the SPI-3 over Chile. The results of this study show that in order to use the CHIRPS 2.0 and PERSIANN-CDR datasets in Chile to monitor spatial patterns in the rainfall and drought intensity conditions, these products should be calibrated to adjust for the overestimation/underestimation of rainfall geographically specially in the North zone and seasonally during the summer and spring months in the other zones.

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.

Seasonality of dizziness and vertigo in a tropical region.

PubMed

Pereira, Alcione Botelho; Almeida, Leonardo Alves Ferreira; Pereira, Nayara Gorette; Menezes, Patrícia Andrade Freitas de; Felipe, Lilian; Volpe, Fernando Madalena

2015-06-01

Vertigo and dizziness are among the most common medical complaints in the emergency room, and are associated with a considerable personal and health care burden. Scarce and conflicting reports indicate those symptoms may present a seasonal distribution. This study aimed at investigating the existence of a seasonal distribution of vertigo/dizziness in a tropical region, and the correlations of these findings with climatic variables. The charts of all patients consecutively admitted between 2009 and 2012 in the emergency room of a Brazilian general hospital were reviewed. A total of 4920 cases containing these terms were sorted from a sample of 276,076 emergency records. Seasonality was assessed using Cosinor Analysis. Pearson's correlations were performed between the incidence of consultations, considering separately dizziness and vertigo and each of the predictor climatic variables of that index month. Significant seasonal patterns were observed for dizziness and vertigo in the emergency room. Vertigo was more frequent in late winter-spring, negatively correlating to humidity (r = -0.374; p = 0.013) and rainfall (r = -0.334; p = 0.020). Dizziness peaked on summer months, and positively correlated to average temperatures (r = 0.520; p < 0.001) and rainfall (r = 0.297; p = 0.040), but negatively to atmospheric pressure (r = -0.424; p = 0.003). The different seasonal patterns evidenced for dizziness and vertigo indicate possible distinct underlying mechanisms of how seasons may influence the occurrence of those symptoms.

[Characteristics of nutrient loss by runoff in sloping arable land of yellow-brown under different rainfall intensities].

PubMed

Chen, Ling; Liu, De-Fu; Song, Lin-Xu; Cui, Yu-Jie; Zhang, Gei

2013-06-01

In order to investigate the loss characteristics of N and P through surface flow and interflow under different rainfall intensities, a field experiment was conducted on the sloping arable land covered by typical yellow-brown soils inXiangxi River watershed by artificial rainfall. The results showed that the discharge of surface flow, total runoff and sediment increased with the increase of rain intensity, while the interflow was negatively correlated with rain intensity under the same total rainfall. TN, DN and DP were all flushed at the very beginning in surface flow underdifferent rainfall intensities; TP fluctuated and kept consistent in surface flow without obvious downtrend. While TN, DN and DP in interflow kept relatively stable in the whole runoff process, TP was high at the early stage, then rapidly decreased with time and kept steady finally. P was directly influenced by rainfall intensity, its concentration in the runoff increased with the increase of the rainfall intensity, the average concentration of N and P both exceeded the threshold of eutrophication of freshwater. The higher the amount of P loss was, the higher the rain intensity. The change of N loss was the opposite. The contribution rate of TN loss carried by surface flow increased from 36.5% to 57.6% with the increase of rainfall intensity, but surface flow was the primary form of P loss which contributed above 90.0%. Thus, it is crucial to control interflow in order to reduce N loss. In addition, measures should be taken to effectively manage soil erosion to mitigate P loss. The proportion of dissolved nitrogen in surface flow elevated with the decrease of rainfall intensity, but in interflow, dissolved form was predominant. P was exported mainly in the form of particulate under different rainfall intensities and runoff conditions.

High-Resolution Rainfall From Radar Reflectivity and Terrestrial Rain Gages for use in Estimating Debris-Flow Susceptibility in the Day Fire, California

NASA Astrophysics Data System (ADS)

Hanshaw, M. N.; Schmidt, K. M.; Jorgensen, D. P.; Stock, J. D.

2007-12-01

Constraining the distribution of rainfall is essential to evaluating the post-fire mass-wasting response of steep soil-mantled landscapes. As part of a pilot early-warning project for flash floods and debris flows, NOAA deployed a portable truck-mounted Shared Mobile Atmospheric Research and Teaching Radar (SMART-R) to the 2006 Day fire in the Transverse Ranges of Southern California. In conjunction with a dense array of ground- based instruments, including 8 tipping-bucket rain gages located within an area of 170 km2, this C-band mobile Doppler radar provided 200-m grid cell estimates of precipitation data at fine temporal and spatial scales in burned steeplands at risk from hazardous flash floods and debris flows. To assess the utility of using this data in process models for flood and debris flow initiation, we converted grids of radar reflectivity to hourly time-steps of precipitation using an empirical relationship for convective storms, sampling the radar data at the locations of each rain gage as determined by GPS. The SMART-R was located 14 km from the farthest rain gage, but <10 km away from our intensive research area, where 5 gages are located within <1-2 km of each other. Analyses of the nine storms imaged by radar throughout the 2006/2007 winter produced similar cumulative rainfall totals between the gages and their SMART-R grid location over the entire season which correlate well on the high side, with gages recording the most precipitation agreeing to within 11% of the SMART-R. In contrast, on the low rainfall side, totals between the two recording systems are more variable, with a 62% variance between the minimums. In addition, at the scale of individual storms, a correlation between ground-based rainfall measurements and radar-based rainfall estimates is less evident, with storm totals between the gages and the SMART-R varying between 7 and 88%, a possible result of these being relatively small, fast-moving storms in an unusually dry winter. The SMART-R also recorded higher seasonal cumulative rainfall than the terrestrial gages, perhaps indicating that not all precipitation reached the ground. For one storm in particular, time-lapse photographs of the ground document snow. This could explain, in part, the discrepancy between storm-specific totals when the rain gages recorded significantly lower totals than the SMART-R. For example, during the storm where snow was observed, the SMART-R recorded a maximum of 66% higher rainfall than the maximum recorded by the gages. Unexpectedly, the highest elevation gage, located in a pre-fire coniferous vegetation community, consistently recorded the lowest precipitation, whereas gages in the lower elevation pre- fire chaparral community recorded the highest totals. The spatial locations of the maximum rainfall inferred by the SMART-R and the terrestrial gages are also offset by 1.6 km, with terrestrial values shifted easterly. The observation that the SMART-R images high rainfall intensities recorded by rain gages suggests that this technology has the ability to quantitatively estimate the spatial distribution over larger areas at a high resolution. Discrepancies on the storm scale, however, need to be investigated further, but we are optimistic that such high resolution data from the SMART-R and the terrestrial gages may lead to the effective application of a prototype debris-flow warning system where such processes put lives at risk.

Forecasting Andean rainfall and crop yield from the influence of El Nino on Pleiades visibility

PubMed

Orlove; Chiang; Cane

2000-01-06

Farmers in drought-prone regions of Andean South America have historically made observations of changes in the apparent brightness of stars in the Pleiades around the time of the southern winter solstice in order to forecast interannual variations in summer rainfall and in autumn harvests. They moderate the effect of reduced rainfall by adjusting the planting dates of potatoes, their most important crop. Here we use data on cloud cover and water vapour from satellite imagery, agronomic data from the Andean altiplano and an index of El Nino variability to analyse this forecasting method. We find that poor visibility of the Pleiades in June-caused by an increase in subvisual high cirrus clouds-is indicative of an El Nino year, which is usually linked to reduced rainfall during the growing season several months later. Our results suggest that this centuries-old method of seasonal rainfall forecasting may be based on a simple indicator of El Nino variability.

Tropical Rainfall Measuring Mission: Monitoring the Global Tropics for 3 Years and Beyond. 1.1

NASA Technical Reports Server (NTRS)

Shepherd, Marshall; Starr, David OC. (Technical Monitor)

2001-01-01

The Tropical Rainfall Measuring Mission (TRMM) was launched in November 1997 as a joint U.S.-Japanese mission to advance understanding of the global energy and water cycle by providing distributions of rainfall and latent heating over the global tropics. As a part of NASA's Earth System Enterprise, TRMM seeks to understand the mechanisms through which changes in tropical rainfall influence global circulation. Additionally, a goal is to improve the ability to model these processes in order to predict global circulations and rainfall variability at monthly and longer time scales. Such understanding has implications for assessing climate processes related to El Nino/La Nina and Global Warming. TRMM has also provided unexpected and exciting new knowledge and applications in areas related to hurricane monitoring, lightning, pollution, hydrology, and other areas. This CD-ROM includes a self-contained PowerPoint presentation that provides an overview of TRMM and significant science results; a set of data movies or animation; and listings of current TRMM-related publications in the literature.

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.

Incident rainfall in Rome and its relation to biodeterioration of buildings

NASA Astrophysics Data System (ADS)

Caneva, G.; Gori, E.; Danin, A.

Intensity and distribution of incident rainfall in Rome, and degree of lithobiont cover of building walls, were estimated, and their correlation was discussed. Rainfall and wind data over 10 years for the Rome Meteorological Observatory of Torre Calandrelli (UCEA) were used to calculate the actual hydrocontribution received over walls at various exposures. The biological colonization by lithobionts was evaluated on a sample of 14 buildings in various places of the city, using a phytosociological scale for quantifying their total cover. During all seasons the rainfall shows a significant peak in the south and the southeast exposures, where the highest cover of lithobionts is found. These results show the role of incident rainfall in the climatic conditions of Rome as the main driving factor for the growth of lithobionts on walls where rainfall is their principal source of water.

Tree ring reconstructed rainfall over the southern Amazon Basin

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Climate trends and projections for Guam

USGS Publications Warehouse

Gingerich, Stephen B.; Keener, Victoria; Finucane, Melissa L.

2015-01-01

The island of Guam experiences a tropical marine climate, which is warm and humid moderated by seasonal tradewinds and a wet and dry season. The dry season lasts from January to June, while the rainy months are from July to December. Annual rainfall totals 84-116 inches (2133-2946 mm), of which two-thirds fall during the rainy season. Seasonal temperatures and precipitation are also affected by the El-Niño Southern Oscillation (ENSO) and tropical cyclones, which cause the largest deviations from average precipitation. An average of three tropical storms and one typhoon pass within 80 nautical miles of Guam each year, and both flooding and drought can impact freshwater supply management and associated infrastructure. 

Remote rainfall sensing for landslide hazard analysis

USGS Publications Warehouse

Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay

2001-01-01

Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

Building rainfall thresholds for large-scales landslides by extracting occurrence time of landslides from seismic records

NASA Astrophysics Data System (ADS)

Yen, Hsin-Yi; Lin, Guan-Wei

2017-04-01

Understanding the rainfall condition which triggers mass moment on hillslope is the key to forecast rainfall-induced slope hazards, and the exact time of landslide occurrence is one of the basic information for rainfall statistics. In the study, we focused on large-scale landslides (LSLs) with disturbed area larger than 10 ha and conducted a string of studies including the recognition of landslide-induced ground motions and the analyses of different terms of rainfall thresholds. More than 10 heavy typhoons during the periods of 2005-2014 in Taiwan induced more than hundreds of LSLs and provided the opportunity to characterize the rainfall conditions which trigger LSLs. A total of 101 landslide-induced seismic signals were identified from the records of Taiwan seismic network. These signals exposed the occurrence time of landslide to assess rainfall conditions. Rainfall analyses showed that LSLs occurred when cumulative rainfall exceeded 500 mm. The results of rainfall-threshold analyses revealed that it is difficult to distinct LSLs from small-scale landslides (SSLs) by the I-D and R-D methods, but the I-R method can achieve the discrimination. Besides, an enhanced three-factor threshold considering deep water content was proposed as the rainfall threshold for LSLs.

Fog in a marginal agricultural area surrounded by montane Andean cloud forest during El Niño climate

NASA Astrophysics Data System (ADS)

García-Santos, G.

2010-07-01

The aim of the present study was to evaluate temporal variations of water inputs, rainfall and fog (cloud water), and its contribution to the water balance in a marginal agricultural area of potato surrounded by tropical montane cloud forest in Colombia. Fog in the air boundary layer was estimated using a cylindrical fog collector. Liquid water content of fog events were evaluated before and during natural climate event of El Niño. Our study shows the temporal variation of these two water inputs in both daily and monthly cycles on Boyacá at 2900 m a.s.l. Rainfall was the most frequently observed atmospheric phenomenon, being present on average 62% of the days per year, whereas fog was 45% of the time. Reflected on the lower frequency, annual amount of fog was 11% of precipitation. However during the anomalous dry climate of El Niño, total amount of rainfall was negligible and the few fog events were the only water source for plant growth. Estimated water crop requirements were higher than the water inputs. The survival of the crops was explained by meteorological conditions during dew and fog events. High relative humidity might have eased the plant’s water stress by decreasing transpiration and temperature in leaves and soil, affecting the water balance and the heat exchange between the atmosphere-land interfaces in the marginal agricultural areas during exceptional dry climate.

Model for forecasting Olea europaea L. airborne pollen in South-West Andalusia, Spain

NASA Astrophysics Data System (ADS)

Galán, C.; Cariñanos, Paloma; García-Mozo, Herminia; Alcázar, Purificación; Domínguez-Vilches, Eugenio

Data on predicted average and maximum airborne pollen concentrations and the dates on which these maximum values are expected are of undoubted value to allergists and allergy sufferers, as well as to agronomists. This paper reports on the development of predictive models for calculating total annual pollen output, on the basis of pollen and weather data compiled over the last 19 years (1982-2000) for Córdoba (Spain). Models were tested in order to predict the 2000 pollen season; in addition, and in view of the heavy rainfall recorded in spring 2000, the 1982-1998 data set was used to test the model for 1999. The results of the multiple regression analysis show that the variables exerting the greatest influence on the pollen index were rainfall in March and temperatures over the months prior to the flowering period. For prediction of maximum values and dates on which these values might be expected, the start of the pollen season was used as an additional independent variable. Temperature proved the best variable for this prediction. Results improved when the 5-day moving average was taken into account. Testing of the predictive model for 1999 and 2000 yielded fairly similar results. In both cases, the difference between expected and observed pollen data was no greater than 10%. However, significant differences were recorded between forecast and expected maximum and minimum values, owing to the influence of rainfall during the flowering period.

Climate variation and incidence of Ross river virus in Cairns, Australia: a time-series analysis.

PubMed Central

Tong, S; Hu, W

2001-01-01

In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values. PMID:11748035

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan

PubMed Central

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-01-01

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (−) and one month ago (−)), and average relative humidity (current and 9 months ago (−)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future. PMID:26848675

Impacts of Climatic Variability on Vibrio parahaemolyticus Outbreaks in Taiwan.

PubMed

Hsiao, Hsin-I; Jan, Man-Ser; Chi, Hui-Ju

2016-02-03

This study aimed to investigate and quantify the relationship between climate variation and incidence of Vibrio parahaemolyticus in Taiwan. Specifically, seasonal autoregressive integrated moving average (ARIMA) models (including autoregression, seasonality, and a lag-time effect) were employed to predict the role of climatic factors (including temperature, rainfall, relative humidity, ocean temperature and ocean salinity) on the incidence of V. parahaemolyticus in Taiwan between 2000 and 2011. The results indicated that average temperature (+), ocean temperature (+), ocean salinity of 6 months ago (+), maximum daily rainfall (current (-) and one month ago (-)), and average relative humidity (current and 9 months ago (-)) had significant impacts on the incidence of V. parahaemolyticus. Our findings offer a novel view of the quantitative relationship between climate change and food poisoning by V. parahaemolyticus in Taiwan. An early warning system based on climate change information for the disease control management is required in future.

A study of 2014 record drought in India with CFSv2 model: role of water vapor transport

NASA Astrophysics Data System (ADS)

Ramakrishna, S. S. V. S.; Brahmananda Rao, V.; Srinivasa Rao, B. R.; Hari Prasad, D.; Nanaji Rao, N.; Panda, Roshmitha

2017-07-01

The Indian summer monsoon season of 2014 was erratic and ended up with a seasonal rainfall deficit of 12 % and a record drought in June. In this study we analyze the moisture transport characteristics for the monsoon season of 2014 using both NCEP FNL reanalysis (FNL) and CFSv2 (CFS) model data. In FNL, in June 2014 there was a large area of divergence of moisture flux. In other months also there was lesser flux. This probably is the cause of 2014 drought. The CFS model overestimated the drought and it reproduces poorly the observed rainfall over central India (65E-95E; 5N-35N). The correlation coefficient (CC) between the IMD observed rainfall and CFS model rainfall is only 0.1 while the CC between rainfall and moisture flux convergence in CFS model is only 0.20 and with FNL data -0.78. This clearly shows that the CFS model has serious difficulty in reproducing the moisture flux convergence and rainfall. We found that the rainfall variations are strongly related to the moisture convergence or divergence. The hypothesis of Krishnamurti et al. (J Atmos Sci 67:3423-3441, 2010) namely the intrusion of west African desert air and the associated low convective available potential energy inhibiting convection and rainfall shows some promise to explain dry spells in Indian summer monsoon. However, the rainfall or lack of it is mainly explained by convergence or divergence of moisture flux.

Rainfall partitioning and related hydrochemical fluxes in a diverse and in a mono specific (Phenakospermum guyannense) secondary vegetation stand in eastern Amazonia.

PubMed

Hölscher, D; Sá, T D A; Möller, R F; Denich, M; Fölster, H

1998-04-01

Rainfall partitioning into throughfall and stemflow was studied in a diverse and in a mono specific stand of secondary vegetation in Eastern Amazonia. The nutrient concentrations in the water were analysed in order to quantify the related hydrochemical fluxes. Secondary vegetation forms the fallow in the local shifting cultivation system and is usually dominated by shrubs and trees. Phenakospermum guyannense (Strelitziaceae), a banana-like herb, is one of the predominant non-woody species. The study was conducted during an 18-month period in a 2.5-year-old relatively species-rich stand and a 10-year-old stand dominated by P. guyannense. In a year with 1956 mm of rainfall 65% (1281 mm) of this quantity reached the soil as throughfall in the diverse stand and 38% (743 mm) in the mono specific stand. Stemflow was estimated to be 23% and 41% respectively. P. guyannense and Banara guianensis (Flacourtiaceae), a tree species, were causing these high funnelling effects. In the young diverse stand B. guianensis had a stemflow of more than 200 l year -1 and P. guyannense had a median flux of 77 l year -1 per pseudostem. In the older stand the taller plants of P.␣guyannense collected 644 l year -1 per pseudostem on the median. The reason for these high values could be the banana-like growth form of P. guyannense and the crown morphology of B. guianensis, which has inclined branches. The low proportion of throughfall and the high stemflow values differ from all previous studies in Amazonian primary forests. The proximity to the Atlantic Ocean strongly influenced the nutrient fluxes via rainfall at our study site. This becomes obvious from the high Na and Cl fluxes with rainfall (19.7 kg Na ha -1 year -1 , 37.2 kg Cl ha -1 year -1 ) which were approximately equal to the Na and Cl fluxes with the sum of throughfall and stemflow for both stands. K fluxes in throughfall and stemflow in both stands were higher than in rainfall by a factor of 8. The high K enrichment during the crown passage is assumed to be caused by a␣high K concentration in the leaf tissue resulting in enhanced leaching from the leaves. In months with low␣rainfall the concentrations of Ca, Mg, S and Cl in throughfall of the diverse stand were significantly higher than in months with high rainfall. This was mainly due to vegetation burns in the dry period, which resulted in ash deposition on the canopy and subsequent wash-off and solution of ash particles.

A critical analysis of climatic influences on indoor radon concentrations: Implications for seasonal correction.

PubMed

Groves-Kirkby, Christopher J; Crockett, Robin G M; Denman, Antony R; Phillips, Paul S

2015-10-01

Although statistically-derived national Seasonal Correction Factors (SCFs) are conventionally used to convert sub-year radon concentration measurements to an annual mean, it has recently been suggested that external temperature could be used to derive local SCFs for short-term domestic measurements. To validate this approach, hitherto unanalysed radon and temperature data from an environmentally-stable location were analysed. Radon concentration and internal temperature were measured over periods totalling 1025 days during an overall period of 1762 days, the greatest continuous sampling period being 334 days, with corresponding meteorological data collected at a weather station 10 km distant. Mean daily, monthly and annual radon concentrations and internal temperatures were calculated. SCFs derived using monthly mean radon concentration, external temperature and internal-external temperature-difference were cross-correlated with each other and with published UK domestic SCF sets. Relatively good correlation exists between SCFs derived from radon concentration and internal-external temperature difference but correlation with external temperature, was markedly poorer. SCFs derived from external temperature correlate very well with published SCF tabulations, confirming that the complexity of deriving SCFs from temperature data may be outweighed by the convenience of using either of the existing domestic SCF tabulations. Mean monthly radon data fitted to a 12-month sinusoid showed reasonable correlation with many of the annual climatic parameter profiles, exceptions being atmospheric pressure, rainfall and internal temperature. Introducing an additional 6-month sinusoid enhanced correlation with these three parameters, the other correlations remaining essentially unchanged. Radon latency of the order of months in moisture-related parameters suggests that the principal driver for radon is total atmospheric moisture content rather than relative humidity. Copyright © 2015 Elsevier Ltd. All rights reserved.

Enhancement of vegetation-rainfall feedbacks on the Australian summer monsoon by the Madden-Julian Oscillation

NASA Astrophysics Data System (ADS)

Notaro, Michael

2018-01-01

A regional climate modeling analysis of the Australian monsoon system reveals a substantial modulation of vegetation-rainfall feedbacks by the Madden Julian Oscillation (MJO), both of which operate at similar sub-seasonal time scales, as evidence that the intensity of land-atmosphere interactions is sensitive to the background atmospheric state. Based on ensemble experiments with imposed modification of northern Australian leaf area index (LAI), the atmospheric responses to LAI anomalies are composited for negative and positive modes of the propagating MJO. In the regional climate model (RCM), northern Australian vegetation feedbacks are characterized by evapotranspiration (ET)-driven rainfall responses, with the moisture feedback mechanism dominating over albedo and roughness feedback mechanisms. During November-April, both Tropical Rainfall Measuring Mission and RCM data reveal MJO's pronounced influence on rainfall patterns across northern Australia, tropical Indian Ocean, Timor Sea, Arafura Sea, and Gulf of Carpentaria, with the MJO dominating over vegetation feedbacks in terms of regulating monsoon rainfall variability. Convectively-active MJO phases support an enhancement of positive vegetation feedbacks on monsoon rainfall. While the MJO imposes minimal regulation of ET responses to LAI anomalies, the vegetation feedback-induced responses in precipitable water, cloud water, and rainfall are greatly enhanced during convectively-active MJO phases over northern Australia, which are characterized by intense low-level convergence and efficient precipitable water conversion. The sub-seasonal response of vegetation-rainfall feedback intensity to the MJO is complex, with significant enhancement of rainfall responses to LAI anomalies in February during convectively-active MJO phases compared to minimal modulation by the MJO during prior and subsequent calendar months.

Association between Childhood Diarrhoeal Incidence and Climatic Factors in Urban and Rural Settings in the Health District of Mbour, Senegal

PubMed Central

Thiam, Sokhna; Diène, Aminata N.; Sy, Ibrahima; Winkler, Mirko S.; Schindler, Christian; Ndione, Jacques A.; Faye, Ousmane; Vounatsou, Penelope; Utzinger, Jürg; Cissé, Guéladio

2017-01-01

We assessed the association between childhood diarrhoeal incidence and climatic factors in rural and urban settings in the health district of Mbour in western Senegal. We used monthly diarrhoeal case records among children under five years registered in 24 health facilities over a four-year period (2011–2014). Climatic data (i.e., daily temperature, night temperature and rainfall) for the same four-year period were obtained. We performed a negative binomial regression model to establish the relationship between monthly diarrhoeal incidence and climatic factors of the same and the previous month. There were two annual peaks in diarrhoeal incidence: one during the cold dry season and one during the rainy season. We observed a positive association between diarrhoeal incidence and high average temperature of 36 °C and above and high cumulative monthly rainfall at 57 mm and above. The association between diarrhoeal incidence and temperature was stronger in rural compared to urban settings, while higher rainfall was associated with higher diarrhoeal incidence in the urban settings. Concluding, this study identified significant health–climate interactions and calls for effective preventive measures in the health district of Mbour. Particular attention should be paid to urban settings where diarrhoea was most common in order to reduce the high incidence in the context of climatic variability, which is expected to increase in urban areas in the face of global warming. PMID:28895927

State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application

NASA Astrophysics Data System (ADS)

Gibbs, Matthew S.; McInerney, David; Humphrey, Greer; Thyer, Mark A.; Maier, Holger R.; Dandy, Graeme C.; Kavetski, Dmitri

2018-02-01

Monthly to seasonal streamflow forecasts provide useful information for a range of water resource management and planning applications. This work focuses on improving such forecasts by considering the following two aspects: (1) state updating to force the models to match observations from the start of the forecast period, and (2) selection of a shorter calibration period that is more representative of the forecast period, compared to a longer calibration period traditionally used. The analysis is undertaken in the context of using streamflow forecasts for environmental flow water management of an open channel drainage network in southern Australia. Forecasts of monthly streamflow are obtained using a conceptual rainfall-runoff model combined with a post-processor error model for uncertainty analysis. This model set-up is applied to two catchments, one with stronger evidence of non-stationarity than the other. A range of metrics are used to assess different aspects of predictive performance, including reliability, sharpness, bias and accuracy. The results indicate that, for most scenarios and metrics, state updating improves predictive performance for both observed rainfall and forecast rainfall sources. Using the shorter calibration period also improves predictive performance, particularly for the catchment with stronger evidence of non-stationarity. The results highlight that a traditional approach of using a long calibration period can degrade predictive performance when there is evidence of non-stationarity. The techniques presented can form the basis for operational monthly streamflow forecasting systems and provide support for environmental decision-making.

Intra-seasonal rainfall variability during the maize growing season in the northern lowlands of Lesotho

NASA Astrophysics Data System (ADS)

Tongwane, Mphethe Isaac; Moeletsi, Mokhele Edmond

2015-05-01

Intra-seasonal rainfall distribution was identified as a priority gap that needs to be addressed for southern Africa to cope with agro-meteorological risks. The region in the northwest of Lesotho is appropriate for crop cultivation due to its relatively favourable climatic conditions and soils. High rainfall variability is often blamed for poor agricultural production in this region. This study aims to determine the onset of rains, cessation of rains and rainy season duration using historical climate data. Temporal variability of these rainy season characteristics was also investigated. The earliest and latest onset dates of the rainy season are during the last week of October at Butha-Buthe and the third week of November at Mapoteng, respectively. Cessation of the season is predominantly in the first week of April making the season approximately 137-163 days long depending on the location. Average seasonal rainfall ranged from 474 mm at Mapoteng to 668 mm at Butha-Buthe. Onset and cessation of the rainfall season vary by 4-7 weeks and 1 week, respectively. Mean coefficient of variation of seasonal rainfall is 39 %, but monthly variations are higher. These variations make annual crop management and planning difficult each year. Trends show a decrease in the rainfall amounts but improvements in both the temporal distribution of annual rainfall, onset and cessation dates.

Characterisation of diffuse pollutions from forested watersheds in Japan during storm events - its association with rainfall and watershed features.

PubMed

Zhang, Zhao; Fukushima, Takehiko; Onda, Yuichi; Mizugaki, Shigeru; Gomi, Takashi; Kosugi, Ken'ichirou; Hiramatsu, Shinya; Kitahara, Hikaru; Kuraji, Koichiro; Terajima, Tomomi; Matsushige, Kazuo; Tao, Fulu

2008-02-01

Forest areas have been identified as important sources of nonpoint pollution in Japan. The managers must estimate stormwater quality and quantities from forested watersheds to develop effective management strategies. Therefore, stormwater runoff loads and concentrations of 10 constituents (total suspended solids, dissolved organic carbon, PO(4)-P, dissolved total phosphorus, total phosphorus, NH(4)-N, NO(2)-N, NO(3)-N, dissolved total nitrogen, and total nitrogen) for 72 events across five regions (Aichi, Kochi, Mie, Nagano, and Tokyo) were characterised. Most loads were significantly and positively correlated with stormwater variables (total event rainfall, event duration, and rainfall intensity), but most discharge-weighted event concentrations (DWECs) showed negative correlations with rainfall intensity. Mean water quality concentration during baseflow was correlated significantly with storm concentrations (r=0.41-0.77). Although all pollutant load equations showed high coefficients of determination (R(2)=0.55-0.80), no models predicted well pollutant concentrations, except those for the three N constituents (R(2)=0.59-0.67). Linear regressions to estimate stormwater concentrations and loads were greatly improved by regional grouping. The lower prediction capability of the concentration models for Mie, compared with the other four regions, indicated that other watershed or storm characteristics should be included in the prediction models. Significant differences among regions were found more frequently in concentrations than in loads for all constituents. Since baseflow conditions implied available pollutant sources for stormwater, the similar spatial characteristics of pollutant concentrations between baseflow and stormflow conditions were an important control for stormwater quality.

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.