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.

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

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.

Identification of trends in rainfall, rainy days and 24 h maximum rainfall over subtropical Assam in Northeast India

NASA Astrophysics Data System (ADS)

Jhajharia, Deepak; Yadav, Brijesh K.; Maske, Sunil; Chattopadhyay, Surajit; Kar, Anil K.

2012-01-01

Trends in rainfall, rainy days and 24 h maximum rainfall are investigated using the Mann-Kendall non-parametric test at twenty-four sites of subtropical Assam located in the northeastern region of India. The trends are statistically confirmed by both the parametric and non-parametric methods and the magnitudes of significant trends are obtained through the linear regression test. In Assam, the average monsoon rainfall (rainy days) during the monsoon months of June to September is about 1606 mm (70), which accounts for about 70% (64%) of the annual rainfall (rainy days). On monthly time scales, sixteen and seventeen sites (twenty-one sites each) witnessed decreasing trends in the total rainfall (rainy days), out of which one and three trends (seven trends each) were found to be statistically significant in June and July, respectively. On the other hand, seventeen sites witnessed increasing trends in rainfall in the month of September, but none were statistically significant. In December (February), eighteen (twenty-two) sites witnessed decreasing (increasing) trends in total rainfall, out of which five (three) trends were statistically significant. For the rainy days during the months of November to January, twenty-two or more sites witnessed decreasing trends in Assam, but for nine (November), twelve (January) and eighteen (December) sites, these trends were statistically significant. These observed changes in rainfall, although most time series are not convincing as they show predominantly no significance, along with the well-reported climatic warming in monsoon and post-monsoon seasons may have implications for human health and water resources management over bio-diversity rich Northeast India.

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

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.

Water Budget for the Island of Kauai, Hawaii

USGS Publications Warehouse

Shade, Patricia J.

1995-01-01

A geographic information system model was created to calculate a monthly water budget for the island of Kauai. Ground-water recharge is the residual component of a monthly water budget calculated using long-term average rainfall, streamflow, and pan-evaporation data, applied irrigation-water estimates, and soil characteristics. The water-budget components are defined seasonally, through the use of the monthly water budget, and spatially by aquifer-system areas, through the use of the geographic information system model. The mean annual islandwide water-budget totals are 2,720 Mgal/d for rainfall plus irrigation; 1,157 Mgal/d for direct runoff; 911 Mgal/d for actual evapotranspiration; and 652 Mgal/d for ground-water recharge. Direct runoff is 43 percent, actual evapotranspiration is 33 percent, and ground-water recharge is 24 percent of rainfall plus irrigation. Ground-water recharge in the natural land-use areas is spatially distributed in a pattern similar to the rainfall distribution. Distinct seasonal variations in the water-budget components are apparent from the monthly water-budget calculations. Rainfall and ground-water recharge peak during the wet winter months with highs in January of 3,698 Mgal/d (million gallons per day) and 981 Mgal/d, respectively; a slight peak in July and August relative to June and September is caused by increased orographic rainfall. Recharge is lowest in June (454 Mgal/d) and November (461 Mgal/d).

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.

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.

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)

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.

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.

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.

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?

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.

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.

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

NASA Technical Reports Server (NTRS)

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

2000-01-01

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

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.

Impact of climate variability on the transmission risk of malaria in northern Côte d'Ivoire.

PubMed

M'Bra, Richard K; Kone, Brama; Soro, Dramane P; N'krumah, Raymond T A S; Soro, Nagnin; Ndione, Jacques A; Sy, Ibrahima; Ceccato, Pietro; Ebi, Kristie L; Utzinger, Jürg; Schindler, Christian; Cissé, Guéladio

2018-01-01

Since the 1970s, the northern part of Côte d'Ivoire has experienced considerable fluctuation in its meteorology including a general decrease of rainfall and increase of temperature from 1970 to 2000, a slight increase of rainfall since 2000, a severe drought in 2004-2005 and flooding in 2006-2007. Such changing climate patterns might affect the transmission of malaria. The purpose of this study was to analyze climate and environmental parameters associated with malaria transmission in Korhogo, a city in northern Côte d'Ivoire. All data were collected over a 10-year period (2004-2013). Rainfall, temperature and Normalized Difference Vegetation Index (NDVI) were the climate and environmental variables considered. Association between these variables and clinical malaria data was determined, using negative binomial regression models. From 2004 to 2013, there was an increase in the annual average precipitation (1100.3-1376.5 mm) and the average temperature (27.2°C-27.5°C). The NDVI decreased from 0.42 to 0.40. We observed a strong seasonality in these climatic variables, which resembled the seasonality in clinical malaria. An incremental increase of 10 mm of monthly precipitation was, on average, associated with a 1% (95% Confidence interval (CI): 0.7 to 1.2%) and a 1.2% (95% CI: 0.9 to 1.5%) increase in the number of clinical malaria episodes one and two months later respectively. A 1°C increase in average monthly temperature was, on average, associated with a decline of a 3.5% (95% CI: 0.1 to 6.7%) in clinical malaria episodes. A 0.1 unit increase in monthly NDVI was associated with a 7.3% (95% CI: 0.8 to 14.1%) increase in the monthly malaria count. There was a similar increase for the preceding-month lag (6.7% (95% CI: 2.3% to 11.2%)). The study results can be used to establish a malaria early warning system in Korhogo to prepare for outbreaks of malaria, which would increase community resilience no matter the magnitude and pattern of climate change.

The geographical co-distribution and socio-ecological drivers of childhood pneumonia and diarrhoea in Queensland, Australia.

PubMed

Xu, Z; Hu, W; Tong, S

2015-04-01

SUMMARY This study aimed to explore the spatio-temporal patterns, geographical co-distribution, and socio-ecological drivers of childhood pneumonia and diarrhoea in Queensland. A Bayesian conditional autoregressive model was used to quantify the impacts of socio-ecological factors on both childhood pneumonia and diarrhoea at a postal area level. A distinct seasonality of childhood pneumonia and diarrhoea was found. Childhood pneumonia and diarrhoea were mainly distributed in the northwest of Queensland. Mount Isa city was the high-risk cluster where childhood pneumonia and diarrhoea co-distributed. Emergency department visits (EDVs) for pneumonia increased by 3% per 10-mm increase in monthly average rainfall in wet seasons. By comparison, a 10-mm increase in monthly average rainfall may cause an increase of 4% in EDVs for diarrhoea. Monthly average temperature was negatively associated with EDVs for childhood diarrhoea in wet seasons. Low socioeconomic index for areas (SEIFA) was associated with high EDVs for childhood pneumonia. Future pneumonia and diarrhoea prevention and control measures in Queensland should focus more on Mount Isa.

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.

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.

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.

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).

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.

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.

Examining spatial-temporal variability and prediction of rainfall in North-eastern Nigeria

NASA Astrophysics Data System (ADS)

Muhammed, B. U.; Kaduk, J.; Balzter, H.

2012-12-01

In the last 50 years rainfall in North-eastern Nigeria under the influence of the West African Monsoon (WAM) has been characterised by large annual variations with severe droughts recorded in 1967-1973, and 1983-1987. This variability in rainfall has a large impact on the regions agricultural output, economy and security where the majority of the people depend on subsistence agriculture. In the 1990s there was a sign of recovery with higher annual rainfall totals compared to the 1961-1990 period but annual totals were slightly above the long term mean for the century. In this study we examine how significant this recovery is by analysing medium-term (1980-2006) rainfall of the region using the Climate Research Unit (CRU) and National Centre for Environment Prediction (NCEP) precipitation ½ degree, 6 hourly reanalysis data set. Percentage coefficient of variation increases northwards for annual rainfall (10%-35%) and the number of rainy days (10%-50%). The standardized precipitation index (SPI) of the area shows 7 years during the period as very wet (1996, 1999, 2003 and 2004) with SPI≥1.5 and moderately wet (1993, 1998, and 2006) with values of 1.0≥SPI≤1.49. Annual rainfall indicates a recovery from the 1990s and onwards but significant increases (in the amount of rainfall and number of days recorded with rainfall) is only during the peak of the monsoon season in the months of August and September (p<0.05) with no significant increases in the months following the onset of rainfall. Forecasting of monthly rainfall was made using the Auto Regressive Integrated Moving Average (ARIMA) model. The model is further evaluated using 24 months rainfall data yielding r=0.79 (regression slope=0.8; p<0.0001) in the sub-humid part of the study area and r=0.65 (regression slope=0.59, and p<0.0001) in the northern semi-arid part. The results suggest that despite the positive changes in rainfall (without significant increases in the months following the onset of the monsoon), the area has not fully recovered from the drought years of the 1960s, 70s, and 80s. These findings also highlight the implications of the current recovery on rain fed agriculture and water resources in the study area. The strong correlation and a root mean square error of 64.8 mm between the ARIMA model and the rainfall data used for this study indicates that the model can be satisfactorily used in forecasting rainfall in the in the sub-humid part of North-eastern Nigeria over a 24 months period.

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.

Rainfall Modification by Major Urban Areas: Observations from Spaceborne Rain Radar on the TRMM Satellite.

NASA Astrophysics Data System (ADS)

Shepherd, J. Marshall; Pierce, Harold; Negri, Andrew J.

2002-07-01

Data from the Tropical Rainfall Measuring Mission (TRMM) satellite's precipitation radar (PR) were employed to identify warm-season rainfall (1998-2000) patterns around Atlanta, Georgia; Montgomery, Alabama; Nashville, Tennessee; and San Antonio, Waco, and Dallas, Texas. Results reveal an average increase of about 28% in monthly rainfall rates within 30-60 km downwind of the metropolis, with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%-116%. The maximum value was 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. Results are consistent with the Metropolitan Meteorological Experiment (METROMEX) studies of St. Louis, Missouri, almost two decades ago and with more recent studies near Atlanta. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

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.

Clinical Malaria Transmission Trends and Its Association with Climatic Variables in Tubu Village, Botswana: A Retrospective Analysis.

PubMed

Chirebvu, Elijah; Chimbari, Moses John; Ngwenya, Barbara Ntombi; Sartorius, Benn

2016-01-01

Good knowledge on the interactions between climatic variables and malaria can be very useful for predicting outbreaks and preparedness interventions. We investigated clinical malaria transmission patterns and its temporal relationship with climatic variables in Tubu village, Botswana. A 5-year retrospective time series data analysis was conducted to determine the transmission patterns of clinical malaria cases at Tubu Health Post and its relationship with rainfall, flood discharge, flood extent, mean minimum, maximum and average temperatures. Data was obtained from clinical records and respective institutions for the period July 2005 to June 2010, presented graphically and analysed using the Univariate ANOVA and Pearson cross-correlation coefficient tests. Peak malaria season occurred between October and May with the highest cumulative incidence of clinical malaria cases being recorded in February. Most of the cases were individuals aged >5 years. Associations between the incidence of clinical malaria cases and several factors were strong at lag periods of 1 month; rainfall (r = 0.417), mean minimum temperature (r = 0.537), mean average temperature (r = 0.493); and at lag period of 6 months for flood extent (r = 0.467) and zero month for flood discharge (r = 0.497). The effect of mean maximum temperature was strongest at 2-month lag period (r = 0.328). Although malaria transmission patterns varied from year to year the trends were similar to those observed in sub-Saharan Africa. Age group >5 years experienced the greatest burden of clinical malaria probably due to the effects of the national malaria elimination programme. Rainfall, flood discharge and extent, mean minimum and mean average temperatures showed some correlation with the incidence of clinical malaria cases.

The Eastern Pacific ITCZ during the Boreal Spring

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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.

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.

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

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

Indonesia sea surface temperature from TRMM Microwave Imaging (TMI) sensor

NASA Astrophysics Data System (ADS)

Marini, Y.; Setiawan, K. T.

2018-05-01

We analysis the Tropical Rainfall Measuring Mission's (TRMM) Microwave Imager (TMI) data to monitor the sea surface temperature (SST) of Indonesia waters for a decade of 2005-2014. The TMI SST data shows the seasonal and interannual SST in Indonesian waters. In general, the SST average was highest in March-May period with SST average was 29.4°C, and the lowest was in June – August period with the SST average was 28.5°C. The monthly SST average fluctuation of Indonesian waters for 10 years tends to increase. The lowest SST average of Indonesia occurred in August 2006 with the SST average was 27.6° C, while the maximum occurred in May 2014 with the monthly SST average temperature was 29.9 ° C.

Rainfall Modification by Urban Areas: New Perspectives from TRMM

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew

2002-01-01

Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48% - 116%. The maximum value was 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. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

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.

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.

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

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Pierce, Harold; Starr, David OC. (Technical Monitor)

2001-01-01

This study represents one of the first published attempts to identify rainfall modification by urban areas using satellite-based rainfall measurements. Data from the first space-based rain-radar, the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of the data enables identification of rainfall patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage chances are relative to an upwind CONTROL area. It was also found that maximum rainfall rates in the downwind impact area can exceed the mean value in the upwind CONTROL area by 48%-116%. The maximum value was 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 consistent with METROMEX studies of St. Louis almost two decades ago and more recent studies near Atlanta. Future work will investi(yate hypothesized factors causing rainfall modification by urban areas. Additional work is also needed to provide more robust validation of space-based rain estimates near major urban areas. Such research has implications for urban planning, water resource management, and understanding human impact on the environment.

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.

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.

Geographical, meteorological and vectorial factors related to malaria re-emergence in Huang-Huai River of central China.

PubMed

Zhou, Shui S; Huang, Fang; Wang, Jian J; Zhang, Shao S; Su, Yun P; Tang, Lin H

2010-11-24

Malaria still represents a significant public health problem in China, and the cases dramatically increased in the areas along the Huang-Huai River of central China after 2001. Considering spatial aggregation of malaria cases and specific vectors, the geographical, meteorological and vectorial factors were analysed to determine the key factors related to malaria re-emergence in these particular areas. The geographic information of 357 malaria cases and 603 water bodies in 113 villages were collected to analyse the relationship between the residence of malaria cases and water body. Spearman rank correlation, multiple regression, curve fitting and trend analysis were used to explain the relationship between the meteorological factors and malaria incidence. Entomological investigation was conducted in two sites to get the vectorial capacity and the basic reproductive rate to determine whether the effect of vector lead to malaria re-emergence. The distances from household of cases to the nearest water-body was positive-skew distributed, the median was 60.9 m and 74% malaria cases were inhabited in the extent of 60 m near the water body, and the risk rate of people live there attacked by malaria was higher than others(OR = 1.6, 95%CI (1.042, 2.463), P < 0.05). The annual average temperature and rainfall may have close relationship with annual incidence. The average monthly temperature and rainfall were the key factors, and the correlation coefficients are 0.501 and 0.304(P < 0.01), respectively. Moreover, 75.3% changes of monthly malaria incidence contributed to the average monthly temperature (T(mean)), the average temperature of last two months(T(mean₀₁)) and the average rainfall of current month (R(mean)) and the regression equation was Y = -2.085 + 0.839I₁ + 0.998T(mean₀) - 0.86T(mean₀₁) + 0.16R(mean₀). All the collected mosquitoes were Anopheles sinensis. The vectorial capacity and the basic reproductive rate of An. sinensis in two sites were 0.6969, 0.4983 and 2.1604, 1.5447, respectively. The spatial distribution between malaria cases and water-body, the changing of meteorological factors, and increasing vectorial capacity and basic reproductive rate of An. sinensis leaded to malaria re-emergence in these areas.

Geographical, meteorological and vectorial factors related to malaria re-emergence in Huang-Huai River of central China

PubMed Central

2010-01-01

Background Malaria still represents a significant public health problem in China, and the cases dramatically increased in the areas along the Huang-Huai River of central China after 2001. Considering spatial aggregation of malaria cases and specific vectors, the geographical, meteorological and vectorial factors were analysed to determine the key factors related to malaria re-emergence in these particular areas. Methods The geographic information of 357 malaria cases and 603 water bodies in 113 villages were collected to analyse the relationship between the residence of malaria cases and water body. Spearman rank correlation, multiple regression, curve fitting and trend analysis were used to explain the relationship between the meteorological factors and malaria incidence. Entomological investigation was conducted in two sites to get the vectorial capacity and the basic reproductive rate to determine whether the effect of vector lead to malaria re-emergence. Results The distances from household of cases to the nearest water-body was positive-skew distributed, the median was 60.9 m and 74% malaria cases were inhabited in the extent of 60 m near the water body, and the risk rate of people live there attacked by malaria was higher than others(OR = 1.6, 95%CI (1.042, 2.463), P < 0.05). The annual average temperature and rainfall may have close relationship with annual incidence. The average monthly temperature and rainfall were the key factors, and the correlation coefficients are 0.501 and 0.304(P < 0.01), respectively. Moreover, 75.3% changes of monthly malaria incidence contributed to the average monthly temperature (Tmean), the average temperature of last two months(Tmean01) and the average rainfall of current month (Rmean) and the regression equation was Y = -2.085 + 0.839I1 + 0.998Tmean0 - 0.86Tmean01 + 0.16Rmean0. All the collected mosquitoes were Anopheles sinensis. The vectorial capacity and the basic reproductive rate of An. sinensis in two sites were 0.6969, 0.4983 and 2.1604, 1.5447, respectively. Conclusion The spatial distribution between malaria cases and water-body, the changing of meteorological factors, and increasing vectorial capacity and basic reproductive rate of An. sinensis leaded to malaria re-emergence in these areas. PMID:21092326

Distinctive Features of Surface Winds over Indian Ocean Between Strong and Weak Indian Summer Monsoons: Implications With Respect To Regional Rainfall Change in India

NASA Astrophysics Data System (ADS)

Zheng, Y.; Bourassa, M. A.; Ali, M. M.

2017-12-01

This observational study focuses on characterizing the surface winds in the Arabian Sea (AS), the Bay of Bengal (BoB), and the southern Indian Ocean (SIO) with special reference to the strong and weak Indian summer monsoon rainfall (ISMR) using the latest daily gridded rainfall dataset provided by the Indian Meteorological Department (IMD) and the Cross-Calibrated Multi-Platform (CCMP) gridded wind product version 2.0 produced by Remote Sensing System (RSS) over the overlapped period 1991-2014. The potential links between surface winds and Indian regional rainfall are also examined. Results indicate that the surface wind speeds in AS and BoB during June-August are almost similar during strong ISMRs and weak ISMRs, whereas significant discrepancies are observed during September. By contrast, the surface wind speeds in SIO during June-August are found to be significantly different between strong and weak ISMRs, where they are similar during September. The significant differences in monthly mean surface wind convergence between strong and weak ISMRs are not coherent in space in the three regions. However, the probability density function (PDF) distributions of daily mean area-averaged values are distinctive between strong and weak ISMRs in the three regions. The correlation analysis indicates the area-averaged surface wind speeds in AS and the area-averaged wind convergence in BoB are highly correlated with regional rainfall for both strong and weak ISMRs. The wind convergence in BoB during strong ISMRs is relatively better correlated with regional rainfall than during weak ISMRs. The surface winds in SIO do not greatly affect Indian rainfall in short timescales, however, they will ultimately affect the strength of monsoon circulation by modulating Indian Ocean Dipole (IOD) mode via atmosphere-ocean interactions.

Comparing Satellite Rainfall Estimates with Rain-Gauge Data: Optimal Strategies Suggested by a Spectral Model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Lau, William K. M. (Technical Monitor)

2002-01-01

Validation of satellite remote-sensing methods for estimating rainfall against rain-gauge data is attractive because of the direct nature of the rain-gauge measurements. Comparisons of satellite estimates to rain-gauge data are difficult, however, because of the extreme variability of rain and the fact that satellites view large areas over a short time while rain gauges monitor small areas continuously. In this paper, a statistical model of rainfall variability developed for studies of sampling error in averages of satellite data is used to examine the impact of spatial and temporal averaging of satellite and gauge data on intercomparison results. The model parameters were derived from radar observations of rain, but the model appears to capture many of the characteristics of rain-gauge data as well. The model predicts that many months of data from areas containing a few gauges are required to validate satellite estimates over the areas, and that the areas should be of the order of several hundred km in diameter. Over gauge arrays of sufficiently high density, the optimal areas and averaging times are reduced. The possibility of using time-weighted averages of gauge data is explored.

Influence of water management and natural variability on dissolved inorganic carbon dynamics in a mangrove-dominated estuary.

PubMed

Volta, Chiara; Ho, David T; Friederich, Gernot; Engel, Victor C; Bhat, Mahadev

2018-09-01

High-resolution time series measurements of temperature, salinity, pH and pCO 2 were made during the period October 2014-September 2015 at the midpoint of Shark River, a 15km tidal river that originates in the freshwater Everglades of south Florida (USA) and discharges into the Gulf of Mexico. Dissolved inorganic carbon dynamics in this system vary over time, and during this study could be classified into three distinct regimes corresponding to October 2014-February 2015 (a wet to dry season transition period), March-May 2015 (dry period) and July-September 2015 (wet period). Average net longitudinal dissolved inorganic carbon (DIC) fluxes and air-water CO 2 fluxes from the Shark River estuary were determined for the three periods. Net DIC fluxes to the coast were estimated to vary between 23.2 and 25.4×10 5 mold -1 with an average daily DIC flux of 24.3×10 5 mold -1 during the year of study. CO 2 emissions ranged between 5.5 and 7.8×10 5 mold -1 with an average daily value of 6.4×10 5 mold -1 during the year. The differences in estuarine carbon fluxes during the study period are attributed to differences in the relative importance of hydro-climatological drivers. Results suggest that, during months characterized by reduced rainfall, carbon fluxes are affected by water management via control structures in the upstream Everglades marshes. During months with high rainfall, when culverts are closed and rainfall events are more frequent, carbon fluxes depend more on other forcings, such as rainfall and groundwater discharge. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Alluvial groundwater recharge estimation in semi-arid environment using remotely sensed data

NASA Astrophysics Data System (ADS)

Coelho, Victor Hugo R.; Montenegro, Suzana; Almeida, Cristiano N.; Silva, Bernardo B.; Oliveira, Leidjane M.; Gusmão, Ana Cláudia V.; Freitas, Emerson S.; Montenegro, Abelardo A. A.

2017-05-01

Data limitations on groundwater (GW) recharge over large areas are still a challenge for efficient water resource management, especially in semi-arid regions. Thus, this study seeks to integrate hydrological cycle variables from satellite imagery to estimate the spatial distribution of GW recharge in the Ipanema river basin (IRB), which is located in the State of Pernambuco in Northeast Brazil. Remote sensing data, including monthly maps (2011-2012) of rainfall, runoff and evapotranspiration, are used as input for the water balance method within Geographic Information Systems (GIS). Rainfall data are derived from the TRMM Multi-satellite Precipitation Analysis (TMPA) Version 7 (3B43V7) product and present the same monthly average temporal distributions from 15 rain gauges that are distributed over the study area (r = 0.93 and MAE = 12.7 mm), with annual average estimates of 894.3 (2011) and 300.7 mm (2012). The runoff from the Natural Resources Conservation Service (NRCS) method, which is based on regional soil information and Thematic Mapper (TM) sensor image, represents 29% of the TMPA rainfall that was observed across two years of study. Actual evapotranspiration data, which were provided by the SEBAL application of MODIS images, present annual averages of 1213 (2011) and 1067 (2012) mm. The water balance results reveal a large inter-annual difference in the IRB GW recharge, which is characterized by different rainfall regimes, with averages of 30.4 (2011) and 4.7 (2012) mm year-1. These recharges were mainly observed between January and July in regions with alluvial sediments and highly permeable soils. The GW recharge approach with remote sensing is compared to the WTF (Water Table Fluctuation) method, which is used in an area of alluvium in the IRB. The estimates from these two methods exhibit reliable annual agreement, with average values of 154.6 (WTF) and 124.6 (water balance) mm in 2011. These values correspond to 14.89 and 13.53% of the rainfall that was recorded at the rain gauges and the TMPA, respectively. Only the WTF method indicates a very low recharge of 15.9 mm for the second year. The values in this paper provide reliable insight regarding the use of remotely sensed data to evaluate the rates of alluvial GW recharge in regions where the potential runoff cannot be disregarded from WB equation and must be calculated spatially.

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Rainfall over Friuli-Venezia Giulia: High amounts and strong geographical gradients

NASA Astrophysics Data System (ADS)

Ceschia, M.; Micheletti, St.; Carniel, R.

1991-12-01

The precipitation distribution over Friuli-Venezia Giulia — the easternmost region of Northern Italy extending from the Adriatic Sea to the Alps — has been studied. Monthly rainfall data over the region and the bordering areas of Veneto and Slovenia during the period from 1951 to 1986 have been analyzed by standard statistical methods, including cluster analysis. The overall results emphasize a distribution with rainfall increasing from the sea to the prealpine areas. The highest precipitations were recorded over the Musi-Canin range, with average values exceeding 3 200 mm per year. Noteworthy is the unforeseen subdivision of the region by the clustering procedure by means of the Angot index.

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.

Epochal changes in the association between malaria epidemics and El Niño in Sri Lanka

PubMed Central

Zubair, Lareef; Galappaththy, Gawrie N; Yang, Hyemin; Chandimala, Janaki; Yahiya, Zeenas; Amerasinghe, Priyanie; Ward, Neil; Connor, Stephen J

2008-01-01

Background El Niño events were suggested as a potential predictor for malaria epidemics in Sri Lanka based on the coincidence of nine out of 16 epidemics with El Niño events from 1870 to 1945. Here the potential for the use of El Niño predictions to anticipate epidemics was examined using enhanced climatic and epidemiological data from 1870 to 2000. Methods The epidemics start years were identified by the National Malaria Control Programme and verified against epidemiological records for consistency. Monthly average rainfall climatologies were estimated for epidemic and non-epidemic years; as well El Niño, Neutral and La Niña climatic phases. The relationship between El Niño indices and epidemics was examined to identify 'epochs' of consistent association. The statistical significance of the association between El Niño and epidemics for different epochs was characterized. The changes in the rainfall-El Niño relationships over the decade were examined using running windowed correlations. The anomalies in rainfall climatology during El Niño events for different epochs were compared. Results The relationship between El Niño and epidemics from 1870 to 1927 was confirmed. The anomalies in monthly average rainfall during El Niño events resembled the anomalies in monthly average rainfall during epidemics during this period. However, the relationship between El Niño and epidemics broke down from 1928 to 1980. Of the three epidemics in these six decades, only one coincided with an El Niño. Not only did this relationship breakdown but epidemics were more likely to occur in periods with a La Niña tendency. After 1980, three of four epidemics coincided with El Niño. Conclusion The breakdown of the association between El Niño and epidemics after 1928 is likely due to an epochal change in the El Niño-rainfall relationship in Sri Lanka around the 1930's. It is unlikely that this breakdown is due to the insecticide spraying programme that began in 1945 since the breakdown started in 1928. Nor does it explain the occurrence of epidemics during La Niña phase from 1928 to 1980. Although there has been renewed coincidence with El Niño after 1980, this record is too short for establishing a reliable relationship. PMID:18652697

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

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.

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.

Scaling Linguistic Characterization of Precipitation Variability

NASA Astrophysics Data System (ADS)

Primo, C.; Gutierrez, J. M.

2003-04-01

Rainfall variability is influenced by changes in the aggregation of daily rainfall. This problem is of great importance for hydrological, agricultural and ecological applications. Rainfall averages, or accumulations, are widely used as standard climatic parameters. However different aggregation schemes may lead to the same average or accumulated values. In this paper we present a fractal method to characterize different aggregation schemes. The method provides scaling exponents characterizing weekly or monthly rainfall patterns for a given station. To this aim, we establish an analogy with linguistic analysis, considering precipitation as a discrete variable (e.g., rain, no rain). Each weekly, or monthly, symbolic precipitation sequence of observed precipitation is then considered as a "word" (in this case, a binary word) which defines a specific weekly rainfall pattern. Thus, each site defines a "language" characterized by the words observed in that site during a period representative of the climatology. Then, the more variable the observed weekly precipitation sequences, the more complex the obtained language. To characterize these languages, we first applied the Zipf's method obtaining scaling histograms of rank ordered frequencies. However, to obtain significant exponents, the scaling must be maintained some orders of magnitude, requiring long sequences of daily precipitation which are not available at particular stations. Thus this analysis is not suitable for applications involving particular stations (such as regionalization). Then, we introduce an alternative fractal method applicable to data from local stations. The so-called Chaos-Game method uses Iterated Function Systems (IFS) for graphically representing rainfall languages, in a way that complex languages define complex graphical patterns. The box-counting dimension and the entropy of the resulting patterns are used as linguistic parameters to quantitatively characterize the complexity of the patterns. We illustrate the high climatological discrimination power of the linguistic parameters in the Iberian peninsula, when compared with other standard techniques (such as seasonal mean accumulated precipitation). As an example, standard and linguistic parameters are used as inputs for a clustering regionalization method, comparing the resulting clusters.

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.

Drought in Southeastern United States

NASA Technical Reports Server (NTRS)

2007-01-01

May 2007 was a record-setting month in Georgia. Typically a dry month in this southern state, May 2007 was exceptionally so, with many locations setting record-low rainfall records and some receiving no rain at all, said state climatologist David Emory Stooksbury on GeorgiaDrought.org. The lack of rain slowed plant growth, as shown in this vegetation index image. The Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Terra satellite collected the data used to make this image between May 9 and May 24, 2007. The image shows vegetation conditions compared to average conditions observed from 2000 through 2006. Areas in which plants are more sparse or are growing more slowly than average are brown, while better-than-average growth is green. Georgia and its neighbors (South Carolina, Alabama, and Florida) are all brown, an indication that the lack of rainfall is suppressing plant growth. The gray area in southern Georgia and northern Florida shows where MODIS could not collect valid vegetation measurements, either because of clouds or smoke. In this case, the area corresponds with land that burned during this period and was probably masked by smoke. NASA image created by Jesse Allen, Earth Observatory, using data provided by Inbal Reshef, Global Agricultural Monitoring Project.

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.

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.

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.

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.

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

PubMed

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

2013-08-01

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

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.

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.

Environmental water demand assessment under climate change conditions.

PubMed

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

2017-07-01

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

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.

Development of microwave rainfall retrieval algorithm for climate applications

NASA Astrophysics Data System (ADS)

KIM, J. H.; Shin, D. B.

2014-12-01

With the accumulated satellite datasets for decades, it is possible that satellite-based data could contribute to sustained climate applications. Level-3 products from microwave sensors for climate applications can be obtained from several algorithms. For examples, the Microwave Emission brightness Temperature Histogram (METH) algorithm produces level-3 rainfalls directly, whereas the Goddard profiling (GPROF) algorithm first generates instantaneous rainfalls and then temporal and spatial averaging process leads to level-3 products. The rainfall algorithm developed in this study follows a similar approach to averaging instantaneous rainfalls. However, the algorithm is designed to produce instantaneous rainfalls at an optimal resolution showing reduced non-linearity in brightness temperature (TB)-rain rate(R) relations. It is found that the resolution tends to effectively utilize emission channels whose footprints are relatively larger than those of scattering channels. This algorithm is mainly composed of a-priori databases (DBs) and a Bayesian inversion module. The DB contains massive pairs of simulated microwave TBs and rain rates, obtained by WRF (version 3.4) and RTTOV (version 11.1) simulations. To improve the accuracy and efficiency of retrieval process, data mining technique is additionally considered. The entire DB is classified into eight types based on Köppen climate classification criteria using reanalysis data. Among these sub-DBs, only one sub-DB which presents the most similar physical characteristics is selected by considering the thermodynamics of input data. When the Bayesian inversion is applied to the selected DB, instantaneous rain rate with 6 hours interval is retrieved. The retrieved monthly mean rainfalls are statistically compared with CMAP and GPCP, respectively.

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

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.

The impact of environmental factors on marine turtle stranding rates

PubMed Central

Flint, Mark; Limpus, Colin J.; Mills, Paul C.

2017-01-01

Globally, tropical and subtropical regions have experienced an increased frequency and intensity in extreme weather events, ranging from severe drought to protracted rain depressions and cyclones, these coincided with an increased number of marine turtles subsequently reported stranded. This study investigated the relationship between environmental variables and marine turtle stranding. The environmental variables examined in this study, in descending order of importance, were freshwater discharge, monthly mean maximum and minimum air temperatures, monthly average daily diurnal air temperature difference and rainfall for the latitudinal hotspots (-27°, -25°, -23°, -19°) along the Queensland coast as well as for major embayments within these blocks. This study found that marine turtle strandings can be linked to these environmental variables at different lag times (3–12 months), and that cumulative (months added together for maximum lag) and non-cumulative (single month only) effects cause different responses. Different latitudes also showed different responses of marine turtle strandings, both in response direction and timing.Cumulative effects of freshwater discharge in all latitudes resulted in increased strandings 10–12 months later. For latitudes -27°, -25° and -23° non-cumulative effects for discharge resulted in increased strandings 7–12 months later. Latitude -19° had different results for the non-cumulative bay with strandings reported earlier (3–6 months). Monthly mean maximum and minimum air temperatures, monthly average daily diurnal air temperature difference and rainfall had varying results for each examined latitude. This study will allow first responders and resource managers to be better equipped to deal with increased marine turtle stranding rates following extreme weather events. PMID:28771635

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

Tagestad, Jerry; Brooks, Matthew; Cullinan, Valerie

Mojave Desert ecosystem processes are dependent upon the amount and seasonality of precipitation. Multi-decadal periods of drought or above-average rainfall affect landscape vegetation condition, biomass and susceptibility to fire. The seasonality of precipitation events can also affect the likelihood of lightning, a key ignition source for fires. To develop an understanding of precipitation regimes and fire patterns we used monthly average precipitation data and GIS data representing burned areas from 1971-2010. We applied a K-means cluster analysis to the monthly precipitation data identifying three distinct precipitation seasons; winter (October – March), spring (April-June) and summer (July-September) and four discrete precipitationmore » regimes within the Mojave ecoregion.« less

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.

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.

Spatial Patterns and Socioecological Drivers of Dengue Fever Transmission in Queensland, Australia

PubMed Central

Clements, Archie; Williams, Gail; Tong, Shilu; Mengersen, Kerrie

2011-01-01

Background: Understanding how socioecological factors affect the transmission of dengue fever (DF) may help to develop an early warning system of DF. Objectives: We examined the impact of socioecological factors on the transmission of DF and assessed potential predictors of locally acquired and overseas-acquired cases of DF in Queensland, Australia. Methods: We obtained data from Queensland Health on the numbers of notified DF cases by local government area (LGA) in Queensland for the period 1 January 2002 through 31 December 2005. Data on weather and the socioeconomic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive model was fitted at the LGA level to quantify the relationship between DF and socioecological factors. Results: Our estimates suggest an increase in locally acquired DF of 6% [95% credible interval (CI): 2%, 11%] and 61% (95% CI: 2%, 241%) in association with a 1-mm increase in average monthly rainfall and a 1°C increase in average monthly maximum temperature between 2002 and 2005, respectively. By contrast, overseas-acquired DF cases increased by 1% (95% CI: 0%, 3%) and by 1% (95% CI: 0%, 2%) in association with a 1-mm increase in average monthly rainfall and a 1-unit increase in average socioeconomic index, respectively. Conclusions: Socioecological factors appear to influence the transmission of DF in Queensland, but the drivers of locally acquired and overseas-acquired DF may differ. DF risk is spatially clustered with different patterns for locally acquired and overseas-acquired cases. PMID:22015625

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.

Epidemiologic and environmental risk factors of rift valley fever in southern Africa from 2008 to 2011

USDA-ARS?s Scientific Manuscript database

BACKGROUND: Rift Valley fever outbreaks have been associated with periods of widespread and above average rainfall over several months which allows for the virus infected mosquito vector populations to emerge and propagate. This has provided basis to develop complex models based on environmental fa...

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.

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.

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.

Influence of rainfall microstructure on rainfall interception

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

When El Nino Rages: How Satellite Data Can Help Water-Stressed Islands

NASA Astrophysics Data System (ADS)

Kruk, M. C.; Sutton, J. R. P.; Luchetti, N.; Wright, E.; Marra, J. J.

2016-02-01

The United States Affiliated Pacific Islands (USAPI) are highly susceptible to extreme precipitation events such as drought and flooding, which directly affect their freshwater availability. Precipitation distribution differs by sub-region, and is predominantly influenced by phases of the El Niño Southern Oscillation (ENSO). Forecasters currently rely on ENSO climatologies from sparse in situ station data to inform their precipitation outlooks. To address this spatial gap, a unique NOAA/NASA collaborative project updated the ENSO-based rainfall climatology for the Exclusive Economic Zones (EEZ's) encompassing Hawaii and the USAPI using NOAA's 15km PERSIANN Climate Data Record. This data provided a 30-year record (1984-2015) of daily precipitation at 0.25° resolution, which was used to calculate monthly, seasonal, and yearly precipitation average. The 478-page satellite-derived reference atlas not only illustrates the long-term average rainfall distribution by month, but also shows the percent departure from average for each three-month season based on the Oceanic Niño Index (ONI) for weak, moderate, and strong ENSO phases. Local weather service offices are already using the atlas to better understand precipitation patterns across their regions, and as such are able to produce more accurate forecasts during different ENSO phases to inform adaptation, conservation, and mitigation options for drought and flooding events. The presentation will showcase the development of the atlas, highlight some of the challenges encountered, and demonstrate how CDRs can be used to inform decision-making.

The Relationship Between Monthdisease Incidence Rate and Climatic Factor of Classical Swine Fever

NASA Astrophysics Data System (ADS)

Wang, Hongbin; Xu, Danning; Xiao, Jianhua; Zhang, Ru; Dong, Jing

The Swine Fever is a kind of acute, highly infective epidemic disease of animals; it is name as Classical Swine Fever (CSF) by World animal Health organization. Meteorological factors such as temperature, air pressure and rainfall affect the epidemic of CSF significantly through intermediary agent and CSF viral directly. However there is significant difference among different region for mode of effects. Accordingly, the analyze must adopt different methods. The dependability between incidence rate each month of CSF and meteorological factors from 1999 to 2004 was analyzed in this paper. The function of meteorological factors on CSF was explored and internal law was expected to be discovered. The correlation between the incidence rate of Swine Fever and meteorological factors, thus the foundation analysis of the early warning and the decision-making was made, the result indicated that the incidence rate of CSF has negative correlation with temperature, rainfall, cloudage; relative humidity has positive correlation with disease; for air pressure, except average air pressure of one month, other air pressure factors have positive correlation with disease; for wind speed, except Difference among moths of wind speed and average temperature of one month. have positive correlation with disease, other wind speed factors has negative correlation with disease.

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

Impact of landslides induced by 2014 northeast monsoon extreme rain in Malaysia

NASA Astrophysics Data System (ADS)

Fukuoka, Hiroshi; Koay, Swee Peng; Sakai, Naoki; Lateh, Habibah

2016-04-01

In December 2014, northeast monsoon brought extreme rainfalls to Malaysia, mainly in the eastern coast of Peninsular Malaysia and coastal area in Sabah and Sarawak. In this month, many of the rain gauge records in this area exceeded 1,000 mm, which is about 1/3 of average annual rainfall precipitation (2,850mm/year) in Malaysia. This unexpected heavy rainfall induced landslides and floods which brought about large-scale losses in Malaysia equivalent to several hundred million USD as thousands of residents had evacuated from hometown for months, and factories, schools and business activities were shut down for weeks. Among the major infrastructure of the nation, East-west Highway was subjected to damages by 21 landslides. Two large-scale landslides cut off the highway for a week. Authors had installed landslide monitoring instruments at reactivated landslide sites along the highway at N05° 36.042' E101° 35.546'. Records by in-situ inclinometers showed clear deformation from 17th December to 26th December, associated with certain change in piezometeres record for groundwater level monitoring. Several cracks occurred in the slope.

Monitoring and Prediction of Precipitable Water Vapor using GPS data in Turkey

NASA Astrophysics Data System (ADS)

Ansari, Kutubuddin; Althuwaynee, Omar F.; Corumluoglu, Ozsen

2016-12-01

Although Global Positioning System (GPS) primarily provide accurate estimates of position, velocity and time of the receiver, as the signals pass through the atmoshphere carrying its signatures, thus offers opportunities for atmoshpheric applications. Precipitable water vapor (PWV) is a vital component of the atmosphere and significantly influences atmospheric processes like rainfall and atmospheric temperature. The developing networks of continuously operating GPS can be used to efficiently estimate PWV. The Turkish Permanent GPS Network (TPGN) is employed to monitor PWV information in Turkey. This work primarily aims to derive long-term data of PWV by using atmospheric path delays observed through continuously operating TPGN from November 2014 to October 2015. A least square mathematical approach was then applied to establish the relation of the observed PWV to rainfall and temperature. The modeled PWV was correlated with PWV estimated from GPS data, with an average correlation of 67.10 %-88.60 %. The estimated root mean square error (RMSE) varied from 2.840 to 6.380, with an average of 4.697. Finally, data of TPGN, rainfall, and temperature were obtained for less than 2 months (November 2015 to December 2015) and assessed to validate the mathematical model. This study provides a basis for determining PWV by using rainfall and temperature data.

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.

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.

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.

An Investigation of the Influence of Urban Areas on Rainfall Using the TRMM Satellite and a Cloud-Mesoscale Model

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; OCStarr, David (Technical Monitor)

2002-01-01

A recent paper by Shepherd and Pierce (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of approx. 28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48%-116%. The maximum value was 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. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

Regionalization of monthly rainfall erosivity patternsin Switzerland

NASA Astrophysics Data System (ADS)

Schmidt, Simon; Alewell, Christine; Panagos, Panos; Meusburger, Katrin

2016-10-01

One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy and a maximum 30 min intensity (I30). Rainfall erosivity is often expressed as R-factor in soil erosion risk models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). As rainfall erosivity is closely correlated with rainfall amount and intensity, the rainfall erosivity of Switzerland can be expected to have a regional characteristic and seasonal dynamic throughout the year. This intra-annual variability was mapped by a monthly modeling approach to assess simultaneously spatial and monthly patterns of rainfall erosivity. So far only national seasonal means and regional annual means exist for Switzerland. We used a network of 87 precipitation gauging stations with a 10 min temporal resolution to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) were used to select spatial covariates which explain the spatial and temporal patterns of the R-factor for each month across Switzerland. The monthly R-factor is mapped by summarizing the predicted R-factor of the regression equation and the corresponding residues of the regression, which are interpolated by ordinary kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been included such as snow depths, a combination product of hourly precipitation measurements and radar observations (CombiPrecip), daily Alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Topographic parameters (elevation, slope) were also significant explanatory variables for single months. The comparison of the 12 monthly rainfall erosivity maps showed a distinct seasonality with the highest rainfall erosivity in summer (June, July, and August) influenced by intense rainfall events. Winter months have the lowest rainfall erosivity. A proportion of 62 % of the total annual rainfall erosivity is identified within four months only (June-September). The highest erosion risk can be expected in July, where not only rainfall erosivity but also erosivity density is high. In addition to the intra-annual temporal regime, a spatial variability of this seasonality was detectable between different regions of Switzerland. The assessment of the dynamic behavior of the R-factor is valuable for the identification of susceptible seasons and regions.

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.

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)

Time series analysis of cholera in Matlab, Bangladesh, during 1988-2001.

PubMed

Ali, Mohammad; Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-03-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001 were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab.

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.

Random errors of oceanic monthly rainfall derived from SSM/I using probability distribution functions

NASA Technical Reports Server (NTRS)

Chang, Alfred T. C.; Chiu, Long S.; Wilheit, Thomas T.

1993-01-01

Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. (1991) are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50-60 percent for each 5 deg x 5 deg box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8 percent, a correlation of 0.7, and an rms difference of 55 percent.

The influence of anthropogenic landscape changes on weather in south Florida

USGS Publications Warehouse

Pielke, R.A.; Walko, R.L.; Steyaert, L.T.; Vidale, P.L.; Liston, G.E.; Lyons, W.A.; Chase, T.N.

1999-01-01

Using identical observed meteorology for lateral boundary conditions, the Regional Atmospheric Modeling System was integrated for July-August 1973 for south Florida. Three experiments were performed-one using the observed 1973 landscape, another the 1993 landscape, and the third the 1900 landscape, when the region was close to its natural state. Over the 2-month period, there was a 9% decrease in rainfall averaged over south Florida with the 1973 landscape and an 11% decrease with the 1993 landscape, as compared with the model results when the 1900 landscape is used. The limited available observations of trends in summer rainfall over this region are consistent with these trends.

Identification of climate-resilient integrated nutrient management practices for rice-rice cropping system--an empirical approach to uphold food security.

PubMed

Subash, N; Gangwar, B; Singh, Rajbir; Sikka, A K

2015-01-01

Yield datasets of long-term experiments on integrated nutrient management in rice-rice cropping systems were used to investigate the relationship of variability in rainfall, temperature, and integrated nutrient management (INM) practices in rice-rice cropping system in three different agroecological regions of India. Twelve treatments with different combinations of inorganic (chemical fertilizer) and organic (farmyard manure, green manure, and paddy straw) were compared with farmer's conventional practice. The intraseasonal variations in rice yields are largely driven by rainfall during kharif rice and by temperature during rabi rice. Half of the standard deviation from the average monthly as well as seasonal rainfall during kharif rice and 1 °C increase or decrease from the average maximum and minimum temperature during rabi rice has been taken as the classification of yield groups. The trends in the date of effective onset of monsoon indicate a 36-day delay during the 30-year period at Rajendranagar, which is statistically significant at 95 % confidence level. The mean annual maximum temperature shows an increasing trend in all the study sites. The length of monsoon also showed a shrinking trend in the rate of 40 days during the 30-year study period at Rajendranagar representing a semiarid region. At Bhubaneshwar, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through green manure resulted in an overall average higher increase of 5.1 % in system productivity under both excess and deficit rainfall years and also during the years having seasonal mean maximum temperature ≥35 °C. However, at Jorhat, the application of 50 % recommended NPK through chemical fertilizers and 50 % N through straw resulted in an overall average higher increase of 7.4 % in system productivity, while at Rajendranagar, the application of 75 % NPK through chemical fertilizers and 25 % N through green manusre resulted in an overall average higher increase of 8.8 % in system productivity. This study highlights the adaptive capacity of different integrated nutrient management practices to rainfall and temperature variability under a rice-rice cropping system in humid, subhumid, and semiarid ecosystems.

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.

Interannual Rainfall Variability in North-East Brazil: Observation and Model Simulation

NASA Astrophysics Data System (ADS)

Harzallah, A.; Rocha de Aragão, J. O.; Sadourny, R.

1996-08-01

The relationship between interannual variability of rainfall in north-east Brazil and tropical sea-surface temperature is studied using observations and model simulations. The simulated precipitation is the average of seven independent realizations performed using the Laboratoire de Météorologie Dynamique atmospheric general model forced by the 1970-1988 observed sea-surface temperature. The model reproduces very well the rainfall anomalies (correlation of 091 between observed and modelled anomalies). The study confirms that precipitation in north-east Brazil is highly correlated to the sea-surface temperature in the tropical Atlantic and Pacific oceans. Using the singular value decomposition method, we find that Nordeste rainfall is modulated by two independent oscillations, both governed by the Atlantic dipole, but one involving only the Pacific, the other one having a period of about 10 years. Correlations between precipitation in north-east Brazil during February-May and the sea-surface temperature 6 months earlier indicate that both modes are essential to estimate the quality of the rainy season.

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.

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.

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.

Hydroelectric production from Brazil's São Francisco River could cease due to climate change and inter-annual variability.

PubMed

de Jong, Pieter; Tanajura, Clemente Augusto Souza; Sánchez, Antonio Santos; Dargaville, Roger; Kiperstok, Asher; Torres, Ednildo Andrade

2018-09-01

By the end of this century higher temperatures and significantly reduced rainfall are projected for the Brazilian North and Northeast (NE) regions due to Global Warming. This study examines the impact of these long-term rainfall changes on the Brazilian Northeast's hydroelectric production. Various studies that use different IPCC models are examined in order to determine the average rainfall reduction by the year 2100 in comparison to baseline data from the end of the 20th century. It was found that average annual rainfall in the NE region could decrease by approximately 25-50% depending on the emissions scenario. Analysis of historical rainfall data in the São Francisco basin during the last 57years already shows a decline of more than 25% from the 1961-90 long-term average. Moreover, average annual rainfall in the basin has been below its long-term average every year bar one since 1992. If this declining trend continues, rainfall reduction in the basin could be even more severe than the most pessimistic model projections. That is, the marked drop in average rainfall projected for 2100, based on the IPCC high emissions scenario, could actually eventuate before 2050. Due to the elasticity factor between rainfall and streamflow and because of increased amounts of irrigation in the São Francisco basin, the reduction in the NE's average hydroelectric production in the coming decades could be double the predicted decline in rainfall. Conversely, it is estimated that wind power potential in the Brazilian NE will increase substantially by 2100. Therefore both wind and solar power will need to be significantly exploited in order for the NE region to sustainably replace lost hydroelectric production. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeling the Effect of Summertime Heating on Urban Runoff Temperature

NASA Astrophysics Data System (ADS)

Thompson, A. M.; Gemechu, A. L.; Norman, J. M.; Roa-Espinosa, A.

2007-12-01

Urban impervious surfaces absorb and store thermal energy, particularly during warm summer months. During a rainfall/runoff event, thermal energy is transferred from the impervious surface to the runoff, causing it to become warmer. As this higher temperature runoff enters receiving waters, it can be harmful to coldwater habitat. A simple model has been developed for the net energy flux at the impervious surfaces of urban areas to account for the heat transferred to runoff. Runoff temperature is determined as a function of the physical characteristics of the impervious areas, the weather, and the heat transfer between the moving film of runoff and the heated impervious surfaces that commonly exist in urban areas. Runoff from pervious surfaces was predicted using the Green- Ampt Mein-Larson infiltration excess method. Theoretical results were compared to experimental results obtained from a plot-scale field study conducted at the University of Wisconsin's West Madison Agricultural Research Station. Surface temperatures and runoff temperatures from asphalt and sod plots were measured throughout 15 rainfall simulations under various climatic conditions during the summers of 2004 and 2005. Average asphalt runoff temperatures ranged from 23.2°C to 37.1°C. Predicted asphalt runoff temperatures were in close agreement with measured values for most of the simulations (average RMSE = 4.0°C). Average pervious runoff temperatures ranged from 19.7° to 29.9°C and were closely approximated by the rainfall temperature (RMSE = 2.8°C). Predicted combined asphalt and sod runoff temperatures using a flow-weighted average were in close agreement with observed values (average RMSE = 3.5°C).

Modeling Seasonal Influenza Transmission and Its Association with Climate Factors in Thailand Using Time-Series and ARIMAX Analyses.

PubMed

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

2015-01-01

Influenza is a worldwide respiratory infectious disease that easily spreads from one person to another. Previous research has found that the influenza transmission process is often associated with climate variables. In this study, we used autocorrelation and partial autocorrelation plots to determine the appropriate autoregressive integrated moving average (ARIMA) model for influenza transmission in the central and southern regions of Thailand. The relationships between reported influenza cases and the climate data, such as the amount of rainfall, average temperature, average maximum relative humidity, average minimum relative humidity, and average relative humidity, were evaluated using cross-correlation function. Based on the available data of suspected influenza cases and climate variables, the most appropriate ARIMA(X) model for each region was obtained. We found that the average temperature correlated with influenza cases in both central and southern regions, but average minimum relative humidity played an important role only in the southern region. The ARIMAX model that includes the average temperature with a 4-month lag and the minimum relative humidity with a 2-month lag is the appropriate model for the central region, whereas including the minimum relative humidity with a 4-month lag results in the best model for the southern region.

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.

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

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.

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.

Drought prediction using co-active neuro-fuzzy inference system, validation, and uncertainty analysis (case study: Birjand, Iran)

NASA Astrophysics Data System (ADS)

Memarian, Hadi; Pourreza Bilondi, Mohsen; Rezaei, Majid

2016-08-01

This work aims to assess the capability of co-active neuro-fuzzy inference system (CANFIS) for drought forecasting of Birjand, Iran through the combination of global climatic signals with rainfall and lagged values of Standardized Precipitation Index (SPI) index. Using stepwise regression and correlation analyses, the signals NINO 1 + 2, NINO 3, Multivariate Enso Index, Tropical Southern Atlantic index, Atlantic Multi-decadal Oscillation index, and NINO 3.4 were recognized as the effective signals on the drought event in Birjand. Based on the results from stepwise regression analysis and regarding the processor limitations, eight models were extracted for further processing by CANFIS. The metrics P-factor and D-factor were utilized for uncertainty analysis, based on the sequential uncertainty fitting algorithm. Sensitivity analysis showed that for all models, NINO indices and rainfall variable had the largest impact on network performance. In model 4 (as the model with the lowest error during training and testing processes), NINO 1 + 2(t-5) with an average sensitivity of 0.7 showed the highest impact on network performance. Next, the variables rainfall, NINO 1 + 2(t), and NINO 3(t-6) with the average sensitivity of 0.59, 0.28, and 0.28, respectively, could have the highest effect on network performance. The findings based on network performance metrics indicated that the global indices with a time lag represented a better correlation with El Niño Southern Oscillation (ENSO). Uncertainty analysis of the model 4 demonstrated that 68 % of the observed data were bracketed by the 95PPU and D-Factor value (0.79) was also within a reasonable range. Therefore, the fourth model with a combination of the input variables NINO 1 + 2 (with 5 months of lag and without any lag), monthly rainfall, and NINO 3 (with 6 months of lag) and correlation coefficient of 0.903 (between observed and simulated SPI) was selected as the most accurate model for drought forecasting using CANFIS in the climatic region of Birjand.

SPECIAL SESSION: (H21) on Global Precipitation Mission for Hydrology and Hydrometeorology. Sampling-Error Considerations for GPM-Era Rainfall Products

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Lau, William K. M. (Technical Monitor)

2002-01-01

The proposed Global Precipitation Mission (GPM) builds on the success of the Tropical Rainfall Measuring Mission (TRMM), offering a constellation of microwave-sensor-equipped smaller satellites in addition to a larger, multiply-instrumented "mother" satellite that will include an improved precipitation radar system to which the precipitation estimates of the smaller satellites can be tuned. Coverage by the satellites will be nearly global rather than being confined as TRMM was to lower latitudes. It is hoped that the satellite constellation can provide observations at most places on the earth at least once every three hours, though practical considerations may force some compromises. The GPM system offers the possibility of providing precipitation maps with much better time resolution than the monthly averages around which TRMM was planned, and therefore opens up new possibilities for hydrology and data assimilation into models. In this talk, methods that were developed for estimating sampling error in the rainfall averages that TRMM is providing will be used to estimate sampling error levels for GPM-era configurations. Possible impacts on GPM products of compromises in the sampling frequency will be discussed.

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 averaging of oceanic rainfall variability using underwater sound: Ionian Sea rainfall experiment 2004.

PubMed

Nystuen, Jeffrey A; Amitai, Eyal; Anagnostou, Emmanuel N; Anagnostou, Marios N

2008-04-01

An experiment to evaluate the inherent spatial averaging of the underwater acoustic signal from rainfall was conducted in the winter of 2004 in the Ionian Sea southwest of Greece. A mooring with four passive aquatic listeners (PALs) at 60, 200, 1000, and 2000 m was deployed at 36.85 degrees N, 21.52 degrees E, 17 km west of a dual-polarization X-band coastal radar at Methoni, Greece. The acoustic signal is classified into wind, rain, shipping, and whale categories. It is similar at all depths and rainfall is detected at all depths. A signal that is consistent with the clicking of deep-diving beaked whales is present 2% of the time, although there was no visual confirmation of whale presence. Co-detection of rainfall with the radar verifies that the acoustic detection of rainfall is excellent. Once detection is made, the correlation between acoustic and radar rainfall rates is high. Spatial averaging of the radar rainfall rates in concentric circles over the mooring verifies the larger inherent spatial averaging of the rainfall signal with recording depth. For the PAL at 2000 m, the maximum correlation was at 3-4 km, suggesting a listening area for the acoustic rainfall measurement of roughly 30-50 km(2).

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.

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

PubMed

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

2014-09-01

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

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.

Precipitation Climatology over Mediterranean Basin from Ten Years of TRMM Measurements

NASA Technical Reports Server (NTRS)

Mehta, Amita V.; Yang, Song

2008-01-01

Climatological features of mesoscale rain activities over the Mediterranean region between 5 W-40 E and 28 N-48 N are examined using the Tropical Rainfall Measuring Mission (TRMM) 3B42 and 2A25 rain products. The 3B42 rainrates at 3-hourly, 0.25 deg x 0.25 deg spatial resolution for the last 10 years (January 1998 to July 2007) are used to form and analyze the 5-day mean and monthly mean climatology of rainfall. Results show considerable regional and seasonal differences of rainfall over the Mediterranean Region. The maximum rainfall (3-5 mm/day) occurs over the mountain regions of Europe, while the minimum rainfall is observed over North Africa (approximately 0.5 mm/day). The main rainy season over the Mediterranean Sea extends from October to March, with maximum rainfall occurring during November-December. Over the Mediterranean Sea, an average rainrate of approximately 1-2 mm/day is observed, but during the rainy season there is 20% larger rainfall over the western Mediterranean Sea than that over the eastern Mediterranean Sea. During the rainy season, mesoscale rain systems generally propagate from west to east and from north to south over the Mediterranean region, likely to be associated with Mediterranean cyclonic disturbances resulting from interactions among large-scale circulation, orography, and land-sea temperature contrast.

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.

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.

The Variation of Tropical Cyclone Rainfall within the North Atlantic and Pacific as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward; Pierce, Harold; Adler, Robert

1999-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations in the North Atlantic and in three equal geographical regions of the North Pacific (i.e., Western, Central, and Eastern North Pacific). These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the 1987-1989, 1991-1998 North Atlantic and Pacific rainfall during June-November when tropical cyclones are most abundant. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from the Defence Meteorological Satellite Program (DMSP) Special Sensor Microwave/ Radiometer (SSM/I) observations within 444 km radius of the center of those North Atlantic and Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are then multiplied by the number of hours in a given month. Mean monthly rainfall amounts are also constructed for all the other North Atlantic and Pacific raining systems during this eleven year period for the purpose of estimating the geographical distribution and intensity of rainfall contributed by non-tropical cyclone systems. Further, the combination of the non-tropical cyclone and tropical cyclone (i.e., total) rainfall is constructed to delineate the fractional amount that tropical cyclones contributed to the total North Pacific rainfall.

A Bayesian approach for estimating under-reported dengue incidence with a focus on non-linear associations between climate and dengue in Dhaka, Bangladesh.

PubMed

Sharmin, Sifat; Glass, Kathryn; Viennet, Elvina; Harley, David

2018-04-01

Determining the relation between climate and dengue incidence is challenging due to under-reporting of disease and consequent biased incidence estimates. Non-linear associations between climate and incidence compound this. Here, we introduce a modelling framework to estimate dengue incidence from passive surveillance data while incorporating non-linear climate effects. We estimated the true number of cases per month using a Bayesian generalised linear model, developed in stages to adjust for under-reporting. A semi-parametric thin-plate spline approach was used to quantify non-linear climate effects. The approach was applied to data collected from the national dengue surveillance system of Bangladesh. The model estimated that only 2.8% (95% credible interval 2.7-2.8) of all cases in the capital Dhaka were reported through passive case reporting. The optimal mean monthly temperature for dengue transmission is 29℃ and average monthly rainfall above 15 mm decreases transmission. Our approach provides an estimate of true incidence and an understanding of the effects of temperature and rainfall on dengue transmission in Dhaka, Bangladesh.

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.

Exogenous factors matter when interpreting the results of an impact evaluation: a case study of rainfall and child health programme intervention in Rwanda.

PubMed

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

2017-12-01

Public health interventions are often implemented at large scale, and their evaluation seems to be difficult because they are usually multiple and their pathways to effect are complex and subject to modification by contextual factors. We assessed whether controlling for rainfall-related variables altered estimates of the efficacy of a health programme in rural Rwanda and have a quantifiable effect on an intervention evaluation outcomes. We conducted a retrospective quasi-experimental study using previously collected cross-sectional data from the 2005 and 2010 Rwanda Demographic and Health Surveys (DHS), 2010 DHS oversampled data, monthly rainfall data collected from meteorological stations over the same period, and modelled output of long-term rainfall averages, soil moisture, and rain water run-off. Difference-in-difference models were used. Rainfall factors confounded the PIH intervention impact evaluation. When we adjusted our estimates of programme effect by controlling for a variety of rainfall variables, several effectiveness estimates changed by 10% or more. The analyses that did not adjust for rainfall-related variables underestimated the intervention effect on the prevalence of ARI by 14.3%, fever by 52.4% and stunting by 10.2%. Conversely, the unadjusted analysis overestimated the intervention's effect on diarrhoea by 56.5% and wasting by 80%. Rainfall-related patterns have a quantifiable effect on programme evaluation results and highlighted the importance and complexity of controlling for contextual factors in quasi-experimental design evaluations. © 2017 John Wiley & Sons Ltd.

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.

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

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.

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.

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 measurement from the opportunistic use of an Earth-space link in the Ku band

NASA Astrophysics Data System (ADS)

Barthès, L.; Mallet, C.

2013-08-01

The present study deals with the development of a low-cost microwave device devoted to the measurement of average rain rates observed along Earth-satellite links, the latter being characterized by a tropospheric path length of a few kilometres. The ground-based power measurements, which are made using the Ku-band television transmissions from several different geostationary satellites, are based on the principle that the atmospheric attenuation produced by rain encountered along each transmission path can be used to determine the path-averaged rain rate. This kind of device could be very useful in hilly areas where radar data are not available or in urban areas where such devices could be directly placed in homes by using residential TV antenna. The major difficulty encountered with this technique is that of retrieving rainfall characteristics in the presence of many other causes of received signal fluctuation, produced by atmospheric scintillation, variations in atmospheric composition (water vapour concentration, cloud water content) or satellite transmission parameters (variations in emitted power, satellite pointing). In order to conduct a feasibility study with such a device, a measurement campaign was carried out over a period of five months close to Paris. The present paper proposes an algorithm based on an artificial neural network, used to identify dry and rainy periods and to model received signal variability resulting from effects not related to rain. When the altitude of the rain layer is taken into account, the rain attenuation can be inverted to obtain the path-averaged rain rate. The rainfall rates obtained from this process are compared with co-located rain gauges and radar measurements taken throughout the full duration of the campaign, and the most significant rainfall events are analysed.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

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.

Time Series Analysis of Cholera in Matlab, Bangladesh, during 1988-2001

PubMed Central

Kim, Deok Ryun; Yunus, Mohammad; Emch, Michael

2013-01-01

The study examined the impact of in-situ climatic and marine environmental variability on cholera incidence in an endemic area of Bangladesh and developed a forecasting model for understanding the magnitude of incidence. Diarrhoea surveillance data collected between 1988 and 2001were obtained from a field research site in Matlab, Bangladesh. Cholera cases were defined as Vibrio cholerae O1 isolated from faecal specimens of patients who sought care at treatment centres serving the Matlab population. Cholera incidence for 168 months was correlated with remotely-sensed sea-surface temperature (SST) and in-situ environmental data, including rainfall and ambient temperature. A seasonal autoregressive integrated moving average (SARIMA) model was used for determining the impact of climatic and environmental variability on cholera incidence and evaluating the ability of the model to forecast the magnitude of cholera. There were 4,157 cholera cases during the study period, with an average of 1.4 cases per 1,000 people. Since monthly cholera cases varied significantly by month, it was necessary to stabilize the variance of cholera incidence by computing the natural logarithm to conduct the analysis. The SARIMA model shows temporal clustering of cholera at one- and 12-month lags. There was a 6% increase in cholera incidence with a minimum temperature increase of one degree celsius in the current month. For increase of SST by one degree celsius, there was a 25% increase in the cholera incidence at currrent month and 18% increase in the cholera incidence at two months. Rainfall did not influenc to cause variation in cholera incidence during the study period. The model forecast the fluctuation of cholera incidence in Matlab reasonably well (Root mean square error, RMSE: 0.108). Thus, the ambient and sea-surface temperature-based model could be used in forecasting cholera outbreaks in Matlab. PMID:23617200

Suspended sediment flux modeling with artificial neural network: An example of the Longchuanjiang River in the Upper Yangtze Catchment, China

NASA Astrophysics Data System (ADS)

Zhu, Yun-Mei; Lu, X. X.; Zhou, Yue

2007-02-01

Artificial neural network (ANN) was used to model the monthly suspended sediment flux in the Longchuanjiang River, the Upper Yangtze Catchment, China. The suspended sediment flux was related to the average rainfall, temperature, rainfall intensity and water discharge. It is demonstrated that ANN is capable of modeling the monthly suspended sediment flux with fairly good accuracy when proper variables and their lag effect on the suspended sediment flux are used as inputs. Compared with multiple linear regression and power relation models, ANN can generate a better fit under the same data requirement. In addition, ANN can provide more reasonable predictions for extremely high or low values, because of the distributed information processing system and the nonlinear transformation involved. Compared with the ANNs that use the values of the dependent variable at previous time steps as inputs, the ANNs established in this research with only climate variables have an advantage because it can be used to assess hydrological responses to climate change.

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

1997-01-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an eleven year period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important. To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444 km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain rate observations are converted to monthly rainfall amounts and then compared to those for non-tropical cyclone systems. The main results of this study indicate that: 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maxima in tropical cyclone rainfall are poleward (5 deg to 10 deg latitude depending on longitude) of the maxima in non-tropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% of the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the ITCZ; and 5) in general, tropical cyclone rainfall is enhanced during the El Nino years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

Contribution of Tropical Cyclones to the North Pacific Climatological Rainfall as Observed from Satellites.

NASA Astrophysics Data System (ADS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.

2000-10-01

Tropical cyclone monthly rainfall amounts are estimated from passive microwave satellite observations for an 11-yr period. These satellite-derived rainfall amounts are used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and interannual distribution of the North Pacific Ocean total rainfall during June-November when tropical cyclones are most important.To estimate these tropical cyclone rainfall amounts, mean monthly rain rates are derived from passive microwave satellite observations within 444-km radius of the center of those North Pacific tropical cyclones that reached storm stage and greater. These rain-rate observations are converted to monthly rainfall amounts and then compared with those for nontropical cyclone systems.The main results of this study indicate that 1) tropical cyclones contribute 7% of the rainfall to the entire domain of the North Pacific during the tropical cyclone season and 12%, 3%, and 4% when the study area is limited to, respectively, the western, central, and eastern third of the ocean; 2) the maximum tropical cyclone rainfall is poleward (5°-10° latitude depending on longitude) of the maximum nontropical cyclone rainfall; 3) tropical cyclones contribute a maximum of 30% northeast of the Philippine Islands and 40% off the lower Baja California coast; 4) in the western North Pacific, the tropical cyclone rainfall lags the total rainfall by approximately two months and shows seasonal latitudinal variation following the Intertropical Convergence Zone; and 5) in general, tropical cyclone rainfall is enhanced during the El Niño years by warm SSTs in the eastern North Pacific and by the monsoon trough in the western and central North Pacific.

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

USGS Publications Warehouse

Bridges, W.C.

1985-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Effects of Land Use Changes on the Water and Energy Balance Over South America

NASA Astrophysics Data System (ADS)

Nascimento, M.; Herdies, D. L.; Angelis, C.

2013-05-01

With the objective of analyzing the effects of land use changes in the Amazon and its consequences on the main components of the water and energy balance over South America, with emphasis on the Amazon and La Plata Basin, two experiments were carried for 10-year period (1999-2008), in which the land use conditions were modified, representing conditions for the 90s (CONTROL Experiment) and current conditions over land use in the Amazon region (Experiment 1). Changes in land use were observed mainly in the Amazon region and southern Brazil. The numerical model used to perform the simulations was the ETA in its climate version, using as an initial and boundary condition the CFSR/NCEP reanalysis datasets. The results show for the analyzed period that there was a reduction of 3.3 mm/month in average rainfall rates in the La Plata Basin and 4.2 mm/month in the Amazon region, with some places where this reduction was more pronounced. Seasonally was observed that during the summer there is an average reduction of 3.9 mm/month in the Amazon region. Already on the La Plata Basin was observed an average increase of 11.7 mm/month in the La Plata Basin during the summer and an reduction in winter season. Through the overall result was also possible to conclude that the changes in land use for more realistic conditions, there were significant reductions in evapotranspiration and latent heat fluxes, as well as an increase in sensible heat fluxes, especially over the regions where the changes were more pronounced. Through the analyzes it can be observed that in general the La Plata Basin is sensitive to changes in land use over the Amazon and adjacent regions, allowing to conclude that such changes can influence the amount of rainfall, the intensity of the major meteorological systems, as well as temperature trends on the regions analyzed.

Chemical and biological quality of Lakes Faith, Hope, and Charity at Maitland, Florida, with emphasis on the effects of storm runoff and bulk precipitation, 1971-1974

USGS Publications Warehouse

Gaggiani, Neville G.; Lamonds, A.G.

1978-01-01

Located in a closed basin, near Orlands, Fla., Lake Faith, Hope, and Charity cover a combined area of 132 acres and are surrounded by residential, citrus grove and undeveloped areas. All of these areas affect the water quality of the lakes through storm runoff and transport of windborne material. During a study from April 1971 to June 1974, stages of Lakes Faith, Hope, and Charity declined 1.5, 1.4, and 3.0 ft, respectively, because the rainfall was 3.78 in. below average for the area. Inflow to the lakes during this 3-year period was approximately 1,966 acre-ft of which 84 percent was by rainfall and 16 percent was by storm runoff. Rainfall and runoff brought in 82 tons of dissolved solids of which storm runoff carried 51 tons and bulk precipitation carried 32 tons. Dissolved solids concentrations in the lakes were relatively low, averaging 91, 132, and 212 mg/liter for Lakes Faith, Hope, and Charity, respecetively. Major ions, trace elements and nutrients were present in the lakes in relatively low concentrations. Phytoplankton and coliform population showed sharp seasonal fluctuations with the maximum population generally occurring during the warmer months. Blue-green algae predominated in all three lakes. (Woodard-USGS)

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

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.

Spatio-temporal trend analysis of projected precipitation data over Rwanda

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Technical Reports Server (NTRS)

Choudhury, Bhaskar J.; Digirolamo, Nicolo E.

1994-01-01

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

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.

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

PubMed Central

Nandargi, S.; Mulye, S. S.

2012-01-01

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

The effect of aerosol optical depth on rainfall with reference to meteorology over metro cities in India.

PubMed

Gunaseelan, Indira; Bhaskar, B Vijay; Muthuchelian, K

2014-01-01

Rainfall is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban environment's impact on rainfall will be increasingly important in ongoing climate diagnostics and prediction. Aerosol optical depth (AOD) measurements on the monsoon seasons of the years 2008 to 2010 were made over four metro regional hotspots in India. The highest average of AOD was in the months of June and July for the four cities during 3 years and lowest was in September. Comparing the four regions, Kolkata was in the peak of aerosol contamination and Chennai was in least. Pearson correlation was made between AOD with climatic parameters. Some changes in the parameters were found during drought year. Temperature, cloud parameters, and humidity play an important role for the drought conditions. The role of aerosols, meteorological parameters, and their impacts towards the precipitation during the monsoon was studied.

C-band attenuation by tropical rainfall in Darwin, Australia, using climatologically tuned Z(e)-R relations

NASA Technical Reports Server (NTRS)

Atlas, David; Rosenfeld, Daniel; Wolff, David B.

1993-01-01

The probability matching method (PMM) is used as a basis for estimating attenuation in tropical rains near Darwin, Australia. PMM provides a climatological relationship between measured radar reflectivity and rain rate, which includes the effects of rain and cloud attenuation. When the radar sample is representative, PMM estimates the rainfall without bias. When the data are stratified for greater than average rates, the method no longer compensates for the higher attenuation and the radar rainfall estimates are biased low. The uncompensated attenuation is used to estimate the climatological attenuation coefficient. The two-way attenuation coefficient was found to be 0.0085 dB/km ( mm/h) exp -1.08 for the tropical rains and associated clouds in Darwin for the first two months of the year for horizontally polarized radiation at 5.63 GHz. This unusually large value is discussed. The risks of making real-time corrections for attenuation are also treated.

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

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

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

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.

Uncertainties in observations and climate projections for the North East India

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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.

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.

[Ecological suitability regionalization for Gastrodia elata in Zhaotong based on Maxent and ArcGIS].

PubMed

Shi, Zi-Wei; Ma, Cong-Ji; Kang, Chuan-Zhi; Wang, Li; Zhang, Zhi-Hui; Chen, Jun-Fei; Zhang, Xiao-Bo; Liu, Da-Hui

2016-09-01

In this paper, the potential distribution information and ecological suitability regionalization for Gastrodia elata in Zhaotong were studied based on the climate, terrain, soil and vegetation factors analysis by Maxent and ArcGIS. The results showed that the highly potential distribution (suitability index>0.6) mainly located in Zhaotong, Yunnan province（Zhenxiong,Yiliang and Daguan county, with an area of 2 872 km²）, and Bijie, Guizhou province （Hezhang,Bijie,Weining county, 1 251 km²）. The AUC of ROC curve was above 0.99, indicating that the predictive results with the Maxent model were highly precise. The main ecological factors determining the potential distribution were the altitude, average rainfall in November, average rainfall in October, vegetation types, average rainfall in March, average rainfall in April,soil types,isothermal characteristic and average rainfall in June. The environmental variables in the highly potential areas were determined as altitude around 1 450-2 200 m,annual average temperature around 18.0-20.4 ℃,annual average precipitation around 900 mm,yellow soil or yellow brown soil,and acid sandy loam or slightly acidic sandy loam.The results will provide valuable references for plantation regionalization and the siting for imitation wild planting of G. elata in Zhaotong. Copyright© by the Chinese Pharmaceutical Association.

Runoff and Leaching of Metolachlor from Mississippi River Alluvial Soil during Seasons of Average and Below-Average Rainfall

USDA-ARS?s Scientific Manuscript database

The movement of metolachlor via runoff and leaching from plots planted to corn on Mississippi River alluvial soil (Commerce silt loam) was measured for a six-year period, 1995-2000. The first three years were characterized by normal rainfall volume, the second three years by reduced rainfall. The ...

Using rainfall radar data to improve interpolated maps of dose rate in the Netherlands.

PubMed

Hiemstra, Paul H; Pebesma, Edzer J; Heuvelink, Gerard B M; Twenhöfel, Chris J W

2010-12-01

The radiation monitoring network in the Netherlands is designed to detect and track increased radiation levels, dose rate more specifically, in 10-minute intervals. The network consists of 153 monitoring stations. Washout of radon progeny by rainfall is the most important cause of natural variations in dose rate. The increase in dose rate at a given time is a function of the amount of progeny decaying, which in turn is a balance between deposition of progeny by rainfall and radioactive decay. The increase in progeny is closely related to average rainfall intensity over the last 2.5h. We included decay of progeny by using weighted averaged rainfall intensity, where the weight decreases back in time. The decrease in weight is related to the half-life of radon progeny. In this paper we show for a rainstorm on the 20th of July 2007 that weighted averaged rainfall intensity estimated from rainfall radar images, collected every 5min, performs much better as a predictor of increases in dose rate than using the non-averaged rainfall intensity. In addition, we show through cross-validation that including weighted averaged rainfall intensity in an interpolated map using universal kriging (UK) does not necessarily lead to a more accurate map. This might be attributed to the high density of monitoring stations in comparison to the spatial extent of a typical rain event. Reducing the network density improved the accuracy of the map when universal kriging was used instead of ordinary kriging (no trend). Consequently, in a less dense network the positive influence of including a trend is likely to increase. Furthermore, we suspect that UK better reproduces the sharp boundaries present in rainfall maps, but that the lack of short-distance monitoring station pairs prevents cross-validation from revealing this effect. Copyright © 2010 Elsevier B.V. All rights reserved.

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

Damaging events along roads during bad weather periods: a case study in Calabria (Italy)

NASA Astrophysics Data System (ADS)

Petrucci, O.; Pasqua, A. A.

2012-02-01

The study focuses on circumstances that affect people during periods of bad weather conditions characterised by winds, rainfall, landslides, flooding, and storm surges. A methodological approach and its application to a study area in southern Italy are presented here. A 10-yr database was generated by mining data from a newspaper. Damaging agents were sorted into five types: flood, urban flooding, landslide, wind, and storm surge. Damage to people occurred in 126 cases, causing 13 victims, 129 injured and about 782 people involved but not injured. For cases of floods, urban flooding and landslides, the analysis does not highlight straightforward relationships between rainfall and damage to people, even if the events showed different features according to the months of occurrence. The events occurring between May and October were characterised by concentrated and intense rainfall, and between May and July, the highest values of hourly (103 mm on the average) and monthly rainfall (114 mm on the average) were recorded. Urban flooding and flash floods were the most common damaging agents: injured, involved people and more rarely, cases with victims were reported. Between November and April, the highest number of events was recorded. Rainfall presented longer durations and hourly and sub-hourly rainfall were lower than those recorded between May and October. Landslides were the most frequent damaging agents but the highest number of cases with victims, which occurred between November and January, were mainly related to floods and urban flooding. Motorists represent the totality of the victims; 84% of the people were injured and the whole of people involved. All victims were men, and the average age was 43 yr. The primary cause of death was drowning caused by floods, and the second was trauma suffered in car accidents caused by urban flooding. The high number of motorists rescued in submerged cars reveals an underestimation of danger in the case of floods, often increased by the sense of security related to the familiarity of the road. In contrast, in the cases of people involved in landslides, when there was enough time to realise the potential risk, people behaved appropriately to avoid negative consequences. Of the victims, 50% were killed along fast-flowing roads; this may be related to the high speed limit in force on these roads, as a car's speed reduces the reaction time of a driver's response to an unexpected situation, whatever the damaging agent is. These results can be used in local information/education campaigns to both increase risk awareness and promote self-protective behaviours. Moreover, the mapping of damaging effects pointed out the regional sectors in which the high frequency of the events suggests further planning of in-depth examinations, which can individuate the critical points and local regulator interventions that might change damage incidences in the future.

Errata Sheet for Post-Closure Inspection and Monitoring Report for Corrective Action Unit 110: Area 3 WMD U-3ax/bl Crater, Nevada Test Site, Nevada

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

NSTec Environmental Restoration

2007-09-13

The last sentence of the second paragraph of the Executive Summary on page ix incorrectly states the period for repair. Cracks or areas of settling exceeding the 15 centimeters (6 inches) deep that extend 1.0 meter (3 feet) or more on the cover will be evaluated and repaired within 60 days of detection. The second sentence of the third paragraph of the Executive Summary on page ix incorrectly states the month that cover repair was performed while omitting the discovery of additional settling, which was repaired during the originally-stated repair month. The corrected sentence (with additional sentences added for clarification)more » reads, 'This area of settling on the cover was repaired in October 2006. Additional cracking was observed during the October 2006 repair that exceeded the action level and was repaired in December 2006.' The last sentence of the fourth bullet of Section 2.2 on page 5 incorrectly states the period for repair. Cracks or areas of settling exceeding the compliance criterion will be evaluated and repaired within 60 days. A repair event was omitted from Section 3.4 on page 13, which should be included as Subsection 3.4.1, 'October 26-30, 2006, Repairs'. The subtext included with this subsection should read, 'During the September 19, 2006, inspection, one area of settling on the southeast portion of the cover exceeded the settling compliance criterion. The area was repaired over the period of October 26-30, 2006. A portable, gas-powered tamper was used to compact the cracks in the cover. The area was backfilled with clean, native soil using wheelbarrows and shovels, and then compacted using the tamper.' Due to the inclusion of the previously-listed omission, Subsection 3.4.1 should be renumbered to Subsection 3.4.2, and the first sentence corrected to read, 'During the October 26-30, 2006, repair, an additional area of settling on the southeast portion of the cover was discovered that exceeded the settling compliance criterion'. The third sentence of the second paragraph of Section 4.0 on page 15 should be clarified to include values for both the current reporting period and 40-year average rainfall. The corrected sentences read, 'After the cover experienced drought conditions again in 2006, the current reporting period indicates continued drought conditions (6.29 cm [2.48 in.]) compared to the historical average since 1960 (16.31 cm [6.42 in.]). This will allow the cover to recover from the prior infiltration events and continue to equilibrate to steady-state conditions, at which time the soil moisture content trigger values will be set'. The first sentence of the second paragraph of Section 4.1 on page 16 incorrectly states the amount of rainfall for the period July 2006 through June 2007. The rainfall for this period should be 6.29 centimeters (2.48 inches). The second sentence of the second paragraph of Section 4.1 on page 16 incorrectly states the average annual precipitation for the period 1960 through 2005, where the average annual precipitation should be reported for the period 1960 through 2006. The average annual precipitation for this period is 16.31 centimeters (6.42 inches). The third sentence of the second paragraph of Section 4.1 on page 16 incorrectly states the amount of annual rainfall for the 2006 calendar year. The rainfall for this period should be 11.0 centimeters (4.33 inches). The last sentence of the second paragraph of Section 4.1 on page 16 incorrectly states the amount of rainfall for the period January 2007 through June 2007. The rainfall for this period should be 2.11 centimeters (0.83 inches).« less

Estimation of evapotranspiration in the Rainbow Springs and Silver Springs basins in North-Central Florida

USGS Publications Warehouse

Knowles, Leel

1996-01-01

Estimates of evapotranspiration (ET) for the Rainbow and Silver Springs ground-water basins in north-central Florida were determined using a regional water-~budget approach and compared to estimates computed using a modified Priestley-Taylor (PT) model calibrated with eddy-correlation data. Eddy-correlation measurements of latent 0~E) and sensible (H) heat flux were made monthly for a few days at a time, and the PT model was used to estimate 3,E between times of measurement during the 1994 water year. A water-budget analysis for the two-basin area indicated that over a 30-year period (196594) annual rainfall was 51.7 inches. Of the annual rainfall, ET accounted for about 37.9 inches; springflow accounted for 13.1 inches; and the remaining 0.7 inch was accounted for by stream-flow, by ground-water withdrawals from the Floridan aquifer system, and by net change in storage. For the same 30-year period, the annual estimate of ET for the Silver Springs basin was 37.6 inches and was 38.5 inches for the Rainbow Springs basin. Wet- and dry-season estimates of ET for each basin averaged between nearly 19 inches and 20 inches, indicating that like rainfall, ET rates during the 4-month wet season were about twice the ET rates during the 8-month dry season. Wet-season estimates of ET for the Rainbow Springs and Silver Springs basins decreased 2.7 inches, and 3.4 inches, respectively, over the 30-year period; whereas, dry-season estimates for the basins decreased about 0.4 inch and1.0 inch, respectively, over the 30-year period. This decrease probably is related to the general decrease in annual rainfall and reduction in net radiation over the basins during the 30-year period. ET rates computed using the modified PT model were compared to rates computed from the water budget for the 1994 water year. Annual ET, computed using the PT model, was 32.0 inches, nearly equal to the ET water-budget estimate of 31.7 inches computed for the Rainbow Springs and Silver Springs basins. Modeled ET rates for 1994 ranged from 14.4 inches per year in January to 51.6 inches per year in May. Water-budget ET rates for 1994 ranged from 12.0 inches per year in March to 61.2 inches per year in July. Potential evapotranspiration rates for 1994 averaged 46.8 inches per year and ranged from 21.6 inches per year in January to 74.4 inches per year in May. Lake evaporation rates averaged 47.1 inches per year and ranged from 18.0 inches per year in January to 72.0 inches per year in May 1994.

An Investigation of the Influence of Urban Areas on Rainfall Using a Cloud-Mesoscale Model and TRMM Satellite

NASA Technical Reports Server (NTRS)

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

2002-01-01

The urban heat island (UHI) has become a widely acknowledged, observed, and researched phenomena because of its broad implications. It is estimated that by the year 2025, 80% of the world's population will live in cities (UNFP, 1999). The UHI has been documented in the literature to affect local and regional temperature distributions, wind patterns and air quality. The UHI can also impact the development of clouds and precipitation in and around cities. This paper will focus primarily on the UHI's impact on precipitation. In the past 30 years, several observational and climatological studies have theorized that the UHI can have a significant influence on mesoscale circulations and resulting precipitation (see Shepherd et al. 2002 for a thorough review). More recent studies have continued to validate and extend the findings from pre and post-METROMEX investigations. Shepherd et al. (2002) was one of the first (and possibly the first) attempts to identify rainfall modification by urban areas using satellite-based rainfall measurements. Using a 15-month (spanning three years) analysis of mean rainfall rates, the cities of Atlanta, Montgomery, Dallas, Waco, and San Antonio were examined. Shepherd et al. (2002) found that the average percentage increase in mean rainfall rate in a hypothesized "downwind maximum impact area" over an "upwind control area" was 28.4% with a range of 14.6 to 51%. The typical distance of the downwind rainfall rate anomaly from the urban center was 30-60 km, consistent with earlier studies. This fact provides confidence that UHI-rainfall effects are real and detectable by TRMM satellite estimates.

The Status of the Tropical Rainfall Measuring Mission (TRMM) after 2 Years in Orbit

NASA Technical Reports Server (NTRS)

Kummerow, C.; Simpson, J.; Thiele, O.; Barnes, W.; Chang, A. T. C.; Stocker, E.; Adler, R. F.; Hou, A.; Kakar, R.; Wentz, F.

1999-01-01

The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, in related modeling applications and in new datasets tailored specifically for these applications. This paper reports the latest results regarding the calibration of the TRMM Microwave Imager, (TMI), Precipitation Radar (PR) and Visible and Infrared Sensor (VIRS). For the TMI, a new product is in place that corrects for a still unknown source of radiation leaking in to the TMI receiver. The PR calibration has been adjusted upward slightly (by 0.6 dBZ) to better match ground reference targets, while the VIRS calibration remains largely unchanged. In addition to the instrument calibration, great strides have been made with the rainfall algorithms as well, with the new rainfall products agreeing with each other to within less than 20% over monthly zonally averaged statistics. The TRMM Science Data and Information System (TSDIS) has responded equally well by making a number of new products, including real-time and fine resolution gridded rainfall fields available to the modeling community. The TRMM Ground Validation (GV) program is also responding with improved radar calibration techniques and rainfall algorithms to provide more accurate GV products which will be further enhanced with the new multiparameter 10 cm radar being developed for TRMM validation and precipitation studies. Progress in these various areas has, in turn, led to exciting new developments in the modeling area where Data Assimilation, and Weather Forecast models are showing dramatic improvements after the assimilation of observed rainfall fields.

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.

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.

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.

Groundwater recharge estimation under semi arid climate: Case of Northern Gafsa watershed, Tunisia

NASA Astrophysics Data System (ADS)

Melki, Achraf; Abdollahi, Khodayar; Fatahi, Rouhallah; Abida, Habib

2017-08-01

Natural groundwater recharge under semi arid climate, like rainfall, is subjected to large variations in both time and space and is therefore very difficult to predict. Nevertheless, in order to set up any strategy for water resources management in such regions, understanding the groundwater recharge variability is essential. This work is interested in examining the impact of rainfall on the aquifer system recharge in the Northern Gafsa Plain in Tunisia. The study is composed of two main parts. The first is interested in the analysis of rainfall spatial and temporal variability in the study basin while the second is devoted to the simulation of groundwater recharge. Rainfall analysis was performed based on annual precipitation data recorded in 6 rainfall stations over a period of 56 years (1960-2015). Potential evapotranspiration data were also collected from 1960 to 2011 (52 years). The hydrologic distributed model WetSpass was used for the estimation of groundwater recharge. Model calibration was performed based on an assessment of the agreement between the sum of recharge and runoff values estimated by the WetSpass hydrological model and those obtained by the climatic method. This latter is based on the difference calculated between rainfall and potential evapotranspiration recorded at each rainy day. Groundwater recharge estimation, on monthly scale, showed that average annual precipitation (183.3 mm/year) was partitioned to 5, 15.3, 36.8, and 42.8% for interception, runoff, actual evapotranspiration and recharge respectively.

Sediment reallocations due to erosive rainfall events in the Three Gorges Reservoir Area, Central China

NASA Astrophysics Data System (ADS)

Stumpf, Felix; Goebes, Philipp; Schmidt, Karsten; Schindewolf, Marcus; Schönbrodt-Stitt, Sarah; Wadoux, Alexandre; Xiang, Wei; Scholten, Thomas

2017-04-01

Soil erosion by water outlines a major threat to the Three Gorges Reservoir Area in China. A detailed assessment of soil conservation measures requires a tool that spatially identifies sediment reallocations due to rainfall-runoff events in catchments. We applied EROSION 3D as a physically based soil erosion and deposition model in a small mountainous catchment. Generally, we aim to provide a methodological frame that facilitates the model parametrization in a data scarce environment and to identify sediment sources and deposits. We used digital soil mapping techniques to generate spatially distributed soil property information for parametrization. For model calibration and validation, we continuously monitored the catchment on rainfall, runoff and sediment yield for a period of 12 months. The model performed well for large events (sediment yield>1 Mg) with an averaged individual model error of 7.5%, while small events showed an average error of 36.2%. We focused on the large events to evaluate reallocation patterns. Erosion occurred in 11.1% of the study area with an average erosion rate of 49.9Mgha 1. Erosion mainly occurred on crop rotation areas with a spatial proportion of 69.2% for 'corn-rapeseed' and 69.1% for 'potato-cabbage'. Deposition occurred on 11.0%. Forested areas (9.7%), infrastructure (41.0%), cropland (corn-rapeseed: 13.6%, potatocabbage: 11.3%) and grassland (18.4%) were affected by deposition. Because the vast majority of annual sediment yields (80.3%) were associated to a few large erosive events, the modelling approach provides a useful tool to spatially assess soil erosion control and conservation measures.

Animal reservoir, natural and socioeconomic variations and the transmission of hemorrhagic fever with renal syndrome in Chenzhou, China, 2006-2010.

PubMed

Xiao, Hong; Tian, Huai-Yu; Gao, Li-Dong; Liu, Hai-Ning; Duan, Liang-Song; Basta, Nicole; Cazelles, Bernard; Li, Xiu-Jun; Lin, Xiao-Ling; Wu, Hong-Wei; Chen, Bi-Yun; Yang, Hui-Suo; Xu, Bing; Grenfell, Bryan

2014-01-01

China has the highest incidence of hemorrhagic fever with renal syndrome (HFRS) worldwide. Reported cases account for 90% of the total number of global cases. By 2010, approximately 1.4 million HFRS cases had been reported in China. This study aimed to explore the effect of the rodent reservoir, and natural and socioeconomic variables, on the transmission pattern of HFRS. Data on monthly HFRS cases were collected from 2006 to 2010. Dynamic rodent monitoring data, normalized difference vegetation index (NDVI) data, climate data, and socioeconomic data were also obtained. Principal component analysis was performed, and the time-lag relationships between the extracted principal components and HFRS cases were analyzed. Polynomial distributed lag (PDL) models were used to fit and forecast HFRS transmission. Four principal components were extracted. Component 1 (F1) represented rodent density, the NDVI, and monthly average temperature. Component 2 (F2) represented monthly average rainfall and monthly average relative humidity. Component 3 (F3) represented rodent density and monthly average relative humidity. The last component (F4) represented gross domestic product and the urbanization rate. F2, F3, and F4 were significantly correlated, with the monthly HFRS incidence with lags of 4 months (r = -0.289, P<0.05), 5 months (r = -0.523, P<0.001), and 0 months (r = -0.376, P<0.01), respectively. F1 was correlated with the monthly HFRS incidence, with a lag of 4 months (r = 0.179, P = 0.192). Multivariate PDL modeling revealed that the four principal components were significantly associated with the transmission of HFRS. The monthly trend in HFRS cases was significantly associated with the local rodent reservoir, climatic factors, the NDVI, and socioeconomic conditions present during the previous months. The findings of this study may facilitate the development of early warning systems for the control and prevention of HFRS and similar diseases.

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.

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

DOE PAGES

Yoo, Chulsang; Lee, Jinwook; Ro, Yonghun

2016-01-01

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

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

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.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the (R)USLE model. The R-factor is calculated from a series of single storm events by multiplying the total storm kinetic energy with the measured maximum 30-minutes rainfall intensity. This estimation requests high temporal resolution (e.g. 30 minutes) rainfall data for sufficiently long time periods (i.e. 20 years) which are not readily available at European scale. The European Commission's Joint Research Centre(JRC) in collaboration with national/regional meteorological services and Environmental Institutions made an extensive data collection of high resolution rainfall data in the 28 Member States of the European Union plus Switzerland in order to estimate rainfall erosivity in Europe. This resulted in the Rainfall Erosivity Database on the European Scale (REDES) which included 1,541 rainfall stations in 2014 and has been updated with 134 additional stations in 2015. The interpolation of those point R-factor values with a Gaussian Process Regression (GPR) model has resulted in the first Rainfall Erosivity map of Europe (Science of the Total Environment, 511, 801-815). The intra-annual variability of rainfall erosivity is crucial for modelling soil erosion on a monthly and seasonal basis. The monthly feature of rainfall erosivity has been added in 2015 as an advancement of REDES and the respective mean annual R-factor map. Almost 19,000 monthly R-factor values of REDES contributed to the seasonal and monthly assessments of rainfall erosivity in Europe. According to the first results, more than 50% of the total rainfall erosivity in Europe takes place in the period from June to September. The spatial patterns of rainfall erosivity have significant differences between Northern and Southern Europe as summer is the most erosive period in Central and Northern Europe and autumn in the Mediterranean area. This spatio-temporal analysis of rainfall erosivity at European scale is very important for policy makers and farmers for soil conservation, optimization of agricultural land use and natural hazards prediction. REDES is also used in combination with future rainfall data from WorldClim to run climate change scenarios. The projection of REDES combined with climate change scenarios (HADGEM2, RCP4.5) and using a robust geo-statistical model resulted in a 10-20% increase of the R-factor in Europe till 2050.

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.

Predicting Malaria occurrence in Southwest and North central Nigeria using Meteorological parameters

NASA Astrophysics Data System (ADS)

Akinbobola, A.; Omotosho, J. Bayo

2013-09-01

Malaria is a major public health problem especially in the tropics with the potential to significantly increase in response to changing weather and climate. This study explored the impact of weather and climate and its variability on the occurrence and transmission of malaria in Akure, the tropical rain forest area of southwest and Kaduna, in the savanna area of Nigeria. We investigate this supposition by looking at the relationship between rainfall, relative humidity, minimum and maximum temperature, and malaria at the two stations. This study uses monthly data of 7 years (2001-2007) for both meteorological data and record of reported cases of malaria infection. Autoregressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Of all the models tested, the ARIMA (1, 0, 1) model fits the malaria incidence data best for Akure and Kaduna according to normalized Bayesian information criterion (BIC) and goodness-of-fit criteria. Humidity and rainfall have almost the same trend of association in all the stations while maximum temperature share the same negative association at southwestern stations and positive in the northern station. Rainfall and humidity have a positive association with malaria incidence at lag of 1 month. In all, we found that minimum temperature is not a limiting factor for malaria transmission in Akure but otherwise in the other stations.

Environmental Change: Precipitation and N, P, K, mg Fertilization Influences on Crop Yield Under Temperate Climate Conditions

NASA Astrophysics Data System (ADS)

László Phd, Dd. M.

2009-04-01

Summary: Agroecological quality has a well estabished dependence on climate-rainfall changes because the water problems are pressing. Therefore, there is, growing concern about the potentially wide ranging risks that climate change would have on these key industries as the nature and extent of anticipated changes have become more evident. It also includes changes in land use and in plant production and their management. These changes are unprecedented in terms of both their rate and their spatial extent. Changes in land use (agrotechnics, soil, cultivation, fertility, quality, protection etc.) and in plant production (plant, nutrition, rotation, protection etc.) are currently the main manifestations. As an interdisciplinary problem it is necessary to study such a complex matter in terms of agricultural production. Generally, among natural catastrophes, droughts and floods cause the greatest problems in field crop production. The droughts and the floods that were experienced in Hungary in the early 1980s have drawn renewed attention to the analyses of these problems. New research on climate change-soil-plant systems are focused on yield and yield quality. This paper reports of the climate changes (rainfall); soil (acidic sandy brown forest) properties, mineral N, P, K, Mg fertilisation level and plant interactions on rye (Secale cereale L.), on potato (Solanum tuberosum L.) and on winter wheat (Triticum aestivum L.) yields in a long term field experiment set up at Nyírlugos in north-eastern Hungary under temperate climate conditions in 1962. Results are summarised from 1962 to 1990. Main conclusions were as follows: 1. Rye: a, Experimental years were characterised by frequent extremes of precipitation variabilities and changes. b, By an average year, at a satisfactory fertilisation level (N: 90 kg ha-1 and NP, NK, NPK, NPKMg combinations) the maximum yield reached 3.8 t ha-1. But yield was decreased by 17% and by 52% due to drought and excess rainfall, respectively. Negative effects (drought, excess rainfall) were diminished by 20-25% with Mg treatments. c, Correlation between rye yields and precipitation during vegetation seasons showed that optimum yield (4.0 t ha-1) develops in the 430-470 mm range. 2. Potato: a, Trial years were estimated by recurrent extremes of climate. b, In vegetation seasons poor in rainfall yield safety in potato cannot be secured by fertilisation (N, NP, NK, NPK, NPKMg) alone. Under this weather condition yield was decreased by 35%. c, Optimum yields range between 17-21 t ha-1 at 280-350 mm. 3. Winter wheat: a, Climate was manifested mainly by precipitation using average, drought, dry and rainy levels. b, Yields from drought year effects with N, NP and NK combinations were diminished to 48% and with NPK and NPKMg treatments fell to 51%. c, Optimum yields (3.5-4.0 t ha-1) were developed at 450-500 mm. This paper summarises quantified results of rye, potato and winter wheat research with regarding to interaction effects and relationships between climate (rainfall)-mineral nutrition-crop production changes in Hungary during a long term field experiment to agricultural sustainability. Key words: ecology, rainfall, crop, fertilization, yield Introduction: "Climate Change" are recognized as a serious environmental issues [1]. Presently the build up of greenhouse gases in the atmosphere and the inertia in trends in emissions means that we can expect significant changes for at least the next few decades and probably for the whole 21th century too [2]. It would badly need to understand what might be involved in adapting to the new climates. A decade ago, researchers asked the „what if" question. For example, what will be the impact if climate changes. Now, we must increasingly address the following question: how do we respond effectivelly to prevent damaging impacts and take advantage of new climatic opportunities [3]. This question requires detailed in information regarding expected impacts and effectíve adaptive measures. Information on adaptation is required for governments, landscape planners, stakeholders, farmers, producers, processors, supermarkets and consumers. Not only the local effects and options, but also the spatial implications must be understood. Will yields be maintained on the present range of farms. Where will new crops be grown. Will new processing plants be required. Will there be competition for water. Most recent agricultural impact studies have concentrated on the effects of mean changes in climate on crop production, whilst only limited investigations into the effects of climate variability on agriculture have been undertaken. The paucity of studies in this area is not least due to the considerable uncertainty regarding how climate variability may change in the future in response to greenhouse gas induced warming but also as a result of the uncertainty in the response of agricultural crops to changes in climate variability, effected most probably through changes in the frequency of extreme climatic events. That changes showed in variance have a greater effect on the frequency of extreme climatic events than do changes in the mean values. Hence, it is important to attempt to include changes in variability in scenarios of climate change. Weather change in Hungary was started about of 1850. Among the natural catastrophes, drought and flooding caused by over-abundant rainfall cause the greatest problem in plant nutrition and in field crop production nowadays too [4]. It is why we found it necessary to revise and to analyse this problem. Rye (Secale cereale L.), potato (Solanum tuberosum L.) and winter wheat (Triticum aestivum L.) are most important crops of many World countries [5] but little research in the field of climate change impact assessment has been undertaken. All three plant are sensitive to the prevailing weather conditions (rainfall) and, hence, it is important to evaluate the effects of anthropogenic climate change on their production. These crops are demanding indicator of soil nutrient status also. Have a particularly high requirement for supply of soil nitrogen, phosphorus, potassium and magnesium. From 1962 to 1990 this paper describes climate-rainfall-change and N, P, K and Mg-mineral fertilisation effects on rye, potato and winter wheat yield on a acidic sandy brown forest soil at long term experiment scale under temperate climate conditions at Hungary. Material and Method: The effect of rainfall quantity and distribution on certain crop fertilisation factors (N, P, K, Mg and yield) were studied in a long-term field experiment on acidic sandy brown forest soil at North-Eastern Hungary set up in 1962 and 2002. Ploughed layer of the experiment soil had a pH(KCl) 4.5, humus 0.5%, CEC 5-10 mgeq 100 g-1. The topsoil was poor in all four macronutrients N, P, K and Mg. Rye, potato and winter wheat experiments involved 2x2x16x8 = 512, 2x2x16x8 = 512 and 2x16x4 = 128 plots. The gross and net plot size was 10x5 = 50 m2 and 35.5 m2. The experimental designe was split-split-plot. Average treatments were rye N:45 kg, P2O5:24, K2O:40, MgO:7.5 kg ha-1 year-1, potato N:75 kg, P2O5:24, K2O:75, MgO:15 kg ha-1 year-1, winter wheat N:45 kg, P2O5:24, K2O:40, MgO:7.5 kg ha-1 year-1 from 1962 to 1980 and N:75 kg, P2O5:90, K2O:90, MgO:140 kg ha-1 year-1 from 1981 to 1990 in the form of 25% calcium ammonium nitrate, 18% superphosphate, 40% potassium chloride, and magnesium sulphate. The groundwater table was at a depth of 2-3 m. Ecological (rainfall) and experimental data bases were estimated by Hungarian traditional [6] and RISSAC-HAS [3] standards and MANOVA (SPSS). Results: Climate-rainfall-change and mineral fertilisation effects on rye yield a. Experimental years were characterised by frequent extremes of precipitation variabilities and changes. One year had an 450 mm average rainfall (1966), one year had a more humid (1970) and three years had a very dry (1964, 1968, 1972) character. b. Weather anomalies as drought or to much rainfall did not cause significant differences on rye yield without fertilisation (average year: 1.66 t ha-1, drought year: 1.51 t ha-1, over rainfall year: 1.47 t ha-1). c. Yields varied from 2.01 to 3.04 t ha-1 under low (N: 30 kg ha-1 and NP, NK, NPK, NPKMg combinations) fertilisation input. Yields were decreased by 14% and 10% by drought and also by excess of rainfall. d. At mean fertilisation (N: 60 kg ha-1 and NP, NK, NPK, NPKMg combinations) level the maximum yield had reached 3.6 t ha-1 in average year. In years with excess rainfall, rye yields decreased as an average of fertilisation treatments by 20%. e. By an average year, at satisfactory fertilisation (N: 90 kg ha-1 and NP, NK, NPK, NPKMg combinations) level the maximum yield reached 3.8 t ha-1. But these yields were decreased with 17% and with 52% by drought and excess rainfall weather conditions respects. Negative effects (drought, excess rainfall) were diminished with 20-25% on the Mg treatments. f. Correlations between rye yields and the sums of precipitations during vegetation period (control: R = 0.99***, N: R = 0.84***, NP: R = 0.84***, NK: R = 0.91***, NPK: R = 0.85***, NPKMg: R = 0.65**) showed that optimum yields will develop in 430-470 mm range. Under and above these range of rainfall yields will decrease. Climate-rainfall-change and mineral fertilisation effects on potato yield a. Trial years (1963, 1965, 1967, 1969, 1971) were characterised by recurrent extremes of climate under vegetation seasons of potato. Three period had average rainfall, while two were very dry. b. All in all, droughts in the winter or summer half-year had much the same effect on yields. Precipitation deficiency in the winter could not be counterbalanced by average rainfall during the vegetation period, and its effect on the yield was similar to that of summer drought. c. Yield and quality were influenced by rainfall to a greater extent than by fertilisation. d. In vegetation periods poor in rainfall yield and quality safety in potato cannot be secured by fertilisation alone, they were decreased to 35%. It was also concluded that economic yields could not be achieved with poor nutrient supply even with a normal quantity and distribution of rainfall. e. The unfavorable effects of climate anomalies (drought, over-abundance of water in the topsoil) on the yield formation, yield quantity and quality of potato depended decisively on the time of year when they were experienced and the period for which they lasted. f. With the help of regression analysis it was found the polynomial correlation between rainfall and yield could be observed in case of the control: R = 0.98***, N: R = 0.95***, NP: R = 0.96***, NK: R = 0.95***, NPK: R = 0.98***, NPKMg: R = 0.96*** nutrition systems. The optimum yield ranges between 17-20 t ha-1 at 280-350 mm of rainfall. Climate-rainfall-change and mineral fertilisation effects on winter wheat yield a. Climate-rainfall-conditions of winter wheat years were determined by mainly precipitation on-, average (1982 and 1989)-, drought (1976 and 1990)-, dry (1974) and rainy (1978 and 1980) level. b. Experimental years climate-rainfall-character were formed by winter half-years (october-march), months (october-september), pre-months of sowing (august), critical sequential month number in vegetation seasons (september-july) and critical sequential month number in experimental years (september-august). c. In average years without any mineral fertilisation wheat yield was stabilized on the level of 1.8 t ha-1. Under N, P, K and Mg fertiliser input minimum and maximum yields were 2.7 and 4.1 t ha-1. Yield was only increased by whole NPK and Mg completed NPKMg treatment. d. Without mineral fertilisation on control plots yield was decreased by drought year effect compared with average with a 39%. On N, NP and NK combinations yields were diminished to 48%. Drought damage on yield production was rised more to 51% by NPK and NPKMg application. e. But in dry years and in average years yields were similar on control plots. Yields were decreased for average year effect on N, NP, NK and NPK, NPKMg treatments with 20% and with 16%. f. Under excess rainy weather conditions without fertiliser application yields were decreased more dramaticaly (56%) than under drought seasons (39%) to case of average rainfall effects. Yield was damaged with a 47% by unfavourable (N, NP, NK) nutrition. But this negative effect of excess rainfall condition was diminished on NPK and NPKMg treatments to 41%. g. Correlations of regression analysis between yields and the sums of precipitations during vegetation seasons (control: R = 0.59***, N: R = 0.57***, NP: R = 0.76***, NK: R = 0.53**, NPK: R = 0.67***, NPKMg R = 0.70**) showed that optimum yields will develop in 450-500 mm range. Above these range of rainfall yields will decrease swiftly. This paper gives opportunities summarise quantified results of rye-potato-winter wheat researches with regarding to interaction effects and relationships between climate (rainfall)-mineral nutrition-crop production changes at Hungary in a long term field experiment system under temperate climate conditions to agricultural sustainability. Acknowledgement: This research was supported by Hungarian Academy of Sciences, H-Budapest References [1] Johnston A.E.: Some aspects of nitrogen use efficiency in arable agriculture. K. Scogs-o. Lantbr. Akad. Tidskr. 2000, 8, 139. [2] Márton L.: Climate change and N, P, K, Mg fertilization effect analysis at Tisza-river basin in a long term field experiment. Szent István University, Gödöllő 2001, 9. [3] Márton L.: Climate change, N-fertilisation effect on rye (Secale cereale L.) yield in a long term field experiment. [in:] Rural development-Ecologically farming-Agriculture, (Eds M Palkovics), University Veszprém, Keszthely 2001, 924-929. [4] José A.B., Estáquio M.J. and Márton L.: Results of Crotalaria ssp. effects on soil conservation. Congress on Conservation Agriculture (Eds Armando MV), ECAF., Madrid, 2001. 5, 1-4. [5] Kádár I., Márton L. and Horváth S.: Mineral fertilisation of potato (Solanum tuberosum L.) on calcareous chernozem soil. Plant Production, 2000, 49, 291-306. [6] Harnos, Zs.: Időjárás és időjárás-termés összefüggéseinek idősoros elemzése, [in:] Aszály 1983 (Szerk.: Baráth Cs-né, Győrffy B., Harnos Zs.). KÉE. Budapest 1993. [7] Márton L.: Climate-Rainfall Change (CRC) and mineral fertilisation (MF) effects on different crop production. [in:] Challenges of the new millennium our joint responsibility. (Eds A. Borhidi). MTA ÖBKI, Budapest 2002, 1, 110-111. [8] Márton L.: Rainfall, mineral fertilisation and winter wheat (Triticum aestivum L.) yield relations. Plant Production, 2002, 51, 529-542.

Virtual Rain and Stream Gauge Information Service to Support Effective Decision Making in Lower Mekong Countries

NASA Astrophysics Data System (ADS)

Basnayake, S. B.; Jayasinghe, S.; Apirumanekul, C.; Pudashine, J.; Anderson, E.; Cutter, P. G.; Ganz, D.; Towashiraporn, P.

2016-12-01

During 1995-2015, about 47% of all weather related disasters affected 2.3 billion people, and the majority (95%) of them were from Asia. About 89% of the deaths due to storms were reported in lower and middle income courtiers even though they only experienced about 26% of all storms. In most of the developing countries, decision making processes are hampered by sparse hydro-meteorological observation networks. Thus, the virtual rain and stream gauge information service is designed and developed by SERVIR-Mekong of Asian Disaster Preparedness Center (ADPC) to support effective decision making in Cambodia, Lao PDR, Myanmar, Thailand and Vietnam. The information service contains four remotely sensed data streams with regional and country specific sub setting features for easy access in limited internet bandwidths conditions. It provides rainfall data from near real time GPM IMERG (6 hours latency) with 30 minutes and 0.1X0.1 degree resolutions; TRMM daily data of 0.25X0.25 degree resolution from 1998; and CHIRPS daily data of 0.05X0.05 degree resolution since 1981 with the latency of one month. Satellite altimetry-based Jason 2 Interim Geophysical Data Record virtual stream gauge data (water body height) is provided with 12 days latency for 15 identified locations in 5 countries since 2008. To regionalize and further promote uptake of these data, TRMM monthly data has been bias corrected for Myanmar as a pilot study with spatially interpolated 18-year average (1998-2015) observed monthly rainfall data using Standard Deviation (SD) Ratio method. The results encourage to use SD ratio method for monthly bias corrections. Gamma distribution method will be tested for correcting biases of daily rainfall data with the notion that it has some limitations of capturing extreme rainfalls. The virtual rain and stream gauge information service is publically accessible through a web-based user interface hosted at SERVIR-Mekong of ADPC. Usage of the information service by partner agencies is ensured through co-development and capacity building programs. This service helps lower Mekong countries and their relevant organizations effectively use of remotely sensed data for day-to-day operations, contingency and development planning.

Modeling seasonal and interannual variability in ecosystem carbon cycling for the Brazilian Amazon region

NASA Astrophysics Data System (ADS)

Potter, Christopher; Klooster, Steven; de Carvalho, Claudio Reis; Genovese, Vanessa Brooks; Torregrosa, Alicia; Dungan, Jennifer; Bobo, Matthew; Coughlan, Joseph

2001-05-01

Previous field measurements have implied that undisturbed Amazon forests may represent a substantial terrestrial sink for atmospheric carbon dioxide. We investigated this hypothesis using a regional ecosystem model for net primary production (NPP) and soil biogeochemical cycling. Seasonal and interannual controls on net ecosystem production (NEP) were studied with integration of high-resolution (8-km) multiyear satellite data to characterize Amazon land surface properties over time. Background analysis of temporal and spatial relationships between regional rainfall patterns and satellite observations (for vegetation land cover, fire counts, and smoke aerosol effects) reveals several notable patterns in the model driver data. Autocorrelation analysis for monthly vegetation "greenness" index (normalized difference vegetation index, NDVI) from the advanced very high resolution radiometer (AVHRR) and monthly rainfall indicates a significant lag time correlation of up to 12 months. At lag times approaching 36 months, autocorrelation function (ACF) values did not exceed the 95% confidence interval at locations west of about 47°W, which is near the transition zone of seasonal tropical forest and other (nonforest) vegetation types. Even at lag times of 12 months or less, the location near Manaus (approximately 60°W) represents the farthest western point in the Amazon region where seasonality of rainfall accounts significantly for monthly variations in forest phenology, as observed using NDVI. Comparisons of NDVI seasonal profiles in areas of the eastern Amazon widely affected by fires (as observed from satellite) suggest that our adjusted AVHRR-NDVI captures year-to-year variation in land cover greenness with minimal interference from small fires and smoke aerosols. Ecosystem model results using this newly generated combination of regional forcing data from satellite suggest that undisturbed Amazon forests can be strong net sinks for atmospheric carbon dioxide, particularly during wet (non El Niño) years. However, drought effects during El Niño years can reduce NPP in primary forests of the eastern Amazon by 10-20%, compared to long-term average estimates of regional productivity. Annual NEP for the region is predicted to range from -0.4 Pg C yr-1 (net CO2 source) to 0.5 Pg C yr-1 (net CO2 sink), with large interannual variability over the states of Pará, Maranhao, and Amazonas. As in the case of predicted NPP, it appears that periods of relatively high solar surface irradiance combined with several months of adequate rainfall are required to sustain the forest carbon sink for positive yearly NEP estimates.

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.

Exploring the Appropriate Drought Index in a Humid Tropical Area with Complex Terrain

NASA Astrophysics Data System (ADS)

Lee, C. H.; Chen, W. T.; Lo, M. H.; Chu, J. L.; Chen, Y. J.; Chen, Y. M.

2017-12-01

The goal of the present study is to identify the most appropriate index to monitor droughts in Taiwan, an extremely humid region with steep terrain. Three drought indices were calculated using in situ high resolution rainfall observations and compared: the Standardized Precipitation Index (SPI), the self-calibrating Palmer Drought Severity Index (sc-PDSI), and the Standardized Precipitation Evapotranspiration Index (SPEI). In Taiwan, the average amount of precipitation is around 2500 mm per year, which is six times of the global average. However, with the complexity of topography and the uneven distribution throughout the year in Taiwan, abundant rainfall during the wet season is mostly lost as runoff. Severe droughts occur frequently at approximately once per decade, while moderate droughts occur every 2 years. Earlier studies indicated that the SPI is limited in describing drought events because the temperature effect is not taken into account in SPI as in the sc-PDSI. In addition, SPEI, which take the Penman-Monteith Potential Evapotranspiration (PET_pm) into account, is also considered in the present study. The atmospheric water demand increases as temperature increasing, which is reflected in PET_pm. To calculate the three drought indices, we will use the monthly average temperature to calculate the PET_pm and monthly accumulated precipitation from automatic weather stations from the Central Weather Bureau. All of the detected droughts are evaluated against the dataset of historical drought records in Taiwan. We explore whether the temperature is an important factor for the occurrence of droughts in Taiwan first. In addition to severe droughts, we expect that SPEI and sc-PDSI can detect more moderate droughts in Taiwan. Second, we survey the performance of three drought indices for the detection of droughts in Taiwan. Because the soil water model used in sc-PDSI doesn't consider the effect of steep terrain, and because SPI only considers the monthly precipitation, we expect SPEI to be the more appropriate index for monitoring drought events in Taiwan.

Phenotypic variation and differentiated gene expression of Australian plants in response to declining rainfall

PubMed Central

Fowler, William; Lim, Sim Lin; Enright, Neal; He, Tianhua

2016-01-01

Declining rainfall is projected to have negative impacts on the demographic performance of plant species. Little is known about the adaptive capacity of species to respond to drying climates, and whether adaptation can keep pace with climate change. In fire-prone ecosystems, episodic recruitment of perennial plant species in the first year post-fire imposes a specific selection environment, offering a unique opportunity to quantify the scope for adaptive response to climate change. We examined the growth of seedlings of four fire-killed species under control and drought conditions for seeds from populations established in years following fire receiving average-to-above-average winter rainfall, or well-below-average winter rainfall. We show that offspring of plants that had established under drought had more efficient water uptake, and/or stored more water per unit biomass, or developed denser leaves, and all maintained higher survival in simulated drought than did offspring of plants established in average annual rainfall years. Adaptive phenotypic responses were not consistent across all traits and species, while plants that had established under severe drought or established in years with average-to-above-average rainfall had an overall different physiological response when growing either with or without water constraints. Seedlings descended from plants established under severe drought also had elevated gene expression in key pathways relating to stress response. Our results demonstrate the capacity for rapid adaptation to climate change through phenotypic variation and regulation of gene expression. However, effective and rapid adaptation to climate change may vary among species depending on their capacity to maintain robust populations under multiple stresses. PMID:28018654

Phenotypic variation and differentiated gene expression of Australian plants in response to declining rainfall.

PubMed

D'Agui, Haylee; Fowler, William; Lim, Sim Lin; Enright, Neal; He, Tianhua

2016-11-01

Declining rainfall is projected to have negative impacts on the demographic performance of plant species. Little is known about the adaptive capacity of species to respond to drying climates, and whether adaptation can keep pace with climate change. In fire-prone ecosystems, episodic recruitment of perennial plant species in the first year post-fire imposes a specific selection environment, offering a unique opportunity to quantify the scope for adaptive response to climate change. We examined the growth of seedlings of four fire-killed species under control and drought conditions for seeds from populations established in years following fire receiving average-to-above-average winter rainfall, or well-below-average winter rainfall. We show that offspring of plants that had established under drought had more efficient water uptake, and/or stored more water per unit biomass, or developed denser leaves, and all maintained higher survival in simulated drought than did offspring of plants established in average annual rainfall years. Adaptive phenotypic responses were not consistent across all traits and species, while plants that had established under severe drought or established in years with average-to-above-average rainfall had an overall different physiological response when growing either with or without water constraints. Seedlings descended from plants established under severe drought also had elevated gene expression in key pathways relating to stress response. Our results demonstrate the capacity for rapid adaptation to climate change through phenotypic variation and regulation of gene expression. However, effective and rapid adaptation to climate change may vary among species depending on their capacity to maintain robust populations under multiple stresses.

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.

Rainwater runoff retention on an aged intensive green roof.

PubMed

Speak, A F; Rothwell, J J; Lindley, S J; Smith, C L

2013-09-01

Urban areas are characterised by large proportions of impervious surfaces which increases rainwater runoff and the potential for surface water flooding. Increased precipitation is predicted under current climate change projections, which will put further pressure on urban populations and infrastructure. Roof greening can be used within flood mitigation schemes to restore the urban hydrological balance of cities. Intensive green roofs, with their deeper substrates and higher plant biomass, are able to retain greater quantities of runoff, and there is a need for more studies on this less common type of green roof which also investigate the effect of factors such as age and vegetation composition. Runoff quantities from an aged intensive green roof in Manchester, UK, were analysed for 69 rainfall events, and compared to those on an adjacent paved roof. Average retention was 65.7% on the green roof and 33.6% on the bare roof. A comprehensive soil classification revealed the substrate, a mineral soil, to be in good general condition and also high in organic matter content which can increase the water holding capacity of soils. Large variation in the retention data made the use of predictive regression models unfeasible. This variation arose from complex interactions between Antecedant Dry Weather Period (ADWP), season, monthly weather trends, and rainfall duration, quantity and peak intensity. However, significantly lower retention was seen for high rainfall events, and in autumn, which had above average rainfall. The study period only covers one unusually wet year, so a longer study may uncover relationships to factors which can be applied to intensive roofs elsewhere. Annual rainfall retention for Manchester city centre could be increased by 2.3% by a 10% increase in intensive green roof construction. The results of this study will be of particular interest to practitioners implementing greenspace adaptation in temperate and cool maritime climates. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Statistical Method for Identification of Potential Groundwater Recharge Zone

NASA Astrophysics Data System (ADS)

Banerjee, Pallavi; Singh, V. S.

2010-05-01

The effective development of groundwater resource is essential for a country like India. Artificial recharge is the planned, human activity of augmenting the amount of groundwater available through works designed to increase the natural replenishment or percolation of surface waters into the groundwater aquifers, resulting in a corresponding increase in the amount of groundwater available for abstraction. India receives good amount of average annual rainfall about 114 cm but most of it's part waste through runoff. The imbalance between rainfall and recharge has caused serious shortage of water for drinking, agriculture and industrial purposes. The over exploitation of groundwater due to increasing population is an additional cause of water crisis that resulting in reduction in per capita availability of water in the country. Thus the planning for effective development of groundwater is essential through artificial recharge. Objective of the paper is to identification of artificial recharge zones by arresting runoff through suitable sites to restore groundwater conditions using statistical technique. The water table variation follows a pattern similar to rainfall variation with time delay. The rainfall and its relationship with recharge is a very important process in a shallow aquifer system. Understanding of this process is of critical importance to management of groundwater resource in any terrain. Groundwater system in a top weathered regolith in a balastic terrain forms shallow aquifer is often classified into shallow water table category. In the present study an effort has been made to understand the suitable recharge zone with relation to rainfall and water level by using statistical analysis. Daily time series data of rainfall and borehole water level data are cross correlated to investigate variations in groundwater level response time during the months of monsoon. This measurement facilitate to demarcate favorable areas for Artificial Recharge. KEYWORDS: Water level; Rainfall; Recharge; Statistical analysis; Cross correlation.

Understanding litter decomposition in semiarid ecosystems: linking leaf traits, UV exposure and rainfall variability

PubMed Central

Gaxiola, Aurora; Armesto, Juan J.

2015-01-01

Differences in litter quality, microbial activity or abiotic conditions cannot fully account for the variability in decomposition rates observed in semiarid ecosystems. Here we tested the role of variation in litter quality, water supply, and UV radiation as drivers of litter decomposition in arid lands. And show that carry-over effects of litter photodegradation during dry periods can regulate decomposition during subsequent wet periods. We present data from a two-phase experiment, where we first exposed litter from a drought-deciduous and an evergreen shrub to natural UV levels during five, rainless summer months and, subsequently, in the laboratory, we assessed the carry-over effects of photodegradation on biomass loss under different irrigation treatments representing the observed range of local rainfall variation among years (15–240 mm). Photodegradation of litter in the field produced average carbon losses of 12%, but deciduous Proustia pungens lost >25%, while evergreen Porlieria chilensis less than 5%. Natural exposure to UV significantly reduced carbon-to-nitrogen and lignin:N ratios in Proustia litter but not in Porlieria. During the subsequent wet phase, remaining litter biomass was lower in Proustia than in Porlieria. Indeed UV exposure increased litter decomposition of Proustia under low and medium rainfall treatments, whereas no carry-over effects were detected under high rainfall treatment. Consequently, for deciduous Proustia carry-over effects of UV exposure were negligible under high irrigation. Litter decomposition of the evergreen Porlieria depended solely on levels of rainfall that promote microbial decomposers. Our two-phase experiment revealed that both the carry-over effects of photodegradation and litter quality, modulated by inter-annual variability in rainfall, can explain the marked differences in decomposition rates and the frequent decoupling between rainfall and litter decomposition observed in semiarid ecosystems. PMID:25852705

Understanding litter decomposition in semiarid ecosystems: linking leaf traits, UV exposure and rainfall variability.

PubMed

Gaxiola, Aurora; Armesto, Juan J

2015-01-01

Differences in litter quality, microbial activity or abiotic conditions cannot fully account for the variability in decomposition rates observed in semiarid ecosystems. Here we tested the role of variation in litter quality, water supply, and UV radiation as drivers of litter decomposition in arid lands. And show that carry-over effects of litter photodegradation during dry periods can regulate decomposition during subsequent wet periods. We present data from a two-phase experiment, where we first exposed litter from a drought-deciduous and an evergreen shrub to natural UV levels during five, rainless summer months and, subsequently, in the laboratory, we assessed the carry-over effects of photodegradation on biomass loss under different irrigation treatments representing the observed range of local rainfall variation among years (15-240 mm). Photodegradation of litter in the field produced average carbon losses of 12%, but deciduous Proustia pungens lost >25%, while evergreen Porlieria chilensis less than 5%. Natural exposure to UV significantly reduced carbon-to-nitrogen and lignin:N ratios in Proustia litter but not in Porlieria. During the subsequent wet phase, remaining litter biomass was lower in Proustia than in Porlieria. Indeed UV exposure increased litter decomposition of Proustia under low and medium rainfall treatments, whereas no carry-over effects were detected under high rainfall treatment. Consequently, for deciduous Proustia carry-over effects of UV exposure were negligible under high irrigation. Litter decomposition of the evergreen Porlieria depended solely on levels of rainfall that promote microbial decomposers. Our two-phase experiment revealed that both the carry-over effects of photodegradation and litter quality, modulated by inter-annual variability in rainfall, can explain the marked differences in decomposition rates and the frequent decoupling between rainfall and litter decomposition observed in semiarid ecosystems.

Effect of Climate Factors on the Childhood Pneumonia in Papua New Guinea: A Time-Series Analysis.

PubMed

Kim, Jinseob; Kim, Jong-Hun; Cheong, Hae-Kwan; Kim, Ho; Honda, Yasushi; Ha, Mina; Hashizume, Masahiro; Kolam, Joel; Inape, Kasis

2016-02-15

This study aimed to assess the association between climate factors and the incidence of childhood pneumonia in Papua New Guinea quantitatively and to evaluate the variability of the effect size according to their geographic properties. The pneumonia incidence in children under five-year and meteorological factors were obtained from six areas, including monthly rainfall and the monthly average daily maximum temperatures during the period from 1997 to 2006 from national health surveillance data. A generalized linear model was applied to measure the effect size of local and regional climate factor. The pooled risk of pneumonia in children per every 10 mm increase of rainfall was 0.24% (95% confidence interval: -0.01%-0.50%), and risk per every 1 °C increase of the monthly mean of the maximum daily temperatures was 4.88% (95% CI: 1.57-8.30). Southern oscillation index and dipole mode index showed an overall negative effect on childhood pneumonia incidence, -0.57% and -4.30%, respectively, and the risk of pneumonia was higher in the dry season than in the rainy season (pooled effect: 12.08%). There was a variability in the relationship between climate factors and pneumonia which is assumed to reflect distribution of the determinants of and vulnerability to pneumonia in the community.

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.

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.

Pattern Analysis of El Nino and La Nina Phenomenon Based on Sea Surface Temperature (SST) and Rainfall Intensity using Oceanic Nino Index (ONI) in West Java Area

NASA Astrophysics Data System (ADS)

Prasetyo, Yudo; Nabilah, Farras

2017-12-01

Climate change occurs in 1998-2016 brings significant alteration in the earth surface. It is affects an extremely anomaly temperature such as El Nino and La Nina or mostly known as ENSO (El Nino Southern Oscillation). West Java is one of the regions in Indonesia that encounters the impact of this phenomenon. Climate change due to ENSO also affects food production and other commodities. In this research, processing data method is conducted using programming language to process SST data and rainfall data from 1998 to 2016. The data are sea surface temperature from NOAA satellite, SST Reynolds (Sea Surface Temperature) and daily rainfall temperature from TRMM satellite. Data examination is done using analysis of rainfall spatial pattern and sea surface temperature (SST) where is affected by El Nino and La Nina phenomenon. This research results distribution map of SST and rainfall for each season to find out the impacts of El Nino and La Nina around West Java. El Nino and La Nina in Java Sea are occurring every August to February. During El Nino, sea surface temperature is between 27°C - 28°C with average temperature on 27.71°C. Rainfall intensity is 1.0 mm/day - 2.0 mm/day and the average are 1.63 mm/day. During La Nina, sea surface temperature is between 29°C - 30°C with average temperature on 29.06°C. Rainfall intensity is 9.0 mm/day - 10 mm/day, and the average is 9.74 mm/day. The correlation between rainfall and SST is 0,413 which is expresses a fairly strong correlation between parameters. The conclusion is, during La Nina SST and rainfall increase. While during El Nino SST and rainfall decrease. Hopefully this research could be a guideline to plan disaster mitigation in West Java region that is related extreme climate change.

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.

The biogeochemistry of arsenic in a remote UK upland site: trends in rainfall and runoff, and comparisons with urban rivers.

PubMed

Rowland, A P; Neal, C; Reynolds, B; Jarvie, H P; Sleep, D; Lawlor, A J; Neal, M

2011-05-01

Ten years of monitoring of rainfall and streams in the remote acidic and acid sensitive moorland and afforested moorland of upland mid-Wales reveals concentrations of arsenic (As) typically <1 µg L(-1). On average, the lowest concentrations occur within rainfall and they have declined over time probably in response to reductions in global emissions. There is a corresponding reduction within the streams except for forested systems where concentrations up to doubled following clear-fell. Within the streams there are both annual cycling and diurnal cycling of As. The annual cycling gives maxima during the summer months and this probably reflects the importance of groundwater inputs and mineralisation/desorption from the surface soil layers. Correspondingly, the diurnal cycling occurs during the summer months at low flow periods with As concentrations highest in the afternoon/evening. For the urban/industrial basins of northern England with historically a much higher As deposition, land contamination and effluent discharges, comparative data indicate As concentrations around three fold higher: strong seasonal patterns are observed for the same reasons as with the uplands. Across the sites, the As concentrations are over an order of magnitude lower than that of environmental concern. Nonetheless, the results clearly show the effects of declining emissions on rainfall deposition and some indication of areas of historic contamination. Arsenic is mainly present in the <0.45 fraction, but cross-flow filtration indicates that approx. 43% is in the colloidal phase at the clean water sites, and 16% in the colloidal phase at the contaminated sites. Part of this colloidal component may well be associated with organic carbon.

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. 

Forecasting zoonotic cutaneous leishmaniasis using meteorological factors in eastern Fars province, Iran: a SARIMA analysis.

PubMed

Tohidinik, Hamid Reza; Mohebali, Mehdi; Mansournia, Mohammad Ali; Niakan Kalhori, Sharareh R; Ali-Akbarpour, Mohsen; Yazdani, Kamran

2018-05-22

To predict the occurrence of zoonotic cutaneous leishmaniasis (ZCL) and evaluate the effect of climatic variables on disease incidence in the east of Fars province, Iran using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The Box-Jenkins approach was applied to fit the SARIMA model for ZCL incidence from 2004 to 2015. Then the model was used to predict the number of ZCL cases for the year 2016. Finally, we assessed the relation of meteorological variables (rainfall, rainy days, temperature, hours of sunshine and relative humidity) with ZCL incidence. SARIMA(2,0,0) (2,1,0)12 was the preferred model for predicting ZCL incidence in the east of Fars province (validation Root Mean Square Error, RMSE = 0.27). It showed that ZCL incidence in a given month can be estimated by the number of cases occurring 1 and 2 months, as well as 12 and 24 months earlier. The predictive power of SARIMA models was improved by the inclusion of rainfall at a lag of 2 months (β = -0.02), rainy days at a lag of 2 months (β = -0.09) and relative humidity at a lag of 8 months (β = 0.13) as external regressors (P-values < 0.05). The latter was the best climatic variable for predicting ZCL cases (validation RMSE = 0.26). Time series models can be useful tools to predict the trend of ZCL in Fars province, Iran; thus, they can be used in the planning of public health programmes. Introducing meteorological variables into the models may improve their precision. © 2018 John Wiley & Sons Ltd.

Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

2016-03-01

Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

Effects of episodic rainfall on a subterranean estuary

NASA Astrophysics Data System (ADS)

Yu, Xiayang; Xin, Pei; Lu, Chunhui; Robinson, Clare; Li, Ling; Barry, D. A.

2017-07-01

Numerical simulations were conducted to examine the effect of episodic rainfall on nearshore groundwater dynamics in a tidally influenced unconfined coastal aquifer, with a focus on both long-term (yearly) and short-term (daily) behavior of submarine groundwater discharge (SGD) and seawater intrusion (SWI). The results showed nonlinear interactions among the processes driven by rainfall, tides, and density gradients. Rainfall-induced infiltration increased the yearly averaged fresh groundwater discharge to the ocean but reduced the extents of the saltwater wedge and upper saline plume as well as the total rate of seawater circulation through both zones. Overall, the net effect of the interactions led to an increase of the SGD. The nearshore groundwater responded to individual rainfall events in a delayed and cumulative fashion, as evident in the variations of daily averaged SGD and salt stored in the saltwater wedge (quantifying the extent of SWI). A generalized linear model (GLM) along with a Gamma distribution function was developed to describe the delayed and prolonged effect of rainfall events on short-term groundwater behavior. This model validated with results of daily averaged SGD and SWI from the simulations of groundwater and solute transport using independent rainfall data sets, performed well in predicting the behavior of the nearshore groundwater system under the combined influence of episodic rainfall, tides, and density gradients. The findings and developed GLM form a basis for evaluating and predicting SGD, SWI, and associated mass fluxes from unconfined coastal aquifers under natural conditions, including episodic rainfall.

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.

Recent variations in geopotential height associated with West African monsoon variability

NASA Astrophysics Data System (ADS)

Okoro, Ugochukwu K.; Chen, Wen; Nath, Debashis

2018-02-01

In the present study, the atmospheric circulation patterns associated with the seasonal West Africa (WA) monsoon (WAM) rainfall variability has been investigated. The observational rainfall data from the Climatic Research Unit (CRU) and atmospheric fields from the National Center for Environmental Prediction (NCEP) reanalysis 2, from 1979 to 2014, have been used. The rainfall variability extremes, classified as wet or dry years, are the outcomes of simultaneous 6-month SPI at the three rainfall zones, which shows increasing trends [Guinea Coast (GC = 0.012 year-1), Eastern Sudano Sahel (ESS = 0.045 year-1) and Western Sudano Sahel (WSS = 0.056 year-1) from Sen's slope]; however, it is significant only in the Sahel region (α = 0.05 and α = 0.001 at ESS and WSS, respectively, from Mann-Kendall test). The vertical profile of the geopotential height (GpH) during the wet and dry years reveals that the 700 hPa anomalies show remarkable pattern at about 8°N to 13°N. This shows varying correlation with the zonal averaged vertically integrated moisture flux convergence and rainfall anomalies, respectively, as well as the oceanic pulsations indexes [Ocean Nino Index (ONI) and South Atlantic Ocean dipole index (SAODI), significant from t test], identified as precursors to the Sahel and GC rainfall variability respectively. The role of GpH anomalies at 700 hPa has been identified as the facilitator to the West African Westerly Jet's input to the moisture flux transported over the WA. This is a new perspective of the circulation processes associated with WAM and serves as a basis for modeling investigations.

Rainfall is a risk factor for sporadic cases of Legionella pneumophila pneumonia.

PubMed

Garcia-Vidal, Carolina; Labori, Maria; Viasus, Diego; Simonetti, Antonella; Garcia-Somoza, Dolors; Dorca, Jordi; Gudiol, Francesc; Carratalà, Jordi

2013-01-01

It is not known whether rainfall increases the risk of sporadic cases of Legionella pneumonia. We sought to test this hypothesis in a prospective observational cohort study of non-immunosuppressed adults hospitalized for community-acquired pneumonia (1995-2011). Cases with Legionella pneumonia were compared with those with non-Legionella pneumonia. Using daily rainfall data obtained from the regional meteorological service we examined patterns of rainfall over the days prior to admission in each study group. Of 4168 patients, 231 (5.5%) had Legionella pneumonia. The diagnosis was based on one or more of the following: sputum (41 cases), antigenuria (206) and serology (98). Daily rainfall average was 0.556 liters/m(2) in the Legionella pneumonia group vs. 0.328 liters/m(2) for non-Legionella pneumonia cases (p = 0.04). A ROC curve was plotted to compare the incidence of Legionella pneumonia and the weighted median rainfall. The cut-off point was 0.42 (AUC 0.54). Patients who were admitted to hospital with a prior weighted median rainfall higher than 0.42 were more likely to have Legionella pneumonia (OR 1.35; 95% CI 1.02-1.78; p = .03). Spearman Rho correlations revealed a relationship between Legionella pneumonia and rainfall average during each two-week reporting period (0.14; p = 0.003). No relationship was found between rainfall average and non-Legionella pneumonia cases (-0.06; p = 0.24). As a conclusion, rainfall is a significant risk factor for sporadic Legionella pneumonia. Physicians should carefully consider Legionella pneumonia when selecting diagnostic tests and antimicrobial therapy for patients presenting with CAP after periods of rainfall.

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.

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.

Erosivity, surface runoff, and soil erosion estimation using GIS-coupled runoff-erosion model in the Mamuaba catchment, Brazil.

PubMed

Marques da Silva, Richarde; Guimarães Santos, Celso Augusto; Carneiro de Lima Silva, Valeriano; Pereira e Silva, Leonardo

2013-11-01

This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha(-1) year(-1); most of the area of the catchment (60%) was predicted to suffer from a low- to moderate-erosion risk (<6 t ha(-1) year(-1)) and, in 20% of the catchment, the soil erosion was estimated to exceed > 12 t ha(-1) year(-1). Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.

Seasonal variation and climate change impact in Rainfall Erosivity across Europe

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

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.

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

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

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.

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.

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.

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

Rainfall Stochastic models

NASA Astrophysics Data System (ADS)

Campo, M. A.; Lopez, J. J.; Rebole, J. P.

2012-04-01

This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series were recorded every ten minutes and hourly, aggregated. Preliminary results show adequate simulation of the main features of rain. Main variables are well simulated for time series of ten minutes, also over one hour precipitation time series, which are those that generate higher rainfall hydrologic design. For coarse scales, less than one hour, rainfall durations are not appropriate under the simulation. A hypothesis may be an excessive number of simulated events, which causes further fragmentation of storms, resulting in an excess of rain "short" (less than 1 hour), and therefore also among rain events, compared with the ones that occur in the actual series.

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.

Forecasting the number of zoonotic cutaneous leishmaniasis cases in south of Fars province, Iran using seasonal ARIMA time series method.

PubMed

Sharafi, Mehdi; Ghaem, Haleh; Tabatabaee, Hamid Reza; Faramarzi, Hossein

2017-01-01

To predict the trend of cutaneous leishmaniasis and assess the relationship between the disease trend and weather variables in south of Fars province using Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The trend of cutaneous leishmaniasis was predicted using Mini tab software and SARIMA model. Besides, information about the disease and weather conditions was collected monthly based on time series design during January 2010 to March 2016. Moreover, various SARIMA models were assessed and the best one was selected. Then, the model's fitness was evaluated based on normality of the residuals' distribution, correspondence between the fitted and real amounts, and calculation of Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC). The study results indicated that SARIMA model (4,1,4)(0,1,0) (12) in general and SARIMA model (4,1,4)(0,1,1) (12) in below and above 15 years age groups could appropriately predict the disease trend in the study area. Moreover, temperature with a three-month delay (lag3) increased the disease trend, rainfall with a four-month delay (lag4) decreased the disease trend, and rainfall with a nine-month delay (lag9) increased the disease trend. Based on the results, leishmaniasis follows a descending trend in the study area in case drought condition continues, SARIMA models can suitably measure the disease trend, and the disease follows a seasonal trend. Copyright © 2017 Hainan Medical University. Production and hosting by Elsevier B.V. All rights reserved.

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.

Predictability of rainfall and teleconnections patterns influencing on Southwest Europe from sea surfaces temperatures

NASA Astrophysics Data System (ADS)

Lorenzo, M. N.; Iglesias, I.; Taboada, J. J.; Gómez-Gesteira, M.; Ramos, A. M.

2009-04-01

This work assesses the possibility of doing a forecast of rainfall and the main teleconnections patterns that influences climate in Southwest Europe by using sea surface temperature anomalies (SSTA). The area under study is located in the NW Iberian Peninsula. This region has a great oceanic influence on its climate and has an important dependency of the water resources. In this way if the different SST patterns are known, the different rainfall situations can be predicted. On the other hand, the teleconnection patterns, which have strong weight on rainfall, are influenced by the SSTA of different areas. In the light of this, the aim of this study is to explore the relationship between global SSTAs, rainfall and the main teleconnection patterns influencing on Europe. The SST data with a 2.0 degree resolution was provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA. A monthly averaged data from 1 January 1951 through December 2006 was considered. The monthly precipitation data from 1951-2006 were obtained from the database CLIMA of the University of Santiago de Compostela with data from the Meteorological State Agency (AEMET) and the Regional Government of Galicia. The teleconnection indices were taken of the Climate Prediction Center of the NOAA between 1950 and 2006. A monthly and seasonal study was analysed considering up to three months of delay in the first case and up to four seasons of delay in the second case. The Pearson product-moment correlation coefficient r was considered to quantify linear associations between SSTA and precipitation and/or SSTA and teleconnection indices. A test for field-significance was applied considering the properties of finiteness and interdependence of the spatial grid to avoid spurious correlations. Analysing the results obtained with the global SSTA and the teleconnection indices, a great number of ocean regions with high correlations can be found. The spatial patterns show very high correlations with Indian Ocean waters which could be related with the Monsoon. Another area with high correlation is Equatorial Pacific Ocean, the area related with the ENSO phenomenon. These SSTAs could be used to forecast rainfall anomalies in spring season in the area of NW Iberian Peninsula. Results show that La Niña years almost always announces dry spring in NW Iberian Peninsula. Nevertheless, El Niño years do not preclude the appearance of wet spring. Because of the progress that has been made in its prediction, the relation between ENSO and climate in NW Iberian Peninsula is of interest with respect to potential seasonal predictability and the results can be extended to the south west of Europe. [1] Lorenzo, M.N. and J. J. Taboada (2005). Influences of atmospheric variability on freshwater input in Galician Rías in winter. Journal of Atmospheric and Ocean Science Vol 10, No 4, 377-387. [2] Lorenzo, M.N. I. Iglesias, J.J. Taboada and M. Gómez-Gesteira. Relationship between monthly rainfall in NW Iberian Peninsula and North Atlantic sea surface temperature. International Journal of Climatology. (Submitted to International Journal of Climatology). [3] Philips, I.D. and J. Thorpe (2006): Icelandic precipitation-North Atlantic sea-surface temperature associations. International Journal of Climatology 26: 1201-1221.

Contributions of Tropical Cyclones to the North Atlantic Climatological Rainfall as Observed from Satellites

NASA Technical Reports Server (NTRS)

Rodgers, Edward B.; Adler, Robert F.; Pierce, Harold F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The tropical cyclone rainfall climatology study that was performed for the North Pacific was extended to the North Atlantic. Similar to the North Pacific tropical cyclone study, mean monthly rainfall within 444 km of the center of the North Atlantic tropical cyclones (i.e., that reached storm stage and greater) was estimated from passive microwave satellite observations during, an eleven year period. These satellite-observed rainfall estimates were used to assess the impact of tropical cyclone rainfall in altering the geographical, seasonal, and inter-annual distribution of the North Atlantic total rainfall during, June-November when tropical cyclones were most abundant. The main results from this study indicate: 1) that tropical cyclones contribute, respectively, 4%, 3%, and 4% to the western, eastern, and entire North Atlantic; 2) similar to that observed in the North Pacific, the maximum in North Atlantic tropical cyclone rainfall is approximately 5 - 10 deg poleward (depending on longitude) of the maximum non-tropical cyclone rainfall; 3) tropical cyclones contribute regionally a maximum of 30% of the total rainfall 'northeast of Puerto Rico, within a region near 15 deg N 55 deg W, and off the west coast of Africa; 4) there is no lag between the months with maximum tropical cyclone rainfall and non-tropical cyclone rainfall in the western North Atlantic, while in the eastern North Atlantic, maximum tropical cyclone rainfall precedes maximum non-tropical cyclone rainfall; 5) like the North Pacific, North Atlantic tropical cyclones Of hurricane intensity generate the greatest amount of rainfall in the higher latitudes; and 6) warm ENSO events inhibit tropical cyclone rainfall.

Spatial and temporal patterns of Amazon rainfall. Consequences for the planning of agricultural occupation and the protection of primary forests.

PubMed

Sombroek, W

2001-11-01

The spatial and temporal pattern of annual rainfall and the strength of the dry season within the Amazon region are poorly known. Existing rainfall maps are based on the data from full-scale, long-term meteorological stations, operated by national organizations linked to the World Meteorological Organisation, such as INMET in Brazil. Stations with 30 or more years of uninterrupted and reliable recordings are very few, considering the size of the region, and most of them are located along the major rivers. It has been suggested that rainfall conditions away from these rivers are substantially different. An analysis has been made of the records of a network of simple pluviometric sites in the Brazilian part of the region as maintained by the National Agency for Electric Energy (ANEEL) since 1970. The latter data sets were used to draw more detailed maps on annual rainfall, and on the strength of the dry season in particular; average number of consecutive months with less than 100 mm, 50 mm, and 10 mm, respectively. Also, some data were obtained on the spatial expression of El Niño events within the region. Subregional differences are large, and it is argued that they are important for the success or failure of agricultural settlements; for the hazard of large-scale fire damage of the still existing primary forest vegetation; for the functioning of this land cover as stock and sink of CO2, and for the likelihood that secondary forests on abandoned agricultural lands will have less biomass. The effects of past El Niño rainfall anomalies on the biodiversity of the natural savannahs within the forest region are discussed.

Spatial variability of mountain stream dynamics along the Ethiopian Rift Valley escarpment

NASA Astrophysics Data System (ADS)

Asfaha, Tesfaalem-Ghebreyohannes; Frankl, Amaury; Zenebe, Amanuel; Haile, Mitiku; Nyssen, Jan

2014-05-01

Changes in hydrogeomorphic characteristics of mountain streams are generally deemed to be controlled mainly by land use/cover changes and rainfall variability. This study investigates the spatial variability of peak discharge in relation to land cover, rainfall and topographic variables in eleven catchments of the Ethiopian Rift Valley escarpment (average slope gradient = 48% (± 13%). Rapid deforestation of the escarpment in the second half of the 20th century resulted in the occurrence of strong flash floods, transporting large amounts of discharge and sediment to the lower graben bottom. Due to integrated reforestation interventions as of the 1980s, many of these catchments do show improvement in vegetation cover at various degrees. Daily rainfall was measured using seven non-recording rain gauges, while peak stage discharges were measured after floods using crest stage gauges installed at eleven stream reaches. Peak discharges were calculated using the Manning's equation. Daily area-weighted rainfall was computed for each catchment using the Thiessen Polygon method. To estimate the vegetation cover of each catchment, the Normalized Difference Vegetation Index was calculated from Landsat TM imagery (mean = 0.14 ± 0.05). In the rainy season of 2012, there was a positive correlation between daily rainfall and peak discharge in each of the monitored catchments. In a multiple linear regression analysis (R² = 0.83; P<0.01), average daily peak discharge in all rivers was positively related with rainfall depth and catchment size and negatively with vegetation cover (as represented by average NDVI values). Average slope gradient of the catchments and Gravelius's compactness index did not show a statistically significant relation with peak discharge. This study shows that though the average vegetation cover of the catchments is still relatively low, differences in vegetation cover, together with rainfall variability plays a determining role in the amount of peak discharges in flashy mountain streams.

Rainfall measurement from opportunistic use of earth-space link in Ku Band

NASA Astrophysics Data System (ADS)

Barthès, L.; Mallet, C.

2013-02-01

The present study deals with the development of a low cost microwave device devoted to measure average rain rate observed along earth - satellite links. The principle is to use rain atmospheric attenuation along Earth - space links in Ku-band to deduce the path averaged rain rate. These links are characterized by a path length of a few km through the troposphere. Ground based power measurements are carried out by receiving TV channels from different geostationary satellites in Ku-band. The major difficulty in this study is to retrieve rain characteristics among many fluctuations of the received signal which are due to atmospheric scintillations, changes in the composition of the atmosphere (water vapour concentration, cloud water content) or satellite features (variation of the emitted power, satellite motions). In order to perform a feasibility study of such a device, a measurement campaign has been performed for five months near Paris. This paper proposes an algorithm based on an artificial neural network to identify drought and rainy periods and to suppress the variability of the received signal due to no-rain effects. Taking into account the height of the rain layer, rain attenuation is then inverted to obtain path averaged rain rate. Obtained rainfall rates are compared with co-located rain gauges and radar measurements on the whole experiment period, then the most significant rainy events are analyzed.

Potentiometric surface of the Upper Floridan aquifer, west-central Florida, September 2010

USGS Publications Warehouse

Ortiz, A.G.

2011-01-01

This report, prepared by the U.S. Geological Survey in cooperation with the Southwest Florida Water Management District, is part of a semi-annual series of Upper Floridan aquifer potentiometric-surface map reports for west-central Florida. Potentiometric surface maps have been prepared for January 1964, May 1969, May 1971, May 1973, May 1974, and for each May and September since 1975. Water-level data are collected in May and September each year to show the approximate annual low and high water-level conditions, respectively. This map report shows the potentiometric surface of the Upper Floridan aquifer measured in September 2010. The potentiometric surface is an imaginary surface connecting points of equal altitude to which water will rise in tightly-cased wells that tap a confined aquifer system (Lohman, 1979). This map represents water-level conditions near the end of the wet season, when groundwater levels usually are at an annual high and withdrawals for agricultural use typically are low. The cumulative average rainfall of 53.17 inches for west-central Florida (from October 2009 through September 2010) was 0.41 inches above the historical cumulative average of 52.76 inches (Southwest Florida Water Management District, 2010). Historical cumulative averages are calculated from regional rainfall summary reports (1915 to most recent complete calendar year) and are updated monthly by the Southwest Florida Water Management District.

The water balance components of Mediterranean pine trees on a steep mountain slope during two hydrologically contrasting years

NASA Astrophysics Data System (ADS)

Eliades, Marinos; Bruggeman, Adriana; Lubczynski, Maciek W.; Christou, Andreas; Camera, Corrado; Djuma, Hakan

2018-07-01

Pines in semi-arid mountain environments manage to survive and thrive despite the limited soil water, due to shallow soil depths, and overall water scarcity. This study aims to develop a method for computing soil evaporation, bedrock water uptake and transpiration from a natural, open forest, based on sap flow (Heat Ratio Method), soil moisture and meteorological observations. The water balance of individual trees was conceptualized with a geometric approach, using canopy projected areas and Voronoi (Thiesen) polygons. The canopy approach assumes that the tree's root area extent is equal to its canopy projected area, while the Voronoi approach assumes that the tree roots exploit the open area that is closer to the tree than to any other tree. The methodology was applied in an open Pinus brutia forest (68% canopy cover) in Cyprus, characterized by steep slopes and fractured bedrock, during two hydrologically contrasting years (2015 wet, 2016 dry). Sap flow sensors, soil moisture sensors, throughfall and stemflow gauges were installed on and around eight trees. Rainfall was 507 mm in 2015 and 359 mm in 2016. According to the canopy approach, the sum of tree transpiration and soil evaporation exceeded the throughfall in both years, which implies that the trees' bedrock water uptake exceeds the surface runoff and drainage losses. This indicated that trees extend their roots beyond the canopy-projected areas and the use of the Voronoi polygons captures this effect. According to the stand scale water balance, average throughfall during the two years was 81% of the rainfall. Transpiration was 61% of the rainfall in 2015, but only 32% in 2016. On the contrary, the soil evaporation fraction increased from 26% in 2015 to 35% in the dry year of 2016. The contribution of bedrock water to tree transpiration was 77% of rainfall in 2015 and 66% in 2016. During the summer months, trees relied 100% on the uptake of water from the fractured bedrock to cover their transpiration needs. Average monthly transpiration areas ranged between 0.1 mm d-1 in October 2016 and 1.7 mm d-1 in April 2015. This study shows that bedrock uptake could be an essential water balance component of semi-arid, mountainous pine forests and should be accounted for in hydrologic models.

The dynamics of rainfall interception by a seasonal temperate rainforest.

Treesearch

Timothy E. Link; Mike Unsworth; Danny Marks

2004-01-01

Net canopy interception (Inet) during rainfall in an old-growth Douglas-fir-western hemlock ecosystem was 22.8 and 25.0% of the gross rainfall (PG) for 1999 and 2000, respectively. The average direct throughfall proportion (p) and canopy storage capacity (

Variations in the chemical properties of landfill leachate

NASA Astrophysics Data System (ADS)

Chu, L. M.; Cheung, K. C.; Wong, M. H.

1994-01-01

Landfill leachates were collected and their chemical properties analyzed once every two months over a ten-month period from the Gin Drinkers' Bay (GDB) and Junk Bay (JB) landfills. The contents of solids, and inorganic and organic components fluctuated considerably with time. In general, the chemical properties of the two leachates correlated negatively ( P<0.05) with the amounts of rainfall prior to the sampling periods. However, magnesium and pH of the leachates remained relatively constant with respect to sampling time. The JB leachate contained higher average contents of solids and inorganic and organic matter than those of GDB with the exception of trace metals. Trace metals were present in the two leachates in trace quantities (<1.0 mg/liter). The concentrations of average ammoniacal nitrogen were 1040 and 549 mg/liter, while chemical oxygen demand (COD) values were 767 and 695 mg/liter for JB and GDB leachates, respectively. These results suggest that the leachates need further treatment before they can be discharged to the coastal waters.

Acid rain at Kennedy Space Center, Florida - Recent observations

NASA Technical Reports Server (NTRS)

Madsen, B. C.

1981-01-01

During the period July, 1977 to September, 1979, rainfall was collected in the vicinity of the Kennedy Space Center and subjected to appropriate chemical analysis for purposes of characterization of general composition and acidity. Results obtained form the basis for future comparisons, should significant alteration of the chemical composition of rain occur during the space shuttle era. Acidity extremes calculated on a monthly basis from event samples collected from five sites within a 200 sq km area varied from pH 5.1 in November, 1977, and April, 1978 to pH 4.3 in July, 1978 and July, 1979. Weighted average pH for the entire period was 4.55. Acidity was due to the presence of sulfuric and nitric acids. The mole ratio of excess SO4(-2):NO3(-) was typically greater than one. Monthly weighted average Cl(-) concentrations ranged from 20-240 micromoles/liter. The Cl(-):Na(+) ratio was slightly lower than that present in sea water.

Protection from wintertime rainfall reduces nutrient losses and greenhouse gas emissions during the decomposition of poultry and horse manure-based amendments.

PubMed

Maltais-Landry, Gabriel; Neufeld, Katarina; Poon, David; Grant, Nicholas; Nesic, Zoran; Smukler, Sean

2018-04-01

Manure-based soil amendments (herein "amendments") are important fertility sources, but differences among amendment types and management can significantly affect their nutrient value and environmental impacts. A 6-month in situ decomposition experiment was conducted to determine how protection from wintertime rainfall affected nutrient losses and greenhouse gas (GHG) emissions in poultry (broiler chicken and turkey) and horse amendments. Changes in total nutrient concentration were measured every 3 months, changes in ammonium (NH 4 + ) and nitrate (NO 3 - ) concentrations every month, and GHG emissions of carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) every 7-14 days. Poultry amendments maintained higher nutrient concentrations (except for K), higher emissions of CO 2 and N 2 O, and lower CH 4 emissions than horse amendments. Exposing amendments to rainfall increased total N and NH 4 + losses in poultry amendments, P losses in turkey and horse amendments, and K losses and cumulative N 2 O emissions for all amendments. However, it did not affect CO 2 or CH 4 emissions. Overall, rainfall exposure would decrease total N inputs by 37% (horse), 59% (broiler chicken), or 74% (turkey) for a given application rate (wet weight basis) after 6 months of decomposition, with similar losses for NH 4 + (69-96%), P (41-73%), and K (91-97%). This study confirms the benefits of facilities protected from rainfall to reduce nutrient losses and GHG emissions during amendment decomposition. The impact of rainfall protection on nutrient losses and GHG emissions was monitored during the decomposition of broiler chicken, turkey, and horse manure-based soil amendments. Amendments exposed to rainfall had large ammonium and potassium losses, resulting in a 37-74% decrease in N inputs when compared with amendments protected from rainfall. Nitrous oxide emissions were also higher with rainfall exposure, although it had no effect on carbon dioxide and methane emissions. Overall, this work highlights the benefits of rainfall protection during amendment decomposition to reduce nutrient losses and GHG emissions.

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.

Effect of Climate Factors on the Childhood Pneumonia in Papua New Guinea: A Time-Series Analysis

PubMed Central

Kim, Jinseob; Kim, Jong-Hun; Cheong, Hae-Kwan; Kim, Ho; Honda, Yasushi; Ha, Mina; Hashizume, Masahiro; Kolam, Joel; Inape, Kasis

2016-01-01

This study aimed to assess the association between climate factors and the incidence of childhood pneumonia in Papua New Guinea quantitatively and to evaluate the variability of the effect size according to their geographic properties. The pneumonia incidence in children under five-year and meteorological factors were obtained from six areas, including monthly rainfall and the monthly average daily maximum temperatures during the period from 1997 to 2006 from national health surveillance data. A generalized linear model was applied to measure the effect size of local and regional climate factor. The pooled risk of pneumonia in children per every 10 mm increase of rainfall was 0.24% (95% confidence interval: −0.01%–0.50%), and risk per every 1 °C increase of the monthly mean of the maximum daily temperatures was 4.88% (95% CI: 1.57–8.30). Southern oscillation index and dipole mode index showed an overall negative effect on childhood pneumonia incidence, −0.57% and −4.30%, respectively, and the risk of pneumonia was higher in the dry season than in the rainy season (pooled effect: 12.08%). There was a variability in the relationship between climate factors and pneumonia which is assumed to reflect distribution of the determinants of and vulnerability to pneumonia in the community. PMID:26891307

Evapotranspiration variability and its association with vegetation dynamics in the Nile Basin, 2002–2011

USGS Publications Warehouse

Alemu, Henok; Senay, Gabriel B.; Kaptue, Armel T.; Kovalskyy, Valeriy

2014-01-01

Evapotranspiration (ET) is a vital component in land-atmosphere interactions. In drylands, over 90% of annual rainfall evaporates. The Nile Basin in Africa is about 42% dryland in a region experiencing rapid population growth and development. The relationship of ET with climate, vegetation and land cover in the basin during 2002–2011 is analyzed using thermal-based Simplified Surface Energy Balance Operational (SSEBop) ET, Normalized Difference Vegetation Index (NDVI)-based MODIS Terrestrial (MOD16) ET, MODIS-derived NDVI as a proxy for vegetation productivity and rainfall from Tropical Rainfall Measuring Mission (TRMM). Interannual variability and trends are analyzed using established statistical methods. Analysis based on thermal-based ET revealed that >50% of the study area exhibited negative ET anomalies for 7 years (2009, driest), while >60% exhibited positive ET anomalies for 3 years (2007, wettest). NDVI-based monthly ET correlated strongly (r > 0.77) with vegetation than thermal-based ET (0.52 < r < 0.73) at p < 0.001. Climate-zone averaged thermal-based ET anomalies positively correlated (r = 0.6, p < 0.05) with rainfall in 4 of the 9 investigated climate zones. Thermal-based and NDVI-based ET estimates revealed minor discrepancies over rainfed croplands (60 mm/yr higher for thermal-based ET), but a significant divergence over wetlands (440 mm/yr higher for thermal-based ET). Only 5% of the study area exhibited statistically significant trends in ET.

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.

The Influence of ENSO to the Rainfall Variability in North Sumatra Province

NASA Astrophysics Data System (ADS)

Irwandi, H.; Pusparini, N.; Ariantono, J. Y.; Kurniawan, R.; Tari, C. A.; Sudrajat, A.

2018-04-01

The El Niño Southern Oscillation (ENSO) is a global phenomenon that affects the variability of rainfall in North Sumatra. The influence of ENSO will be different for each region. This review will analyse the influence of ENSO activity on seasonal and annual rainfall variability. In this research, North Sumatra Province will be divided into 4 (four) regions based on topographical conditions, such as: East Coast (EC), East Slope (ES), Mountains (MT), and West Coast (WC). The method used was statistical and descriptive analysis. Data used in this research were rainfall data from 15 stations / climate observation posts which spread in North Sumatera region and also anomaly data of Nino 3.4 region from period 1981-2016. The results showed that the active El Niño had an effect on the decreasing the rainfall during the period of DJF, JJA and SON in East Coast, East Slope, and Mountains with the decreasing of average percentage of annual rainfall up to 7%. On the contrary, the active La Nina had an effect on the addition of rainfall during the period DJF and JJA in the East Coast and Mountains with the increasing of average percentage of annual rainfall up to 6%.

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.

Ensemble flood simulation for a small dam catchment in Japan using 10 and 2 km resolution nonhydrostatic model rainfalls

NASA Astrophysics Data System (ADS)

Kobayashi, Kenichiro; Otsuka, Shigenori; Apip; Saito, Kazuo

2016-08-01

This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.

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.

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.

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.

Slopewash, surface runoff and fine-litter transport in forest and landslide scars in humid-tropical steeplands, Luquillo Experimental Forest, Puerto Rico

USGS Publications Warehouse

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

1999-01-01

Rainfall, slopewash (the erosion of soil particles), surface runoff and fine-litter transport at humid-tropical steepland sites in the Luquillo Experimental Forest, Puerto Rico (18??20' N, 65??45' W) were measured from 1991 to 1995. Hillslopes underlain by (1) Cretaceous tuffaceous sandstone and siltstone in subtropical rain (tabonuco) forest with vegetation recovering from Hurricane Hugo (1989), and (2) Tertiary quartz diorite in subtropical lower montane wet (colorado and dwarf) forest with undisturbed forest canopy were compared to recent landslide scars. Monthly surface runoff on these very steep hillslopes (24??to 43??) was only 0.2 to 0.5 per cent of monthly rainfall. Slopewash was higher in sandy loam soils whose parent material is quartz diorite (averaging 46 g m-2 a-1) than in silty clay loam soils derived from tuffaceous sandstone and siltstone where the average was 9 g m-2 a-1. Annual slopewash of 100 to 349 g m-2 on the surfaces of two recent, small landslide scars was measured initially but slopewash decreased to only 3 to 4 g m-2 a-1 by the end of the study. The mean annual mass of fine litter (mainly leaves and twigs) transported downslope at the forested sites ranged from 5 to 8 g m-2 and was lower at the tabonuco forest site, where post-Hurricane Hugo recovery is still in progress. Mean annual fine-litter transport was 2.5 g m-2 on the two landslide scars.

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.

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.

A Stochastic Model of Space-Time Variability of Tropical Rainfall: I. Statistics of Spatial Averages

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, Thomas L.; Lau, William K. M. (Technical Monitor)

2002-01-01

Global maps of rainfall are of great importance in connection with modeling of the earth s climate. Comparison between the maps of rainfall predicted by computer-generated climate models with observation provides a sensitive test for these models. To make such a comparison, one typically needs the total precipitation amount over a large area, which could be hundreds of kilometers in size over extended periods of time of order days or months. This presents a difficult problem since rain varies greatly from place to place as well as in time. Remote sensing methods using ground radar or satellites detect rain over a large area by essentially taking a series of snapshots at infrequent intervals and indirectly deriving the average rain intensity within a collection of pixels , usually several kilometers in size. They measure area average of rain at a particular instant. Rain gauges, on the other hand, record rain accumulation continuously in time but only over a very small area tens of centimeters across, say, the size of a dinner plate. They measure only a time average at a single location. In making use of either method one needs to fill in the gaps in the observation - either the gaps in the area covered or the gaps in time of observation. This involves using statistical models to obtain information about the rain that is missed from what is actually detected. This paper investigates such a statistical model and validates it with rain data collected over the tropical Western Pacific from ship borne radars during TOGA COARE (Tropical Oceans Global Atmosphere Coupled Ocean-Atmosphere Response Experiment). The model incorporates a number of commonly observed features of rain. While rain varies rapidly with location and time, the variability diminishes when averaged over larger areas or longer periods of time. Moreover, rain is patchy in nature - at any instant on the average only a certain fraction of the observed pixels contain rain. The fraction of area covered by rain decreases, as the size of a pixel becomes smaller. This means that within what looks like a patch of rainy area in a coarse resolution view with larger pixel size, one finds clusters of rainy and dry patches when viewed on a finer scale. The model makes definite predictions about how these and other related statistics depend on the pixel size. These predictions were found to agree well with data. In a subsequent second part of the work we plan to test the model with rain gauge data collected during the TRMM (Tropical Rainfall Measuring Mission) ground validation campaign.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Vertical Motion Changes Related to North-East Brazil Rainfall Variability: a GCM Simulation

NASA Astrophysics Data System (ADS)

Roucou, Pascal; Oribe Rocha de Aragão, José; Harzallah, Ali; Fontaine, Bernard; Janicot, Serge

1996-08-01

The atmospheric structure over north-east Brazil during anomalous rainfall years is studied in the 11 levels of the outputs of the Laboratoire de Météorologie Dynamique atmospheric general circulation model (LMD AGCM). Seven 19-year simulations were performed using observed sea-surface temperature (SST) corresponding to the period 1970- 1988. The ensemble mean is calculated for each month of the period, leading to an ensemble-averaged simulation. The simulated March-April rainfall is in good agreement with observations. Correlations of simulated rainfall and three SST indices relative to the equatorial Pacific and northern and southern parts of the Atlantic Ocean exhibit stronger relationships in the simulation than in the observations. This is particularly true with the SST gradient in the Atlantic (Atlantic dipole). Analyses on 200 ;hPa velocity potential, vertical velocity, and vertical integral of the zonal component of mass flux are performed for years of abnormal rainfall and positive/negative SST anomalies in the Pacific and Atlantic oceans in March-April during the rainy season over the Nordeste region. The results at 200 hPa show a convergence anomaly over Nordeste and a divergence anomaly over the Pacific concomitant with dry seasons associated with warm SST anomalies in the Pacific and warm (cold) waters in the North (South) Atlantic. During drought years convection inside the ITCZ indicated by the vertical velocity exhibits a displacement of the convection zone corresponding to a northward migration of the ITCZ. The east-west circulation depicted by the zonal divergent mass flux shows subsiding motion over Nordeste and ascending motion over the Pacific in drought years, accompanied by warm waters in the eastern Pacific and warm/cold waters in northern/southern Atlantic. Rainfall variability of the Nordeste rainfall is linked mainly to vertical motion and SST variability through the migration of the ITCZ and the east-west circulation.

Landslide triggering by rain infiltration

USGS Publications Warehouse

Iverson, Richard M.

2000-01-01

Landsliding in response to rainfall involves physical processes that operate on disparate timescales. Relationships between these timescales guide development of a mathematical model that uses reduced forms of Richards equation to evaluate effects of rainfall infiltration on landslide occurrence, timing, depth, and acceleration in diverse situations. The longest pertinent timescale is A/D0, where D0 is the maximum hydraulic diffusivity of the soil and A is the catchment area that potentially affects groundwater pressures at a prospective landslide slip surface location with areal coordinates x, y and depth H. Times greater than A/D0 are necessary for establishment of steady background water pressures that develop at (x, y, H) in response to rainfall averaged over periods that commonly range from days to many decades. These steady groundwater pressures influence the propensity for landsliding at (x, y, H), but they do not trigger slope failure. Failure results from rainfall over a typically shorter timescale H2/D0 associated with transient pore pressure transmission during and following storms. Commonly, this timescale ranges from minutes to months. The shortest timescale affecting landslide responses to rainfall is √(H/g), where g is the magnitude of gravitational acceleration. Postfailure landslide motion occurs on this timescale, which indicates that the thinnest landslides accelerate most quickly if all other factors are constant. Effects of hydrologic processes on landslide processes across these diverse timescales are encapsulated by a response function, R(t*) = √(t*/π) exp (-1/t*) - erfc (1/√t*), which depends only on normalized time, t*. Use of R(t*) in conjunction with topographic data, rainfall intensity and duration information, an infinite-slope failure criterion, and Newton's second law predicts the timing, depth, and acceleration of rainfall-triggered landslides. Data from contrasting landslides that exhibit rapid, shallow motion and slow, deep-seated motion corroborate these predictions.

Understanding the Impacts of Climate and Hydrologic Extremes on Diarrheal Diseases in Southwestern Amazon

NASA Astrophysics Data System (ADS)

Fonseca, P. A. M.

2015-12-01

Bacterial diarrheal diseases have a high incidence rate during and after flooding episodes. In the Brazilian Amazon, flood extreme events have become more frequent, leading to high incidence rates for infant diarrhea. In this study we aimed to find a statistical association between rainfall, river levels and diarrheal diseases in children under 5, in the river Acre basin, in the State of Acre (Brazil). We also aimed to identify the time-lag and annual season of extreme rainfall and flooding in different cities in the water basin. The results using Tropical Rainfall Measuring Mission (TRMM) Satellite rainfall data show robustness of these estimates against observational stations on-ground. The Pearson coefficient correlation results (highest 0.35) indicate a time-lag, up to 4 days in three of the cities in the water-basin. In addition, a correlation was also tested between monthly accumulated rainfall and the diarrheal incidence during the rainy season (DJF). Correlation results were higher, especially in Acrelândia (0.7) and Brasiléia and Epitaciolândia (0.5). The correlation between water level monthly averages and diarrheal diseases incidence was 0.3 and 0.5 in Brasiléia and Epitaciolândia. The time-lag evidence found in this paper is critical to inform stakeholders, local populations and civil defense authorities about the time available for preventive and adaptation measures between extreme rainfall and flooding events in vulnerable cities. This study was part of a pilot application in the state of Acre of the PULSE-Brazil project (http://www.pulse-brasil.org/tool/), an interface of climate, environmental and health data to support climate adaptation. The next step of this research is to expand the analysis to other climate variables on diarrheal diseases across the whole Brazilian Amazon Basin and estimate the relative risk (RR) of a child getting sick. A statistical model will estimate RR based on the observed values and seasonal forecasts (higher accuracy for the Amazon region) will be used so the government can be prepared for extreme climate events forecasted. It is expected that these results can be helpful during and post extreme events to improve health surveillance preparedness and better allocate available results in adapting vulnerable cities to climate extreme events.

Variations in evapotranspiration and climate for an Amazonian semi-deciduous forest over seasonal, annual, and El Niño cycles.

PubMed

Vourlitis, George L; de Souza Nogueira, José; de Almeida Lobo, Francisco; Pinto, Osvaldo Borges

2015-02-01

Tropical forests exchange large amounts of water and energy with the atmosphere and are important in controlling regional and global climate; however, climate and evaportranspiration (E) vary significantly across multiple time scales. To better understand temporal patterns in E and climate, we measured the energy balance and meteorology of a semi-deciduous forest in the rainforest-savanna ecotone of northern Mato Grosso, Brazil, over a 7-year period and analyzed regional climate patterns over a 16-year period. Spectral analysis revealed that E and local climate exhibited consistent cycles over annual, seasonal, and weekly time scales. Annual and seasonal cycles were also apparent in the regional monthly rainfall and humidity time series, and a cycle on the order of 3-5.5 years was also apparent in the regional air temperature time series, which is coincident with the average return interval of El Niño. Annual rates of E were significantly affected by the 2002 El Niño. Prior to this event, annual E was on average 1,011 mm/year and accounted for 52% of the annual rainfall, while after, annual E was 931 mm/year and accounted for 42% of the annual rainfall. Our data also suggest that E declined significantly over the 7-year study period while air temperature significantly increased, which was coincident with a long-term, regional warming and drying trend. These results suggest that drought and warming induced by El Niño and/or climate change cause declines in E for semi-deciduous forests of the southeast Amazon Basin.

Variations in evapotranspiration and climate for an Amazonian semi-deciduous forest over seasonal, annual, and El Niño cycles

NASA Astrophysics Data System (ADS)

Vourlitis, George L.; de Souza Nogueira, José; de Almeida Lobo, Francisco; Pinto, Osvaldo Borges

2015-02-01

Tropical forests exchange large amounts of water and energy with the atmosphere and are important in controlling regional and global climate; however, climate and evaportranspiration ( E) vary significantly across multiple time scales. To better understand temporal patterns in E and climate, we measured the energy balance and meteorology of a semi-deciduous forest in the rainforest-savanna ecotone of northern Mato Grosso, Brazil, over a 7-year period and analyzed regional climate patterns over a 16-year period. Spectral analysis revealed that E and local climate exhibited consistent cycles over annual, seasonal, and weekly time scales. Annual and seasonal cycles were also apparent in the regional monthly rainfall and humidity time series, and a cycle on the order of 3-5.5 years was also apparent in the regional air temperature time series, which is coincident with the average return interval of El Niño. Annual rates of E were significantly affected by the 2002 El Niño. Prior to this event, annual E was on average 1,011 mm/year and accounted for 52 % of the annual rainfall, while after, annual E was 931 mm/year and accounted for 42 % of the annual rainfall. Our data also suggest that E declined significantly over the 7-year study period while air temperature significantly increased, which was coincident with a long-term, regional warming and drying trend. These results suggest that drought and warming induced by El Niño and/or climate change cause declines in E for semi-deciduous forests of the southeast Amazon Basin.

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;

A long-term monitoring study of chlorophyll, microbial contaminants, and pesticides in a coastal residential stormwater pond and its adjacent tidal creek.

PubMed

DeLorenzo, Marie E; Thompson, Brian; Cooper, Emily; Moore, Janet; Fulton, Michael H

2012-01-01

Stormwater ponds are commonly used in residential and commercial areas to control flooding. The accumulation of urban contaminants in stormwater ponds can lead to water-quality problems including nutrient enrichment, chemical contamination, and bacterial contamination. This study presents 5 years of monitoring data assessing water quality of a residential subdivision pond and adjacent tidal creek in coastal South Carolina, USA. The stormwater pond is eutrophic, as described by elevated concentrations of chlorophyll and phosphorus, and experiences periodic cyanobacterial blooms. A maximum monthly average chlorophyll concentration of 318.75 μg/L was measured in the stormwater pond and 227.63 μg/L in the tidal creek. Fecal coliform bacteria (FCB) levels were measured in both the pond and the tidal creek that exceeded health and safety standards for safe recreational use. A maximum monthly average FCB level of 1,247 CFU/100 mL was measured in the stormwater pond and 12,850 CFU/100 mL in the tidal creek. In addition, the presence of antibiotic resistant bacteria and pathogenic bacteria were detected. Low concentrations of herbicides (atrazine and 2,4-D: ), a fungicide (chlorothalonil), and insecticides (pyrethroids and imidacloprid) were measured. Seasonal trends were identified, with the winter months having the lowest concentrations of chlorophyll and FCB. Statistical differences between the stormwater pond and the tidal creek were also noted within seasons. The tidal creek had higher FCB levels than the stormwater pond in the spring and summer, whereas the stormwater pond had higher chlorophyll levels than the tidal creek in the summer and fall seasons. Chlorophyll and FCB levels in the stormwater pond were significantly correlated with monthly average temperature and total rainfall. Pesticide concentrations were also significantly correlated with temperature and rainfall. Pesticide concentrations in the stormwater pond were significantly correlated with pesticide concentrations in the adjacent tidal creek. Chlorophyll and FCB levels in the tidal creek, however, were not significantly correlated with levels in the pond. While stormwater ponds are beneficial in controlling flooding, they may pose environmental and human health risks due to biological and chemical contamination. Management to reduce residential runoff may improve water quality in coastal stormwater ponds and their adjacent estuarine ecosystems.

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.

Use of TRMM Rainfall Information in Improving Long-Term, Satellite-Based Global Precipitation Analyses

NASA Technical Reports Server (NTRS)

Starr, David OC. (Technical Monitor); Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric

2002-01-01

The TRMM rainfall products are inter-compared among themselves and to the 23 year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/ GEWEX) Global Precipitation Climatology Project (GPCP). Ways in which the TRMM-based estimates can be used to improve the long-term data set are described. These include improvement of the passive microwave algorithm that is applied to the 15 year SSM/I record and calibration or adjustment of the current GPCP fields utilizing the 4-5 year overlap of TRMM and GPCP. A comparison of the GPCP monthly surface precipitation fields and the TRMM-based multi-satellite analyses indicates that the two are similar, but have significant differences that relate to the different input data sets. Although on a zonal average basis over the ocean the two analyses are similar in the deep Tropics, there are subtle differences between the eastern and western Pacific Ocean in the relative magnitudes. In mid-latitudes the GPCP has somewhat larger mean precipitation than TRMM. Statistical comparisons of TRMM and GPCP monthly fields are carried out in terms of histogram matching for both ocean and land regions and for small areas to diagnose differences. These comparisons form the basis for a TRMM calibration of the GPCP fields using matched histograms over regional areas as a function of season. Although final application of this procedure will likely await the Version 6 of the TRMM products, tests using Version 5 are shown that provide a TRMM-calibrated GPCP version that will produce an improved climatology and a more accurate month-to-month precipitation analysis for the last 20 years.

[Three-dimension temporal and spatial dynamics of soil water for the artificial vegetation in the center of Taklimakan desert under saline water drip-irrigation].

PubMed

Ding, Xin-yuan; Zhou, Zhi-bin; Xu, Xin-wen; Lei, Jia-qiang; Lu, Jing-jing; Ma, Xue-xi; Feng, Xiao

2015-09-01

Three-dimension temporal and spatial dynamics of the soil water characteristics during four irrigating cycles of months from April to July for the artificial vegetation in the center of Taklimakan Desert under saline water drip-irrigation had been analyzed by timely measuring the soil water content in horizontal and vertical distances 60 cm and 120 cm away from the irrigating drips, respectively. Periodic spatial and temporal variations of soil water content were observed. When the precipitation effect was not considered, there were no significant differences in the characteristics of soil water among the irrigation intervals in different months, while discrepancies were obvious in the temporal and spatial changes of soil moisture content under the conditions of rainfall and non-rainfall. When it referred to the temporal changes of soil water, it was a little higher in April but a bit lower in July, and the soil water content in June was the highest among four months because some remarkable events of precipitation happened in this month. However, as a whole, the content of soil moisture was reduced as months (from April to July) went on and it took a decreasing tendency along with days (1-15 d) following a power function. Meanwhile, the characteristics of soil water content displayed three changeable stages in an irrigation interval. When it referred to the spatial distributions of soil water, the average content of soil moisture was reduced along with the horizontal distance following a linear regression function, and varied with double peaks along with the vertical distance. In addition, the spatial distribution characteristics of the soil water were not influenced by the factors of precipitation and irrigating time but the physical properties of soil.

Compilation of water resources development and hydrologic data of Saipan, Mariana Islands

USGS Publications Warehouse

Van der Brug, Otto

1985-01-01

Saipan is the largest island of the Northern Mariana Islands, a chain of 14 islands north of Guam. Saipan comprises one third of the land area of the islands. No long-term rainfall record is available at any location, but some rainfall records are for periods up to 16 years, some of which began in 1901. Average annual rainfall for the island is 81 inches, with the southern end receiving about 10 inches less annually than the rest of the island. The amount of rainfall which runs off in northeast Saipan ranges from 23 to 64 percent and averages about 40 percent. Runoff on the rest of the island is from springs or occurs only during heavy rainfall. Surface-water development appears impractical. Ground water is the main source of water for the island and production was almost 4 million gallons per day in 1982. However, chloride concentration in ground water exceeds 1,000 milligrams per liter in many locations. The average chloride concentration of the domestic water stays near the maximum permissible level (600 milligrams per liter). This report summarizes the history of the water-resources development and presents all available hydrologic data, including rainfall records since 1901, streamflow records since 1968, and drilling logs, pumping tests, chemical analyses, and production figures from 180 testholes and wells drilled on Saipan. (USGS)

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

2018-01-01

Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDF) that are traditionally derived from rain-gauges and more recently also from remote sensing instruments, such as weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation on a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a unique radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area (northern Israel). Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting Generalized Extreme Value (GEV) distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel (on average, ∼70%). The subpixel variability of rainfall extreme was found to increase with longer return periods and shorter durations (e.g. from a maximum variability of 10% for a return period of 2 years and a duration of 4 h to 30% for 50 years return period and 20 min duration). For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for different applications that require very local estimates of rainfall extremes.

Cutaneous Leishmaniasis and Sand Fly Fluctuations Are Associated with El Niño in Panamá

PubMed Central

Chaves, Luis Fernando; Calzada, José E.; Valderrama, Anayansí; Saldaña, Azael

2014-01-01

Background Cutaneous Leishmaniasis (CL) is a neglected tropical vector-borne disease. Sand fly vectors (SF) and Leishmania spp parasites are sensitive to changes in weather conditions, rendering disease transmission susceptible to changes in local and global scale climatic patterns. Nevertheless, it is unclear how SF abundance is impacted by El Niño Southern Oscillation (ENSO) and how these changes might relate to changes in CL transmission. Methodology and Findings We studied association patterns between monthly time series, from January 2000 to December 2010, of: CL cases, rainfall and temperature from Panamá, and an ENSO index. We employed autoregressive models and cross wavelet coherence, to quantify the seasonal and interannual impact of local climate and ENSO on CL dynamics. We employed Poisson Rate Generalized Linear Mixed Models to study SF abundance patterns across ENSO phases, seasons and eco-epidemiological settings, employing records from 640 night-trap sampling collections spanning 2000–2011. We found that ENSO, rainfall and temperature were associated with CL cycles at interannual scales, while seasonal patterns were mainly associated with rainfall and temperature. Sand fly (SF) vector abundance, on average, decreased during the hot and cold ENSO phases, when compared with the normal ENSO phase, yet variability in vector abundance was largest during the cold ENSO phase. Our results showed a three month lagged association between SF vector abundance and CL cases. Conclusion Association patterns of CL with ENSO and local climatic factors in Panamá indicate that interannual CL cycles might be driven by ENSO, while the CL seasonality was mainly associated with temperature and rainfall variability. CL cases and SF abundance were associated in a fashion suggesting that sudden extraordinary changes in vector abundance might increase the potential for CL epidemic outbreaks, given that CL epidemics occur during the cold ENSO phase, a time when SF abundance shows its highest fluctuations. PMID:25275503

Forecasting malaria incidence based on monthly case reports and environmental factors in Karuzi, Burundi, 1997–2003

PubMed Central

Gomez-Elipe, Alberto; Otero, Angel; van Herp, Michel; Aguirre-Jaime, Armando

2007-01-01

Background The objective of this work was to develop a model to predict malaria incidence in an area of unstable transmission by studying the association between environmental variables and disease dynamics. Methods The study was carried out in Karuzi, a province in the Burundi highlands, using time series of monthly notifications of malaria cases from local health facilities, data from rain and temperature records, and the normalized difference vegetation index (NDVI). Using autoregressive integrated moving average (ARIMA) methodology, a model showing the relation between monthly notifications of malaria cases and the environmental variables was developed. Results The best forecasting model (R2adj = 82%, p < 0.0001 and 93% forecasting accuracy in the range ± 4 cases per 100 inhabitants) included the NDVI, mean maximum temperature, rainfall and number of malaria cases in the preceding month. Conclusion This model is a simple and useful tool for producing reasonably reliable forecasts of the malaria incidence rate in the study area. PMID:17892540

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

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

The 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.

Major winter and nonwinter floods in selected basins in New York and Pennsylvania

USGS Publications Warehouse

Langbein, Walter Basil

1947-01-01

The scientific design of flood-control works is based on an evaluation of the hydrologic factors basic to flood events, particularly how rainfall and snow runoff, soil conditions, and channel influences can combine to produce greater or lesser floods. For this purpose an analysis of the pertinent hydrologic data is needed. The methods of analysis adopted should conform as closely as possible to those already in use and must be adapted to the quality of the available information. Maximum floods in 8 basins in New York and Pennsylvania during the winter and nonwinter months were studied, a total of 21 floods. The most outstanding winter flood of record in the North Atlantic region was that of March 1936. Rainfall plus snow melt in the basins studied ranged between 3.04 and 6.87 inches, and associated volumes of direct runoff from 1.88 to 5.63 inches. Winter floods have a common characteristic in their relation to freezing temperature. The antecedent periods, representing a period of snow accumulation and frost penetration, are below freezing, and the flood itself is contemporaneous with a period of above-freezing temperatures, usually associated with rain, during which the previously accumulated snow is melted. A second common characteristic of major winter floods is their tendency to be associated with widespread causal meteorologic conditions. There was a more complete conversion of rainfall and snow melt into runoff during the winter storms studied than during the wettest nonwinter flood. Snow melt during winter floods ranged from 0.04 to 0.07 inch per degree-day above 32° F. The depth of mean areal rainfall produced by the nonwinter storms studied ranged from 3.05 to 4.96 inches. The maximum 24-hour quantity at single stations was 14 inches, which was measured during the storm of July 1935 in New York. The volume of direct runoff ranged between 1.39 and 3.41 inches. The portion of rainfall that was converted into runoff varied in accordance with the rate of antecedent base flow, expressed in second-feet per square mile, and emphasized the influence of antecedent conditions. The average volume of direct runoff during winter floods was 4.24 inches, and the average during nonwinter floods was 2.44 inches. The latter, however, were more concentrated as to time, tending to compensate for large volume of runoff in winter, so that the crest rates of direct runoff averaged 0.056 inches per hour during the winter and 0.051 inches during the nonwinter period.

Karst Aquifer in Qatar and its bearing on Natural Rainfall Recharge

NASA Astrophysics Data System (ADS)

Baalousha, Husam; Ackerer, Philippe

2017-04-01

Qatar is an arid country with little rainfall and high evaporation. Surface water is non-existent so aquifer is the only source of natural water. The annual long-term averages of rainfall and evaporation are 80 mm and more than 2000 mm, respectively. Despite the low rainfall and high evaporation, natural recharge from rainfall occurs at an average of approximately 50 million m3 per year. Rainfall recharge in Qatar takes in land depressions that occur all over the country. These depressions are a result of land collapse due to sinkholes and cavity in the limestone formation. In the northern part of the country, karst features occur as a result of dissolution of limestone, which leads to land depressions. Results of this study shows groundwater recharge occurs in land depression areas, especially in the northern part of the country, where surface runoff accumulates in these land depressions and recharges the aquifer. This paper was made possible by NPRP grant # [NPRP 9-030-1-008] from the Qatar National Research Fund (a member of Qatar Foundation). The findings achieved herein are solely the responsibility of the author[s]."

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.

Lightning activity with rainfall during El Nino and La Nina events over India

NASA Astrophysics Data System (ADS)

Tinmaker, M. I. R.; Aslam, M. Y.; Ghude, Sachin D.; Chate, D. M.

2017-10-01

This paper appraises the association of lightning flash count (FC) with rainfall using the satellite-borne Lightning Imaging Sensor's (LIS) data along with gridded rainfall data (0.5o × 0.5o) for Indian summer monsoon seasons over 10 years (2001-2010). During strong El Nino years, 2002 and 2009, FCs were greater in magnitude by about 26.5 % and 37 %, than the long-term average, respectively, while during weak El Nino year (2004), it was more by 8 %. During the same years, the rainfall was deficient by about 10 % than the long-term average. Similarly, a rise in aerosol optical depth (AOD) over its average value (by about 15 % and 20 %) reduces the ratio of rainfall to FC (RLR) by 41 % and 44 % for strong El Nino years 2002 and 2009, respectively, and for weak El Nino year (2004), a 6.5 % rise in AOD lowers the RLR by 20 %. Bowen ratio more by 11 % and 17 % of its average value reduces the RLR by 41 % and 44 % for strong El Nino years 2002 and 2009, respectively, and, also, Bowen ratio higher by 8 % for 2004 declines RLR by 20 %. On the other hand, Bowen ratio less by 9 % and 6 % raises the RLR by 19 % and 56 % for moderate La Nina year (2007) and strong La Nina year (2010), respectively. Results for the daily rainfall, AOD and Bowen ratio over Indian regions, are discussed for strong El Nino and La Nina years. Correlations of FC with AOD and Bowen ratio of 0.66 and 0.71, respectively, while, that of FC with ONI of 0.56 indicates numerous (fewer) break days during El Nino (La Nina) years.

Satellite observations of rainfall effect on sea surface salinity in the waters adjacent to Taiwan

NASA Astrophysics Data System (ADS)

Ho, Chung-Ru; Hsu, Po-Chun; Lin, Chen-Chih; Huang, Shih-Jen

2017-10-01

Changes of oceanic salinity are highly related to the variations of evaporation and precipitation. To understand the influence of rainfall on the sea surface salinity (SSS) in the waters adjacent to Taiwan, satellite remote sensing data from the year of 2012 to 2014 are employed in this study. The daily rain rate data obtained from Special Sensor Microwave Imager (SSM/I), Tropical Rainfall Measuring Mission's Microwave Imager (TRMM/TMI), Advanced Microwave Scanning Radiometer (AMSR), and WindSat Polarimetric Radiometer. The SSS data was derived from the measurements of radiometer instruments onboard the Aquarius satellite. The results show the average values of SSS in east of Taiwan, east of Luzon and South China Sea are 33.83 psu, 34.05 psu, and 32.84 psu, respectively, in the condition of daily rain rate higher than 1 mm/hr. In contrast to the rainfall condition, the average values of SSS are 34.07 psu, 34.26 psu, and 33.09 psu in the three areas, respectively at no rain condition (rain rate less than 1 mm/hr). During the cases of heavy rainfall caused by spiral rain bands of typhoon, the SSS is diluted with an average value of -0.78 psu when the average rain rate is higher than 4 mm/hr. However, the SSS was increased after temporarily decreased during the typhoon cases. A possible reason to explain this phenomenon is that the heavy rainfall caused by the spiral rain bands of typhoon may dilute the sea surface water, but the strong winds can uplift the higher salinity of subsurface water to the sea surface.

Validation and correction of rainfall data from the WegenerNet high density network in southeast Austria

NASA Astrophysics Data System (ADS)

O, Sungmin; Foelsche, U.; Kirchengast, G.; Fuchsberger, J.

2018-01-01

Eight years of daily rainfall data from WegenerNet were analyzed by comparison with data from Austrian national weather stations. WegenerNet includes 153 ground level weather stations in an area of about 15 km × 20 km in the Feldbach region in southeast Austria. Rainfall has been measured by tipping bucket gauges at 150 stations of the network since the beginning of 2007. Since rain gauge measurements are considered close to true rainfall, there are increasing needs for WegenerNet data for the validation of rainfall data products such as remote sensing based estimates or model outputs. Serving these needs, this paper aims at providing a clearer interpretation on WegenerNet rainfall data for users in hydro-meteorological communities. Five clusters - a cluster consists of one national weather station and its four closest WegenerNet stations - allowed us close comparison of datasets between the stations. Linear regression analysis and error estimation with statistical indices were conducted to quantitatively evaluate the WegenerNet daily rainfall data. It was found that rainfall data between the stations show good linear relationships with an average correlation coefficient (r) of 0.97 , while WegenerNet sensors tend to underestimate rainfall according to the regression slope (0.87). For the five clusters investigated, the bias and relative bias were - 0.97 mm d-1 and - 11.5 % on average (except data from new sensors). The average of bias and relative bias, however, could be reduced by about 80 % through a simple linear regression-slope correction, with the assumption that the underestimation in WegenerNet data was caused by systematic errors. The results from the study have been employed to improve WegenerNet data for user applications so that a new version of the data (v5) is now available at the WegenerNet data portal (www.wegenernet.org).

SOIL GAS RADON MEASUREMENT AROUND FAULT LINES ON THE WESTERN SECTION OF THE NORTH ANATOLIAN FAULT ZONE IN TURKEY.

PubMed

Yakut, Hakan; Tabar, Emre; Yildirim, Eray; Zenginerler, Zemine; Ertugral, Filiz; Demirci, Nilufer

2017-04-15

Soil gas radon activity measurements were made around the western section of the North Anatolian Fault Zone. In the study, the variation of radon concentration at 12 different locations along the fault line was monitored by using LR-115 (solid-state nuclear track detectors) detectors for 12-monthly periods. Twelve radon stations were determined in the study region, and in each station, LR-115 films were installed in the borehole of ∼50 cm. The recorded radon concentration varies from 29 to 7059 Bqm-3 with an average value of 1930 Bqm-3. The influence of meteorological parameters such as temperature, pressure, total rainfall and humidity on soil radon concentrations in the study area was also investigated. The positive and poor correlation was observed between average value of 222Rn concentration and temperature. There is a reverse proportion between radon level with other meteorological factors (humidity, pressure and rainfall). The results show that the measured soil gas radon activity concentration shows seasonal variation in a highly permeable sandy-gravelly soil with definite seasons without obvious long transitional periods. The summer (from June 2013 to September 2013) is characterised by 1.8 times higher average soil gas radon activity concentration (median is 2.372 kBqm-3) than the winter (from December 2012 to March 2013) (median is 1.298 kBqm-3). © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Monitoring Rainfall by Combining Ground-based Observed Precipitation and PERSIANN Satellite Product (Case Study Area: Lake Urmia Basin)

NASA Astrophysics Data System (ADS)

Abrishamchi, A.; Mirshahi, A.

2015-12-01

The global coverage, quick access, and appropriate spatial-temporal resolution of satellite precipitation data renders the data appropriate for hydrologic studies, especially in regions with no sufficient rain-gauge network. On the other hand, satellite precipitation products may have major errors. The present study aims at reduction of estimation error of the PERSIANN satellite precipitation product. Bayesian logic employed to develop a statistical relationship between historical ground-based and satellite precipitation data. This relationship can then be used to reduce satellite precipitation product error in near real time, when there is no ground-based precipitation observation. The method was evaluated in the Lake Urmia basin with a monthly time scale; November to May of 2000- 2008 for the purpose of model development and two years of 2009 and 2010 for the validation of the established relationships. Moreover, Kriging interpolation method was employed to estimate the average rainfall in the basin. Furthermore, to downscale the satellite precipitation product from 0.25o to 0.05o, data-location downscaling algorithm was used. In 76 percent of months, the final product, compared with the satellite precipitation, had less error during the validation period. Additionally, its performance was marginally better than adjusted PERSIANN product.

Association between heavy precipitation events and waterborne outbreaks in four Nordic countries, 1992-2012.

PubMed

Guzman Herrador, Bernardo; de Blasio, Birgitte Freiesleben; Carlander, Anneli; Ethelberg, Steen; Hygen, Hans Olav; Kuusi, Markku; Lund, Vidar; Löfdahl, Margareta; MacDonald, Emily; Martinez-Urtaza, Jaime; Nichols, Gordon; Schönning, Caroline; Sudre, Bertrand; Trönnberg, Linda; Vold, Line; Semenza, Jan C; Nygård, Karin

2016-12-01

We conducted a matched case-control study to examine the association between heavy precipitation events and waterborne outbreaks (WBOs) by linking epidemiological registries and meteorological data between 1992 and 2012 in four Nordic countries. Heavy precipitation events were defined by above average (exceedance) daily rainfall during the preceding weeks using local references. We performed conditional logistic regression using the four previous years as the controls. Among WBOs with known onset date (n = 89), exceedance rainfall on two or more days was associated with occurrence of outbreak, OR = 3.06 (95% CI 1.38-6.78), compared to zero exceedance days. Stratified analyses revealed a significant association with single household water supplies, ground water as source and for outbreaks occurring during spring and summer. These findings were reproduced in analyses including all WBOs with known outbreak month (n = 186). The vulnerability of single households to WBOs associated with heavy precipitation events should be communicated to homeowners and implemented into future policy planning to reduce the risk of waterborne illness.

Water uptake by two river red gum ( Eucalyptus camaldulensis) clones in a discharge site plantation in the Western Australian wheatbelt

NASA Astrophysics Data System (ADS)

Marshall, John K.; Morgan, Anne L.; Akilan, Kandia; Farrell, Richard C. C.; Bell, David T.

1997-12-01

The heat-pulse technique was used to estimate year-long water uptake in a discharge zone plantation of 9-year-old clonal Eucalyptus camaldulensis Dehnh. near Wubin, Western Australia. Water uptake matched rainfall closely during weter months but exceeded rainfall as the dry season progressed. Average annual water uptake (1148 mm) exceeded rainfall (432 mm) by about 2.7 fold and approached 56% of pan evaporation for the area. The data suggest that at least 37% (i.e. ( {1}/{2.7}) × 100 ) of the lower catchment discharge zone should be planted to prevent the rise of groundwater. Water uptake varied with soil environment, season and genotype. Upslope trees used more water than did downslope trees. Water uptake was higher in E. camaldulensis clone M80 than in clone M66 until late spring. The difference reversed as summer progressed. Both clones, however, have the potential to dry out the landscape when potential evapotranspiration exceeds rainfall. This variation in water uptake within the species indicates the potential for manipulating plantation uptake by matching tree characteristics to site characteristics. Controlled experiments on the heat-pulse technique indicated accuracy errors of approximately 10%. This, combined with the ability to obtain long-term, continuous data and the superior logistics of use of the heat-pulse technique, suggests that results obtained by it would be much more reliable than those achieved by the ventilated chamber technique.

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.

[The warning model and influence of climatic changes on hemorrhagic fever with renal syndrome in Changsha city].

PubMed

Xiao, Hong; Tian, Huai-yu; Zhang, Xi-xing; Zhao, Jian; Zhu, Pei-juan; Liu, Ru-chun; Chen, Tian-mu; Dai, Xiang-yu; Lin, Xiao-ling

2011-10-01

To realize the influence of climatic changes on the transmission of hemorrhagic fever with renal syndrome (HFRS), and to explore the adoption of climatic factors in warning HFRS. A total of 2171 cases of HFRS and the synchronous climatic data in Changsha from 2000 to 2009 were collected to a climate-based forecasting model for HFRS transmission. The Cochran-Armitage trend test was employed to explore the variation trend of the annual incidence of HFRS. Cross-correlations analysis was then adopted to assess the time-lag period between the climatic factors, including monthly average temperature, relative humidity, rainfall and Multivariate Elño-Southern Oscillation Index (MEI) and the monthly HFRS cases. Finally the time-series Poisson regression model was constructed to analyze the influence of different climatic factors on the HFRS transmission. The annual incidence of HFRS in Changsha between 2000 - 2009 was 13.09/100 000 (755 cases), 9.92/100 000 (578 cases), 5.02/100 000 (294 cases), 2.55/100 000 (150 cases), 1.13/100 000 (67 cases), 1.16/100 000 (70 cases), 0.95/100 000 (58 cases), 1.40/100 000 (87 cases), 0.75/100 000 (47 cases) and 1.02/100 000 (65 cases), respectively. The incidence showed a decline during these years (Z = -5.78, P < 0.01). The results of Poisson regression model indicated that the monthly average temperature (18.00°C, r = 0.26, P < 0.01, 1-month lag period; IRR = 1.02, 95%CI: 1.00 - 1.03, P < 0.01), relative humidity (75.50%, r = 0.62, P < 0.01, 3-month lag period; IRR = 1.03, 95%CI: 1.02 - 1.04, P < 0.01), rainfall (112.40 mm, r = 0.25, P < 0.01, 6-month lag period; IRR = 1.01, 95CI: 1.01 - 1.02, P = 0.02), and MEI (r = 0.31, P < 0.01, 3-month lag period; IRR = 0.77, 95CI: 0.67 - 0.88, P < 0.01) were closely associated with monthly HFRS cases (18.10 cases). Climate factors significantly influence the incidence of HFRS. If the influence of variable-autocorrelation, seasonality, and long-term trend were controlled, the accuracy of forecasting by the time-series Poisson regression model in Changsha would be comparatively high, and we could forecast the incidence of HFRS in advance.

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...

Climate change increases the probability of heavy rains in Northern England/Southern Scotland like those of storm Desmond—a real-time event attribution revisited

NASA Astrophysics Data System (ADS)

Otto, Friederike E. L.; van der Wiel, Karin; van Oldenborgh, Geert Jan; Philip, Sjoukje; Kew, Sarah F.; Uhe, Peter; Cullen, Heidi

2018-02-01

On 4-6 December 2015, storm Desmond caused very heavy rainfall in Northern England and Southern Scotland which led to widespread flooding. A week after the event we provided an initial assessment of the influence of anthropogenic climate change on the likelihood of one-day precipitation events averaged over an area encompassing Northern England and Southern Scotland using data and methods available immediately after the event occurred. The analysis was based on three independent methods of extreme event attribution: historical observed trends, coupled climate model simulations and a large ensemble of regional model simulations. All three methods agreed that the effect of climate change was positive, making precipitation events like this about 40% more likely, with a provisional 2.5%-97.5% confidence interval of 5%-80%. Here we revisit the assessment using more station data, an additional monthly event definition, a second global climate model and regional model simulations of winter 2015/16. The overall result of the analysis is similar to the real-time analysis with a best estimate of a 59% increase in event frequency, but a larger confidence interval that does include no change. It is important to highlight that the observational data in the additional monthly analysis does not only represent the rainfall associated with storm Desmond but also that of storms Eve and Frank occurring towards the end of the month.

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.

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.

Study on Rainfall Forecasting by Using Weather Satellite Imagery in a Small Watershed Located at Mountainous Area of Central Taiwan

NASA Astrophysics Data System (ADS)

Wei, C.; Cheng, K. S.

Using meteorological radar and satellite imagery had become an efficient tool for rainfall forecasting However few studies were aimed to predict quantitative rainfall in small watersheds for flood forecasting by using remote sensing data Due to the terrain shelter and ground clutter effect of Central Mountain Ridges the application of meteorological radar data was limited in mountainous areas of central Taiwan This study devises a new scheme to predict rainfall of a small upstream watershed by combing GOES-9 geostationary weather satellite imagery and ground rainfall records which can be applied for local quantitative rainfall forecasting during periods of typhoon and heavy rainfall Imagery of two typhoon events in 2004 and five correspondent ground raingauges records of Chitou Forest Recreational Area which is located in upstream region of Bei-Shi river were analyzed in this study The watershed accounts for 12 7 square kilometers and altitudes ranging from 1000 m to 1800 m Basin-wide Average Rainfall BAR in study area were estimated by block kriging Cloud Top Temperature CTT from satellite imagery and ground hourly rainfall records were medium correlated The regression coefficient ranges from 0 5 to 0 7 and the value decreases as the altitude of the gauge site increases The regression coefficient of CCT and next 2 to 6 hour accumulated BAR decrease as the time scale increases The rainfall forecasting for BAR were analyzed by Kalman Filtering Technique The correlation coefficient and average hourly deviates between estimated and observed value of BAR for

Coupling loss characteristics of runoff-sediment-adsorbed and dissolved nitrogen and phosphorus on bare loess slope.

PubMed

Wu, Lei; Qiao, Shanshan; Peng, Mengling; Ma, Xiaoyi

2018-05-01

Soil and nutrient loss is a common natural phenomenon but it exhibits unclear understanding especially on bare loess soil with variable rainfall intensity and slope gradient, which makes it difficult to design control measures for agricultural diffuse pollution. We employ 30 artificial simulated rainfalls (six rainfall intensities and five slope gradients) to quantify the coupling loss correlation of runoff-sediment-adsorbed and dissolved nitrogen and phosphorus on bare loess slope. Here, we show that effects of rainfall intensity on runoff yield was stronger than slope gradient with prolongation of rainfall duration, and the effect of slope gradient on runoff yield reduced gradually with increased rainfall intensity. But the magnitude of initial sediment yield increased significantly from an average value of 6.98 g at 5° to 36.08 g at 25° with increased slope gradient. The main factor of sediment yield would be changed alternately with the dual increase of slope gradient and rainfall intensity. Dissolved total nitrogen (TN) and dissolved total phosphorus (TP) concentrations both showed significant fluctuations with rainfall intensity and slope gradient, and dissolved TP concentration was far less than dissolved TN. Under the double influences of rainfall intensity and slope gradient, adsorbed TN concentration accounted for 7-82% of TN loss concentration with an average of 58.6% which was the main loss form of soil nitrogen, adsorbed TP concentration accounted for 91.8-98.7% of TP loss concentration with an average of 96.6% which was also the predominant loss pathway of soil phosphorus. Nitrate nitrogen (NO 3 - -N) accounted for 14.59-73.92% of dissolved TN loss, and ammonia nitrogen (NH 4 + -N) accounted for 1.48-18.03%. NO 3 - -N was the main loss pattern of TN in runoff. Correlation between dissolved TN, runoff yield, and rainfall intensity was obvious, and a significant correlation was also found between adsorbed TP, sediment yield, and slope gradient. Our results provide the underlying insights needed to guide the control of nitrogen and phosphorus loss on loess hills.

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.

Ensemble averaging and stacking of ARIMA and GSTAR model for rainfall forecasting

NASA Astrophysics Data System (ADS)

Anggraeni, D.; Kurnia, I. F.; Hadi, A. F.

2018-04-01

Unpredictable rainfall changes can affect human activities, such as in agriculture, aviation, shipping which depend on weather forecasts. Therefore, we need forecasting tools with high accuracy in predicting the rainfall in the future. This research focus on local forcasting of the rainfall at Jember in 2005 until 2016, from 77 rainfall stations. The rainfall here was not only related to the occurrence of the previous of its stations, but also related to others, it’s called the spatial effect. The aim of this research is to apply the GSTAR model, to determine whether there are some correlations of spatial effect between one to another stations. The GSTAR model is an expansion of the space-time model that combines the time-related effects, the locations (stations) in a time series effects, and also the location it self. The GSTAR model will also be compared to the ARIMA model that completely ignores the independent variables. The forcested value of the ARIMA and of the GSTAR models then being combined using the ensemble forecasting technique. The averaging and stacking method of ensemble forecasting method here provide us the best model with higher acuracy model that has the smaller RMSE (Root Mean Square Error) value. Finally, with the best model we can offer a better local rainfall forecasting in Jember for the future.

Overland flow connectivity in olive orchard plots with cover crops and conventional tillage, and under different rainfall scenarios

NASA Astrophysics Data System (ADS)

López-Vicente, Manuel; García-Ruiz, Roberto; Guzmán, Gema; Vicente-Vicente, José Luis; Gómez, José Alfonso

2016-04-01

The study of overland flow connectivity (QC) allows understanding the redistribution dynamics of runoff and soil components as an emergent property of the spatio-temporal interactions of hydrological and geomorphic processes. However, very few studies have dealt with runoff connectivity in olive orchards. In this study we simulated QC in four olive orchard plots, located on the Santa Marta farm (37° 20' 33.6" N, 6° 13' 44" W), in Seville province (Andalusia) in SW Spain. The olive plantation was established in 1985 with trees planted at 8 m x 6 m. Each bounded plot is 8 m wide (between 2 tree lines) and 60 m long (total area of 480 m2), laid out with the longest dimension parallel to the maximum slope and to the tree lines. The slope is uniform, with an average steepness of 11%. Two plots (P2 and P4) were devoted to conventional tillage (CT) consisting of regular chisel plow passes depending on weed growth. Another set of two plots had two types of cover crops (CC) in the inter tree rows (the area outside the vertical olive canopy projection): uniform CC of Lolium multiflorum (P3) and a mixture of L. rigidum and L. multiflorum together with other species (P5). The tree rows were treated with herbicide to keep bare soil. We selected the Index of runoff and sediment Connectivity (IC) of Borselli et al. (2008) to simulate three rainfall scenarios: i) low rainfall intensity (Sc-LowInt) and using the MD flow accumulation algorithm; ii) moderate rainfall intensity (Sc-ModInt) and using MD8; and iii) high rainfall intensity (Sc-HighInt) and using D8. After analysing the values of rainfall intensity during two hydrological years (Oct'09-Sep'10 and Oct'10-Sep'11) we associated the three scenarios with the followings months: Sc-LowInt during the period Jan-Mar, that summarizes 42% of all annual rainfall events; Sc-ModInt during Oct-Nov and Apr-May (32% of all events); and Sc-HighInt during the period Jun-Sep and in December (26% of all events). Instead of using the C-RUSLE factor as it is indicated in the original version of the IC model, we chosen the product between the C (cover-management) and P (support-practices) factors. Previous studies in olive orchards (Gómez et al., 2003) demonstrated that this product is advisable in soil erosion studies. We distinguished four areas within the plots: inter-row-CC, inter-row-CT, olive trees and bare soil under the tree line. Values of the C-RUSLE factor were obtained from previous studies (e.g. Moreira-Madueño, 1991 in Andalusia; Panagos et al., 2015 in Europe). The minimum, mean and maximum values of connectivity in the two plots with CC were lower (-8% on average) than the corresponding values in the two plots under CT. This trend remained by using any of the three algorithms. CC efficiently reduced overland flow connectivity. Areas with low connectivity (deposition-prone areas) appeared more frequently in inter-row-CC in comparison with CT. The assessment of the C-RUSLE factor for each month according to the phenology of the CC and the sowing practices will be explored in further research.

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 ...

Average Annual Rainfall Over the Globe

NASA Astrophysics Data System (ADS)

Agrawal, D. C.

2013-12-01

The atmospheric recycling of water is a very important phenomenon on the globe because it not only refreshes the water but it also redistributes it over land and oceans/rivers/lakes throughout the globe. This is made possible by the solar energy intercepted by the Earth. The half of the globe facing the Sun, on the average, intercepts 1.74×1017 J of solar radiation per second and it is divided over various channels as given in Table 1. It keeps our planet warm and maintains its average temperature2 of 288 K with the help of the atmosphere in such a way that life can survive. It also recycles the water in the oceans/rivers/ lakes by initial evaporation and subsequent precipitation; the average annual rainfall over the globe is around one meter. According to M. King Hubbert the amount of solar power going into the evaporation and precipitation channel is 4.0×1016 W. Students can verify the value of average annual rainfall over the globe by utilizing this part of solar energy. This activity is described in the next section.

Mean transit times in headwater catchments: insights from the Otway Ranges, Australia

NASA Astrophysics Data System (ADS)

Howcroft, William; Cartwright, Ian; Morgenstern, Uwe

2018-01-01

Understanding the timescales of water flow through catchments and the sources of stream water at different flow conditions is critical for understanding catchment behaviour and managing water resources. Here, tritium (3H) activities, major ion geochemistry and streamflow data were used in conjunction with lumped parameter models (LPMs) to investigate mean transit times (MTTs) and the stores of water in six headwater catchments in the Otway Ranges of southeastern Australia. 3H activities of stream water ranged from 0.20 to 2.14 TU, which are significantly lower than the annual average 3H activity of modern local rainfall, which is between 2.4 and 3.2 TU. The 3H activities of the stream water are lowest during low summer flows and increase with increasing streamflow. The concentrations of most major ions vary little with streamflow, which together with the low 3H activities imply that there is no significant direct input of recent rainfall at the streamflows sampled in this study. Instead, shallow younger water stores in the soils and regolith are most likely mobilised during the wetter months. MTTs vary from approximately 7 to 230 years. Despite uncertainties of several years in the MTTs that arise from having to assume an appropriate LPM, macroscopic mixing, and uncertainties in the 3H activities of rainfall, the conclusion that they range from years to decades is robust. Additionally, the relative differences in MTTs at different streamflows in the same catchment are estimated with more certainty. The MTTs in these and similar headwater catchments in southeastern Australia are longer than in many catchments globally. These differences may reflect the relatively low rainfall and high evapotranspiration rates in southeastern Australia compared with headwater catchments elsewhere. The long MTTs imply that there is a long-lived store of water in these catchments that can sustain the streams over drought periods lasting several years. However, the catchments are likely to be vulnerable to decadal changes in land use or climate. Additionally, there may be considerable delay in contaminants reaching the stream. An increase in nitrate and sulfate concentrations in several catchments at high streamflows may represent the input of contaminants through the shallow groundwater that contributes to streamflow during the wetter months. Poor correlations between 3H activities and catchment area, drainage density, land use, and average slope imply that the MTTs are not controlled by a single parameter but a variety of factors, including catchment geomorphology and the hydraulic properties of the soils and aquifers.

Identifying multiple timescale rainfall controls on Mojave Desert ecohydrology using an integrated data and modeling approach for Larrea tridentata

USGS Publications Warehouse

Ng, Gene-Hua Crystal; Bedford, David R.; Miller, David M.

2015-01-01

The perennial shrub Larrea tridentata is widely successful in North American warm deserts but is also susceptible to climatic perturbations. Understanding its response to rainfall variability requires consideration of multiple timescales. We examine intra-annual to multi-year relationships using model simulations of soil moisture and vegetation growth over 50 years in the Mojave National Preserve in southeastern California (USA). Ecohydrological model parameters are conditioned on field and remote sensing data using an ensemble Kalman filter. Although no specific periodicities were detected in the rainfall record, simulated leaf-area-index exhibits multi-year dynamics that are driven by multi-year (∼3-years) rains, but with up to a 1-year delay in peak response. Within a multi-year period, Larrea tridentata is more sensitive to winter rains than summer. In the most active part of the root zone (above ∼80 cm), >1-year average soil moisture drives vegetation growth, but monthly average soil moisture is controlled by root uptake. Moisture inputs reach the lower part of the root zone (below ∼80 cm) infrequently, but once there they can persist over a year to help sustain plant growth. Parameter estimates highlight efficient plant physiological properties facilitating persistent growth and high soil hydraulic conductivity allowing deep soil moisture stores. We show that soil moisture as an ecological indicator is complicated by bidirectional interactions with vegetation that depend on timescale and depth. Under changing climate, Larrea tridentata will likely be relatively resilient to shorter-term moisture variability but will exhibit higher sensitivity to shifts in seasonal to multi-year moisture inputs.

Intra-annual variation in turbidity in response to terrestrial runoff on near-shore coral reefs of the Great Barrier Reef

NASA Astrophysics Data System (ADS)

Fabricius, Katharina E.; De'ath, Glenn; Humphrey, Craig; Zagorskis, Irena; Schaffelke, Britta

2013-01-01

Seawater turbidity is a fundamental driver of the ecology of coastal marine systems, and is widely used as indicator for environmental reporting. However, the time scales and processes leading to changes in turbidity in tropical coastal waters remain poorly understood. This study investigates the main determinants of inshore turbidity in four inshore regions along ˜1000 km of the Australian Great Barrier Reef, based on ˜3 years of almost continuous in situ turbidity logger data on 14 reefs. Generalized additive mixed models were used to predict spatial and temporal variation in weekly mean turbidity based on variation in resuspension and runoff conditions. At any given wave height, wave period and tidal range, turbidity was significantly affected by river flow and rainfall. Averaged across all reefs, turbidity was 13% lower (range: 5-37%) in weeks with low compared with high rainfall and river flows. Additionally, turbidity was on average 43% lower 250 days into the dry season than at the start of the dry season on reefs with long-term mean turbidity >1.1 NTU. The data suggest the time scale of winnowing or consolidation of newly imported materials in this zone is months to years. In contrast, turbidity returned to low levels within weeks after river flows and rainfall on reefs with long-term mean turbidity of <1.1 NTU. Turbidity was also up to 10-fold higher on reefs near compared to away from river mouths, suggesting inter-annual accumulation of fine resuspendible sediments. The study suggests that a reduction in the river loads of fine sediments and nutrients through improved land management should lead to measurably improved inshore water clarity in the most turbid parts of the GBR.

The influence of intra- and inter-annual meteorological variability on dengue transmission: a multi-level modeling analysis

NASA Astrophysics Data System (ADS)

Wen, Tzai-Hung; Chen, Tzu-Hsin

2017-04-01

Dengue fever is one of potentially life-threatening mosquito-borne diseases and IPCC Fifth Assessment Report (AR5) has confirmed that dengue incidence is sensitive to the critical weather conditions, such as effects of temperature. However, previous literature focused on the effects of monthly or weekly average temperature or accumulative precipitation on dengue incidence. The influence of intra- and inter-annual meteorological variability on dengue outbreak is under investigated. The purpose of the study focuses on measuring the effect of the intra- and inter-annual variations of temperature and precipitation on dengue outbreaks. We developed the indices of intra-annual temperature variability are maximum continuity, intermittent, and accumulation of most suitable temperature (MST) for dengue vectors; and also the indices of intra-annual precipitation variability, including the measure of continuity of wetness or dryness during a pre-epidemic period; and rainfall intensity during an epidemic period. We used multi-level modeling to investigate the intra- and inter-annual meteorological variations on dengue outbreaks in southern Taiwan from 1998-2015. Our results indicate that accumulation and maximum continuity of MST are more significant than average temperature on dengue outbreaks. The effect of continuity of wetness during the pre-epidemic period is significantly more positive on promoting dengue outbreaks than the rainfall effect during the epidemic period. Meanwhile, extremely high or low rainfall density during an epidemic period do not promote the spread of dengue epidemics. Our study differentiates the effects of intra- and inter-annual meteorological variations on dengue outbreaks and also provides policy implications for further dengue control under the threats of climate change. Keywords: dengue fever, meteorological variations, multi-level model

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...

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

USDA-ARS?s Scientific Manuscript database

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

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Species biogeography predicts drought responses in a seasonally dry tropical forest

NASA Astrophysics Data System (ADS)

Schwartz, N.; Powers, J. S.; Vargas, G.; Xu, X.; Smith, C. M.; Brodribb, T.; Werden, L. K.; Becknell, J.; Medvigy, D.

2017-12-01

The timing, distribution, and amount of rainfall in the seasonal tropics have shifted in recent years, with consequences for seasonally dry tropical forests (SDTF). SDTF are sensitive to changing rainfall regimes and drought conditions, but sensitivity to drought varies substantially across species. One potential explanation of species differences is that species that experience dry conditions more frequently throughout their range will be better able to cope with drought than species from wetter climates, because species from drier climates will be better adapted to drought. An El-Niño induced drought in 2015 presented an opportunity to assess species-level differences in mortality in SDTF, and to ask whether the ranges of rainfall conditions species experience and the average rainfall regimes in species' ranges predict differences in mortality rates in Costa Rican SDTF. We used field plot data from northwest Costa Rica to determine species' level mortality rates. Mortality rates ranged substantially across species, with some species having no dead individuals to as high as 50% mortality. To quantify rainfall conditions across species' ranges, we used species occurrence data from the Global Biodiversity Information Facility, and rainfall data from the Chelsa climate dataset. We found that while the average and range of mean annual rainfall across species ranges did not predict drought-induced mortality in the field plots, across-range averages of the seasonality index, a measure of rainfall seasonality, was strongly correlated with species-level drought mortality (r = -0.62, p < 0.05), with species from more strongly seasonal climates experiencing less severe drought mortality. Furthermore, we found that the seasonality index was a stronger predictor of mortality than any individual functional trait we considered. This result shows that species' biogeography may be an important factor for how species will respond to future drought, and may be a more integrative predictor than individual functional traits.

Characterizing the Spatial Contiguity of Extreme Precipitation over the US in the Recent Past

NASA Astrophysics Data System (ADS)

Touma, D. E.; Swain, D. L.; Diffenbaugh, N. S.

2016-12-01

The spatial characteristics of extreme precipitation over an area can define the hydrologic response in a basin, subsequently affecting the flood risk in the region. Here, we examine the spatial extent of extreme precipitation in the US by defining its "footprint": a contiguous area of rainfall exceeding a certain threshold (e.g., 90th percentile) on a given day. We first characterize the climatology of extreme rainfall footprint sizes across the US from 1980-2015 using Daymet, a high-resolution observational gridded rainfall dataset. We find that there are distinct regional and seasonal differences in average footprint sizes of extreme daily rainfall. In the winter, the Midwest shows footprints exceeding 500,000 sq. km while the Front Range exhibits footprints of 10,000 sq. km. Alternatively, the summer average footprint size is generally smaller and more uniform across the US, ranging from 10,000 sq. km in the Southwest to 100,000 sq. km in Montana and North Dakota. Moreover, we find that there are some significant increasing trends of average footprint size between 1980-2015, specifically in the Southwest in the winter and the Northeast in the spring. While gridded daily rainfall datasets allow for a practical framework in calculating footprint size, this calculation heavily depends on the interpolation methods that have been used in creating the dataset. Therefore, we assess footprint size using the GHCN-Daily station network and use geostatistical methods to define footprints of extreme rainfall directly from station data. Compared to the findings from Daymet, preliminary results using this method show fewer small daily footprint sizes over the US while large footprints are of similar number and magnitude to Daymet. Overall, defining the spatial characteristics of extreme rainfall as well as observed and expected changes in these characteristics allows us to better understand the hydrologic response to extreme rainfall and how to better characterize flood risks.

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.

Comparing groundwater recharge and storage variability from GRACE satellite observations with observed water levels and recharge model simulations

NASA Astrophysics Data System (ADS)

Allen, D. M.; Henry, C.; Demon, H.; Kirste, D. M.; Huang, J.

2011-12-01

Sustainable management of groundwater resources, particularly in water stressed regions, requires estimates of groundwater recharge. This study in southern Mali, Africa compares approaches for estimating groundwater recharge and understanding recharge processes using a variety of methods encompassing groundwater level-climate data analysis, GRACE satellite data analysis, and recharge modelling for current and future climate conditions. Time series data for GRACE (2002-2006) and observed groundwater level data (1982-2001) do not overlap. To overcome this problem, GRACE time series data were appended to the observed historical time series data, and the records compared. Terrestrial water storage anomalies from GRACE were corrected for soil moisture (SM) using the Global Land Data Assimilation System (GLDAS) to obtain monthly groundwater storage anomalies (GRACE-SM), and monthly recharge estimates. Historical groundwater storage anomalies and recharge were determined using the water table fluctuation method using observation data from 15 wells. Historical annual recharge averaged 145.0 mm (or 15.9% of annual rainfall) and compared favourably with the GRACE-SM estimate of 149.7 mm (or 14.8% of annual rainfall). Both records show lows and peaks in May and September, respectively; however, the peak for the GRACE-SM data is shifted later in the year to November, suggesting that the GLDAS may poorly predict the timing of soil water storage in this region. Recharge simulation results show good agreement between the timing and magnitude of the mean monthly simulated recharge and the regional mean monthly storage anomaly hydrograph generated from all monitoring wells. Under future climate conditions, annual recharge is projected to decrease by 8% for areas with luvisols and by 11% for areas with nitosols. Given this potential reduction in groundwater recharge, there may be added stress placed on an already stressed resource.

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.

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.

Climate controls on C3 vs. C4 productivity in North American grasslands from carbon isotope composition of soil organic matter

USGS Publications Warehouse

von Fischer, J.C.; Tieszen, L.L.; Schimel, D.S.

2008-01-01

We analyzed the ??13 C of soil organic matter (SOM) and fine roots from 55 native grassland sites widely distributed across the US and Canadian Great Plains to examine the relative production of C3 vs. C4 plants (hereafter %C4) at the continental scale. Our climate vs. %C4 results agreed well with North American field studies on %C4, but showed bias with respect to %C4 from a US vegetation database (statsgo) and weak agreement with a physiologically based prediction that depends on crossover temperature. Although monthly average temperatures have been used in many studies to predict %C4, our analysis shows that high temperatures are better predictors of %C4. In particular, we found that July climate (average of daily high temperature and month's total rainfall) predicted %C4 better than other months, seasons or annual averages, suggesting that the outcome of competition between C3 and C4 plants in North American grasslands was particularly sensitive to climate during this narrow window of time. Root ??13 C increased about 1??? between the A and B horizon, suggesting that C 4 roots become relatively more common than C3 roots with depth. These differences in depth distribution likely contribute to the isotopic enrichment with depth in SOM where both C3 and C4 grasses are present. ?? 2008 The Authors Journal compilation ?? 2008 Blackwell Publishing Ltd.

Weather variability, tides, and Barmah Forest virus disease in the Gladstone region, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; McMichael, Anthony J; Dale, Pat; Tong, Shilu

2006-05-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (b=0.15, p-value<0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (b=-1.03, p-value=0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

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.

Regional grassland productivity responses to precipitation during multiyear above- and below-average rainfall periods.

PubMed

Petrie, Matthew D; Peters, Debra P C; Yao, Jin; Blair, John M; Burruss, Nathan D; Collins, Scott L; Derner, Justin D; Gherardi, Laureano A; Hendrickson, John R; Sala, Osvaldo E; Starks, Patrick J; Steiner, Jean L

2018-05-01

There is considerable uncertainty in the magnitude and direction of changes in precipitation associated with climate change, and ecosystem responses are also uncertain. Multiyear periods of above- and below-average rainfall may foretell consequences of changes in rainfall regime. We compiled long-term aboveground net primary productivity (ANPP) and precipitation (PPT) data for eight North American grasslands, and quantified relationships between ANPP and PPT at each site, and in 1-3 year periods of above- and below-average rainfall for mesic, semiarid cool, and semiarid warm grassland types. Our objective was to improve understanding of ANPP dynamics associated with changing climatic conditions by contrasting PPT-ANPP relationships in above- and below-average PPT years to those that occurred during sequences of multiple above- and below-average years. We found differences in PPT-ANPP relationships in above- and below-average years compared to long-term site averages, and variation in ANPP not explained by PPT totals that likely are attributed to legacy effects. The correlation between ANPP and current- and prior-year conditions changed from year to year throughout multiyear periods, with some legacy effects declining, and new responses emerging. Thus, ANPP in a given year was influenced by sequences of conditions that varied across grassland types and climates. Most importantly, the influence of prior-year ANPP often increased with the length of multiyear periods, whereas the influence of the amount of current-year PPT declined. Although the mechanisms by which a directional change in the frequency of above- and below-average years imposes a persistent change in grassland ANPP require further investigation, our results emphasize the importance of legacy effects on productivity for sequences of above- vs. below-average years, and illustrate the utility of long-term data to examine these patterns. © 2018 John Wiley & Sons Ltd.

Estimation of underground river water availability based on rainfall in the Maros karst region, South Sulawesi

NASA Astrophysics Data System (ADS)

Arsyad, Muhammad; Ihsan, Nasrul; Tiwow, Vistarani Arini

2016-02-01

Maros karst region, covering an area of 43.750 hectares, has water resources that determine the life around it. Water resources in Maros karst are in the rock layers or river underground in the cave. The data used in this study are primary and secondary data. Primary data includes characteristics of the medium. Secondary data is rainfall data from BMKG, water discharge data from the PSDA, South Sulawesi province in 1990-2010, and the other characteristics data Maros karst, namely cave, flora and fauna of the Bantimurung Bulusaraung National Park. Data analysis was conducted using laboratory test for medium characteristics Maros karst, rainfall and water discharge were analyzed using Minitab Program 1.5 to determine their profile. The average rainfall above 200 mm per year occurs in the range of 1999 to 2005. The availability of the water discharge at over 50 m3/s was happened in 1993 and 1995. Prediction was done by modeling Autoregressive Integrated Moving Average (ARIMA), with the rainfall data shows that the average precipitation for four years (2011-2014) will sharply fluctuate. The prediction of water discharge in Maros karst region was done for the period from January to August in 2011, including the type of 0. In 2012, the addition of the water discharge started up in early 2014.

The O and H stable isotope composition of freshwaters in the British Isles. 2. Surface waters and groundwater

NASA Astrophysics Data System (ADS)

Darling, W. G.; Bath, A. H.; Talbot, J. C.

The utility of stable isotopes as tracers of the water molecule has a long pedigree. The study reported here is part of an attempt to establish a comprehensive isotopic "baseline" for the British Isles as background data for a range of applications. Part 1 of this study (Darling and Talbot, 2003) considered the isotopic composition of rainfall in Britain and Ireland. The present paper is concerned with the composition of surface waters and groundwater. In isotopic terms, surface waters (other than some upland streams) are poorly characterised in the British Isles; their potential variability has yet to be widely used as an aid in hydrological research. In what may be the first study of a major British river, a monthly isotopic record of the upper River Thames during 1998 was obtained. This shows high damping of the isotopic variation compared to that in rainfall over most of the year, though significant fluctuations were seen for the autumn months. Smaller rivers such as the Stour and Darent show a more subdued response to the balance between runoff and baseflow. The relationship between the isotopic composition of rainfall and groundwater is also considered. From a limited database, it appears that whereas Chalk groundwater is a representative mixture of weighted average annual rainfall, for Triassic sandstone groundwater there is a seasonal selection of rainfall biased towards isotopically-depleted winter recharge. This may be primarily the result of physical differences between the infiltration characteristics of rock types, though other factors (vegetation, glacial history) could be involved. In the main, however, groundwaters appear to be representative of bulk rainfall within an error band of 0.5‰ δ18O. Contour maps of the δ18O and δ2H content of recent groundwaters in the British Isles show a fundamental SW-NE depletion effect modified by topography. The range of measured values, while much smaller than those for rainfall, still covers some ‰ for δ18O and 30‰ for δ2H. Over lowland areas the "altitude effect" is of little significance, but in upland areas is consistent with a range of -0.2 to -0.3‰ per 100 m increase in altitude. Groundwaters dating from the late Pleistocene are usually modified in δ18O and δ2H owing to the effects of climate change on the isotopic composition of rainfall and thus of recharge. Contour maps of isotopic variability prior to 10 ka BP, based on the relatively limited information available from the British Isles, allow a first comparison between groundwaters now and at the end of the last Ice Age. The position of the British Isles in the context of the stable isotope systematics of NW Europe is reviewed briefly.

Analysis of rainfall distribution in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Che Ros, Faizah; Tosaka, Hiroyuki

2018-03-01

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

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.

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.

Linking the isotopic composition of monthly precipitation, cave drip water and tree ring cellulose - 15 years of monitoring and data-model comparison

NASA Astrophysics Data System (ADS)

Labuhn, Inga; Genty, Dominique; Daux, Valérie; Bourges, François; Hoffmann, Georg

2013-04-01

The isotopic composition of proxies used for palaeoclimate reconstruction, like tree ring cellulose or speleothem calcite, is controlled to a large extent by the isotopic composition of precipitation. In order to calibrate and interpret these proxies in terms of climate, it is necessary to study water isotopes in rainfall and their link with the proxies' source water. We present 10 to 15-year series of stable hydrogen and oxygen isotopes in monthly precipitation from three sites in the south of France, along with corresponding REMOiso model simulations, a monitoring of cave drip water from two of these sites (Villars cave in the south-west and Chauvet cave in the south-east), as well as measurements of oxygen isotopes in tree ring cellulose from oak trees growing in the same area. The isotopic composition of monthly precipitation at the three sites displays a typical annual cycle. At the south-west sites, under Atlantic influence, the interannual variability is much more pronounced during the winter months than during the summer, whereas the south-eastern Mediterranean site shows the same variability throughout the year. The model simulations are able to reproduce the annual cycle of monthly precipitation δ18O as well as the intra-seasonal variability. Compared to the data, however, the modelled average isotopic values and the seasonal amplitude are overestimated. Correlations between temperature and precipitation δ18O are generally weak at all our sites, on both the monthly and the annual scale, even when using temperature averages weighted by the amount of precipitation. Consequently, a proxy which is controlled by the δ18O of precipitation cannot be directly interpreted in terms of temperature in this region. The isotopic composition of cave drip water in both caves remains stable throughout the monitoring period. By calculating different weighted averages of precipitation δ18O for time periods ranging from months to years, we demonstrate that the cave drip water isotopic composition is the result of several years of rainfall mixing. The precipitation of every month must be considered in order to attain the drip water values, which means that rain water infiltrates throughout the year. There is no modification of the soil water isotopic composition by evaporation and no seasonal bias introduced by transpiring plants; they use water from reserves which represents several months or years of mixing. For the interpretation of tree ring cellulose δ18O, this implies that - at least for the monitoring period of 15 years - the source water signal is more or less constant. Therefore, the variability of cellulose δ18O must be mainly due to evaporation at the leaf level, which is strongly dependent on summer temperature. Insights on the variability and temperature correlations of stable isotopes in precipitation and on the origin and composition of cave drip water are important for the interpretation of proxies. Long-term monitoring is needed for model validation, and the locally validated and corrected model can provide longer time series for a reliable proxy calibration.

Acute childhood asthma in Galway city from 1985-2005: relationship to air pollution and climate.

PubMed

Loftus, A; Loftus, B G; Muircheartaigh, I O; Newell, J; Scarrott, C; Jennings, S

2014-01-01

We examine the relationship of air pollution and climatic variables to asthma admission rates of children in Galway city over a 21 year period. Paediatric asthma admissions were recorded from 1985-2005, and admission rates per thousand calculated for pre-school (1-4 years), school aged (5-14 years) and all children (1-14 years) on a monthly and annual basis. These data were compared to average monthly and annual climatic variables (rainfall, humidity, sunshine, wind speed and temperature) and black smoke levels for the city. Simple correlation and Poisson Generalized Additive Models (GAM) were used. Admission rates each month are significantly correlated with smoke levels (p = 0.007). Poisson GAM also shows a relationship between admissions and pollution (p = 0.07). Annual smoke levels impact more on admission rates of preschoolers (p = 0.04) than school age children (p = 0.10). These data suggest that air pollution is an important factor in the epidemiology of acute childhood asthma.

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

USGS Publications Warehouse

Brabets, Timothy P.

1999-01-01

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

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.

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.

Long-range Prediction of climatic Change in the Eastern Seaboard of Thailand over the 21st Century using various Downscaling Approaches

NASA Astrophysics Data System (ADS)

Bejranonda, Werapol; Koch, Manfred; Koontanakulvong, Sucharit

2010-05-01

Triggered by a long drought, a huge water supply crisis took place at the Eastern Seaboard of Thailand (east of the Gulf of Thailand) in 2005. In that year no rainfall occurred for four months after the beginning of the rainy season which led to the situation that the industrial estates of the Eastern Seaboard were not able to fully operate. Normally, most of the urban and industrial water used in this coastal region along east of the Gulf of Thailand, which is part of the Pacific Ocean, is surface water stored in a large-scale reservoir-network across the main watershed in the region. Thus the three major reservoirs usually gather water from monsoon storms that blow from the South and provide accumulative 80% of the annual rainfall during the 6 months of the rainy season which normally lasts from May-October. During the dry season (November - April) the winds are blowing from northern Indo-China land mass and rain drops only a few days in a month. Because of this typical tropical climate system, surface water resources across most of the southeastern Asia-Pacific region and the Eastern Seaboard of Thailand, in particular, rely on the annual occurrence of the monsoon season. There is now sufficient evidence that the named extreme weather conditions of 2005 occurring in that part of Thailand are not a singularity, but might be another signal of recent ongoing climate change in that country as a whole. Because of this imminent threat to the water resources of the region, and for the set-up of appropriate water management schemes for the near future, a climate impact study is proposed here. More specifically, the water budget of the Khlong Yai basin, which is the main watershed of the Eastern Seaboard, is modeled using the distributed hydrological model SWAT. To that avail the watershed model is coupled sequentially to a global climate model (GCM), whereby the latter provides the input forcing parameters (e.g. precipitation and temperature) to the former. Because of the different scales of the hydrological (local to regional) and of the GCM (global), one is faced with the problem of 'downscaling' the coarse grid resolution output of the GCM to the fine grid of the hydrological model. Although there have been numerous downscaling approaches proposed to that regard over the last decade, the jury is still out about the best method to use in a particular application. The focus here is on the downscaling part of the investigation, i.e. the proper preparation of the GCM's output to serve as input, i.e. the driving force, to the hydrological model (which is not further discussed here). Daily ensembles of climate variables computed by means of the CGCM3 model of the Canadian Climate Center which has a horizontal grid resolution of approximately the size of the whole study basin are used here, indicating clearly the need for downscaling. Daily observations of local climate variables available since 1971 are used as additional input to the various downscaling tools proposed which are, namely, the stochastic weather generator (LARS-WG), the statistical downscaling model (SDSM), and a multiple linear regression model between the observed variables and the CGCM3 predictors. Both the 2D and the 3D versions of the CGCM3 model are employed to predict, 100 years ahead up to year 2100, the monthly rainfall and temperatures, based on the past calibration period (training period) 1971-2000. To investigate the prediction performance, multiple linear regression, autoregressive (AR) and autoregressive integrated moving average (ARIMA) models are applied to the time series of the observation data which are aggregated into monthly time steps to be able compare them with the downscaling results above. Likewise, multiple linear regression and ARIMA models also executed on the CGCM3 predictors and the Pacific / Indian oceans indices as external regressors to predict short-term local climate variations. The results of the various downscaling method are validated for years 2001-2006 at selected meteorological stations in the Khlong Yai basin, assuming the IPCC's A1B and A2 emission scenarios. The performance of the monthly climate prediction has been evaluated by comparison with observed data using the Nash-Sutcliffe model efficiency measure. Among the statistical/stochastical downscaling and the forecasting methods used, the climate prediction by the ARIMA model with ocean indices and CGCM predictor included as external regressors are the most reliable. Thus for the verification period 2001-2006 Nash-Sutcliffe coefficient of 0.84, 0.47 and 0.50 are obtained for the minimum and maximum temperatures and the rainfall, respectively, whereas the corresponding 1-year ahead predictions are 0.77, 0.43 and 0.48, respectively. The best external regressor for the prediction of the minimum temperatures in the basin is, surprisingly, the El Niño 1.2 SST anomaly time series; for the prediction of the maximum temperatures, the minimum surface air temperature predictor in CGCM3 (tasmin); and for the prediction of the rainfall, the 850hPa eastward-wind predictor in CGCM3 (p8_uas). Based on year 2000, the downscaling results show that the average minimum temperature will be higher by 0.4 to 5.9 ° C by year 2100, while the average maximum temperature will be rather stable, with only little change between -0.2 to +0.3° C. As for the rainfall at year 2100, a possible change from +0.2 to 12.0 mm/month is obtained. These climate prediction results mean that, although there will be more rainfall in the future, the much higher temperature will lead to more evapotranspiration, i.e. more agricultural water demand. Besides, the increasing rainfall will most likely lead to unexpected flood events in the future that will require precautionary planning at the watershed-scale. This will be further analyzed during the course of the ongoing study using the SWAT hydrological model mentioned above.

RAINLINK: Retrieval algorithm for rainfall monitoring employing microwave links from a cellular communication network

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Overeem, A.; Leijnse, H.; Rios Gaona, M. F.

2017-12-01

The basic principle of rainfall estimation using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated, which can be converted to average rainfall intensities over the length of a link. Microwave links from cellular communication networks have been proposed as a promising new rainfall measurement technique for one decade. They are particularly interesting for those countries where few surface rainfall observations are available. Yet to date no operational (real-time) link-based rainfall products are available. To advance the process towards operational application and upscaling of this technique, there is a need for freely available, user-friendly computer code for microwave link data processing and rainfall mapping. Such software is now available as R package "RAINLINK" on GitHub (https://github.com/overeem11/RAINLINK). It contains a working example to compute link-based 15-min rainfall maps for the entire surface area of The Netherlands for 40 hours from real microwave link data. This is a working example using actual data from an extensive network of commercial microwave links, for the first time, which will allow users to test their own algorithms and compare their results with ours. The package consists of modular functions, which facilitates running only part of the algorithm. The main processings steps are: 1) Preprocessing of link data (initial quality and consistency checks); 2) Wet-dry classification using link data; 3) Reference signal determination; 4) Removal of outliers ; 5) Correction of received signal powers; 6) Computation of mean path-averaged rainfall intensities; 7) Interpolation of rainfall intensities ; 8) Rainfall map visualisation. Some applications of RAINLINK will be shown based on microwave link data from a temperate climate (the Netherlands), and from a subtropical climate (Brazil). We hope that RAINLINK will promote the application of rainfall monitoring using microwave links in poorly gauged regions around the world. We invite researchers to contribute to RAINLINK to make the code more generally applicable to data from different networks and climates.

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

Effects of Agricultural Land-Use Changes and Rainfall on Ground-Water Recharge in Central and West Maui, Hawai`i, 1926-2004

USGS Publications Warehouse

Engott, John A.; Vana, Thomas T.

2007-01-01

Concern surrounding declines in ground-water levels and an increase in the chloride concentration of water pumped from wells in the Iao aquifer system on the Island of Maui has prompted an investigation into the long-term sustainability of current (2006) and future ground-water withdrawals. As part of this investigation, a water budget for central and west Maui was calculated from which (1) ground-water recharge was estimated for the period 1926-2004 and (2) the effects of agricultural land-use changes and drought were analyzed. Estimated mean ground-water recharge decreased 44 percent from 1979 to 2004 in central and west Maui. Reduction in agricultural irrigation, resulting from more efficient irrigation methods and a reduction in the acreage used for agriculture, is largely responsible for the declining recharge. Recently, periods of lower-than-average rainfall have further reduced recharge. During the period 1926-79, ground-water recharge averaged 693 Mgal/d, irrigation averaged 437 Mgal/d, and rainfall averaged 897 Mgal/d. During the period 2000-04, ground-water recharge averaged 391 Mgal/d, irrigation averaged 237 Mgal/d, and rainfall averaged 796 Mgal/d. Simulations of hypothetical future conditions indicate that a cessation of agriculture in central and west Maui would reduce mean ground-water recharge by 18 percent in comparison with current conditions, assuming that current climatic conditions are the same as the long-term-average conditions during the period 1926-2004. A period of drought identical to that of 1998-2002 would reduce mean recharge by 27 percent. Mean recharge would decrease by 46 percent if this drought were to occur after a cessation of agriculture in central and western Maui. Whereas droughts are transient phenomena, a reduction in agricultural irrigation is likely a permanent condition.

Soil erosion assessment of a Himalayan river basin using TRMM data

NASA Astrophysics Data System (ADS)

Pandey, A.; Mishra, S. K.; Gautam, A. K.; Kumar, D.

2015-04-01

In this study, an attempt has been made to assess the soil erosion of a Himalayan river basin, the Karnali basin, Nepal, using rainfall erosivity (R-factor) derived from satellite-based rainfall estimates (TRMM-3B42 V7). Average annual sediment yield was estimated using the well-known Universal Soil Loss Equation (USLE). The eight-year annual average rainfall erosivity factor (R) for the Karnali River basin was found to be 2620.84 MJ mm ha-1 h-1 year-1. Using intensity-erosivity relationships and eight years of the TRMM daily rainfall dataset (1998-2005), average annual soil erosion was also estimated for Karnali River basin. The minimum and maximum values of the rainfall erosivity factor were 1108.7 and 4868.49 MJ mm ha-1 h-1 year-1, respectively, during the assessment period. The average annual soil loss of the Karnali River basin was found to be 38.17 t ha-1 year-1. Finally, the basin area was categorized according to the following scale of erosion severity classes: Slight (0 to 5 t ha-1 year-1), Moderate (5 to 10 t ha-1 year-1), High (10 to 20 t ha-1 year-1), Very High (20 to 40 t ha-1 year-1), Severe (40 to 80 t ha-1 year-1) and Very Severe (>80 t ha-1 year-1). About 30.86% of the river basin area was found to be in the slight erosion class. The areas covered by the moderate, high, very high, severe and very severe erosion potential zones were 13.09%, 6.36%, 11.09%, 22.02% and 16.64% respectively. The study revealed that approximately 69% of the Karnali River basin needs immediate attention from a soil conservation point of view.

Influence of declining mean annual rainfall on the behavior and yield of sediment and particulate organic carbon from tropical watersheds

NASA Astrophysics Data System (ADS)

Strauch, Ayron M.; MacKenzie, Richard A.; Giardina, Christian P.; Bruland, Gregory L.

2018-04-01

The capacity to forecast climate and land-use driven changes to runoff, soil erosion and sediment transport in the tropics is hindered by a lack of long-term data sets and model study systems. To address these issues we utilized three watersheds characterized by similar shape, geology, soils, vegetation cover, and land use arranged across a 900 mm gradient in mean annual rainfall (MAR). Using this space-for-time design, we quantified suspended sediment (SS) and particulate organic carbon (POC) export over 18 months to examine how large-scale climate trends (MAR) affect sediment supply and delivery patterns (hysteresis) in tropical watersheds. Average daily SS yield ranged from 0.128 to 0.618 t km- 2 while average daily POC ranged from 0.002 to 0.018 t km- 2. For the largest storm events, we found that sediment delivery exhibited similar clockwise hysteresis patterns among the watersheds, with no significant differences in the similarity function between watershed pairs, indicating that: (1) in-stream and near-stream sediment sources drive sediment flux; and (2) the shape and timing of hysteresis is not affected by MAR. With declining MAR, the ratio of runoff to baseflow and inter-storm length between pulse events both increased. Despite increases in daily rainfall and the number of days with large rainfall events increasing with MAR, there was a decline in daily SS yield possibly due to the exhaustion of sediment supply by frequent runoff events in high MAR watersheds. By contrast, mean daily POC yield increased with increasing MAR, possibly as a result of increased soil organic matter decomposition, greater biomass, or increased carbon availability in higher MAR watersheds. We compared results to modeled values using the Load Estimator (LOADEST) FORTRAN model, confirming the negative relationship between MAR and sediment yield. However, because of its dependency on mean daily flow, LOADEST tended to under predict sediment yield, a result of its poor ability to capture the high variability in tropical streamflow. Taken together, results indicate that declines in MAR can have contrasting effects on hydrological processes in tropical watersheds, with consequences for instream ecology, downstream water users, and nearshore habitat.

Assessment of water availability and its relationship with vegetation distribution over a tropical montane system

NASA Astrophysics Data System (ADS)

Streher, A. S.; Sobreiro, J. F. F.; Silva, T. S. F.

2017-12-01

Water availability is one of the main drivers of vegetation distribution, but assessing it over mountainous regions is difficult given the effects of rugged topography on hydroclimatic dynamics (orographic rainfall, soil water, and runoff). We assessed how water availability may influence the distribution of vegetation types in the Espinhaço Range, a South American tropical mountain landscape comprised of savannas, grasslands, rock outcrops, cloud forests, and semi-deciduous/deciduous forests. For precipitation, we used CHIRPS monthly and daily products (1981- 2016) and 112 rain gauge ground stations, and assessed potential evapotranspiration (PET) using the MODIS MOD16A3 (2000-2013) product. Vegetation types were classified according to the Global Ecoregions by WWF. We show that rainfall has well-defined rainy and dry seasons with a strong latitudinal pattern, there is evidence for local orographic effects. Dry forests (907 mm/yr; 8% cv) and caatinga vegetation (795 mm/yr; 7% cv) had the lowest average annual precipitation and low variance, whilst Atlantic tropical forest in the southeast (1267 mm/yr; 15% cv), cerrado savanna vegetation in the west (1086 mm/yr; 15% cv) and rupestrian grasslands above 800m (1261 mm/yr; 20% cv) received the highest annual precipitation, with the largest observed variance due to their wide latitudinal distribution. Forests and rupestrian grasslands in the windward side of the mountain had a higher frequency of intense rainfall events (> 20mm), accounting for 6% of the CHIRPS daily time series, suggesting orographic effects on precipitation. Annual average PET was highest for dry forests (2437 mm/yr) and caatinga (2461 mm/yr), intermediate for cerrado (2264 mm/yr) and lowest for Atlantic tropical forest (2083 mm/yr) and rupestrian grasslands (2136 mm/yr). All vegetation types received less rainfall than its PET capacity based on yearly data, emphasizing the need for ecophysiological adaptations to water use. Climate change threatens these ecosystems by possible alterations on the hydrological cycle and, consequently, capacity for adaptations on water use. These could lead to shifts in vegetation composition and distribution within the studied region. Further investigation of seasonal trends on water availability and edaphic factors would improve these analyses.

First Evaluation of Rainfall Derived from Commercial Microwave Links in São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Raupach, T.

2017-12-01

Rainfall estimation from commercial microwave link (CML) networks has gained a lot of attention from the hydrometeorological community in the last decade. Path-averaged rainfall intensities can be retrieved from the signal attenuation between cell phone towers. Such a technique offers rainfall retrievals at high spatiotemporal resolutions. High spatiotemporal rainfall measurements are highly important for urban hydrology, given the often deadly impact of flash floods to society. This study evaluates CML rainfall retrievals for a subtropical climate. Rainfall estimation for subtropical climates is highly relevant, since many countries with few surface rainfall observations are located in such areas. The evaluation is done for the Brazilian city of São Paulo. RAINLINK (the open-source algorithm) retrieves rainfall intensities from attenuation measurements. We evaluated CMLs in the São Paulo metropolitan area for 81 days between October 2014 and January 2015. The evaluation was done against a dense automatic gauge network. High correlations (>0.9) and low biases ( 30%) are obtained, especially for short CMLs.

Stormwater-runoff data, Madison, Wisconsin, 1993-94

USGS Publications Warehouse

Waschbusch, R.J.

1996-01-01

As required by Section 402(P) of the Water Quality Control Act of 1987, stormwater-runoff samples collected during storms that met three criteria (rainfall depths 50 to 150 percent of average depth range, rainfall durations 50 to 150 percent of average duration, and antecedent dry-weather period of at least 72 hours) were analyzed for semivolatile organic chemicals, total metals, pesticides, polychlorinated biphenyls, inorganic constituents, bacteria, oil and grease, pH, and water temperature. Two of the seven sites also had samples analyzed for volatile organic chemicals. In addition to the required sampling, additional runoff samples that did not necessarily meet the three rainfall criteria, were analyzed for total metals and inorganic constituents. Storm loads of selected constituents were computed.

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...

Association of climate drivers with rainfall in New South Wales, Australia, using Bayesian Model Averaging

NASA Astrophysics Data System (ADS)

Duc, Hiep Nguyen; Rivett, Kelly; MacSween, Katrina; Le-Anh, Linh

2017-01-01

Rainfall in New South Wales (NSW), located in the southeast of the Australian continent, is known to be influenced by four major climate drivers: the El Niño/Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD). Many studies have shown the influences of ENSO, IPO modulation, SAM and IOD on rainfall in Australia and on southeast Australia in particular. However, only limited work has been undertaken using a multiple regression framework to examine the extent of the combined effect of these climate drivers on rainfall. This paper analysed the role of these combined climate drivers and their interaction on the rainfall in NSW using Bayesian Model Averaging (BMA) to account for model uncertainty by considering each of the linear models across the whole model space which is equal to the set of all possible combinations of predictors to find the model posterior probabilities and their expected predictor coefficients. Using BMA for linear regression models, we are able to corroborate and confirm the results from many previous studies. In addition, the method gives the ranking order of importance and the probability of the association of each of the climate drivers and their interaction on the rainfall at a site. The ability to quantify the relative contribution of the climate drivers offers the key to understand the complex interaction of drivers on rainfall, or lack of rainfall in a region, such as the three big droughts in southeastern Australia which have been the subject of discussion and debate recently on their causes.

Climate Effects on Corn Yield in Missouri(.

NASA Astrophysics Data System (ADS)

Hu, Qi; Buyanovsky, Gregory

2003-11-01

Understanding climate effects on crop yield has been a continuous endeavor aiming at improving farming technology and management strategy, minimizing negative climate effects, and maximizing positive climate effects on yield. Many studies have examined climate effects on corn yield in different regions of the United States. However, most of those studies used yield and climate records that were shorter than 10 years and were for different years and localities. Although results of those studies showed various influences of climate on corn yield, they could be time specific and have been difficult to use for deriving a comprehensive understanding of climate effects on corn yield. In this study, climate effects on corn yield in central Missouri are examined using unique long-term (1895 1998) datasets of both corn yield and climate. Major results show that the climate effects on corn yield can only be explained by within-season variations in rainfall and temperature and cannot be distinguished by average growing-season conditions. Moreover, the growing-season distributions of rainfall and temperature for high-yield years are characterized by less rainfall and warmer temperature in the planting period, a rapid increase in rainfall, and more rainfall and warmer temperatures during germination and emergence. More rainfall and cooler-than-average temperatures are key features in the anthesis and kernel-filling periods from June through August, followed by less rainfall and warmer temperatures during the September and early October ripening time. Opposite variations in rainfall and temperature in the growing season correspond to low yield. Potential applications of these results in understanding how climate change may affect corn yield in the region also are discussed.

Interflow, overland flow and leaching of natural nutrients on an Alfisol slope of southern Bahia, Brazil

NASA Astrophysics Data System (ADS)

De Oliveira Leite, J.

1985-09-01

Two experimental plots for hydrologic studies, 3595 and 7060 m 2, were delimited on a slope of Alfisol planted with cacao in Bahia, Brazil. Volumes of overland flow and interflow were measured daily and samples of collected water were taken monthly for analysis of Ca, Mg, Na, K, N, P and Fe. The highest overland-flow volumes represented 24% and the highest interflow 53% of the rainfall but on the average the volumes of overland flow and interflow were found to represent 1 and 14% of the annual rainfall. The percentage of interflow increases with increasing rainfall. In winter, it is higher than in summer, except during the highest rains observed. The mean annual loss for calcium was 85.8 kg ha -1 yr -1; for magnesium 18.2; potassium 17.0; sodium 23.5; nitrogen 22.1; iron 5.5 and phosphorus 0.9. In relative terms, considering the chemical components of the soils, the K losses are highest, indicating that this element is most leachable. The interflow volumes and the amounts of Na, K, N and P correlated at the 1% significance level in both plots. A general conclusion is that the leaching of nutrients varied with the intensity of the interflow, especially for Na, K, N and P, the leaching of nutrients through overland flow being of less importance.

Review of TRMM/GPM Rainfall Algorithm Validation

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2004-01-01

A review is presented concerning current progress on evaluation and validation of standard Tropical Rainfall Measuring Mission (TRMM) precipitation retrieval algorithms and the prospects for implementing an improved validation research program for the next generation Global Precipitation Measurement (GPM) Mission. All standard TRMM algorithms are physical in design, and are thus based on fundamental principles of microwave radiative transfer and its interaction with semi-detailed cloud microphysical constituents. They are evaluated for consistency and degree of equivalence with one another, as well as intercompared to radar-retrieved rainfall at TRMM's four main ground validation sites. Similarities and differences are interpreted in the context of the radiative and microphysical assumptions underpinning the algorithms. Results indicate that the current accuracies of the TRMM Version 6 algorithms are approximately 15% at zonal-averaged / monthly scales with precisions of approximately 25% for full resolution / instantaneous rain rate estimates (i.e., level 2 retrievals). Strengths and weaknesses of the TRMM validation approach are summarized. Because the dew of convergence of level 2 TRMM algorithms is being used as a guide for setting validation requirements for the GPM mission, it is important that the GPM algorithm validation program be improved to ensure concomitant improvement in the standard GPM retrieval algorithms. An overview of the GPM Mission's validation plan is provided including a description of a new type of physical validation model using an analytic 3-dimensional radiative transfer model.

Seasonally timed treatment programs for Ascaris lumbricoides to increase impact—An investigation using mathematical models

PubMed Central

Danon, Leon; Prada, Joaquín M.; Gunawardena, Sharmini A.; Truscott, James E.; Vlaminck, Johnny; Anderson, Roy M.; Levecke, Bruno; Morgan, Eric R; Hollingsworth, T. Deirdre

2018-01-01

There is clear empirical evidence that environmental conditions can influence Ascaris spp. free-living stage development and host reinfection, but the impact of these differences on human infections, and interventions to control them, is variable. A new model framework reflecting four key stages of the A. lumbricoides life cycle, incorporating the effects of rainfall and temperature, is used to describe the level of infection in the human population alongside the environmental egg dynamics. Using data from South Korea and Nigeria, we conclude that settings with extreme fluctuations in rainfall or temperature could exhibit strong seasonal transmission patterns that may be partially masked by the longevity of A. lumbricoides infections in hosts; we go on to demonstrate how seasonally timed mass drug administration (MDA) could impact the outcomes of control strategies. For the South Korean setting the results predict a comparative decrease of 74.5% in mean worm days (the number of days the average individual spend infected with worms across a 12 month period) between the best and worst MDA timings after four years of annual treatment. The model found no significant seasonal effect on MDA in the Nigerian setting due to a narrower annual temperature range and no rainfall dependence. Our results suggest that seasonal variation in egg survival and maturation could be exploited to maximise the impact of MDA in certain settings. PMID:29346383

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Ijaz; Spöck, Gunter; Pilz, Jürgen; Yu, Hwa-Lung

2010-08-01

Spatio-temporal estimation of precipitation over a region is essential to the modeling of hydrologic processes for water resources management. The changes of magnitude and space-time heterogeneity of rainfall observations make space-time estimation of precipitation a challenging task. In this paper we propose a Box-Cox transformed hierarchical Bayesian multivariate spatio-temporal interpolation method for the skewed response variable. The proposed method is applied to estimate space-time monthly precipitation in the monsoon periods during 1974-2000, and 27-year monthly average precipitation data are obtained from 51 stations in Pakistan. The results of transformed hierarchical Bayesian multivariate spatio-temporal interpolation are compared to those of non-transformed hierarchical Bayesian interpolation by using cross-validation. The software developed by [11] is used for Bayesian non-stationary multivariate space-time interpolation. It is observed that the transformed hierarchical Bayesian method provides more accuracy than the non-transformed hierarchical Bayesian method.

Recharge estimation in semi-arid karst catchments: Central West Bank, Palestine

NASA Astrophysics Data System (ADS)

Jebreen, Hassan; Wohnlich, Stefan; Wisotzky, Frank; Banning, Andre; Niedermayr, Andrea; Ghanem, Marwan

2018-03-01

Knowledge of groundwater recharge constitutes a valuable tool for sustainable management in karst systems. In this respect, a quantitative evaluation of groundwater recharge can be considered a pre-requisite for the optimal operation of groundwater resources systems, particular for semi-arid areas. This paper demonstrates the processes affecting recharge in Palestine aquifers. The Central Western Catchment is one of the main water supply sources in the West Bank. Quantification of potential recharge rates are estimated using chloride mass balance (CMB) and empirical recharge equations over the catchment. The results showing the spatialized recharge rate, which ranges from 111-216 mm/year, representing 19-37% of the long-term mean annual rainfall. Using Water Balance models and climatological data (e. g. solar radiation, monthly temperature, average monthly relative humidity and precipitation), actual evapotranspiration (AET) is estimated. The mean annual actual evapotranspiration was about 66-70% of precipitation.

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.

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).

Effects of recharge, Upper Floridan aquifer heads, and time scale on simulated ground-water exchange with Lake Starr, a seepage lake in central Florida

USGS Publications Warehouse

Swancar, Amy; Lee, Terrie Mackin

2003-01-01

Lake Starr and other lakes in the mantled karst terrain of Florida's Central Lake District are surrounded by a conductive surficial aquifer system that receives highly variable recharge from rainfall. In addition, downward leakage from these lakes varies as heads in the underlying Upper Floridan aquifer change seasonally and with pumpage. A saturated three-dimensional finite-difference ground-water flow model was used to simulate the effects of recharge, Upper Floridan aquifer heads, and model time scale on ground-water exchange with Lake Starr. The lake was simulated as an active part of the model using high hydraulic conductivity cells. Simulated ground-water flow was compared to net ground-water flow estimated from a rigorously derived water budget for the 2-year period August 1996-July 1998. Calibrating saturated ground-water flow models with monthly stress periods to a monthly lake water budget will result in underpredicting gross inflow to, and leakage from, ridge lakes in Florida. Underprediction of ground-water inflow occurs because recharge stresses and ground-water flow responses during rainy periods are averaged over too long a time period using monthly stress periods. When inflow is underestimated during calibration, leakage also is underestimated because inflow and leakage are correlated if lake stage is maintained over the long term. Underpredicted leakage reduces the implied effect of ground-water withdrawals from the Upper Floridan aquifer on the lake. Calibrating the weekly simulation required accounting for transient responses in the water table near the lake that generated the greater range of net ground-water flow values seen in the weekly water budget. Calibrating to the weekly lake water budget also required increasing the value of annual recharge in the nearshore region well above the initial estimate of 35 percent of the rainfall, and increasing the hydraulic conductivity of the deposits around and beneath the lake. To simulate the total ground-water inflow to lakes, saturated-flow models of lake basins need to account for the potential effects of rapid and efficient recharge in the surficial aquifer system closest to the lake. In this part of the basin, the ability to accurately estimate recharge is crucial because the water table is shallowest and the response time between rainfall and recharge is shortest. Use of the one-dimensional LEACHM model to simulate the effects of the unsaturated zone on the timing and magnitude of recharge in the nearshore improved the simulation of peak values of ground-water inflow to Lake Starr. Results of weekly simulations suggest that weekly recharge can approach the majority of weekly rainfall on the nearshore part of the lake basin. However, even though a weekly simulation with higher recharge in the nearshore was able to reproduce the extremes of ground-water exchange with the lake more accurately, it was not consistently better at predicting net ground-water flow within the water budget error than a simulation with lower recharge. The more subtle effects of rainfall and recharge on ground-water inflow to the lake were more difficult to simulate. The use of variably saturated flow modeling, with time scales that are shorter than weekly and finer spatial discretization, is probably necessary to understand these processes. The basin-wide model of Lake Starr had difficulty simulating the full spectrum of ground-water inflows observed in the water budget because of insufficient information about recharge to ground water, and because of practical limits on spatial and temporal discretization in a model at this scale. In contrast, the saturated flow model appeared to successfully simulate the effects of heads in the Upper Floridan aquifer on water levels and ground-water exchange with the lake at both weekly and monthly stress periods. Most of the variability in lake leakage can be explained by the average vertical head difference between the lake and a re

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.

Real-time adjusting of rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Bareš, Vojtěch

2017-04-01

Urban stormwater predictions require reliable rainfall information with space-time resolution higher than commonly provided by standard rainfall monitoring networks of national weather services. Rainfall data from commercial microwave links (CMLs) could fill this gap. CMLs are line-of-sight radio connections widely used by cellular operators which operate at millimeter bands, where radio waves are attenuated by raindrops. Attenuation data of each single CML in the cellular network can be remotely accessed in (near) real-time with virtually arbitrary sampling frequency and convert to rainfall intensity. Unfortunately, rainfall estimates from CMLs can be substantially biased. Fencl et al., (2017), therefore, proposed adjusting method which enables to correct for this bias. They used rain gauge (RG) data from existing rainfall monitoring networks, which would have otherwise insufficient spatial and temporal resolution for urban rainfall monitoring when used alone without CMLs. In this investigation, we further develop the method to improve its performance in a real-time setting. First, a shortcoming of the original algorithm which delivers unreliable results at the beginning of a rainfall event is overcome by introducing model parameter prior distributions estimated from previous parameter realizations. Second, weights reflecting variance between RGs are introduced into cost function, which is minimized when optimizing model parameters. Finally, RG data used for adjusting are preprocessed by moving average filter. The performance of improved adjusting method is evaluated on four short CMLs (path length < 2 km) located in the small urban catchment (2.3 km2) in Prague-Letnany (CZ). The adjusted CMLs are compared to reference rainfall calculated from six RGs in the catchment. The suggested improvements of the method lead on average to 10% higher Nash-Sutcliffe efficiency coefficient (median value 0.85) for CML adjustment to hourly RG data. Reliability of CML rainfall estimates is especially improved at the beginning of rainfall events and during strong convective rainfalls, whereas performance during longer frontal rainfalls is almost unchanged. Our results clearly demonstrate that adjusting of CMLs to existing RGs represents a viable approach with great potential for real-time applications in stormwater management. This work was supported by the project of Czech Science Foundation (GACR) No.17-16389S. References: Fencl, M., Dohnal, M., Rieckermann, J. and Bareš, V.: Gauge-Adjusted Rainfall Estimates from Commercial Microwave Links, Hydrol Earth Syst. Sci., 2017 (accepted).

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.

The Global Precipitation Climatology Project: First Algorithm Intercomparison Project

NASA Technical Reports Server (NTRS)

Arkin, Phillip A.; Xie, Pingping

1994-01-01

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

Responses of Forest Vegetation to Unusual Drought in Wet Forest in Eastern Puerto Rico: A "Dry Run" for Climate Change?

NASA Astrophysics Data System (ADS)

Zimmerman, J. K.; Hogan, J. A.; Rifkin, S.; Stankavitch, S.

2016-12-01

Droughts occur rarely in wet tropical forests but are predicted to become more frequent under modeled global climate change scenarios. 2015 was unusually dry in northeastern Puerto Rico, resulting from one of the strongest recorded El Niño events in history. We used these long-term measurements to characterize the ecosystem responses to drought focusing on vegetation responses by contrasting the observed patterns from 2015 with patterns from previous decades. Rainfall was measured at El Verde Field Station (EVFS; 350 masl); stream flow was gauged in the nearby Quebrada Sonadora ( 400 m masl), and litterfall was collected in 3 replicate 0.09 ha plots located between 350 - 500 masl ( 1 km from EVFS). Reproductive phenology (120 flower/seed traps) and tree diameter growth (from the 1000 largest trees) were monitored in the 16-ha Luquillo Forest Dynamics Plot (LFDP; 333-428 masl and 0.5-1 km from EVFS). During all of 2015, rainfall was approximately 50% of normal. Departure from the 40-year average of cumulative rainfall was evident by April. Stream flows were well below 25-year average levels by early May and this departure was evident through early November. Litter fall exhibited a strong peak in mid-May followed by reduced inputs until early September, when Tropical Storm Erika brought down additional litter. The peak was 3.5-fold greater than the 12-yr average for May and was associated with large numbers of aborted fruits in seed/flower traps. Diameter increments of trees in the LFDP were 30% reduced in 2015 in contrast to the previous two years. Fall storms brought an end to meteorological drought and, eventually, the hydrological drought. The timing of the 2105 drought mimicked patterns predicted by global circulation models (GCMs), i.e., a much stronger mid-summer drought than has been normally observed (usually no more than a month in duration). The drought was clearly stressful for forest vegetation at this elevation in the Luquillo Mountains. Assuming these conditions become more common as currently predicted by GCMs, these forests would suffer significant alteration of phenology and tree growth at increasing frequency.

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.

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

Potential solar radiation and land cover contributions to digital climate surface modeling

NASA Astrophysics Data System (ADS)

Puig, Pol; Batalla, Meritxell; Pesquer, Lluís; Ninyerola, Miquel

2016-04-01

Overview: We have designed a series of ad-hoc experiments to study the role of factors that a priori have a strong weight in developing digital models of temperature and precipitation, such as solar radiation and land cover. Empirical test beds have been designed to improve climate (mean air temperature and total precipitation) digital models using statistical general techniques (multiple regression) with residual correction (interpolated with inverse weighting distance). Aim: Understand what roles these two factors (solar radiation and land cover) play to incorporate them into the process of generating mapping of temperature and rainfall. Study area: The Iberian Peninsula and supported in this, Catalonia and the Catalan Pyrenees. Data: The dependent variables used in all experiments relate to data from meteorological stations precipitation (PL), mean temperature (MT), average temperature minimum (MN) and maximum average temperature (MX). These data were obtained monthly from the AEMET (Agencia Estatal de Meteorología). Data series of stations covers the period between 1950 to 2010. Methodology: The idea is to design ad hoc, based on a sample of more equitable space statistician, to detect the role of radiation. Based on the influence of solar radiation on the temperature of the air from a quantitative point of view, the difficulty in answering this lies in the fact that there are lots of weather stations located in areas where solar radiation is similar. This suggests that the role of the radiation variable remains "off" when, instead, we intuitively think that would strongly influence the temperature. We have developed a multiple regression analysis between these meteorological variables as the dependent ones (Temperature and rainfall), and some geographical variables: altitude (ALT), latitude (LAT), continentality (CON) and solar radiation (RAD) as the independent ones. In case of the experiment with land covers, we have used the NDVI index as a proxy of land covers and added this variable in to the independents to improve the models. Results: The role of solar radiation does not improve models only under certain conditions and areas, especially in the Pyrennes. The vegetation index NDVI and therefore the land cover on which the station is located, helps improve rainfall and temperature patterns, obtaining various degrees of improvement in terms of molded variables and months.

Radioactive contamination in the Tokyo metropolitan area in the early stage of the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident and its fluctuation over five years

PubMed Central

Yamazaki, Hideo

2017-01-01

Radioactive contamination in the Tokyo metropolitan area in the immediate aftermath of the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident was analyzed via surface soil sampled during a two-month period after the accident. 131I, 134Cs, and 137Cs were detected in these soil samples. The activity and inventory of radioactive material in the eastern part of Tokyo tended to be high. The 134Cs/137Cs activity ratio in soil was 0.978 ± 0.053. The 131I/137Cs ratio fluctuated widely, and was 19.7 ± 9.0 (weighted average 18.71 ± 0.13, n = 14) in the Tokyo metropolitan area. The radioactive plume with high 131I activity spread into the Tokyo metropolitan area and was higher than the weighted average of 6.07 ± 0.04 (n = 26) in other areas. The radiocesium activity and inventory surveyed in soil from a garden in Chiyoda Ward in the center of Tokyo, fell approximately 85% in the four months after the accident, and subsequently tended to rise slightly while fluctuating widely. It is possible that migration and redistribution of radiocesium occurred. The behavior of radiocesium in Tokyo was analyzed via monitoring of radiocesium in sludge incineration ash. The radiocesium activity in the incineration ash was high at wastewater treatment centers that had catchment areas in eastern Tokyo and low at those with catchment areas in western Tokyo. Similar to the case of the garden soil, even in incineration ash, the radiocesium activity dropped rapidly immediately after the accident. The radiocesium activity in the incineration ash fell steadily from the tenth month after the accident until December 2016, and its half-life was about 500 days. According to frequency analysis, in central Tokyo, the cycles of fluctuation of radiocesium activity in incineration ash and rainfall conformed, clearly showing that radiocesium deposited in urban areas was resuspended and transported by rainfall run-off. PMID:29136641

Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system

NASA Astrophysics Data System (ADS)

Segoni, Samuele; Rosi, Ascanio; Lagomarsino, Daniela; Fanti, Riccardo; Casagli, Nicola

2018-03-01

We communicate the results of a preliminary investigation aimed at improving a state-of-the-art RSLEWS (regional-scale landslide early warning system) based on rainfall thresholds by integrating mean soil moisture values averaged over the territorial units of the system. We tested two approaches. The simplest can be easily applied to improve other RSLEWS: it is based on a soil moisture threshold value under which rainfall thresholds are not used because landslides are not expected to occur. Another approach deeply modifies the original RSLEWS: thresholds based on antecedent rainfall accumulated over long periods are substituted with soil moisture thresholds. A back analysis demonstrated that both approaches consistently reduced false alarms, while the second approach reduced missed alarms as well.

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.

Estimates of peak flood discharge for 21 sites in the Front Range in Colorado in response to extreme rainfall in September 2013

USGS Publications Warehouse

Moody, John A.

2016-03-21

Extreme rainfall in September 2013 caused destructive floods in part of the Front Range in Boulder County, Colorado. Erosion from these floods cut roads and isolated mountain communities for several weeks, and large volumes of eroded sediment were deposited downstream, which caused further damage of property and infrastructures. Estimates of peak discharge for these floods and the associated rainfall characteristics will aid land and emergency managers in the future. Several methods (an ensemble) were used to estimate peak discharge at 21 measurement sites, and the ensemble average and standard deviation provided a final estimate of peak discharge and its uncertainty. Because of the substantial erosion and deposition of sediment, an additional estimate of peak discharge was made based on the flow resistance caused by sediment transport effects.Although the synoptic-scale rainfall was extreme (annual exceedance probability greater than 1,000 years, about 450 millimeters in 7 days) for these mountains, the resulting peak discharges were not. Ensemble average peak discharges per unit drainage area (unit peak discharge, [Qu]) for the floods were 1–2 orders of magnitude less than those for the maximum worldwide floods with similar drainage areas and had a wide range of values (0.21–16.2 cubic meters per second per square kilometer [m3 s-1 km-2]). One possible explanation for these differences was that the band of high-accumulation, high-intensity rainfall was narrow (about 50 kilometers wide), oriented nearly perpendicular to the predominant drainage pattern of the mountains, and therefore entire drainage areas were not subjected to the same range of extreme rainfall. A linear relation (coefficient of determination [R2]=0.69) between Qu and the rainfall intensity (ITc, computed for a time interval equal to the time-of-concentration for the drainage area upstream from each site), had the form: Qu=0.26(ITc-8.6), where the coefficient 0.26 can be considered to be an area-averaged peak runoff coefficient for the September 2013 rain storms in Boulder County, and the 8.6 millimeters per hour to be the rainfall intensity corresponding to a soil moisture threshold that controls the soil infiltration rate. Peak discharge estimates based on the sediment transport effects were generally less than the ensemble average and indicated that sediment transport may be a mechanism that limits velocities in these types of mountain streams such that the Froude number fluctuates about 1 suggesting that this type of floodflow can be approximated as critical flow.

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.

A Web Architecture to Geographically Interrogate CHIRPS Rainfall and eMODIS NDVI for Land Use Change

NASA Technical Reports Server (NTRS)

Burks, Jason E.; Limaye, Ashutosh

2014-01-01

Monitoring of rainfall and vegetation over the continent of Africa is important for assessing the status of crop health and agriculture, along with long-term changes in land use change. These issues can be addressed through examination of long-term precipitation (rainfall) data sets and remote sensing of land surface vegetation and land use types. Two products have been used previously to address these goals: the Climate Hazard Group Infrared Precipitation with Stations (CHIRPS) rainfall data, and multi-day composites of Normalized Difference Vegetation Index (NDVI) from the USGS eMODIS product. Combined, these are very large data sets that require unique tools and architecture to facilitate a variety of data analysis methods or data exploration by the end user community. To address these needs, a web-enabled system has been developed to allow end-users to interrogate CHIRPS rainfall and eMODIS NDVI data over the continent of Africa. The architecture allows end-users to use custom defined geometries, or the use of predefined political boundaries in their interrogation of the data. The massive amount of data interrogated by the system allows the end-users with only a web browser to extract vital information in order to investigate land use change and its causes. The system can be used to generate daily, monthly and yearly averages over a geographical area and range of dates of interest to the user. It also provides analysis of trends in precipitation or vegetation change for times of interest. The data provided back to the end-user is displayed in graphical form and can be exported for use in other, external tools. The development of this tool has significantly decreased the investment and requirements for end-users to use these two important datasets, while also allowing the flexibility to the end-user to limit the search to the area of interest.

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%.

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.

The population density of Lymnaea columella (Say, 1817) (Mollusca, Lymnaeidae) an intermediate host of Fasciola hepatica (Linnaeus, 1758), in the Caparaó microregion, ES, Brazil.

PubMed

D'Almeida, S C G; Freitas, D F; Carneiro, M B; Camargo, P F; Azevedo, J C; Martins, I V F

2016-06-01

The aim of this study was to monitor the population density of Lymnaea columella, an intermediate host of Fasciola hepatica, in various aquatic habitats and in drinking water in the area of the Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo, on Caparaó Microregion, municipality of Alegre, state of Espírito Santo, Brazil. Monthly samplings were performed at certain points between drainage areas and drinking water in cattle and goat production systems during the years 2010 to 2013. The mean temperature, precipitation and the frequency of samples of L. columella were analysed graphically according the monthly average during the study period. A total of 2,038 molluscs were collected, 1558 of which were L. columella, that predominated in all sampled points. The highest average of specimens observed for L. columella was in the years 2010 and 2013 (51.0), and occurred decreased in 2011 (19.8). The temperature and precipitation averaged is 23.7 °C and 141 mm/year, respectively. Rainfall peak occurred in March (2011, 2013) and November (2012), during these periods the population of L. columella growth. There was no significant difference in the relationship between the specimens observed with seasons (dry-wet), thus the population of L. columella remained stable and can be found throughout the year.

An Experimental Study of Small-Scale Variability of Raindrop Size Distribution

NASA Technical Reports Server (NTRS)

Tokay, Ali; Bashor, Paul G.

2010-01-01

An experimental study of small-scale variability of raindrop size distributions (DSDs) has been carried out at Wallops Island, Virginia. Three Joss-Waldvogel disdrometers were operated at a distance of 0.65, 1.05, and 1.70 km in a nearly straight line. The main purpose of the study was to examine the variability of DSDs and its integral parameters of liquid water content, rainfall, and reflectivity within a 2-km array: a typical size of Cartesian radar pixel. The composite DSD of rain events showed very good agreement among the disdrometers except where there were noticeable differences in midsize and large drops in a few events. For consideration of partial beam filling where the radar pixel was not completely covered by rain, a single disdrometer reported just over 10% more rainy minutes than the rainy minutes when all three disdrometers reported rainfall. Similarly two out of three disdrometers reported5%more rainy minutes than when all three were reporting rainfall. These percentages were based on a 1-min average, and were less for longer averaging periods. Considering only the minutes when all three disdrometers were reporting rainfall, just over one quarter of the observations showed an increase in the difference in rainfall with distance. This finding was based on a 15-min average and was even less for shorter averaging periods. The probability and cumulative distributions of a gamma-fitted DSD and integral rain parameters between the three disdrometers had a very good agreement and no major variability. This was mainly due to the high percentage of light stratiform rain and to the number of storms that traveled along the track of the disdrometers. At a fixed time step, however, both DSDs and integral rain parameters showed substantial variability. The standard deviation (SD) of rain rate was near 3 mm/h, while the SD of reflectivity exceeded 3 dBZ at the longest separation distance. These standard deviations were at 6-min average and were higher at shorter averaging periods. The correlations decreased with increasing separation distance. For rain rate, the correlations were higher than previous gauge-based studies. This was attributed to the differences in data processing and the difference in rainfall characteristics in different climate regions. It was also considered that the gauge sampling errors could be a factor. In this regard, gauge measurements were simulated employing existing disdrometer dataset. While a difference was noticed in cumulative distribution of rain occurrence between the simulated gauge and disdrometer observations, the correlations in simulated gauge measurements did not differ from the disdrometer measurements.

Rain fall data for the design of sewer pipe systems

NASA Astrophysics Data System (ADS)

Arnell, V.

1982-03-01

A comparison of designs of sewer pipes for different types of rainfall data is presented. Local coefficients were evaluated from an 18-year historical rainfall record for the following design storms: The Average-Intensity-Duration Design Storm, The Chicago Design Storm, The Sifalda Design Storm, The Illinois State Water Survey Design Storm, and The Flood Studies Report Design Storm. Historical rainfalls as well as the above design storms were used for the calculations of peak-flow values.

[Characteristics of Nitrogen and Phosphorus Losses in Longhong Ravine Basin of Westlake in Rainstorm Runoff].

PubMed

Yang, Fan; Jiang, Yi-feng; Wang, Cui-cui; Huang, Xiao-nan; Wu, Zhi-ying; Chen, Lin

2016-01-15

In order to understand the non-point source pollution status in Longhong ravine basin of Westlake, the characteristics of nutrient losses in runoff was investigated during three rainstorms in one year. The results showed that long duration rainstorm event generally formed several runoff peaks, and the time of its lag behind the peaks of rain intensity was dependent on the distribution of heavy rainfall. The first flush was related to the antecedent rainfall, and the less rainfall in the earlier period, the more total phosphorus (TP) and ammonia (NH4+ -N) in runoff was washed off. During the recession of runoff, more subsurface runoff would result in a concentration peak of total nitrogen (TN) and nitrogen (NO3- -N) . The event mean concentration (EMC) of runoff nitrogen had a negative correlation with rainfall, rainfall duration, maximum rain intensity and average rain intensity except for antecedent rainfall, whereas the change in TP EMC showed the opposite trend. The transport fluxes of nutrients increased with an elevation in runoffs, and Pearson analysis showed that the transport fluxes of TN and NO3- -N had good correlations with runoff depth. The average transport fluxes of TP, TN, NH4+ -N and NO3- -N were 34.10, 1195.55, 1006.62 and 52.38 g x hm(-2), respectively, and NO3- -N was the main nitrogen form and accounted for 84% of TN.

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia

PubMed Central

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S.; McMichael, Anthony J.; Dale, Pat; Tong, Shilu

2006-01-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention. PMID:16675420

Soil Erosion Risk Map based on irregularity of the vegetative activity

NASA Astrophysics Data System (ADS)

Saa-Requejo, Antonio; Tarquis, Ana Maria; Martín-Sotoca, Juan J.; Valencia, Jose L.; Gobin, Anne; Rodriguez-Sinobas, Leonor

2016-04-01

Because of the difficulties to build on both daily rainfall and base shorter time, we explored the possibilities of building indexes based on land cover, which also provide us the opportunity to evaluate their evolution over time. We consider the Fournier index (Fournier, 1960) which is used to assess the rainfall erosivity based on monthly rainfall, alternatively to use of the rainfall intensity in time bases under one hour (eg., van der Knijff et al., 1999; Shamshad et al, 2008). This index can also be interpreted as an index of irregularity and representing a ratio between maximum monthly precipitation and annual rainfall. We propose to calculate this irregularity in terms of irregularity of the vegetative activity. This activity is related to precipitation, but also with the availability of water in the soil reservoir and land use. Therefore, we propose a kind of Fournier index on the effective use of water, which is also closely related to variations in infiltration. Higher is the presence of vegetation higher is the effective use of water. For this "modified Fourier index" we used the NDVI (Normalized Difference Vegetation Index) as index of available vegetative activity, which is widely reported in the literature (Jensen, 2000). Initial calculations have been done with MODIS 500 x 500 m satellite data. The selected area was Cega-Eresma-Adaja subbasin during the period from 2009 to 2012. We selected 8 days composite images product. The calculation of the valid values to eliminate areas with clouds or snow is performed according to the criteria of Martinez Sotoca (2014), ie with a Saturation (based on HSL color model) greater or equal to 0.15. Then, an average of these values was estimated to represent each month of the year. The results are very interesting when we compare Modified Fournier Index on NDVIs with the map of potential soil loss. We have found surprisingly similar patterns and practical equivalence between several classes. Therefore, the Modified Fournier Index on NDVI values seems to synthesize the different parameters of the USLE, referring to rainfall, soil, geomorphology and vegetation cover. Acknowledgements Authors are grateful to TALE project (CICYT PCIN-2014-080) and DURERO project (Env.C1.3913442) for their financial support. References Fournier, F. (1960), Climat et erosion. P.U.F. Paris. Jensen, J.R. (2000). Remote Sensing of the Environment: An Earth Resource Perpective, Prentice Hall, New Jersey. Martínez Sotoca, J. J. (2014) estructura espacial de la sequía en pastos y sus aplicaciones en el seguro agrario indexado. (In Spanish) Master Thesis, UPM. Shamshad, A., Azhari M.N., Isaac, M.H., wan Hussin, W.M.A., Parida, B.P.. (2008). Development of an appropriate procedure for estimation of RUSLE EI30 index and preparation of erosivity maps for Pulau Penang in Peninsular Malaysia. Catena, 72, 423-432. van der Knijff, J.M., Jones, R.J.A., Montanarella, L. (1999). Soil Erosion Risk Assessment Italy Soil Erosion Risk Assessment in Italy. European Commission Soil Bureau Joint Research Centre European Commission. EUR 19022EN.

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.

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.

Ensemble climate projections of mean and extreme rainfall over Vietnam

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

The evaluation of rainfall influence on combined sewer overflows characteristics: the Berlin case study.

PubMed

Sandoval, S; Torres, A; Pawlowsky-Reusing, E; Riechel, M; Caradot, N

2013-01-01

The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSOs), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of partial least squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main influences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutant concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutant loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R² < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.

Assessment of Rainfall-induced Landslide Potential and Spatial Distribution

NASA Astrophysics Data System (ADS)

Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Chiang, Jie-Lun; Hsieh, Shun-Chieh; Chue, Yung-Sheng

2016-04-01

Recently, due to the global climate change, most of the time the rainfall in Taiwan is of short duration but with high intensity. Due to Taiwan's steep terrain, rainfall-induced landslides often occur and lead to human causalities and properties loss. Taiwan's government has invested huge reconstruction funds to the affected areas. However, after rehabilitation they still face the risk of secondary sediment disasters. Therefore, this study assesses rainfall-induced (secondary) landslide potential and spatial distribution in watershed of Southern Taiwan under extreme climate change. The study areas in this research are Baolai and Jianshan villages in the watershed of the Laonongxi River Basin in the Southern Taiwan. This study focused on the 3 years after Typhoon Morakot (2009 to 2011). During this period, the study area experienced six heavy rainfall events including five typhoons and one heavy rainfall. The genetic adaptive neural network, texture analysis and GIS were implemented in the analysis techniques for the interpretation of satellite images and to obtain surface information and hazard log data and to analyze land use change. A multivariate hazards evaluation method was applied to quantitatively analyze the weights of various natural environmental and slope development hazard factors. Furthermore, this study established a slope landslide potential assessment model and depicted a slope landslide potential diagram by using the GIS platform. The interaction between (secondary) landslide mechanism, scale, and location was analyzed using association analysis of landslide historical data and regional environmental characteristics. The results of image classification before and after six heavy rainfall events show that the values of coefficient of agreement are at medium-high level. By multivariate hazards evaluation method, geology and the effective accumulative rainfall (EAR) are the most important factors. Slope, distance from fault, aspect, land disturbance, and elevation are the secondary important factors. Under the different rainfall, the greater the average of EAR, the more the landslide occurrence and area increments. The determination coefficients of trend lines on the charts of the average of EAR versus number and area of landslide increment are 0.83 and 0.92, respectively. The relations between landslide potential level, degree of land disturbance, and the ratio of number and area of landslide increment corresponding six heavy rainfall events are positive and the determination coefficients of trend lines are 0.82 and 0.72, respectively. The relation between the average of EAR and the area of landslide increment corresponding five heavy rainfall events (excluding Morakot) is positive and the determination coefficient of trend line is 0.98. Furthermore, the relation between the area increment of secondary landslide, average of EAR or the slope disturbance is positive. Under the same slope disturbance, the greater the EAR, the more the area increment of secondary landslide. Contrarily, under the same EAR, the greater the slope disturbance, the more the area increment of secondary landslide. The results of the analysis of this study can be a reference for the government for subsequent countermeasures for slope sediment disaster sensitive area to reduce the number of casualties and significantly reduce the social cost of post-disaster.

Climate and ET: Does Plant Water Requirements Increase during Droughts?

NASA Astrophysics Data System (ADS)

Fipps, G.

2015-12-01

Municipalities, engineering consultants and State agencies use reference evapotranspiration (ETo) data (directly and indirectly) for long-term water planning, for designing hydraulic structures, and for establishing regulatory guidance and conservation programs intended to reduce water waste. The use ETo data for agricultural and landscape irrigation scheduling is becoming more common in Texas as ETo-based controllers and automation technologies become more affordable. Until recently, most ETo data has been available as monthly values averaged over many years. Today, automated weather stations and irrigation controllers equipped with specialized instrumentation allow for real-time ETo measurements. With the expected rise in global warming and increased frequency of extreme climate variability in the coming decades, conservation and efficient use of water resources is essential and must make use of the most accurate and representative data available. 2011 marked the driest year on record in the State of Texas. Compounding the lack of rainfall was record heat during the Summer of 2011. An analysis of real time ETo (reference evapotranspiration) data in Texas found that ET was 30 to 50% higher than historic averages during the 2011 Summer. The implications are quite serious, as most current water planning and drought contingency plans do not take into consideration increases in ET during such periods, and irrigation planning and capacity sizing are based on historic averages of consumptive use. This paper examines the relationship between ET and climate during this extreme climatic event. While the solar radiation was near normal levels, temperature and wind was much higher and dew points much lower than norms. The variability and statistical difference between average monthly ETo data and daily, monthly and seasonal ETo measurements (from 2006 to 2014) for selected weather stations of the Texas ET Network. This study will also examine the suitability of using average ETo rates for use in regional water planning and in irrigation scheduling.

Exploring the new long-term (150 years) precipitation dataset in Azores archipelago

NASA Astrophysics Data System (ADS)

Hernández, Armand; Trigo, Ricardo M.; Kutiel, Haim; Valente, Maria A.; Sigró, Javier

2015-04-01

Within the scope of the two major international projects of long-term reanalysis for the 20th century coordinated by NOAA (Compo et al. 2011) and ECMWF (Hersbach et al. 2013) the IDL Institute from the University of Lisbon has digitized a large number of long-term stations records from Portugal and former Portuguese Colonies (Stickler et al. 2014). Recently we have finished the digitization of all precipitation values from Ponta Delgada (capital of the Azores archipelago) obtaining an uninterrupted precipitation monthly time series since 1864 and additionally an almost complete corresponding daily precipitation series, with the exception of some years (1864/1872; 1878/1879; 1888/1905; 1931; 1936 and 1938) for which only monthly values are available. Here, we present an annually, seasonally and daily resolution study of the rainfall regime in Ponta Delgada for the last 150 years and the North Atlantic Oscillation (NAO) influence over this precipitation regime. The distribution of precipitation presents an evident seasonal pattern, with a strong difference between the 'rainy season' (November/March) and the 'dry season' (June/August) with very little rainfall. April/May and September/October correspond to the transitional seasons. The mean annual rainfall in Ponta Delgada is approximately 910 mm and is accumulated (on average) in about 120 rainy days. The precipitation regime in Azores archipelago reveals large inter-annual and intra-annual variability and both have increased considerably in the last decades. The entire studied period (1865-2012) shows an increase in the rainfall conditions between a drier earlier period (1865-1938) and a wetter recent period (1939-2012). At daily resolution, we have used an approach based on different characteristics of rain spells (consecutive days with rainfall accumulation) that has been proved to be satisfactory for the analysis of the different parameters related to the rainfall regime (Kutiel and Trigo, 2014). This approach shows that the increase in precipitation is mainly due to more intense events which are reflected by higher rain spell yields (amount of precipitation) and rain spell intensity (amount of precipitation by day) values in the last decades. On the other hand, despite the fact that one of the most widely used NAO definitions includes sea level pressure from the Ponta Delgada station, its long-term impact on the Azores archipelago climate is not well established yet. Here, we assessed the NAO influence over the precipitation regime according to Spearman's rank correlation coefficients. Results show that the inter-annual variability of precipitation is largely modulated by the NAO mode. Correlation values of r=-0.90, r=-0.79 and r=-0.63 were obtained for years with positive (>1) or negative (

Spatially distributed groundwater recharge estimated using a water-budget model for the Island of Maui, Hawai`i, 1978–2007

USGS Publications Warehouse

Johnson, Adam G.; Engott, John A.; Bassiouni, Maoya; Rotzoll, Kolja

2014-12-14

Demand for freshwater on the Island of Maui is expected to grow. To evaluate the availability of fresh groundwater, estimates of groundwater recharge are needed. A water-budget model with a daily computation interval was developed and used to estimate the spatial distribution of recharge on Maui for average climate conditions (1978–2007 rainfall and 2010 land cover) and for drought conditions (1998–2002 rainfall and 2010 land cover). For average climate conditions, mean annual recharge for Maui is about 1,309 million gallons per day, or about 44 percent of precipitation (rainfall and fog interception). Recharge for average climate conditions is about 39 percent of total water inflow consisting of precipitation, irrigation, septic leachate, and seepage from reservoirs and cesspools. Most recharge occurs on the wet, windward slopes of Haleakalā and on the wet, uplands of West Maui Mountain. Dry, coastal areas generally have low recharge. In the dry isthmus, however, irrigated fields have greater recharge than nearby unirrigated areas. For drought conditions, mean annual recharge for Maui is about 1,010 million gallons per day, which is 23 percent less than recharge for average climate conditions. For individual aquifer-system areas used for groundwater management, recharge for drought conditions is about 8 to 51 percent less than recharge for average climate conditions. The spatial distribution of rainfall is the primary factor determining spatially distributed recharge estimates for most areas on Maui. In wet areas, recharge estimates are also sensitive to water-budget parameters that are related to runoff, fog interception, and forest-canopy evaporation. In dry areas, recharge estimates are most sensitive to irrigated crop areas and parameters related to evapotranspiration.

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.

Application and Evaluation of a Snowmelt Runoff Model in the Tamor River Basin, Eastern Himalaya Using a Markov Chain Monte Carlo (MCMC) Data Assimilation Approach

NASA Technical Reports Server (NTRS)

Panday, Prajjwal K.; Williams, Christopher A.; Frey, Karen E.; Brown, Molly E.

2013-01-01

Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree-day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash-Sutcliffe metric approx. 0.84, annual volume bias <3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002-2006 period is estimated to be 29.7+/-2.9% (which includes 4.2+/-0.9% from snowfall that promptly melts), whereas 70.3+/-2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000-5500m range contributes the most to basin runoff, averaging 56.9+/-3.6% of all snowmelt input and 28.9+/-1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree-day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds.

A Stochastic Model of Space-Time Variability of Mesoscale Rainfall: Statistics of Spatial Averages

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, Thomas L.

2003-01-01

A characteristic feature of rainfall statistics is that they depend on the space and time scales over which rain data are averaged. A previously developed spectral model of rain statistics that is designed to capture this property, predicts power law scaling behavior for the second moment statistics of area-averaged rain rate on the averaging length scale L as L right arrow 0. In the present work a more efficient method of estimating the model parameters is presented, and used to fit the model to the statistics of area-averaged rain rate derived from gridded radar precipitation data from TOGA COARE. Statistical properties of the data and the model predictions are compared over a wide range of averaging scales. An extension of the spectral model scaling relations to describe the dependence of the average fraction of grid boxes within an area containing nonzero rain (the "rainy area fraction") on the grid scale L is also explored.

Chemical quality of water in abandoned zinc mines in northeastern Oklahoma and southeastern Kansas

USGS Publications Warehouse

Playton, Stephen J.; Davis, Robert Ellis; McClaflin, Roger G.

1978-01-01

Onsite measurements of pH, specific conductance, and water temperature show that water temperatures in seven mine shafts in northeastern Oklahoma and southeastern Kansas is stratified. With increasing sampling depth, specific conductance and water temperature tend to increase, and pH tends to decrease. Concentrations of dissolved solids and chemical constituents in mine-shaft water, such as total, and dissolved metals and dissolved sulfate also increase with depth. The apparently unstable condition created by cooler, denser water overlying warmer, less-dense water is offset by the greater density of the lower water strata due to higher dissolved solids content.Correlation analysis showed that several chemical constituents and properties of mine-shaft water, including dissolved solids, total hardness, and dissolved sulfate, calcium, magnesium, and lithium, are linearly related to specific conductance. None of the constituents or properties of mine-shaft water tested had a significant linear relationship to pH. However, when values of dissolved aluminum, zinc, and nickel were transformed to natural or Napierian logarithms, significant linear correlation to pH resulted. During the course of the study - September 1975 to June 1977 - the water level in a well penetrating the mine workings rose at an average rate of 1.2 feet per month.  Usually, the rate of water-level rise was greater than average after periods of relatively high rainfall, and lower than average during periods of relatively low rainfall.Water in the mine shafts is unsuited for most uses without treatment.  The inability of current domestic water treatment practices to remove high concentrations of toxic metals, such as cadmium and lead, precludes use of the water for a public supply.

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.

Water withdrawals, wastewater discharge, and water consumption in the Apalachicola-Chattahoochee-Flint River Basin, 2005, and water-use trends, 1970-2005

USGS Publications Warehouse

Marella, Richard L.; Fanning, Julia L.

2011-01-01

In 2000, an estimated 49 percent of the water withdrawn for public supply in the basin was consumed, and the remaining 51 percent was returned to the hydrologic system through wastewater treatment systems. In 2005, an estimated 38 percent was consumed and 62 percent was returned to the hydrologic system. This contrast between water withdrawals and wastewater discharges for these years was caused primarily by below-average rainfall during 2000 (a dry year) and above-average rainfall during 2005 (a wet year).

Detecting Climate Variability in Tropical Rainfall

NASA Astrophysics Data System (ADS)

Berg, W.

2004-05-01

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

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.

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.

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.

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.

Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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.

Interannual Rainfall Variability in the Tropical Atlantic Region

NASA Technical Reports Server (NTRS)

Gu, Guojun

2005-01-01

Rainfall variability on seasonal and interannual-to-interdecadal time scales in the tropical Atlantic is quantified using a 25-year (1979-2003) monthly rainfall dataset from the Global Precipitation Climatology Project (GPCP). The ITCZ measured by monthly rainfall between 15-37.5 deg W attains its peak as moving to the northernmost latitude (4-10 deg N) during July-September in which the most total rainfall is observed in the tropical Atlantic basin (17.5 deg S-22.5 deg N, 15 deg-37.5 deg W); the ITCZ becomes weakest during January-February with the least total rainfall as it moves to the south. In contrast, rainfall variability on interannual to interdecadal time scales shows a quite different seasonal preference. The most intense interannual variability occurs during March-May when the ITCZ tends to be near the equator and becomes weaker. Significant, negative correlations between the ITCZ strength and latitude anomalies are observed during boreal spring and early summer. The ITCZ strength and total rainfall amount in the tropical Atlantic basin are significantly modulated by the Pacific El Nino and the Atlantic equatorial mode (or Atlantic Nino) particularly during boreal spring and summer; whereas the impact of the Atlantic interhemispheric mode is considerably weaker. Regarding the anomalous latitudes of the ITCZ, the influence can come from both local, i.e., the Atlantic interhemispheric and equatorial modes, and remote forcings, i. e., El Nino; however, a direct impact of El Nino on the latitudes of the ITCZ can only be found during April-July, not in winter and early spring in which the warmest SST anomalies are usually observed in the equatorial Pacific.

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.

Analyzing remotely sensed datasets for improved characterization of field-scale interventions for food security

NASA Astrophysics Data System (ADS)

Limaye, A. S.; Ellenburg, W. L., II; Coffee, K.; Ashmall, W.; Stanton, K.; Burks, J.; Irwin, D.

2017-12-01

Agriculture interventions such as irrigation, improved fertilization, and advanced cultivars have the potential to increase food security and ensure climate resilience. However, in order broaden the support of activities like these, environmental managers must be able to assess their impact. Often field data are difficult to obtain and decisions are made with limited information. Satellite products can provide relevant information at field and village wide scales that can assist in this process. SERVIR is taking an aim of helping connect the space-based products to help the efficacy of village scale interventions through a couple of web-based tools, called ClimateSERV and AgriSERV. ClimateSERV has been active since 2014, and has increased in the data holdings and access points. Currently, ClimateSERV enables users to create geographic regions of their choosing and to compute key statistics for those regions. Rainfall (GPM IMERG, CHIRPS), vegetation indices (eMODIS Normalized Difference Vegetation Index - NDVI; Evaporative Stress Index), and North American Multi-model Ensemble-based seasonal climate forecasts of rainfall and temperature. ClimateSERV can also query the Google Earth Engine holdings for datasets, currently, ClimateSERV provides access to the daytime MODIS Land Surface Temperature (LST). Our first such derived product is a monthly rainfall analysis feature which combines CHIRPS historic rainfall with seasonal forecast models AgriSERV is a derived web-based tool based on the ClimateSERV data holdings. It is designed to provide easy to interpret analysis, based NDVI and rainfall. This tool allows users to draw two areas of interest, one control with no intervention and another that has experienced intervention. An on-demand comparative analysis is performed and the user is presented with side-by-side charts and summary data that highlight the differences of the two areas in terms of vegetation health, derived growing season lengths and rainfall. The analysis is based on an area-weighted average of the gridded NDVI and rainfall data. The users can download the summary data table as well as the full dataset for the period specified. This presentation is intended to showcase the utility of the intervention programs and to provide an objective rationale for expansion of those intervention programs.

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.

Bioclimatic changes and landslide recurrence in the mountainous region of Rio de Janeiro: are we ready to face the next landslide disaster?

NASA Astrophysics Data System (ADS)

Luiza Coelho Netto, Ana; Facadio, Ana Carolina; Pereira, Roberta; Lima, Pedro Henrique

2017-04-01

Paleo-environmental studies point out an alternation of wet and dry periods during the Holocene in southeastern Brazil, marked by the expansion and retraction of the humid tropical rainforest in alternation with the campos de altitude vegetation ('high altitude grassland'); successive episodes of natural fire were recorded from 10,000 to 4,000 years BP in the mountainous region of SE-Brazil, reflecting warm-dry conditions. Present seasonal climatic variability is indicated by an increasing dry spell frequency throughout the XX and early XXI centuries together with an increasing rainfall concentration in the summer when extreme daily totals (above 100 mm) become progressively more frequent. Historical land use changes, at both regional and local scales, are mostly related to this climatic variability. Therefore extreme rainfall induced landslides have been responsible for severe disasters as recorded along the Atlantic slopes of Serra do Mar. The extreme one occurred in January 2011, affecting the municipalities of Nova Friburgo, Teresópolis and Petrópolis. Studies in Nova Friburgo shown the occurrence of 3.622 landslides scars within an area of 421 km2; this rainfall event reached the expected average monthly rainfall (300 mm) in less than 10 hours. The D'Antas creek basin (53 km2) was the most affected area by landslides; 86% of 326 scars where associated with shallow translational mechanisms among which 67% occurred within shallow concave up topographic hollows of 32° slope angle in average. Most of these landslide scars occurred in granite rocks and degraded vegetation due to historical land use changes (last 200 years) including secondary forest (64%) and grasslands (25%). The present-day association between extreme rainfall induced landslides and human induced vegetation changes seem to reflect similar geomorphic responses to natural Holocene bioclimatic changes; a common phenomenon between the two periods is fire (natural fire in the past time and man-induced fire nowadays). Despite all field evidences on the relevance of landslides on hillslope evolution in the mountainous domain, local communities at risk and governmental institutions are not yet ready to face the next extreme rain event. Since November 2014 a new governance and risk management model has been developed in the Córrego D'Antas basin, through a multi-institutional network integrating local communities, university and governmental institutions as will be presented in this paper.

Metals and polybrominated diphenyl ethers leaching from electronic waste in simulated landfills.

PubMed

Kiddee, Peeranart; Naidu, Ravi; Wong, Ming H

2013-05-15

Landfills established prior to the recognition of potential impacts from the leaching of heavy metals and toxic organic compounds often lack appropriate barriers and pose significant risks of contamination of groundwater. In this study, bioavailable metal(oids) and polybrominated diphenyl ethers (PBDEs) in leachates from landfill columns that contained intact or broken e-waste were studied under conditions that simulate landfills in terms of waste components and methods of disposal of e-wastes, and with realistic rainfall. Fourteen elements and PBDEs were analysed in leachates over a period of 21 months. The results demonstrate that the average concentrations of Al, Ba, Be, Cd, Co, Cr, Cu, Ni, Pb, Sb and V in leachates from the column that contained broken e-waste items were significantly higher than the column without e-waste. BDE-153 was the highest average PBDEs congener in all columns but the average of ∑PBDEs levels in columns that contained intact e-waste were (3.7 ng/l) and were not significantly higher than that in the leachates from the control column. Copyright © 2013 Elsevier B.V. All rights reserved.

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...

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

USGS Publications Warehouse

Torikai, J.D.

1996-01-01

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 December 1995, although the report focuses on hydrologic events from October through December 1995 (fourth quarter of 1995). Cumulative rainfall for October through December 1995 was about 41 inches, which is 32 percent more than the mean cumulative rainfall of about 31 inches for October through December. The period October through December is within the annual wet season. Mean cumulative rainfall is calculated for the fixed base period 1951-90. Ground-water withdrawal during October through December 1995 averaged 931,000 gallons per day. Withdrawal for the same 3 months in 1994 averaged 902,900 gallons per day. Patterns of withdrawal during the fourth quarter of 1995 did not change significantly since 1993 at all five ground-water production areas. At the end of December 1995, the chloride concentration of the composite water supply was 60 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 1995 ranged between 28 and 67 milligrams per liter. Chloride concentration of ground water in monitoring wells at Cantonment and Air Operations continued to decrease during the fourth quarter of 1995, with water from the deepest monitoring wells decreasing in chloride concentration by as much as 2,000 milligrams per liter. This trend follows increases in chloride concentration during the first half of 1995. 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 divert fuel migration away from water-supply wells by recirculating about 150,000 gallons of water each day.

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

USGS Publications Warehouse

Torikai, J.D.

1996-01-01

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 September 1995, although the report focuses on hydrologic events from July through September 1995. Cumulative rainfall for July through September 1995 was about 15 inches which is 32 percent less than the mean cumulative rainfall of about 22 inches for July through September. July and August are within the annual dry season, while September is the start of the annual wet season. Mean cumulative rainfall is calculated for the fixed base period 1951-90. Ground-water withdrawal during July through September 1995 averaged 888,500 gallons per day. Withdrawal for the same 3 months in 1994 averaged 919,400 gallons per day. Patterns of withdrawal during the third quarter of 1995 did not change significantly since 1993 at all five ground-water production areas. At the end of September 1995, the chloride concentration of the composite water supply was 51 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 1995 ranged between 42 and 68 milligrams per liter. Chloride concentration of ground water in monitoring wells at Cantonment and Air Operations continued to increase since April 1995, with water from the deepest monitoring wells increasing in chloride concentration by as much as 2,000 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 divert fuel migration away from water-supply wells by recirculating about 150,000 gallons of water each day.

Ozone and TFA impacts in North America from degradation of 2,3,3,3-Tetrafluoropropene (HFO-1234yf), a potential greenhouse gas replacement.

PubMed

Luecken, Deborah J; L Waterland, Robert; Papasavva, Stella; Taddonio, Kristen N; Hutzell, William T; Rugh, John P; Andersen, Stephen O

2010-01-01

We use a regional-scale, three-dimensional atmospheric model to evaluate U.S. air quality effects that would result from replacing HFC-134a in automobile air conditioners in the U.S. with HFO-1234yf. Although HFO-1234yf produces tropospheric ozone, the incremental amount is small, averaging less than 0.01% of total ozone formed during the simulation. We show that this production of ozone could be compensated for by a modest improvement in air conditioner efficiency. Atmospheric decomposition of HFO-1234yf produces trifluoroacetic acid (TFA), which is subject to wet and dry deposition. Deposition and concentrations of TFA are spatially variable due to HFO-1234yf's short atmospheric lifetime, with more localized peaks and less global transport when compared to HFC-134a. Over the 2.5 month simulation, deposition of TFA in the continental U.S. from mobile air conditioners averages 0.24 kg km(-2), substantially higher than previous estimates from all sources of current hydrofluorocarbons. Automobile air conditioning HFO-1234yf emissions are predicted to produce concentrations of TFA in Eastern U.S. rainfall at least double the values currently observed from all sources, natural and man-made. Our model predicts peak concentrations in rainfall of 1264 ng L(-1), a level that is 80x lower than the lowest level considered safe for the most sensitive aquatic organisms.

Life history of the striped newt at a north-central Florida breeding pond

USGS Publications Warehouse

Johnson, S.A.

2002-01-01

I studied the life history of Striped Newts (Notophthalmus perstriatus) at a breeding pond in north-central Florida. Newts were captured in pitfall traps at a drift-fence as they migrated into and out of the pond basin. During the 2-year study, I recorded 10,290 captures (8,127 individuals) of newts at the drift-fence. Newts were active during each month of the study, but there were four peak activity periods, each of which included immigration and emigration events. Immigration events were almost exclusively comprised of adults, whereas emigration events were comprised of adults and recently transformed larvae. I documented 5,296 recently transformed, immature larvae (efts) and 435 recently transformed mature larvae (paedomorphs) during four distinct periods of emigration. Efts matured in the uplands before returning to the pond to breed. In the uplands, male efts (n = 16) grew 0.0183 mm/day on average, whereas average female (n = 24) growth was 0.0167 mm/day. Immigrating adults of both sexes were significantly smaller than emigrating adults. Emigrating efts were smallest, followed by emigrating paedomorphs, immigrating adults, then emigrating adults. The overall adult sex ratio was 1:1.25 (m:f). Sex ratio of emigrating paedomorphs was highly skewed towards females, with one male for every 4.43 females. Newts tended to move during wetter periods, and captures were significantly correlated with rainfall, but rainfall was a poor predictor of the magnitude of newt movements.

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.

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.

Hydrologic conditions and quality of rainfall and storm runoff for two agricultural areas of the Oso Creek Watershed, Nueces County, Texas, 2005-07

USGS Publications Warehouse

Ockerman, Darwin J.

2008-01-01

The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board, Coastal Bend Bays and Estuaries Program, and Texas AgriLife Research and Extension Center at Corpus Christi, studied hydrologic conditions and quality of rainfall and storm runoff of two (primarily) agricultural areas (subwatersheds) of the Oso Creek watershed in Nueces County, Texas. One area, the upper West Oso Creek subwatershed, is 5,145 acres. The other area, a subwatershed drained by an unnamed Oso Creek tributary (hereinafter, Oso Creek tributary), is 5,287 acres. Rainfall and runoff (streamflow) were continuously monitored at the outlets of the two subwatersheds during October 2005-September 2007. Fourteen rainfall samples were collected and analyzed for nutrients and major inorganic ions. Nineteen composite runoff samples (10 West Oso Creek, nine Oso Creek tributary) were collected and analyzed for nutrients, major inorganic ions, and pesticides. Twenty-two discrete suspended-sediment samples (10 West Oso Creek, 12 Oso Creek tributary) and 13 bacteria samples (eight West Oso Creek, five Oso Creek tributary) were collected and analyzed. These data were used to estimate, for selected constituents, rainfall deposition to and runoff loads and yields from the study subwatersheds. Quantities of fertilizers and pesticides applied in the subwatersheds were compared with quantities of nutrients and pesticides in rainfall and runoff. For the study period, total rainfall was greater than average. Most of the runoff at both subwatershed outlet sites occurred in response to a few specific storm periods. The West Oso Creek subwatershed produced more runoff during the study period than the Oso Creek tributary subwatershed, 10.83 inches compared with 7.28 inches. Runoff response was quicker and peak flows were higher in the West Oso Creek subwatershed than in the Oso Creek tributary subwatershed. Total nitrogen runoff yield for the 2-year study period averaged 2.61 pounds per acre per year from the West Oso Creek subwatershed and 0.966 pound per acre per year from the Oso Creek tributary subwatershed. Total phosphorus yields from the West Oso Creek and the Oso Creek tributary subwatersheds for the 2-year period were 0.776 and 0.498 pound per acre per year. Runoff yields of nitrogen and phosphorus were relatively small compared to inputs of nitrogen in fertilizer and rainfall deposition. Average annual runoff yield of total nitrogen (subwatersheds combined) represents about 2.4 percent of nitrogen applied as fertilizer and nitrogen entering the subwatersheds through rainfall deposition. Average annual runoff yield of total phosphorus (subwatersheds combined) represents about 4.4 percent of the phosphorus in applied fertilizer and rainfall deposition. Suspended-sediment yields from the West Oso Creek subwatershed were more than twice those from the Oso Creek tributary subwatershed. The average suspended-sediment yield from the West Oso Creek subwatershed was 582 pounds per acre per year. The average suspended-sediment yield from the Oso Creek tributary subwatershed was 257 pounds per acre per year. Twenty-two herbicides and eight insecticides were detected in runoff samples collected from the two subwatershed outlet sites. At the West Oso Creek site, 18 herbicides and four insecticides were detected, and at the Oso Creek tributary site, 17 herbicides and six insecticides. Seventeen pesticides were detected in only one sample at low concentrations (near the laboratory reporting level). Atrazine, atrazine degradation byproducts 2-chloro-4-isopropylamino-6-amino-s-triazine (CIAT) and 2-hydroxy-4-isopropylamino-6-ethylamino-s-triazine (OIET), glyphosate, and glyphosate byproduct aminomethylphosphonic acid (AMPA) were detected in all samples. Of all pesticides detected in runoff, the highest runoff yields were for glyphosate, 0.013 pound per acre per year for the West Oso Creek subwatershed and 0.001 pound per acre per year for the Oso Creek t

Spatial and seasonal responses of precipitation in the Ganges and Brahmaputra river basins to ENSO and Indian Ocean dipole modes: implications for flooding and drought

USGS Publications Warehouse

Pervez, Md Shahriar; Henebry, Geoffry M.

2015-01-01

We evaluated the spatial and seasonal responses of precipitation in the Ganges and Brahmaputra basins as modulated by the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) modes using Global Precipitation Climatology Centre (GPCC) full data reanalysis of monthly global land-surface precipitation data from 1901 to 2010 with a spatial resolution of 0.5° × 0.5°. The GPCC monthly total precipitation climatology targeting the period 1951–2000 was used to compute gridded monthly anomalies for the entire time period. The gridded monthly anomalies were averaged for the years influenced by combinations of climate modes. Occurrences of El Niño alone significantly reduce (88% of the long-term average (LTA)) precipitation during the monsoon months in the western and southeastern Ganges Basin. In contrast, occurrences of La Niña and co-occurrences of La Niña and negative IOD events significantly enhance (110 and 109% of LTA in the Ganges and Brahmaputra Basin, respectively) precipitation across both basins. When El Niño co-occurs with positive IOD events, the impacts of El Niño on the basins' precipitation diminishes. When there is no active ENSO or IOD events (occurring in 41 out of 110 years), precipitation remains below average (95% of LTA) in the agriculturally intensive areas of Haryana, Uttar Pradesh, Rajasthan, Madhya Pradesh, and Western Nepal in the Ganges Basin, whereas precipitation remains average to above average (104% of LTA) across the Brahmaputra Basin. This pattern implies that a regular water deficit is likely, especially in the Ganges Basin, with implications for the agriculture sector due to its reliance on consistent rainfall for successful production. Historically, major droughts occurred during El Niño and co-occurrences of El Niño and positive IOD events, while major flooding occurred during La Niña and co-occurrences of La Niña and negative IOD events in the basins. This observational analysis will facilitate well-informed decision making in minimizing natural hazard risks and climate impacts on agriculture, and supports development of strategies ensuring optimized use of water resources in best management practice under a changing climate.

Skiff-based Sonar/LiDAR Survey to Calibrate Reservoir Volumes for Watershed Sediment Yield Studies: Carmel River Example

NASA Astrophysics Data System (ADS)

Smith, D. P.; Kvitek, R.; Quan, S.; Iampietro, P.; Paddock, E.; Richmond, S. F.; Gomez, K.; Aiello, I. W.; Consulo, P.

2009-12-01

Models of watershed sediment yield are complicated by spatial and temporal variability of geologic substrate, land cover, and precipitation parameters. Episodic events such as ENSO cycles and severe wildfire are frequent enough to matter in the long-term average yield, and they can produce short-lived, extreme geomorphic responses. The sediment yield from extreme events is difficult to accurately capture because of the obvious dangers associated with field measurements during flood conditions, but it is critical to include extreme values for developing realistic models of rainfall-sediment yield relations, and for calculating long term average denudation rates. Dammed rivers provide a time-honored natural laboratory for quantifying average annual sediment yield and extreme-event sediment yield. While lead-line surveys of the past provided crude estimates of reservoir sediment trapping, recent advances in geospatial technology now provide unprecedented opportunities to improve volume change measurements. High-precision digital elevation models surveyed on an annual basis, or before-and-after specific rainfall-runoff events can be used to quantify relations between rainfall and sediment yield as a function of landscape parameters, including spatially explicit fire intensity. The Basin-Complex Fire of June and July 2008 resulted in moderate to severe burns in the 114 km^2 portion of the Carmel River watershed above Los Padres Dam. The US Geological Survey produced a debris flow probability/volume model for the region indicating that the reservoir could lose considerable capacity if intense enough precipitation occurred in the 2009-10 winter. Loss of Los Padres reservoir capacity has implications for endangered steelhead and red-legged frogs, and groundwater on municipal water supply. In anticipation of potentially catastrophic erosion, we produced an accurate volume calculation of the Los Padres reservoir in fall 2009, and locally monitored hillslope and fluvial processes during winter months. The pre-runoff reservoir volume was developed by collecting and merging sonar and LiDAR data from a small research skiff equipped with a high-precision positioning and attitude-correcting system. The terrestrial LiDAR data were augmented with shore-based total station positioning. Watershed monitoring included benchmarked serial stream surveys and semi-quantitative assessment of a variety of near-channel colluvial processes. Rainfall in the 2009-10 water year was not intense enough to trigger widespread debris flows of slope failure in the burned watershed, but dry ravel was apparently accelerated. The geomorphic analysis showed that sediment yield was not significantly higher during this low-rainfall year, despite the wide-spread presence of very steep, fire-impacted slopes. Because there was little to no increase in sediment yield this year, we have postponed our second reservoir survey. A predicted ENSO event that might bring very intense rains to the watershed is currently predicted for winter 2009-10.

Using remote sensing environmental data to forecast malaria incidence at a rural district hospital in Western Kenya.

PubMed

Sewe, Maquins Odhiambo; Tozan, Yesim; Ahlm, Clas; Rocklöv, Joacim

2017-06-01

Malaria surveillance data provide opportunity to develop forecasting models. Seasonal variability in environmental factors correlate with malaria transmission, thus the identification of transmission patterns is useful in developing prediction models. However, with changing seasonal transmission patterns, either due to interventions or shifting weather seasons, traditional modelling approaches may not yield adequate predictive skill. Two statistical models,a general additive model (GAM) and GAMBOOST model with boosted regression were contrasted by assessing their predictive accuracy in forecasting malaria admissions at lead times of one to three months. Monthly admission data for children under five years with confirmed malaria at the Siaya district hospital in Western Kenya for the period 2003 to 2013 were used together with satellite derived data on rainfall, average temperature and evapotranspiration(ET). There was a total of 8,476 confirmed malaria admissions. The peak of malaria season changed and malaria admissions reduced overtime. The GAMBOOST model at 1-month lead time had the highest predictive skill during both the training and test periods and thus can be utilized in a malaria early warning system.

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.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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.

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.

Soil CO2, CH4 and N2O effluxes and concentrations in soil profiles down to 15.5m depth in eucalypt plantations under contrasted rainfall regimes

NASA Astrophysics Data System (ADS)

Germon, A.; Nouvellon, Y.; Christophe, J.; Chapuis-Lardy, L.; Robin, A.; Rosolem, C. A.; Gonçalves, J. L. D. M.; Guerrini, I. A.; Laclau, J. P.

2017-12-01

Silvicultural practices in planted forests affect the fluxes of greenhouse gases at the soil surface and the major factors driving greenhouse gas production in forest soils (substrate supply, temperature, water content,…) vary with soil depth. Our study aimed to assess the consequences of drought on the temporal variability of CO2, CH4 and N2O fluxes throughout very deep soil profiles in Eucalyptus grandis plantations 3 months before the harvest then in coppice, the first 18 months after clear-cutting. Two treatments were compared: one with 37% of throughfall excluded by plastic sheets (TE), and one without rainfall exclusion (WE). Measurements of soil CO2 efflux were made every two weeks for 30 months using a closed-path Li8100 system in both treatment. Every two weeks for 21 months, CO2, CH4 and N2O surface effluxes were measured using the closed-chamber method and concentrations in the soil were measured at 7 depths down to 15.5 m in both TE and WE. At most measurement dates, soil CO2 efflux were significantly higher in TE than in WE. Across the two treatments and the measurement dates, CO2 concentrations increased from 4446 ± 2188 ppm at 10 cm deep to 15622 ± 3523 ppm at 15.5 m, CH4 concentrations increased from 0.41 ± 0.17 ppm at 10 cm deep to 0.77 ± 0.24 ppm at 15.5 m and N2O concentrations remained roughly constant and were on average 478 ± 55 ppb between soil surface and 15.5 m deep. CO2 and N2O concentrations were on average 20.7 and 7.6% lower in TE than in WE, respectively, across the sampling depths. However, CH4 concentrations in TE were on average 44.4% higher than in WE, throughout the soil profile. Those results suggest that extended drought periods might reduce the production of CO2 and N2O but increase the accumulation of CH4 in eucalypt plantations established in deep tropical soils. Very deep tropical soils cover huge areas worldwide and improving our understanding of the spatiotemporal dynamics of gas concentrations in deep soil layers is essential to: i) quantify more accurately C source/sink fluxes as part of the global carbon budget, ii) improve the current biogeochemical models predicting the effect of drought periods on greenhouse gas effluxes, and iii) identify more sustainable silvicultural practices for tropical planted forests in a context of climate change.

Predicting watershed acidification under alternate rainfall conditions

USGS Publications Warehouse

Huntington, T.G.

1996-01-01

The effect of alternate rainfall scenarios on acidification of a forested watershed subjected to chronic acidic deposition was assessed using the model of acidification of groundwater in catchments (MAGIC). The model was calibrated at the Panola Mountain Research Watershed, near Atlanta, Georgia, U.S.A. using measured soil properties, wet and dry deposition, and modeled hydrologic routing. Model forecast simulations were evaluated to compare alternate temporal averaging of rainfall inputs and variations in rainfall amount and seasonal distribution. Soil water alkalinity was predicted to decrease to substantially lower concentrations under lower rainfall compared with current or higher rainfall conditions. Soil water alkalinity was also predicted to decrease to lower levels when the majority of rainfall occurred during the growing season compared with other rainfall distributions. Changes in rainfall distribution that result in decreases in net soil water flux will temporarily delay acidification. Ultimately, however, decreased soil water flux will result in larger increases in soil- adsorbed sulfur and soil-water sulfate concentrations and decreases in alkalinity when compared to higher water flux conditions. Potential climate change resulting in significant changes in rainfall amounts, seasonal distribution of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading.

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.

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.

[Rainfall intensity effects on nutrients transport in surface runoff from farmlands in gentle slope hilly area of Taihu Lake Basin].

PubMed

Li, Rui-ling; Zhang, Yong-chun; Liu, Zhuang; Zeng, Yuan; Li, Wei-xin; Zhang, Hong-ling

2010-05-01

To investigate the effect of rainfall on agricultural nonpoint source pollution, watershed scale experiments were conducted to study the characteristics of nutrients in surface runoff under different rainfall intensities from farmlands in gentle slope hilly areas around Taihu Lake. Rainfall intensity significantly affected N and P concentrations in runoff. Rainfall intensity was positively related to TP, PO4(3-) -P and NH4+ -N event mean concentrations(EMC). However, this study have found the EMC of TN and NO3- -N to be positively related to rainfall intensity under light rain and negatively related to rainfall intensity under heavy rain. TN and TP site mean amounts (SMA) in runoff were positively related to rainfall intensity and were 1.91, 311.83, 127.65, 731.69 g/hm2 and 0.04, 7.77, 2.99, 32.02 g/hm2 with rainfall applied under light rain, moderate rain, heavy rain and rainstorm respectively. N in runoff was mainly NO3- -N and NH4+ -N and was primarily in dissolved form from Meilin soils. Dissolved P (DP) was the dominant form of TP under light rain, but particulate P (PP) mass loss increased with the increase of rainfall intensity and to be the dominant form when the rainfall intensity reaches rainstorm. Single relationships were used to describe the dependence of TN and TP mass losses in runoff on rainfall, maximum rainfall intensity, average rainfall intensity and rainfall duration respectively. The results showed a significant positive correlation between TN mass loss and rainfall, maximum rainfall intensity respectively (p < 0.01) and also TP mass loss and rainfall, maximum rainfall intensity respectively (p < 0.01).

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.

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.

Analysis of Darwin Rainfall Data: Implications on Sampling Strategy

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

A groundwater recharge perspective on locating tree plantations within low-rainfall catchments to limit water resource losses

NASA Astrophysics Data System (ADS)

Dean, J. F.; Webb, J. A.; Jacobsen, G. E.; Chisari, R.; Dresel, P. E.

2015-02-01

Despite the many studies that consider the impacts of plantation forestry on groundwater recharge, and others that explore the spatial heterogeneity of recharge in low-rainfall regions, there is little marriage of the two subjects in forestry management guidelines and legislation. Here we carry out an in-depth analysis of the impact of reforestation on groundwater recharge in a low-rainfall (< 700 mm annually), high-evapotranspiration paired catchment characterized by ephemeral streams. Water table fluctuation (WTF) estimates of modern recharge indicate that little groundwater recharge occurs along the topographic highs of the catchments (average 18 mm yr-1); instead the steeper slopes in these areas direct runoff downslope to the lowland areas, where most recharge occurs (average 78 mm yr-1). Recharge estimates using the chloride mass balance (CMB) method were corrected by replacing the rainfall input Cl- value with that for streamflow, because most recharge occurs from infiltration of runoff through the streambed and adjacent low gradient slopes. The calculated CMB recharge values (average 10 mm yr-1) are lower than the WTF recharge values (average 47 mm yr-1), because they are representative of groundwater that was mostly recharged prior to European land clearance (> BP 200 years). The tree plantation has caused a progressive drawdown in groundwater levels due to tree water use; the decline is less in the upland areas. The results of this study show that spatial variations in recharge are important considerations for locating tree plantations. To conserve water resources for downstream users in low-rainfall, high-evapotranspiration regions, tree planting should be avoided in the dominant zone of recharge, i.e. the topographically low areas and along the drainage lines, and should be concentrated on the upper slopes, although this may negatively impact the economic viability of the plantation.

Northern Arkansas Spring Precipitation Reconstructed from Tree Rings, 1023-1992 A.D.

Treesearch

Malcolm K. Cleaveland

2001-01-01

Three baldcypress (Taxodium distichum (L.) Rich.) tree-ring chronologies in northeastern Arkansas and southeastern Missouri respond strongly to April-June (spring) rainfall in northern Arkansas. I used regression to reconstruct an average of spring rainfall in the three climatic divisions of northern Arkansas since 1023 A.D. The reconstruction was...

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.

Secular spring rainfall variability at local scale over Ethiopia: trend and associated dynamics

NASA Astrophysics Data System (ADS)

Tsidu, Gizaw Mengistu

2017-10-01

Spring rainfall secular variability is studied using observations, reanalysis, and model simulations. The joint coherent spatio-temporal secular variability of gridded monthly gauge rainfall over Ethiopia, ERA-Interim atmospheric variables and sea surface temperature (SST) from Hadley Centre Sea Ice and SST (HadISST) data set is extracted using multi-taper method singular value decomposition (MTM-SVD). The contemporaneous associations are further examined using partial Granger causality to determine presence of causal linkage between any of the climate variables. This analysis reveals that only the northwestern Indian Ocean secular SST anomaly has direct causal links with spring rainfall over Ethiopia and mean sea level pressure (MSLP) over Africa inspite of the strong secular covariance of spring rainfall, SST in parts of subtropical Pacific, Atlantic, Indian Ocean and MSLP. High secular rainfall variance and statistically significant linear trend show consistently that there is a massive decline in spring rain over southern Ethiopia. This happened concurrently with significant buildup of MSLP over East Africa, northeastern Africa including parts of the Arabian Peninsula, some parts of central Africa and SST warming over all ocean basins with the exception of the ENSO regions. The east-west pressure gradient in response to the Indian Ocean warming led to secular southeasterly winds over the Arabian Sea, easterly over central Africa and equatorial Atlantic. These flows weakened climatological northeasterly flow over the Arabian Sea and southwesterly flow over equatorial Atlantic and Congo basins which supply moisture into the eastern Africa regions in spring. The secular divergent flow at low level is concurrent with upper level convergence due to the easterly secular anomalous flow. The mechanisms through which the northwestern Indian Ocean secular SST anomaly modulates rainfall are further explored in the context of East Africa using a simplified atmospheric general circulation model (AGCM) coupled to mixed-layer oceanic model. The rainfall anomaly (with respect to control simulation), forced by the northwestern Indian Ocean secular SST anomaly and averaged over the 30-year period, exhibits prevalence of dry conditions over East and equatorial Africa in agreement with observation. The atmospheric response to secular SST warming anomaly led to divergent flow at low levels and subsidence at the upper troposphere over regions north of 5° S on the continent and vice versa over the Indian Ocean. This surface difluence over East Africa, in addition to its role in suppressing convective activity, deprives the region of moisture supply from the Indian Ocean as well as the Atlantic and Congo basins.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

NASA Astrophysics Data System (ADS)

Martin, Gill M.; Klingaman, Nicholas P.; Moise, Aurel F.

2017-01-01

This study analyses tropical rainfall variability (on a range of temporal and spatial scales) in a set of parallel Met Office Unified Model (MetUM) simulations at a range of horizontal resolutions, which are compared with two satellite-derived rainfall datasets. We focus on the shorter scales, i.e. from the native grid and time step of the model through sub-daily to seasonal, since previous studies have paid relatively little attention to sub-daily rainfall variability and how this feeds through to longer scales. We find that the behaviour of the deep convection parametrization in this model on the native grid and time step is largely independent of the grid-box size and time step length over which it operates. There is also little difference in the rainfall variability on larger/longer spatial/temporal scales. Tropical convection in the model on the native grid/time step is spatially and temporally intermittent, producing very large rainfall amounts interspersed with grid boxes/time steps of little or no rain. In contrast, switching off the deep convection parametrization, albeit at an unrealistic resolution for resolving tropical convection, results in very persistent (for limited periods), but very sporadic, rainfall. In both cases, spatial and temporal averaging smoothes out this intermittency. On the ˜ 100 km scale, for oceanic regions, the spectra of 3-hourly and daily mean rainfall in the configurations with parametrized convection agree fairly well with those from satellite-derived rainfall estimates, while at ˜ 10-day timescales the averages are overestimated, indicating a lack of intra-seasonal variability. Over tropical land the results are more varied, but the model often underestimates the daily mean rainfall (partly as a result of a poor diurnal cycle) but still lacks variability on intra-seasonal timescales. Ultimately, such work will shed light on how uncertainties in modelling small-/short-scale processes relate to uncertainty in climate change projections of rainfall distribution and variability, with a view to reducing such uncertainty through improved modelling of small-/short-scale processes.

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.

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.

Trends in autumn rain of West China from 1961 to 2014

NASA Astrophysics Data System (ADS)

Zhang, Chi; Wang, Zunya; Zhou, Botao; Li, Yonghua; Tang, Hongyu; Xiang, Bo

2018-02-01

Autumn rain of West China is a typical climate phenomenon, which is characterized by continuous rainy days and large rainfall amounts and exerts profound impacts on the economic society. Based on daily precipitation data from 524 observation stations for the period of 1961-2014, this article comprehensively examined secular changes in autumn rain of West China, including its amount, frequency, intensity, and associated extremes. The results generally show a significant reduction of rainfall amount and rainy days and a significant enhancement of mean rainfall intensity for the average of West China during autumn (September-October) since 1961. Meanwhile, decreasing trends are consistently observed in the maximum daily rainfall, the longest consecutive rainy days, the greatest consecutive rainfall amount, and the frequencies of the extreme daily rainfall, consecutive rainfall, and consecutive rainfall process. Further analysis indicates that the decreases of autumn rainfall and related extremes in West China are associated with the decreases in both water vapor content and atmospheric unstable stratification during the past decades. On the regional scale, some differences exist in the changes of autumn rainfall between the eastern and western parts of West China. Besides, it is found that the autumn rainy season tends to start later and terminate earlier particularly in eastern West China.

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.

Influence of riverine input on the growth of Glycymeris glycymeris in the Bay of Brest, North-West France

PubMed Central

2017-01-01

A crossdated, replicated, chronology of 114 years (1901–2014) was developed from internal growth increments in the shells of Glycymeris glycymeris samples collected monthly from the Bay of Brest, France. Bivalve sampling was undertaken between 2014 and 2015 using a dredge. In total 401 live specimens and 243 articulated paired valves from dead specimens were collected, of which 38 individuals were used to build the chronology. Chronology strength, assessed as the Expressed Population Signal, was above 0.7 throughout, falling below the generally accepted threshold of 0.85 before 1975 because of reduced sample depth. Significant positive correlations were identified between the shell growth and the annual averages of rainfall (1975–2008; r = 0.34) and inflow from the river Elorn (1989–2009; r = 0.60). A significant negative correlation was identified between shell growth and the annual average salinity (1998–2014; r = -0.62). Analysis of the monthly averages indicates that these correlations are associated with the winter months (November–February) preceding the G. glycymeris growth season suggesting that winter conditions predispose the benthic environment for later shell growth. Concentration of suspended particulate matter within the river in February is also positively correlated with shell growth, leading to the conclusion that food availability is also important to the growth of G. glycymeris in the Bay of Brest. With the addition of principle components analysis, we were able to determine that inflow from the River Elorn, nitrite levels and salinity were the fundamental drivers of G. glycymeris growth and that these environmental parameters were all linked. PMID:29261749

Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection

PubMed Central

Kirchner, James W.; Neal, Colin

2013-01-01

The chemical dynamics of lakes and streams affect their suitability as aquatic habitats and as water supplies for human needs. Because water quality is typically monitored only weekly or monthly, however, the higher-frequency dynamics of stream chemistry have remained largely invisible. To illuminate a wider spectrum of water quality dynamics, rainfall and streamflow were sampled in two headwater catchments at Plynlimon, Wales, at 7-h intervals for 1–2 y and weekly for over two decades, and were analyzed for 45 solutes spanning the periodic table from H+ to U. Here we show that in streamflow, all 45 of these solutes, including nutrients, trace elements, and toxic metals, exhibit fractal 1/fα scaling on time scales from hours to decades (α = 1.05 ± 0.15, mean ± SD). We show that this fractal scaling can arise through dispersion of random chemical inputs distributed across a catchment. These 1/f time series are non–self-averaging: monthly, yearly, or decadal averages are approximately as variable, one from the next, as individual measurements taken hours or days apart, defying naive statistical expectations. (By contrast, stream discharge itself is nonfractal, and self-averaging on time scales of months and longer.) In the solute time series, statistically significant trends arise much more frequently, on all time scales, than one would expect from conventional t statistics. However, these same trends are poor predictors of future trends—much poorer than one would expect from their calculated uncertainties. Our results illustrate how 1/f time series pose fundamental challenges to trend analysis and change detection in environmental systems. PMID:23842090

Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection

NASA Astrophysics Data System (ADS)

Kirchner, James W.; Neal, Colin

2013-07-01

The chemical dynamics of lakes and streams affect their suitability as aquatic habitats and as water supplies for human needs. Because water quality is typically monitored only weekly or monthly, however, the higher-frequency dynamics of stream chemistry have remained largely invisible. To illuminate a wider spectrum of water quality dynamics, rainfall and streamflow were sampled in two headwater catchments at Plynlimon, Wales, at 7-h intervals for 1-2 y and weekly for over two decades, and were analyzed for 45 solutes spanning the periodic table from H+ to U. Here we show that in streamflow, all 45 of these solutes, including nutrients, trace elements, and toxic metals, exhibit fractal 1/fα scaling on time scales from hours to decades (α = 1.05 ± 0.15, mean ± SD). We show that this fractal scaling can arise through dispersion of random chemical inputs distributed across a catchment. These 1/f time series are non-self-averaging: monthly, yearly, or decadal averages are approximately as variable, one from the next, as individual measurements taken hours or days apart, defying naive statistical expectations. (By contrast, stream discharge itself is nonfractal, and self-averaging on time scales of months and longer.) In the solute time series, statistically significant trends arise much more frequently, on all time scales, than one would expect from conventional t statistics. However, these same trends are poor predictors of future trends-much poorer than one would expect from their calculated uncertainties. Our results illustrate how 1/f time series pose fundamental challenges to trend analysis and change detection in environmental systems.

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.

Analysis for water level data for Everglades National Park, Florida

USGS Publications Warehouse

Buchanan, T.J.; Hartwell, J.H.

1972-01-01

Stage-duration curves were developed for five gaging stations in Everglades National Park, Florida. Four of the five curves show similar characteristics with an increase in the slope when the water level is below land surface. Monthly stage-duration curves, developed for one of the stations, reflect the seasonal trends of the water level. Recession curves were prepared for the same five stations. These curves represent the average water-level decline during periods of little or no rainfall. They show the decline in level at the end of 10, 20, and 60 days for any given initial stage. A family of curves was also prepared to give the recession from various initial stages for any period up to 60 days.

Tropical rain mapping radar on the Space Station

NASA Technical Reports Server (NTRS)

Im, Eastwood; Li, Fuk

1989-01-01

The conceptual design for a tropical rain mapping radar for flight on the manned Space Station is discussed. In this design the radar utilizes a narrow, dual-frequency (9.7 GHz and 24.1 GHz) beam, electronically scanned antenna to achieve high spatial (4 km) and vertical (250 m) resolutions and a relatively large (800 km) cross-track swath. An adaptive scan strategy will be used for better utilization of radar energy and dwell time. Such a system can detect precipitation at rates of up to 100 mm/hr with accuracies of roughly 15 percent. With the proposed space-time sampling strategy, the monthly averaged rainfall rate can be estimated to within 8 percent, which is essential for many climatological studies.

Application of Archimedean copulas to the impact assessment of hydro-climatic variables in semi-arid aquifers of western India

NASA Astrophysics Data System (ADS)

Wable, Pawan S.; Jha, Madan K.

2018-02-01

The effects of rainfall and the El Niño Southern Oscillation (ENSO) on groundwater in a semi-arid basin of India were analyzed using Archimedean copulas considering 17 years of data for monsoon rainfall, post-monsoon groundwater level (PMGL) and ENSO Index. The evaluated dependence among these hydro-climatic variables revealed that PMGL-Rainfall and PMGL-ENSO Index pairs have significant dependence. Hence, these pairs were used for modeling dependence by employing four types of Archimedean copulas: Ali-Mikhail-Haq, Clayton, Gumbel-Hougaard, and Frank. For the copula modeling, the results of probability distributions fitting to these hydro-climatic variables indicated that the PMGL and rainfall time series are best represented by Weibull and lognormal distributions, respectively, while the non-parametric kernel-based normal distribution is the most suitable for the ENSO Index. Further, the PMGL-Rainfall pair is best modeled by the Clayton copula, and the PMGL-ENSO Index pair is best modeled by the Frank copula. The Clayton copula-based conditional probability of PMGL being less than or equal to its average value at a given mean rainfall is above 70% for 33% of the study area. In contrast, the spatial variation of the Frank copula-based probability of PMGL being less than or equal to its average value is 35-40% in 23% of the study area during El Niño phase, while it is below 15% in 35% of the area during the La Niña phase. This copula-based methodology can be applied under data-scarce conditions for exploring the impacts of rainfall and ENSO on groundwater at basin scales.

Hydroclimate temporal variability in a coastal Mediterranean watershed: the Tafna basin, North-West Algeria

NASA Astrophysics Data System (ADS)

Boulariah, Ouafik; Longobardi, Antonia; Meddi, Mohamed

2017-04-01

One of the major challenges scientists, practitioners and stakeholders are nowadays involved in, is to provide the worldwide population with reliable water supplies, protecting, at the same time, the freshwater ecosystems quality and quantity. Climate and land use changes undermine the balance between water demand and water availability, causing alteration of rivers flow regime. Knowledge of hydro-climate variables temporal and spatial variability is clearly helpful to plan drought and flood hazard mitigation strategies but also to adapt them to future environmental scenarios. The present study relates to the coastal semi-arid Tafna catchment, located in the North-West of Algeria, within the Mediterranean basin. The aim is the investigation of streamflow and rainfall indices temporal variability in six sub-basins of the large catchment Tafna, attempting to relate streamflow and rainfall changes. Rainfall and streamflow time series have been preliminary tested for data quality and homogeneity, through the coupled application of two-tailed t test, Pettitt test and Cumsum tests (significance level of 0.1, 0.05 and 0.01). Subsequently maximum annual daily rainfall and streamflow and average daily annual rainfall and streamflow time series have been derived and tested for temporal variability, through the application of the Mann Kendall and Sen's test. Overall maximum annual daily streamflow time series exhibit a negative trend which is however significant for only 30% of the station. Maximum annual daily rainfall also e exhibit a negative trend which is intend significant for the 80% of the stations. In the case of average daily annual streamflow and rainfall, the tendency for decrease in time is unclear and, in both cases, appear significant for 60% of stations.

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.

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.

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.

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.

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.