On the distributions of annual and seasonal daily rainfall extremes in central Arizona and their spatial variability

Science.gov (United States)

Mascaro, Giuseppe

2018-04-01

This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.

The Impact of Amazonian Deforestation on Dry-Season Rainfall

Science.gov (United States)

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

2002-01-01

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

Prediction of East African Seasonal Rainfall Using Simplex Canonical Correlation Analysis.

Science.gov (United States)

Ntale, Henry K.; Yew Gan, Thian; Mwale, Davison

2003-06-01

A linear statistical model, canonical correlation analysis (CCA), was driven by the Nelder-Mead simplex optimization algorithm (called CCA-NMS) to predict the standardized seasonal rainfall totals of East Africa at 3-month lead time using SLP and SST anomaly fields of the Indian and Atlantic Oceans combined together by 24 simplex optimized weights, and then `reduced' by the principal component analysis. Applying the optimized weights to the predictor fields produced better March-April-May (MAM) and September-October-November (SON) seasonal rain forecasts than a direct application of the same, unweighted predictor fields to CCA at both calibration and validation stages. Northeastern Tanzania and south-central Kenya had the best SON prediction results with both validation correlation and Hanssen-Kuipers skill scores exceeding +0.3. The MAM season was better predicted in the western parts of East Africa. The CCA correlation maps showed that low SON rainfall in East Africa is associated with cold SSTs off the Somali coast and the Benguela (Angola) coast, and low MAM rainfall is associated with a buildup of low SSTs in the Indian Ocean adjacent to East Africa and the Gulf of Guinea.

Seasonal rainfall predictability over the Lake Kariba catchment area

CSIR Research Space (South Africa)

Muchuru, S

2014-07-01

Full Text Available The Lake Kariba catchment area in southern Africa has one of the most variable climates of any major river basin, with an extreme range of conditions across the catchment and through time. Marked seasonal and interannual fluctuations in rainfall...

Animal perception of seasonal thresholds: changes in elephant movement in relation to rainfall patterns.

Science.gov (United States)

Birkett, Patricia J; Vanak, Abi T; Muggeo, Vito M R; Ferreira, Salamon M; Slotow, Rob

2012-01-01

The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal's behaviour, which contributes to an understanding of species' responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana), in relation to local and regional rainfall patterns. We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007-2009). Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal's perspective, for delineating seasons or other extrinsic shifts in ecological studies, rather than arbitrarily fixed definitions

Animal perception of seasonal thresholds: changes in elephant movement in relation to rainfall patterns.

Directory of Open Access Journals (Sweden)

Patricia J Birkett

Full Text Available BACKGROUND: The identification of temporal thresholds or shifts in animal movement informs ecologists of changes in an animal's behaviour, which contributes to an understanding of species' responses in different environments. In African savannas, rainfall, temperature and primary productivity influence the movements of large herbivores and drive changes at different scales. Here, we developed a novel approach to define seasonal shifts in movement behaviour by examining the movements of a highly mobile herbivore (elephant; Loxodonta africana, in relation to local and regional rainfall patterns. METHODOLOGY/PRINCIPAL FINDINGS: We used speed to determine movement changes of between 8 and 14 GPS-collared elephant cows, grouped into five spatial clusters, in Kruger National Park, South Africa. To detect broad-scale patterns of movement, we ran a three-year daily time-series model for each individual (2007-2009. Piecewise regression models provided the best fit for elephant movement, which exhibited a segmented, waveform pattern over time. Major breakpoints in speed occurred at the end of the dry and wet seasons of each year. During the dry season, female elephant are constrained by limited forage and thus the distances they cover are shorter and less variable. Despite the inter-annual variability of rainfall, speed breakpoints were strongly correlated with both local and regional rainfall breakpoints across all three years. Thus, at a multi-year scale, rainfall patterns significantly affect the movements of elephant. The variability of both speed and rainfall breakpoints across different years highlights the need for an objective definition of seasonal boundaries. CONCLUSIONS/SIGNIFICANCE: By using objective criteria to determine behavioural shifts, we identified a biologically meaningful indicator of major changes in animal behaviour in different years. We recommend the use of such criteria, from an animal's perspective, for delineating seasons or

Synergistic effects of seasonal rainfall, parasites and demography on fluctuations in springbok body condition

Science.gov (United States)

Turner, Wendy C.; Versfeld, Wilferd D.; Kilian, J. Werner; Getz, Wayne M.

2011-01-01

Summary 1. Seasonality of rainfall can exert a strong influence on animal condition and on host-parasite interactions. The body condition of ruminants fluctuates seasonally in response to changes in energy requirements, foraging patterns and resource availability, and seasonal variation in parasite infections may further alter ruminant body condition. 2. This study disentangles effects of rainfall and gastrointestinal parasite infections on springbok (Antidorcas marsupialis) body condition and determines how these factors vary among demographic groups. 3. Using data from four years and three study areas, we investigated i) the influence of rainfall variation, demographic factors and parasite interactions on parasite prevalence or infection intensity, ii) whether parasitism or rainfall is a more important predictor of springbok body condition and iii) how parasitism and condition vary among study areas along a rainfall gradient. 4. We found that increased parasite intensity is associated with reduced body condition only for adult females. For all other demographic groups, body condition was significantly related to prior rainfall and not to parasitism. Rainfall lagged by two months had a positive effect on body condition. 5. Adult females showed evidence of a “periparturient rise” in parasite intensity, and had higher parasite intensity and lower body condition than adult males after parturition and during early lactation. After juveniles were weaned, adult females had lower parasite intensity than adult males. Sex differences in parasitism and condition may be due to differences between adult females and males in the seasonal timing of reproductive effort and its effects on host immunity, as well as documented sex differences in vulnerability to predation. 6. Our results highlight that parasites and the environment can synergistically affect host populations, but that these interactions might be masked by their interwoven relationships, their differential

Indian Summer Monsoon Sub-seasonal Low-Level Circulation Predictability and its Association with Rainfall in a Coupled Model

KAUST Repository

Sagalgile, Archana P.; Chowdary, Jasti S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Singh, Prem

2017-01-01

This study investigates predictability of the sub-seasonal Indian summer monsoon (ISM) circulation and its relation with rainfall variations in the coupled model National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Hindcasts based on CFSv2 for the period of 1982–2009 are used for detailed analysis. Though the model is capable of predicting the seasonal ISM rainfall at long lead months, the predication skill of the model for sub-seasonal rainfall in general is poor for short and long lead except for September. Rainfall over the ISM region/Indian Subcontinent is highly correlated with the low-level jet (LLJ) or Somali jet both in the observations and the model. The model displays improved skill in predicting LLJ as compared to precipitation in seasonal mean and September, whereas the model skill is poor for June and August. Detailed analysis reveals that the model LLJ variations throughout the season are overdependent on the El Niño-Southern Oscillation (ENSO) unlike in the observations. This is mainly responsible for the model’s low skill in predicting LLJ especially in July and August, which is the primary cause for the poor rainfall skill. Though LLJ is weak in September, the model skill is reasonably good because of its ENSO dependency both in model and the observations and which is contributed to the seasonal mean skill. Thus, to improve the skill of seasonal mean monsoon forecast, it is essential to improve the skill of individual months/sub-seasonal circulation and rainfall skill.

Indian Summer Monsoon Sub-seasonal Low-Level Circulation Predictability and its Association with Rainfall in a Coupled Model

KAUST Repository

Sagalgile, Archana P.

2017-10-26

This study investigates predictability of the sub-seasonal Indian summer monsoon (ISM) circulation and its relation with rainfall variations in the coupled model National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). Hindcasts based on CFSv2 for the period of 1982–2009 are used for detailed analysis. Though the model is capable of predicting the seasonal ISM rainfall at long lead months, the predication skill of the model for sub-seasonal rainfall in general is poor for short and long lead except for September. Rainfall over the ISM region/Indian Subcontinent is highly correlated with the low-level jet (LLJ) or Somali jet both in the observations and the model. The model displays improved skill in predicting LLJ as compared to precipitation in seasonal mean and September, whereas the model skill is poor for June and August. Detailed analysis reveals that the model LLJ variations throughout the season are overdependent on the El Niño-Southern Oscillation (ENSO) unlike in the observations. This is mainly responsible for the model’s low skill in predicting LLJ especially in July and August, which is the primary cause for the poor rainfall skill. Though LLJ is weak in September, the model skill is reasonably good because of its ENSO dependency both in model and the observations and which is contributed to the seasonal mean skill. Thus, to improve the skill of seasonal mean monsoon forecast, it is essential to improve the skill of individual months/sub-seasonal circulation and rainfall skill.

Historical and future seasonal rainfall variability in Nusa Tenggara Barat Province, Indonesia: Implications for the agriculture and water sectors

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Dewi G.C. Kirono

2016-01-01

Full Text Available Climate change impacts are most likely to be felt by resource-dependent communities, and consequently locally-relevant data are necessary to inform livelihood adaptation planning. This paper presents information for historical and future seasonal rainfall variability in Nusa Tenggara Barat (NTB Province, Indonesia, where rural livelihoods are highly vulnerable to current climate variability and future change. Historical rainfall variability is investigated using observational data from two stations located on the islands of Lombok and Sumbawa. Future rainfall is examined using an ensemble of six downscaled climate model simulations at a spatial resolution of 14 km for 1971–2100, applying the IPCC SRES-A2 ‘Business as Usual’ emissions scenario, and the six original global climate models (GCMs. Analyses of the observed seasonal rainfall data highlight cyclical variability and long-term declines. The observed periodicities are of about 2–4, 5, 8, 11, and 40–50 years. Furthermore, dry season rainfall is significantly correlated with the El Niño Southern Oscillation (ENSO, while wet season rainfall is weakly correlated with ENSO. The simulated rainfall data reproduce the observed seasonal cycle very well, but overestimate the magnitude of rainfall and underestimate inter-annual rainfall variability. The models also show that the observed rainfall periodicities will continue throughout the 21st century. The models project that rainfall will decline, although with wide ranges of uncertainty, depending on season and location. Crop water demand estimates show that the projected changes will potentially impact the first growing period for rice during November–March. Rainfall may also be insufficient to meet water demand for many crops in the second growing period of March–June, when high value commodities such as chillies and tobacco are produced. The results reinforce the importance to consider all uncertainties when utilizing climate

Sub-Seasonal Prediction of the Maritime Continent Rainfall of Wet-Dry Transitional Seasons in the NCEP Climate Forecast Version 2

Directory of Open Access Journals (Sweden)

Tuantuan Zhang

2016-02-01

Full Text Available This study investigates the characteristics and prediction of the Maritime Continent (MC rainfall for the transitional periods between wet and dry seasons. Several observational data sets and the output from the 45-day hindcast by the U.S. National Centers for Environmental Prediction (NCEP Climate Forecast System version 2 (CFSv2 are used. Results show that the MC experiences a sudden transition from wet season to dry season (WTD around the 27th pentad, and a gradual transition from dry season to wet season (DTW around the 59th pentad. Correspondingly, the westerlies over the equatorial Indian Ocean, the easterlies over the equatorial Pacific Ocean, and the Australia High become weaker, contributing to weakening of the convergence over the MC. The subtropical western Pacific high intensifies and extends northeastward during the WTD. The Mascarene High becomes weaker, an anomalous anticyclonic circulation forms over the northeast of the Philippines, and an anomalous low-level convergence occurs over the western MC during the DTW. The NCEP CFSv2 captures the major features of rainfall and related atmospheric circulation when forecast lead time is less than three weeks for WTD and two weeks for DTW. The model predicts a weaker amplitude of the changes in rainfall and related atmospheric circulation for both WTD and DTW as lead time increases.

Statistical bias correction modelling for seasonal rainfall forecast for the case of Bali island

Science.gov (United States)

Lealdi, D.; Nurdiati, S.; Sopaheluwakan, A.

2018-04-01

Rainfall is an element of climate which is highly influential to the agricultural sector. Rain pattern and distribution highly determines the sustainability of agricultural activities. Therefore, information on rainfall is very useful for agriculture sector and farmers in anticipating the possibility of extreme events which often cause failures of agricultural production. This research aims to identify the biases from seasonal forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) rainfall forecast and to build a transfer function in order to correct the distribution biases as a new prediction model using quantile mapping approach. We apply this approach to the case of Bali Island, and as a result, the use of bias correction methods in correcting systematic biases from the model gives better results. The new prediction model obtained with this approach is better than ever. We found generally that during rainy season, the bias correction approach performs better than in dry season.

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

Science.gov (United States)

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

2009-02-25

The movement of the herbicide metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)acetamide] via runoff and leaching from 0.21 ha plots planted to corn on Mississippi River alluvial soil (Commerce silt loam) was measured for a 6-year period, 1995-2000. The first three years received normal rainfall (30 year average); the second three years experienced reduced rainfall. The 4-month periods prior to application plus the following 4 months after application were characterized by 1039 +/- 148 mm of rainfall for 1995-1997 and by 674 +/- 108 mm for 1998-2000. During the normal rainfall years 216 +/- 150 mm of runoff occurred during the study seasons (4 months following herbicide application), accompanied by 76.9 +/- 38.9 mm of leachate. For the low-rainfall years these amounts were 16.2 +/- 18.2 mm of runoff (92% less than the normal years) and 45.1 +/- 25.5 mm of leachate (41% less than the normal seasons). Runoff of metolachlor during the normal-rainfall seasons was 4.5-6.1% of application, whereas leaching was 0.10-0.18%. For the below-normal periods, these losses were 0.07-0.37% of application in runoff and 0.22-0.27% in leachate. When averages over the three normal and the three less-than-normal seasons were taken, a 35% reduction in rainfall was characterized by a 97% reduction in runoff loss and a 71% increase in leachate loss of metolachlor on a percent of application basis. The data indicate an increase in preferential flow in the leaching movement of metolachlor from the surface soil layer during the reduced rainfall periods. Even with increased preferential flow through the soil during the below-average rainfall seasons, leachate loss (percent of application) of the herbicide remained below 0.3%. Compared to the average rainfall seasons of 1995-1997, the below-normal seasons of 1998-2000 were characterized by a 79% reduction in total runoff and leachate flow and by a 93% reduction in corresponding metolachlor movement via these routes

Seasonal variation and climate change impact in Rainfall Erosivity across Europe

Science.gov (United States)

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

Seasonal rainfall-runoff relationships in a lowland forested watershed in the southeastern USA

Science.gov (United States)

Ileana La Torre Torres; Devendra Amatya; Ge Sun; Timothy Callahan

2011-01-01

Hydrological processes of lowland watersheds of the southern USA are not well understood compared to a hilly landscape due to their unique topography, soil compositions, and climate. This study describes the seasonal relationships between rainfall patterns and runoff (sum of storm flow and base flow) using 13 years (1964–1976) of rainfall and stream flow data for a low...

The Impact of a Amazonian Deforestation on Dry-Season Rainfall

Science.gov (United States)

Negri, Andrew J.; Adler, Robert F.; Xu, Liming; Surratt, Jason

2003-01-01

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

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

Science.gov (United States)

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

2018-03-01

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

Analysis and Modeling of Time-Correlated Characteristics of Rainfall-Runoff Similarity in the Upstream Red River Basin

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Xiuli Sang

2012-01-01

Full Text Available We constructed a similarity model (based on Euclidean distance between rainfall and runoff to study time-correlated characteristics of rainfall-runoff similar patterns in the upstream Red River Basin and presented a detailed evaluation of the time correlation of rainfall-runoff similarity. The rainfall-runoff similarity was used to determine the optimum similarity. The results showed that a time-correlated model was found to be capable of predicting the rainfall-runoff similarity in the upstream Red River Basin in a satisfactory way. Both noised and denoised time series by thresholding the wavelet coefficients were applied to verify the accuracy of model. And the corresponding optimum similar sets obtained as the equation solution conditions showed an interesting and stable trend. On the whole, the annual mean similarity presented a gradually rising trend, for quantitatively estimating comprehensive influence of climate change and of human activities on rainfall-runoff similarity.

Prediction of rainfall anomalies during the dry to wet transition season over the Southern Amazonia using machine learning tools

Science.gov (United States)

Shan, X.; Zhang, K.; Zhuang, Y.; Fu, R.; Hong, Y.

2017-12-01

Seasonal prediction of rainfall during the dry-to-wet transition season in austral spring (September-November) over southern Amazonia is central for improving planting crops and fire mitigation in that region. Previous studies have identified the key large-scale atmospheric dynamic and thermodynamics pre-conditions during the dry season (June-August) that influence the rainfall anomalies during the dry to wet transition season over Southern Amazonia. Based on these key pre-conditions during dry season, we have evaluated several statistical models and developed a Neural Network based statistical prediction system to predict rainfall during the dry to wet transition for Southern Amazonia (5-15°S, 50-70°W). Multivariate Empirical Orthogonal Function (EOF) Analysis is applied to the following four fields during JJA from the ECMWF Reanalysis (ERA-Interim) spanning from year 1979 to 2015: geopotential height at 200 hPa, surface relative humidity, convective inhibition energy (CIN) index and convective available potential energy (CAPE), to filter out noise and highlight the most coherent spatial and temporal variations. The first 10 EOF modes are retained for inputs to the statistical models, accounting for at least 70% of the total variance in the predictor fields. We have tested several linear and non-linear statistical methods. While the regularized Ridge Regression and Lasso Regression can generally capture the spatial pattern and magnitude of rainfall anomalies, we found that that Neural Network performs best with an accuracy greater than 80%, as expected from the non-linear dependence of the rainfall on the large-scale atmospheric thermodynamic conditions and circulation. Further tests of various prediction skill metrics and hindcasts also suggest this Neural Network prediction approach can significantly improve seasonal prediction skill than the dynamic predictions and regression based statistical predictions. Thus, this statistical prediction system could have

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

Science.gov (United States)

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.

Similarity-based multi-model ensemble approach for 1-15-day advance prediction of monsoon rainfall over India

Science.gov (United States)

Jaiswal, Neeru; Kishtawal, C. M.; Bhomia, Swati

2018-04-01

The southwest (SW) monsoon season (June, July, August and September) is the major period of rainfall over the Indian region. The present study focuses on the development of a new multi-model ensemble approach based on the similarity criterion (SMME) for the prediction of SW monsoon rainfall in the extended range. This approach is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional MME approaches. In this approach, the training dataset has been selected by matching the present day condition to the archived dataset and days with the most similar conditions were identified and used for training the model. The coefficients thus generated were used for the rainfall prediction. The precipitation forecasts from four general circulation models (GCMs), viz. European Centre for Medium-Range Weather Forecasts (ECMWF), United Kingdom Meteorological Office (UKMO), National Centre for Environment Prediction (NCEP) and China Meteorological Administration (CMA) have been used for developing the SMME forecasts. The forecasts of 1-5, 6-10 and 11-15 days were generated using the newly developed approach for each pentad of June-September during the years 2008-2013 and the skill of the model was analysed using verification scores, viz. equitable skill score (ETS), mean absolute error (MAE), Pearson's correlation coefficient and Nash-Sutcliffe model efficiency index. Statistical analysis of SMME forecasts shows superior forecast skill compared to the conventional MME and the individual models for all the pentads, viz. 1-5, 6-10 and 11-15 days.

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

Directory of Open Access Journals (Sweden)

A. Schepen

2018-03-01

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

The role of mesoscale convective systems in the diurnal cycle of rainfall and its seasonality over sub-Saharan Northern Africa

Science.gov (United States)

Liu, Weiran; Cook, Kerry H.; Vizy, Edward K.

2018-03-01

This study evaluates the role of MCSs in the total rainfall distribution as a function of season from a climatological perspective (1998-2014) over sub-Saharan northern Africa and examines how the diurnal cycle of rainfall changes with season. Tropical Rainfall Measuring Mission (TRMM) 3B42V7 rainfall estimates and European Centre for Medium-Range Weather Forecasts ERA-Interim reanalysis are used to evaluate the climatology. The percentages of the full TRMM precipitation delivered by MCSs have meridional structures in spring, fall and winter, ranging from 0 to 80% across sub-Saharan northern Africa, while the percentages are homogenous in summer (> 80%). The diurnal cycles of MCS-associated precipitation coincide with the full TRMM rainfall. Attributes of MCSs, including size, count, and intensity, vary synchronously with the diurnal cycle of rainfall. The diurnal peaks are classified into three categories: single afternoon peak, continuous afternoon peak, and nocturnal peak. Single afternoon peaks dominate in spring and fall while continuous afternoon and nocturnal peaks are more common in summer, indicating the seasonality of the diurnal cycle. The continuous afternoon peak combines rainfall from two system types—one locally-generated and one propagating. The seasonality of the diurnal cycle is related to the seasonality of MCS lifetimes, and propagation speeds and directions. The moisture component of the MSE profile contributes to the instability most in summer when convection is more frequent. Low-level temperature, which is related to surface warming and sensible heat fluxes, influences the instability more during winter and spring.

Relationship between summer monsoon rainfall and cyclogenesis over Bay of Bengal during post-monsoon (October-December) season

Digital Repository Service at National Institute of Oceanography (India)

Sadhuram, Y; Maneesha, K.

peak monsoon (October–November) season and concluded that the frequency of cyclones is modulated by negative and positive IOD rather than El-Nino and La-Nina. In this study, the relationship between southwest monsoon rainfall (June–September) and TNDC... Relationship between summer monsoon rainfall and cyclogenesis over Bay of Bengal during post-monsoon (October–December) season Y Sadhuram∗ and K Maneesha CSIR–National Institute of Oceanography, 176, Lawsons Bay Colony, Visakhapatnam 530 017, India...

Exploring changes in rainfall intensity and seasonal variability in the Southeastern U.S.: Stakeholder engagement, observations, and adaptation

Directory of Open Access Journals (Sweden)

Daniel R. Dourte

2015-01-01

Full Text Available The distribution of rainfall has major impacts in agriculture, affecting the soil, hydrology, and plant health in agricultural systems. The goal of this study was to test for recent changes in rainfall intensity and seasonal rainfall variability in the Southeastern U.S. by exploring the data collaboratively with agricultural stakeholders. Daily rainfall records from the Global Historical Climatology Network were used to analyze changes in rain intensity and seasonal rainfall variability. During the last 30 years (1985–2014, there has been a significant change (53% increase in the number of extreme rainfall days (>152.4 mm/day and there have been significant decreases in the number of moderate intensity (12.7–25.4 mm/day and heavy (25.4–76.2 mm/day rainfall days in the Southeastern U.S., when compared to the previous 30-year period (1955–1984. There have also been significant decreases in the return period of months in which greater than half of the monthly total rain occurred in a single day; this is an original, stakeholder-developed rainfall intensity metric. The variability in spring and summer rainfall increased during the last 30 years, but winter and fall showed less variability in seasonal totals in the last 30 years. In agricultural systems, rainfall is one of the leading factors affecting yield variability; so it can be expected that more variable rainfall and more intense rain events could bring new challenges to agricultural production. However, these changes can also present opportunities for producers who are taking measures to adjust management strategies to make their systems more resilient to increased rain intensity and variability.

Rainfall and its seasonality over the Amazon in the 21st century as assessed by the coupled models for the IPCC AR4

Science.gov (United States)

Li, Wenhong; Fu, Rong; Dickinson, Robert E.

2006-01-01

The global climate models for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4) predict very different changes of rainfall over the Amazon under the SRES A1B scenario for global climate change. Five of the eleven models predict an increase of annual rainfall, three models predict a decrease of rainfall, and the other three models predict no significant changes in the Amazon rainfall. We have further examined two models. The UKMO-HadCM3 model predicts an El Niño-like sea surface temperature (SST) change and warming in the northern tropical Atlantic which appear to enhance atmospheric subsidence and consequently reduce clouds over the Amazon. The resultant increase of surface solar absorption causes a stronger surface sensible heat flux and thus reduces relative humidity of the surface air. These changes decrease the rate and length of wet season rainfall and surface latent heat flux. This decreased wet season rainfall leads to drier soil during the subsequent dry season, which in turn can delay the transition from the dry to wet season. GISS-ER predicts a weaker SST warming in the western Pacific and the southern tropical Atlantic which increases moisture transport and hence rainfall in the Amazon. In the southern Amazon and Nordeste where the strongest rainfall increase occurs, the resultant higher soil moisture supports a higher surface latent heat flux during the dry and transition season and leads to an earlier wet season onset.

Projected changes of rainfall seasonality and dry spells in a high greenhouse gas emissions scenario

OpenAIRE

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

2016-01-01

In this diagnostic study we analyze changes of rainfall seasonality and dry spells by the end of the twenty-first century under the most extreme IPCC5 emission scenario (RCP8.5) as projected by twenty-four coupled climate models contributing to Coupled Model Intercomparison Project 5 (CMIP5). We use estimates of the centroid of the monthly rainfall distribution as an index of the rainfall timing and a threshold-independent, information theory-based quantity such as relative entropy (RE) to qu...

Seasonality in cholera dynamics: A rainfall-driven model explains the wide range of patterns in endemic areas

Science.gov (United States)

Baracchini, Theo; King, Aaron A.; Bouma, Menno J.; Rodó, Xavier; Bertuzzo, Enrico; Pascual, Mercedes

2017-10-01

Seasonal patterns in cholera dynamics exhibit pronounced variability across geographical regions, showing single or multiple peaks at different times of the year. Although multiple hypotheses related to local climate variables have been proposed, an understanding of this seasonal variation remains incomplete. The historical Bengal region, which encompasses the full range of cholera's seasonality observed worldwide, provides a unique opportunity to gain insights on underlying environmental drivers. Here, we propose a mechanistic, rainfall-temperature driven, stochastic epidemiological model which explicitly accounts for the fluctuations of the aquatic reservoir, and analyze with this model the historical dataset of cholera mortality in the Bengal region. Parameters are inferred with a recently developed sequential Monte Carlo method for likelihood maximization in partially observed Markov processes. Results indicate that the hydrological regime is a major driver of the seasonal dynamics of cholera. Rainfall tends to buffer the propagation of the disease in wet regions due to the longer residence times of water in the environment and an associated dilution effect, whereas it enhances cholera resurgence in dry regions. Moreover, the dynamics of the environmental water reservoir determine whether the seasonality is unimodal or bimodal, as well as its phase relative to the monsoon. Thus, the full range of seasonal patterns can be explained based solely on the local variation of rainfall and temperature. Given the close connection between cholera seasonality and environmental conditions, a deeper understanding of the underlying mechanisms would allow the better management and planning of public health policies with respect to climate variability and climate change.

Impact of rainfall interception on hydrologic partitioning and soil erosion in natural and managed seasonally dry ecosystems

Science.gov (United States)

Moura, A. E.; Montenegro, S. M.; Silva, B. B.; Bartlett, M. S.; Porporato, A. M.; Antonino, A. C.

2013-12-01

Quantifying the effects of land use change and rainfall variability in seasonal, dry ecosystems is crucial to sustainable management of soil and water resources. In particular, changes in rainfall interception effects on hydrologic partitioning and soil erosion due to land use change are among the least known processes, despite their importance for water resource managements, in terms of water availability for ecosystem and society and water quality and erosion problems. In this work we quantify the interception losses in different types of vegetation (coffee, lemon and vegetation of natural forest) found in the Tapacurá basin in the Pernambuco state of NE Brazil, coupling field experiments and analytical models. The interception losses were measured with rain gauges installed in three types of vegetation along with stemflow collectors. Close to the coffee plantation, a meteorological station was also installed for measurement of the necessary variables for the model calibrations. As expected, the results show that rainfall events of smaller magnitude proportionally have larger relative interception losses, with larger differences in the wet season. The model results also allow us to quantify the nonlinear behavior of the interception process, at the same time providing a valuable tool to estimate the interception loss due to changes in vegetation and rainfall regime and thus to improve water resource management in seasonally dry tropics .

South African mid-summer seasonal rainfall prediction performance by a coupled ocean-atmosphere model

CSIR Research Space (South Africa)

Landman, WA

2011-01-01

Full Text Available . 2000; Goddard and Mason, 2002). Such a so-called two-tiered procedure to predict the outcome of the rainfall season has been employed in South Africa for a number of years already (e.g., Landman et al., 2001). The advent of fully coupled ocean...

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

Science.gov (United States)

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

2015-04-01

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

Inter-annual rainfall variability in the eastern Antilles and coupling with the regional and intra-seasonal circulation

Science.gov (United States)

Jury, Mark R.

2016-11-01

Climate variability in the eastern Antilles island chain is analyzed via principal component analysis of high-resolution monthly rainfall in the period 1981-2013. The second mode reflecting higher rainfall in July-October season between Martinique and Grenada is the focus of this study. Higher rainfall corresponds with a weakened trade wind and boundary current along the southern edge of the Caribbean. This quells the coastal upwelling off Venezuela and builds the freshwater plume east of Trinidad. There is corresponding upper easterly wind flow that intensifies passing tropical waves. During a storm event over the Antilles on 4-5 October 2010, there was inflow from east of Guyana where low salinity and high sea temperatures enable surplus latent heat fluxes. A N-S convective rain band forms ˜500 km east of the cyclonic vortex. Many features at the weather timescale reflect the seasonal correlation and composite difference maps and El Nino Southern Oscillation (ENSO) modulation of oceanic inter-basin transfers.

A Comparative Frequency Analysis of Maximum Daily Rainfall for a SE Asian Region under Current and Future Climate Conditions

Directory of Open Access Journals (Sweden)

Velautham Daksiya

2017-01-01

Full Text Available The impact of changing climate on the frequency of daily rainfall extremes in Jakarta, Indonesia, is analysed and quantified. The study used three different models to assess the changes in rainfall characteristics. The first method involves the use of the weather generator LARS-WG to quantify changes between historical and future daily rainfall maxima. The second approach consists of statistically downscaling general circulation model (GCM output based on historical empirical relationships between GCM output and station rainfall. Lastly, the study employed recent statistically downscaled global gridded rainfall projections to characterize climate change impact rainfall structure. Both annual and seasonal rainfall extremes are studied. The results show significant changes in annual maximum daily rainfall, with an average increase as high as 20% in the 100-year return period daily rainfall. The uncertainty arising from the use of different GCMs was found to be much larger than the uncertainty from the emission scenarios. Furthermore, the annual and wet seasonal analyses exhibit similar behaviors with increased future rainfall, but the dry season is not consistent across the models. The GCM uncertainty is larger in the dry season compared to annual and wet season.

Trends in rainfall erosivity in NE Spain at annual, seasonal and daily scales, 1955–2006

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S. Beguería

2012-10-01

Full Text Available Rainfall erosivity refers to the ability of precipitation to erode soil, and depends on characteristics such as its total volume, duration, and intensity and amount of energy released by raindrops. Despite the relevance of rainfall erosivity for soil degradation prevention, very few studies have addressed its spatial and temporal variability. In this study the time variation of rainfall erosivity in the Ebro Valley (NE Spain is assessed for the period 1955–2006. The results show a general decrease in annual and seasonal rainfall erosivity, which is explained by a decrease of very intense rainfall events whilst the frequency of moderate and low events increased. This trend is related to prevailing positive conditions of the main atmospheric teleconnection indices affecting the West Mediterranean, i.e. the North Atlantic Oscillation (NAO, the Mediterranean Oscillation (MO and the Western Mediterranean Oscillation (WeMO.

Stochastic modelling of daily rainfall sequences

NARCIS (Netherlands)

Buishand, T.A.

1977-01-01

Rainfall series of different climatic regions were analysed with the aim of generating daily rainfall sequences. A survey of the data is given in I, 1. When analysing daily rainfall sequences one must be aware of the following points:
a. Seasonality. Because of seasonal variation

Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia

Directory of Open Access Journals (Sweden)

Yen Yi Loo

2015-11-01

Full Text Available Global warming and climate change is one of the most extensively researched and discussed topical issues affecting the environment. Although there are enough historical evidence to support the theory that climate change is a natural phenomenon, many research scientists are widely in agreement that the increase in temperature in the 20th century is anthropologically related. The associated effects are the variability of rainfall and cyclonic patterns that are being observed globally. In Southeast Asia the link between global warming and the seasonal atmospheric flow during the monsoon seasons shows varying degree of fuzziness. This study investigates the impact of climate change on the seasonality of monsoon Asia and its effect on the variability of monsoon rainfall in Southeast Asia. The comparison of decadal variation of precipitation and temperature anomalies before the 1970s found general increases which were mostly varying. But beyond the 1970s, global precipitation anomalous showed increases that almost corresponded with increases in global temperature anomalies for the same period. There are frequent changes and a shift westward of the Indian summer monsoon. Although precipitation is observed to be 70% below normal levels, in some areas the topography affects the intensity of rainfall. These shifting phenomenon of other monsoon season in the region are impacting on the variability of rainfall and the onset of monsoons in Southeast Asia and is predicted to delay for 15 days the onset of the monsoon in the future. The variability of monsoon rainfall in the SEA region is observed to be decadal and the frequency and intensity of intermittent flooding of some areas during the monsoon season have serious consequences on the human, financial, infrastructure and food security of the region.

Spatio-temporal variability and trends of precipitation and extreme rainfall events in Ethiopia in 1980-2010

Science.gov (United States)

Gummadi, Sridhar; Rao, K. P. C.; Seid, Jemal; Legesse, Gizachew; Kadiyala, M. D. M.; Takele, Robel; Amede, Tilahun; Whitbread, Anthony

2017-12-01

-eastern parts of Ethiopia extending to the south-west covering Somali and Oromia regions. Similar trends are also observed in the greatest 3-, 5- and 10-day rainfall amounts. Changes in the consecutive dry and wet days showed that consecutive wet days during Belg and Kiremt seasons decreased significantly in many areas in Ethiopia while consecutive dry days increased. The consistency in the trends over large spatial areas confirms the robustness of the trends and serves as a basis for understanding the projected changes in the climate. These results were discussed in relation to their significance to agriculture.

Uganda rainfall variability and prediction

Science.gov (United States)

Jury, Mark R.

2018-05-01

This study analyzes large-scale controls on Uganda's rainfall. Unlike past work, here, a May-October season is used because of the year-round nature of agricultural production, vegetation sensitivity to rainfall, and disease transmission. The Uganda rainfall record exhibits steady oscillations of ˜3 and 6 years over 1950-2013. Correlation maps at two-season lead time resolve the subtropical ridge over global oceans as an important feature. Multi-variate environmental predictors include Dec-May south Indian Ocean sea surface temperature, east African upper zonal wind, and South Atlantic wind streamfunction, providing a 33% fit to May-Oct rainfall time series. Composite analysis indicates that cool-phase El Niño Southern Oscillation supports increased May-Oct Uganda rainfall via a zonal overturning lower westerly/upper easterly atmospheric circulation. Sea temperature anomalies are positive in the east Atlantic and negative in the west Indian Ocean in respect of wet seasons. The northern Hadley Cell plays a role in limiting the northward march of the equatorial trough from May to October. An analysis of early season floods found that moist inflow from the west Indian Ocean converges over Uganda, generating diurnal thunderstorm clusters that drift southwestward producing high runoff.

Climatological studies on precipitation features and large-scale atmospheric fields on the heavy rainfall days in the eastern part of Japan from the Baiu to midsummer season

Science.gov (United States)

Matsumoto, Kengo; Kato, Kuranoshin; Otani, Kazuo

2017-04-01

more than 10mm/h was large in the southern half of the heavy rainfall area, moderate rain with less than 10 mm/h contributed greatly to the total rainfall in the northern half. In Patter B, that heavy rainfall area was located just in the area with strong low-level warm advection around the Baiu front to the east of the typhoon. The warm advection near the heavy rainfall area was also found in Pattern A, the heavy rainfall occurred just on the southwest of the large advection. It is noted that, although the very warm humid air can intrude northward by the strong S-ly wind to the east of the typhoon in both Pattern A and B, the low-level baroclinicity around the eastern Japan was stronger in Pattern B. In midsummer, the similar situations to while the "Pattern B"-like situation was not seen. This might be greatly reflected by the seasonal change in the southern boundary of the Okhotsk air mass from the Baiu to midsummer and we will also examine that in the future.

Interannual variability of seasonal rainfall over the Cape south coast of South Africa and synoptic type association

CSIR Research Space (South Africa)

Engelbrecht, CJ

2015-09-01

Full Text Available The link between interannual variability of seasonal rainfall over the Cape south coast of South Africa and different synoptic types as well as selected teleconnections is explored. Synoptic circulation over the region is classified into different...

Heavy daily-rainfall characteristics over the Gauteng Province

African Journals Online (AJOL)

2009-02-09

Feb 9, 2009 ... the lowest number of heavy and very heavy rainfall days. The highest 24-h ... With regard to seasonal rainfall, the 1995/96 summer rainfall season had ..... The Gauteng Province is approximately 16 500 km2 in size. When the ...

Caribbean Sea rainfall variability during the rainy season and relationship to the equatorial Pacific and tropical Atlantic SST

Energy Technology Data Exchange (ETDEWEB)

Wu, Renguang [Institute of Global Environment and Society, Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); Kirtman, Ben P. [University of Miami, Rosenstiel School of Marine and Atmospheric Sciences, Miami, FL (United States)

2011-10-15

The present study investigates the Caribbean Sea rainfall variability during the early and late rainy seasons and its association with sea surface temperature (SST) and air-sea interaction based on observational estimates, the NCEP Climate Forecast System (CFS) and Global Forecast System (GFS) simulations, and the CFS retrospective forecasts. Analysis of the observational estimates indicates that air-sea interaction is important over the Caribbean Sea, whereas the atmospheric forcing of SST dominates over the Gulf of Mexico. The CFS simulation captures the basic elements of this observed air-sea relationship. The GFS simulation produces spurious SST forcing of the atmosphere over the Gulf of Mexico largely due to prescribing SST. The CFS forecasts capture the air-sea relationship in the late rainy season (August-October), but cannot reproduce the SST forcing of atmosphere over the Caribbean Sea in the early rainy season (May-July). An empirical orthogonal function (EOF) analysis indicates that the leading modes of percent anomalies of the rainy season precipitation have the largest loading in the southern Caribbean Sea in observations. The model simulations and forecasts skillfully reproduce the spatial pattern, but not the temporal evolution. The Caribbean Sea rainfall variability in the early rainy season is mainly due to the tropical North Atlantic (TNA) SST anomalies in observations, is contributed by both the TNA and eastern equatorial Pacific (EEP) SST anomalies in the CFS simulation, and has an overly large impact from the EEP SST anomalies in the GFS simulation and the CFS forecasts. The observed Caribbean Sea rainfall variability in the late rainy season has a leading impact from the EEP SST anomalies, with a secondary contribution from the TNA SST anomalies. In comparison, the model simulations and forecasts overestimate the impacts of the EEP SST anomalies due to an earlier development and longer duration of the El Nino-Southern Oscillation in the CFS

Monthly Rainfall Erosivity Assessment for Switzerland

Science.gov (United States)

Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

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

Influence of the balance of the intertropical front on seasonal variations of the isotopic composition in rainfall at Kisiba Masoko (Rungwe Volcanic Province, SW, Tanzania).

Science.gov (United States)

Nivet, Fantine; Bergonzini, Laurent; Mathé, Pierre-Etienne; Noret, Aurélie; Monvoisin, Gaël; Majule, Amos; Williamson, David

2018-08-01

Tropical rainfall isotopic composition results from complex processes. The climatological and environmental variability in East Africa increases this complexity. Long rainfall isotope datasets are needed to fill the lack of observations in this region. At Kisiba Masoko, Tanzania, rainfall and rain isotopic composition have been monitored during 6 years. Mean year profiles allow to analyse the seasonal variations. The mean annual rainfall is 2099 mm with a rain-weighted mean composition of -3.2 ‰ for δ 18 O and -11.7 ‰ for δ 2 H. The results are consistent with available data although they present their own specificity. Thus, if the local meteoric water line is δ 2 H = 8.6 δ 18 O + 14.8, two seasonal lines are observed. The seasonality of the isotopic composition in rain and deuterium excess has been compared with precipitating air masses backtracking trajectories to characterize a simple scheme of vapour histories. The three major oceanic sources have two moisture signatures with their own trajectory histories: one originated from the tropical Indian Ocean at the beginning of the rainy season and one from the Austral Ocean at its end. The presented isotopic seasonality depends on the balance of the intertropical front and provides a useful dataset to improve the knowledge about local processes.

Impacts of climate change on rainfall, seasonal flooding, and evapotranspiration in the Okavango Delta, Botswana

Science.gov (United States)

Konecky, B. L.; Noone, D.; Mosimanyana, E.; Gondwe, M.

2016-12-01

The Okavango Delta in northern Botswana is one of the world's richest biodiversity hotspots. A UNESCO World Heritage Site, the Delta is known for its unique annual flood pulse, whereby the wetland and its neighboring river systems are inundated with waters that travel nearly 1000 km before reaching this subtropical, semi-arid destination. The livelihoods of northern Botswana's ecosystems and human populations rely on these floods to supplement the short and variable rainy season, which in many years is too minimal to ameliorate regional drought. However, anthropogenic climate change is reducing the amount of water that reaches the delta by increasing evaporation from soils and rivers, and transpiration by vegetation, during its long transit to Botswana. Future changes in rainfall patterns, extreme events, and increased upstream water use could exacerbate this water stress. Unfortunately, it remains difficult to assess the impacts of climate change on the delta because few data exist to constrain its complex climatic and seasonal water cycling regimes. This study presents a novel characterization of the water cycle in and around the Okavango Delta based on a survey of free-flowing surface waters, stagnant pools, precipitation, and groundwater carried out during the 2016 rainy and early-flood season. We use stable isotope and water quality data to assess local moisture sources, transport, evaporation, wetland flushing, and land-atmosphere exchanges, all of which are subject to change under global warming. We find a strong evaporation gradient and a progressive flushing of stagnant swamp waters along the northeastern and northwestern channels of the Delta. The evaporation gradient is more limited in nearby rivers with more limited wetlands. We contrast results with a survey of the Delta performed in the 1970's in order to assess changes over the past 40 years. Since some of these changes may arise from rainfall supply, we also present new analysis of rainfall moisture

Predicting watershed acidification under alternate rainfall conditions

International Nuclear Information System (INIS)

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, USA 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 soilwater 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 distributions of rainfall, or evapotranspiration will change net soil water flux and, consequently, will affect the dynamics of the acidification response to continued sulfate loading. 29 refs., 7 figs., 4 tabs

Quantifying Rainfall Interception Loss of a Subtropical Broadleaved Forest in Central Taiwan

Directory of Open Access Journals (Sweden)

Yi-Ying Chen

2016-01-01

Full Text Available The factors controlling seasonal rainfall interception loss are investigated by using a double-mass curve analysis, based on direct measurements of high-temporal resolution gross rainfall, throughfall and stemflow from 43 rainfall events that occurred in central Taiwan from April 2008 to April 2009. The canopy water storage capacity for the wet season was estimated to be 1.86 mm, about twice that for the dry season (0.91 mm, likely due to the large reduction in the leaf area index (LAI from 4.63 to 2.23 (m2·m−2. Changes in seasonal canopy structure and micro-meteorological conditions resulted in temporal variations in the amount of interception components, and rainfall partitioning into stemflow and throughfall. Wet canopy evaporation after rainfall contributed 41.8% of the wet season interception loss, but only 17.1% of the dry season interception loss. Wet canopy evaporation during rainfall accounted for 82.9% of the dry season interception loss, but only 58.2% of the wet season interception loss. Throughfall accounted for over 79.7% of the dry season precipitation and 76.1% of the wet season precipitation, possibly due to the change in gap fraction from 64.2% in the dry season to 50.0% in the wet season. The reduced canopy cover in the dry season also produced less stemflow than that of the wet season. The rainfall stemflow ratio ( P s f / P g was reduced from 12.6% to 8.9%. Despite relatively large changes in canopy structure, seasonal variation of the ratio of rainfall partitioned to interception was quite small. Rainfall interception loss accounted for nearly 12% of gross precipitation for both dry and wet seasons.

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

Science.gov (United States)

Lau, William K. M.; Wu, Jenny, H.-T.; Kim, Kyu-Myong

2012-01-01

Changes in rainfall characteristic induced by global warming are examined from outputs of IPCC AR5 models. Different scenarios of climate warming including a high emissions scenario (RCP 8.5), a medium mitigation scenario (RCP 4.5), and 1% per year CO2 increase are compared to 20th century simulations (historical). Results show that even though the spatial distribution of monthly rainfall anomalies vary greatly among models, the ensemble mean from a sizable sample (about 10) of AR5 models show a robust signal attributable to GHG warming featuring a shift in the global rainfall probability distribution function (PDF) with significant increase (>100%) in very heavy rain, reduction (10-20% ) in moderate rain and increase in light to very light rains. Changes in extreme rainfall as a function of seasons and latitudes are also examined, and are similar to the non-seasonal stratified data, but with more specific spatial dependence. These results are consistent from TRMM and GPCP rainfall observations suggesting that extreme rainfall events are occurring more frequently with wet areas getting wetter and dry-area-getting drier in a GHG induced warmer climate.

Understanding the evolution of the 2014–2016 summer rainfall seasons in southern Africa: Key lessons

Directory of Open Access Journals (Sweden)

Emma Rosa Mary Archer

2017-01-01

Full Text Available The recent 2015/16 summer rainfall season in the terrestrial Southern African Development Community (SADC region appears to be the most severe since the droughts of the early 1980s and 1990s; with well-publicized significant impacts on agriculture and food security. Impacts have been particularly concerning since the 2015/6 season followed a poor rainy season in 2014/15, in certain areas compounding already compromised production (total maize production was, for example, down 40% relative to the previous 5 year average. This paper reviews climate forecasts and observations of the two seasons, and presents examples of the resulting impacts on agriculture within the region. We conclude by considering what may be learnt from this experience, focussing on operational recommendations for early warning within SADC, as well as longstanding needs for awareness raising and capacity building.

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

Science.gov (United States)

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

2014-12-01

The prediction skills of climate model simulations in the western tropical Pacific (WTP) and East Asian region are assessed using the retrospective forecasts of seven state-of-the-art coupled models and their multi-model ensemble (MME) for boreal summers (June-August) during the period 1983-2005, along with corresponding observed and reanalyzed data. The prediction of summer rainfall anomalies in East Asia is difficult, while the WTP has a strong correlation between model prediction and observation. We focus on developing a new approach to further enhance the seasonal prediction skill for summer rainfall in East Asia and investigate the influence of convective activity in the WTP on East Asian summer rainfall. By analyzing the characteristics of the WTP convection, two distinct patterns associated with El Niño-Southern Oscillation (ENSO) developing and decaying modes are identified. Based on the multiple linear regression method, the East Asia Rainfall Index (EARI) is developed by using the interannual variability of the normalized Maritime continent-WTP indices (MPIs), as potentially useful predictors for rainfall prediction over East Asia, obtained from the above two main patterns. For East Asian summer rainfall, the EARI has superior performance to the East Asia summer monsoon index (EASMI) or each MP index (MPI). Therefore, the regressed rainfall from EARI also shows a strong relationship with the observed East Asian summer rainfall pattern. In addition, we evaluate the prediction skill of the East Asia reconstructed rainfall obtained by statistical-empirical approach using the cross-validated EARI from the individual models and their MME. The results show that the rainfalls reconstructed from simulations capture the general features of observed precipitation in East Asia quite well. This study convincingly demonstrates that rainfall prediction skill is considerably improved by using the statistical-empirical method compared to the dynamical models

ENSO modulation of seasonal rainfall and extremes in Indonesia

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Supari; Tangang, Fredolin; Salimun, Ester; Aldrian, Edvin; Sopaheluwakan, Ardhasena; Juneng, Liew

2017-12-01

This paper provides a detailed description of how ENSO events affect seasonal and extreme precipitation over Indonesia. Daily precipitation data from 97 stations across Indonesia covering the period from 1981 to 2012 were used to investigate the effects of El Niño and La Niña on extreme precipitation characteristics including intensity, frequency and duration, as defined based on a subset of the Expert Team on Climate Change Detection and Indices (ETCCDI). Although anomalous signals in these three indices were consistent with those of total rainfall, anomalies in the duration of extremes [i.e., consecutive dry days (CDD) and consecutive wet days (CWD)] were much more robust. El Niño impacts were particularly prominent during June-July-August (JJA) and September-October-November (SON), when anomalously dry conditions were experienced throughout the country. However, from SON, a wet anomaly appeared over northern Sumatra, later expanding eastward during December-January-February (DJF) and March-April-May (MAM), creating contrasting conditions of wet in the west and dry in the east. We attribute this apparent eastward expansion of a wet anomaly during El Niño progression to the equatorial convergence of two anti-cyclonic circulations, one residing north of the equator and the other south of the equator. These anti-cyclonic circulations strengthen and weaken according to seasonal changes and their coupling with regional seas, hence shaping moisture transport and convergence. During La Niña events, the eastward expansion of an opposite (i.e., dry) anomaly was also present but less prominent than that of El Niño. We attribute this to differences in regional ocean—atmosphere coupling, which result in the contrasting seasonal evolution of the two corresponding anomalous cyclonic circulations and in turn suggests the strong nonlinearity of El Niño and La Niña responses over the Maritime Continent. Based on the seasonal behaviour of anomalous CDD and CWD, we

Regionalization of monthly rainfall erosivity patternsin Switzerland

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

Science.gov (United States)

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

2017-10-01

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

Persistence Characteristics of Australian Rainfall Anomalies

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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.

Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

Science.gov (United States)

White, C. J.; Franks, S. W.; McEvoy, D.

2015-06-01

Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

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

Science.gov (United States)

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.

Synchrony, compensatory dynamics, and the functional trait basis of phenological diversity in a tropical dry forest tree community: effects of rainfall seasonality

Science.gov (United States)

Lasky, Jesse R.; Uriarte, María; Muscarella, Robert

2016-11-01

Interspecific variation in phenology is a key axis of functional diversity, potentially mediating how communities respond to climate change. The diverse drivers of phenology act across multiple temporal scales. For example, abiotic constraints favor synchronous reproduction (positive covariance among species), while biotic interactions can favor synchrony or compensatory dynamics (negative covariance). We used wavelet analyses to examine phenology of community flower and seed production for 45 tree species across multiple temporal scales in a tropical dry forest in Puerto Rico with marked rainfall seasonality. We asked three questions: (1) do species exhibit synchronous or compensatory temporal dynamics in reproduction, (2) do interspecific differences in phenology reflect variable responses to rainfall, and (3) is interspecific variation in phenology and response to a major drought associated with functional traits that mediate responses to moisture? Community-level flowering was synchronized at seasonal scales (˜5-6 mo) and at short scales (˜1 mo, following rainfall). However, seed rain exhibited significant compensatory dynamics at intraseasonal scales (˜3 mo), suggesting interspecific variation in temporal niches. Species with large leaves (associated with sensitivity to water deficit) peaked in reproduction synchronously with the peak of seasonal rainfall (˜5 mo scale). By contrast, species with high wood specific gravity (associated with drought resistance) tended to flower in drier periods. Flowering of tall species and those with large leaves was most tightly linked to intraseasonal (˜2 mo scale) rainfall fluctuations. Although the 2015 drought dramatically reduced community-wide reproduction, functional traits were not associated with the magnitude of species-specific declines. Our results suggest opposing drivers of synchronous versus compensatory dynamics at different temporal scales. Phenology associations with functional traits indicated that

Optimization of rainfall networks using information entropy and temporal variability analysis

Science.gov (United States)

Wang, Wenqi; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-04-01

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

Using subseasonal-to-seasonal (S2S extreme rainfall forecasts for extended-range flood prediction in Australia

Directory of Open Access Journals (Sweden)

C. J. White

2015-06-01

Full Text Available Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal. Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

Rainfall: Features and Variations over Saudi Arabia, A Review

Directory of Open Access Journals (Sweden)

Hosny Hasanean

2015-08-01

Full Text Available The Saudi Arabia (SA climate varies greatly, depending on the geography and the season. According to K ppen and Geiger, the climates of SA is “desert climate”. The analysis of the seasonal rainfall detects that spring and winter seasons have the highestrainfall incidence, respectively. Through the summer,small quantities of precipitation are observed, while autumn received more precipitation more than summer season considering the total annual rainfall. In all seasons, the SW area receives rainfall, with a maximum in spring, whereas in the summer season, the NE and NW areas receive very little quantities of precipitation. The Rub Al-Khali (the SE region is almost totally dry. The maximum amount of annual rainfall does not always happen at the highest elevation. Therefore, the elevation is not the only factor in rainfall distribution.A great inter-annual change in the rainfall over the SA for the period (1978–2009 is observed. In addition, in the same period, a linear decreasing trend is found in the observed rainfall, whilst in the recent past (1994–2009 a statistically significant negative trend is observed. In the Southern part of the Arabian Peninsula (AP and along the coast of the Red Sea, it is interesting to note that rainfall increased, whilst it decreased over most areas of SA during the 2000–2009 decade, compared to 1980–1989.Statistical and numerical models are used to predict rainfall over Saudi Arabia (SA. The statistical models based on stochastic models of ARIMA and numerical models based on Providing Regional Climates for Impact Studies of Hadley Centre (PRECIS. Climate and its qualitative character and quantified range of possible future changes are investigated. The annual total rainfall decreases in most regions of the SA and only increases in the south. The summertime precipitation will be the highest between other seasons over the southern, the southwestern provinces and Asir mountains, while the wintertime

A northern Australian coral record of seasonal rainfall and terrestrial runoff (1775-1986)

Science.gov (United States)

Patterson, E. W.; Cole, J. E.; Vetter, L.; Lough, J.

2017-12-01

Northern Australia is a climatically dynamic region influenced by both the El Niño-Southern Oscillation (ENSO) and the Australian monsoon. However, this region is largely devoid of long climate records with sub-annual resolution. Understanding long-term climate variations is essential to assess how the storm-prone coasts and rainfall-reliant rangelands of northern Australia have been impacted in the past and may be in the future. In this study, we present a continuous multicentury (1775-1986) coral reconstruction of rainfall and hydroclimate in northern Australia, developed from a Porites spp. coral core collected off the coast of Darwin, Northern Territory, Australia. We combined Ba/Ca measurements with luminescence data as tracers of terrestrial erosion and river discharge respectively. Our results show a strong seasonal cycle in Ba/Ca linked to wet austral summers driven by the Australian monsoon. The Ba/Ca record is corroborated by oxygen isotope data from the same coral and indices of regional river discharge and rainfall. Consistently high levels of Ba measured throughout the record further attest to the importance of river influence on this coral. Our record also shows changes in variability and the baseline level of Ba in coastal waters through time, which may be driven in part by historical land-use change, such as damming or agricultural practices. We will additionally use these records to examine decadal to centennial-scale variability in monsoonal precipitation and regional ENSO signals.

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

Wu, F.; Cui, X.; Zhang, D. L.; Lin, Q.

2017-12-01

The relationship between lightning activity and rainfall associated with 2925 short-duration rainfall (SDR) events over the Beijing metropolitan region (BMR) is examined during the warm seasons of 2006-2007, using the cloud-to-ground (CG) and intracloud (IC) lightning data from Surveillance et Alerte Foudre par Interférometrie Radioélectrique (SAFIR)-3000 and 5-min rainfall data from automatic weather stations (AWSs). To facilitate the analysis of the rainfall-lightning correlations, the SDR events are categorized into six different intensity grades according to their hourly rainfall rates (HRRs), and an optimal radius of 10 km from individual AWSs for counting their associated lightning flashes is used. Results show that the lightning-rainfall correlations vary significantly with different intensity grades. Weak correlations (R 0.4) are found in the weak SDR events, and 40-50% of the events are no-flash ones. And moderate correlation (R 0.6) are found in the moderate SDR events, and > 10-20% of the events are no-flash ones. In contrast, high correlations (R 0.7) are obtained in the SDHR events, and < 10% of the events are no-flash ones. The results indicate that lightning activity is observed more frequently and correlated more robust with the rainfall in the SDHR events. Significant time lagged correlations between lightning and rainfall are also found. About 80% of the SDR events could reach their highest correlation coefficients when the associated lightning flashes shift at time lags of < 25 min before and after rainfall begins. The percentages of SDR events with CG or total lightning activity preceding, lagging or coinciding with rainfall shows that (i) in about 55% of the SDR events lightning flashes preceded rainfall; (ii) the SDR events with lightning flashes lagging behind rainfall accounted for about 30%; and (iii) the SDR events without any time shifts accounted for the remaining 15%. Better lightning-rainfall correlations can be attained when time

Hydrologic and Erosional Response to Natural Rainfall and Effects of Conservation and Rehabilitation Measures in a Degraded Dry Sub-Humid Watershed of the Ethiopian Highlands

Science.gov (United States)

McHugh, O. V.; Liu, B. M.; Steenhuis, T. S.

2005-12-01

moderate rainfall intensities, but tied ridges performed similarly or worse than conventional tillage during seasons with many high intensity storms and on steep slopes (> 9 %). Subsoiling performed statistically similar to tillage with the conventional maresha plow, but considerably increased soil loss rates on moderate and steep slopes (3-11 %).

10 Characterisation of Seasonal Rainfall.cdr

African Journals Online (AJOL)

Administrator

El Nino-South Oscillation (ENSO) phenomenon occurs in the Equatorial Eastern Pacific Ocean and has been noted to ... of crops. There is need for more research attention on the onset of rainfall and ... impacts of adverse weather conditions or.

How El-Nino affects Ethiopian summer rainfall

Science.gov (United States)

Gleixner, Stephanie; Keenlyside, Noel; Viste, Ellen

2016-04-01

Ethiopian economy and society are strongly dependent on agriculture and therefore rainfall. Reliable forecasts for the rainy seasons are important to allow for agricultural planning and drought preparations. The operational seasonal forecasts for Ethiopia are based on analogue methods relying mainly on sea surface temperature (SST) indices. A better understanding of the physical links between Ethiopian rainfall and SST may help to improve forecasts. The highest rainfall rates are observed in the Kiremt season (defined as JJAS), which is the rainy season in Central and Northwestern Ethiopia. Kiremt rainfall shows clear negative correlation with Central Pacific SST, linking dry Ethiopian summers with ENSO-like warm SST anomalies. We use the atmosphere general circulation model Echam5.3 to investigate the physical link between Pacific SST anomalies and Kiremt rainfall. We compare a historical simulation with a T106 horizontal resolution (~ 1.125°), forced with reconstructed SST data, to gauge-based rainfall observations for the time period of 1961 to 2009. Composite analysis for model and observations show warm SST anomalies in the Central Pacific and a corresponding large-scale circulation anomaly with subsidence over Ethiopia in dry Kiremt seasons. Horizontal wind fields show a slow-down of the whole Indian monsoon system with a weaker Tropical Easterly Jet (TEJ) and a weaker East African Low-Level Jet (EALLJ) in these summers. We conducted a sensitivity experiment with El Nino like SST anomalies in the Central Pacific with the same Echam version. Its results show that warm Pacific SST anomalies cause dry summer conditions over Ethiopia. While the large-scale subsidence over East Africa is present in the experiment, there is no significant weakening of the Indian monsoon system. We rather find an anomalous circulation cell over Northern Africa with westerlies at 100-200 hPa and easterlies below 500 hPa. The anomalous easterly flow in the lower and middle

An Atlantic influence on Amazon rainfall

Energy Technology Data Exchange (ETDEWEB)

Yoon, Jin-Ho [University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States); Zeng, Ning [University of Maryland, Earth System Science Interdisciplinary Center, College Park, MD (United States); University of Maryland, Department of Atmospheric and Oceanic Science, College Park, MD (United States)

2010-02-15

Rainfall variability over the Amazon basin has often been linked to variations in Pacific sea surface temperature (SST), and in particular, to the El Nino/Southern Oscillation (ENSO). However, only a fraction of Amazon rainfall variability can be explained by ENSO. Building upon the recent work of Zeng (Environ Res Lett 3:014002, 2008), here we provide further evidence for an influence on Amazon rainfall from the tropical Atlantic Ocean. The strength of the North Atlantic influence is found to be comparable to the better-known Pacific ENSO connection. The tropical South Atlantic Ocean also shows some influence during the wet-to-dry season transition period. The Atlantic influence is through changes in the north-south divergent circulation and the movement of the ITCZ following warm SST. Therefore, it is strongest in the southern part of the Amazon basin during the Amazon's dry season (July-October). In contrast, the ENSO related teleconnection is through anomalous east-west Walker circulation with largely concentrated in the eastern (lower) Amazon. This ENSO connection is seasonally locked to boreal winter. A complication due to the influence of ENSO on Atlantic SST causes an apparent North Atlantic SST lag of Amazon rainfall. Removing ENSO from North Atlantic SST via linear regression resolves this causality problem in that the residual Atlantic variability correlates well and is in phase with the Amazon rainfall. A strong Atlantic influence during boreal summer and autumn is particularly significant in terms of the impact on the hydro-ecosystem which is most vulnerable during the dry season, as highlighted by the severe 2005 Amazon drought. Such findings have implications for both seasonal-interannual climate prediction and understanding the longer-term changes of the Amazon rainforest. (orig.)

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

Science.gov (United States)

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

2015-10-01

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

Does GPM-based multi-satellite precipitation enhance rainfall estimates over Pakistan and Bolivia arid regions?

Science.gov (United States)

Hussain, Y.; Satgé, F.; Bonnet, M. P.; Pillco, R.; Molina, J.; Timouk, F.; Roig, H.; Martinez-Carvajal, H., Sr.; Gulraiz, A.

2016-12-01

Arid regions are sensitive to rainfall variations which are expressed in the form of flooding and droughts. Unfortunately, those regions are poorly monitored and high quality rainfall estimates are still needed. The Global Precipitation Measurement (GPM) mission released two new satellite rainfall products named Integrated Multisatellite Retrievals GPM (IMERG) and Global Satellite Mapping of Precipitation version 6 (GSMaP-v6) bringing the possibility of accurate rainfall monitoring over these countries. This study assessed both products at monthly scale over Pakistan considering dry and wet season over the 4 main climatic zones from 2014 to 2016. With similar climatic conditions, the Altiplano region of Bolivia is considered to quantify the influence of big lakes (Titicaca and Poopó) in rainfall estimates. For comparison, the widely used TRMM-Multisatellite Precipitation Analysis 3B43 (TMPA-3B43) version 7 is also involved in the analysis to observe the potential enhancement in rainfall estimate brought by GPM products. Rainfall estimates derived from 110 rain-gauges are used as reference to compare IMERG, GSMaP-v6 and TMPA-3B43 at the 0.1° and 0.25° spatial resolution. Over both regions, IMERG and GSMaP-v6 capture the spatial pattern of precipitation as well as TMPA-3B43. All products tend to over estimates rainfall over very arid regions. This feature is even more marked during dry season. However, during this season, both reference and estimated rainfall remain very low and do not impact seasonal water budget computation. On a general way, IMERG slightly outperforms TMPA-3B43 and GSMaP-v6 which provides the less accurate rainfall estimate. The TMPA-3B43 rainfall underestimation previously found over Lake Titicaca is still observed in IMERG estimates. However, GSMaP-v6 considerably decreases the underestimation providing the most accurate rainfall estimate over the lake. MOD11C3 Land Surface Temperature (LST) and ASTER Global Emissivity Dataset reveal strong

Projected changes of rainfall event characteristics for the Czech Republic

Directory of Open Access Journals (Sweden)

Svoboda Vojtěch

2016-12-01

Full Text Available Projected changes of warm season (May–September rainfall events in an ensemble of 30 regional climate model (RCM simulations are assessed for the Czech Republic. Individual rainfall events are identified using the concept of minimum inter-event time and only heavy events are considered. The changes of rainfall event characteristics are evaluated between the control (1981–2000 and two scenario (2020–2049 and 2070–2099 periods. Despite a consistent decrease in the number of heavy rainfall events, there is a large uncertainty in projected changes in seasonal precipitation total due to heavy events. Most considered characteristics (rainfall event depth, mean rainfall rate, maximum 60-min rainfall intensity and indicators of rainfall event erosivity are projected to increase and larger increases appear for more extreme values. Only rainfall event duration slightly decreases in the more distant scenario period according to the RCM simulations. As a consequence, the number of less extreme heavy rainfall events as well as the number of long events decreases in majority of the RCM simulations. Changes in most event characteristics (and especially in characteristics related to the rainfall intensity depend on changes in radiative forcing and temperature for the future periods. Only changes in the number of events and seasonal total due to heavy events depend significantly on altitude.

Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

Science.gov (United States)

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

2017-11-01

This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

Rainfall and crop modeling-based water stress assessment for rainfed maize cultivation in peninsular India

Science.gov (United States)

Manivasagam, V. S.; Nagarajan, R.

2018-04-01

Water stress due to uneven rainfall distribution causes a significant impact on the agricultural production of monsoon-dependent peninsular India. In the present study, water stress assessment for rainfed maize crop is carried out for kharif (June-October) and rabi (October-February) cropping seasons which coincide with two major Indian monsoons. Rainfall analysis (1976-2010) shows that the kharif season receives sufficient weekly rainfall (28 ± 32 mm) during 26th-39th standard meteorological weeks (SMWs) from southwest monsoon, whereas the rabi season experiences a major portion of its weekly rainfall due to northeast monsoon between the 42nd and 51st SMW (31 ± 42 mm). The later weeks experience minimal rainfall (5.5 ± 15 mm) and thus expose the late sown maize crops to a severe water stress during its maturity stage. Wet and dry spell analyses reveal a substantial increase in the rainfall intensity over the last few decades. However, the distribution of rainfall shows a striking decrease in the number of wet spells, with prolonged dry spells in both seasons. Weekly rainfall classification shows that the flowering and maturity stages of kharif maize (33rd-39th SMWs) can suffer around 30-40% of the total water stress. In the case of rabi maize, the analysis reveals that a shift in the sowing time from the existing 42nd SMW (16-22 October) to the 40th SMW (1-7 October) can avoid terminal water stress. Further, AquaCrop modeling results show that one or two minimal irrigations during the flowering and maturity stages (33rd-39th SMWs) of kharif maize positively avoid the mild water stress exposure. Similarly, rabi maize requires an additional two or three lifesaving irrigations during its flowering and maturity stages (48th-53rd SMWs) to improve productivity. Effective crop planning with appropriate sowing time, short duration crop, and high yielding drought-resistant varieties will allow for better utilization of the monsoon rain, thus reducing water stress with

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

Science.gov (United States)

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.

Rainfall and runoff characteristics of Namman Basin in the Kingdom of Saudi Arabia

International Nuclear Information System (INIS)

Al-Wagdany, A.S.

2008-01-01

Namman basin is an arid mountainous basin located in the western region of Saudi Arabia and has drainage area of about 650 km2. Namman unconfined groundwater aquifer is the source of water to the historic underground galleries known as Ain Zubaidah. The galleries became dry due to the fall of groundwater levels dramatically in the last few decades. The galleries can only be restored only if a proper water resources management is utilized in the basin. The aim of this research is to investigate two major hydrological components, namely rainfall and runoff, which are essential for a proper management of the water resources of the basin. Rainfall and runoff records for ten rain gauge stations and one runoff gauge station are used to investigate major characteristics of rainfall and runoff in Namman basin. Rainfall records are analyzed to derive conclusion about rainfall occurrence, depth duration, temporal distribution and extreme values. The relation between rainfall depth and elevation is also investigated. Runoff records are utilized to investigate seasonal variation of runoff. Values of runoff coefficient for all runoff events are computed and the relation between rainfall and runoff for the basin are discussed. The results show that there are more than 30 rainstorms per year and only about two runoff events are usually observed. The temporal analysis of rainfall and runoff indicates that there are two rainy seasons, one is during fall and winter season and other is during spring seasons while runoff is mainly observed in the winter season and the other is during spring seasons while runoff is mainly observed in the winter season. Values of runoff coefficient were very low with mean value of 0.013, which indicate that most rainfall infiltrate through the alluvial channels of the basin. (author)

Hydrological similarity approach and rainfall satellite utilization for mini hydro power dam basic design (case study on the ungauged catchment at West Borneo, Indonesia)

Science.gov (United States)

Prakoso, W. G.; Murtilaksono, K.; Tarigan, S. D.; Purwanto, Y. J.

2018-05-01

An approach on flow duration and flood design estimation on the ungauged catchment with no rainfall and discharge data availability was been being develop with hydrological modelling including rainfall run off model implemented with watershed characteristic dataset. Near real time Rainfall data from multi satellite platform e.g. TRMM can be utilized for regionalization approach on the ungauged catchment. Watershed hydrologically similarity analysis were conducted including all of the major watershed in Borneo which was predicted to be similar with the Nanga Raun Watershed. It was found that a satisfactory hydrological model calibration could be achieved using catchment weighted time series of TRMM daily rainfall data, performed on nearby catchment deemed to be sufficiently similar to Nanga Raun catchment in hydrological terms. Based on this calibration, rainfall runoff parameters were then transferred to a model. Relatively reliable flow duration curve and extreme discharge value estimation were produced with reasonable several limitation. Further approach may be performed in order to deal with the primary limitations inherent in the hydrological and statistical analysis, especially to give prolongation to the availability of the rainfall and climate data with some novel approach like downscaling of global climate model.

Gridded daily Indian monsoon rainfall for 14 seasons: Merged ...

Indian Academy of Sciences (India)

Indian monsoon is an important component of earth's climate system. Daily rainfall data for longer period is vital to study components and processes related to Indian monsoon. Daily observed gridded rainfall data covering both land and adjoining oceanic regions are required for numerical model vali- dation and model ...

River catchment rainfall series analysis using additive Holt-Winters method

Science.gov (United States)

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.

Seasonal rainfall predictability over the Lake Kariba catchment area ...

African Journals Online (AJOL)

Retroactive forecasts are produced for lead times of up to 5 months and probabilistic forecast performances evaluated for extreme rainfall thresholds of the 25th and 75th percentile values of the climatological record. The verification of the retroactive forecasts shows that rainfall over the catchment is predictable at extended ...

Dry spell, onset and cessation of the wet season rainfall in the Upper Baro-Akobo Basin, Ethiopia

Science.gov (United States)

Kebede, Asfaw; Diekkrüger, Bernd; Edossa, Desalegn C.

2017-08-01

In this study, maximum dry spell length and number of dry spell periods of rainy seasons in the upper Baro-Akobo River basin which is a part of the Nile basin, Western Ethiopia, were investigated to analyse the drought trend. Daily rainfall records of the period 1972-2000 from eight rain gauge stations were used in the analysis, and Mann-Kendall test was used to test trends for significance. Furthermore, the beginning and end of the trend development in the dry spell were also tested using the sequential version of Mann-Kendall test. Results have shown that there is neither clear monotonic trend found in dry spell for the basin nor significant fluctuation in the onset, cession and duration of rainfall in the Baro-Akobo river basin. This sufficiently explains why rain-fed agriculture has suffered little in the western part of Ethiopia. The predictable nature of dry spell pattern may have allowed farmers to adjust to rainfall variability in the basin. Unlike many parts of Ethiopia, the Baro-Akobo basin climate variability is not a limiting factor for rain-fed agriculture productivity which may contribute significantly to national food security.

Enhancement of vegetation-rainfall feedbacks on the Australian summer monsoon by the Madden-Julian Oscillation

Science.gov (United States)

Notaro, Michael

2018-01-01

A regional climate modeling analysis of the Australian monsoon system reveals a substantial modulation of vegetation-rainfall feedbacks by the Madden Julian Oscillation (MJO), both of which operate at similar sub-seasonal time scales, as evidence that the intensity of land-atmosphere interactions is sensitive to the background atmospheric state. Based on ensemble experiments with imposed modification of northern Australian leaf area index (LAI), the atmospheric responses to LAI anomalies are composited for negative and positive modes of the propagating MJO. In the regional climate model (RCM), northern Australian vegetation feedbacks are characterized by evapotranspiration (ET)-driven rainfall responses, with the moisture feedback mechanism dominating over albedo and roughness feedback mechanisms. During November-April, both Tropical Rainfall Measuring Mission and RCM data reveal MJO's pronounced influence on rainfall patterns across northern Australia, tropical Indian Ocean, Timor Sea, Arafura Sea, and Gulf of Carpentaria, with the MJO dominating over vegetation feedbacks in terms of regulating monsoon rainfall variability. Convectively-active MJO phases support an enhancement of positive vegetation feedbacks on monsoon rainfall. While the MJO imposes minimal regulation of ET responses to LAI anomalies, the vegetation feedback-induced responses in precipitable water, cloud water, and rainfall are greatly enhanced during convectively-active MJO phases over northern Australia, which are characterized by intense low-level convergence and efficient precipitable water conversion. The sub-seasonal response of vegetation-rainfall feedback intensity to the MJO is complex, with significant enhancement of rainfall responses to LAI anomalies in February during convectively-active MJO phases compared to minimal modulation by the MJO during prior and subsequent calendar months.

Analysis of Spatiotemporal Statistical Properties of Rainfall in the Phoenix Metropolitan Area

Science.gov (United States)

Mascaro, G.

2016-12-01

The analysis of the rainfall statistical properties at multiple spatiotemporal scales is a necessary preliminary step to support modeling of urban hydrology, including flood prediction and simulation of impacts of land use changes. In this contribution, the rainfall statistical properties are analyzed in the Phoenix Metropolitan area and its surroundings ( 29600 km2) in Arizona using observations from 310 gauges of the Flood Control District of the Maricopa County network. Different techniques are applied to investigate the rainfall properties at temporal scales from 1 min to years and to quantify the associated spatial variability. Results reveal the following. The rainfall regime is characterized by high interannual variability, which is partially explained by teleconnections with El Niño Southern Oscillation, and marked seasonality, with two maxima in the monsoon season from July to September and in winter from November to March. Elevation has a significant control on seasonal rainfall accumulation, strength of thermal convective activity during the monsoon, and peak occurrence of the rainfall diurnal cycle present in summer. The spatial correlation of wintertime rainfall is high even at short aggregation times (cells).

From TRMM to GPM: How well can heavy rainfall be detected from space?

Science.gov (United States)

Prakash, Satya; Mitra, Ashis K.; Pai, D. S.; AghaKouchak, Amir

2016-02-01

In this study, we investigate the capabilities of the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and the recently released Integrated Multi-satellitE Retrievals for GPM (IMERG) in detecting and estimating heavy rainfall across India. First, the study analyzes TMPA data products over a 17-year period (1998-2014). While TMPA and reference gauge-based observations show similar mean monthly variations of conditional heavy rainfall events, the multi-satellite product systematically overestimates its inter-annual variations. Categorical as well as volumetric skill scores reveal that TMPA over-detects heavy rainfall events (above 75th percentile of reference data), but it shows reasonable performance in capturing the volume of heavy rain across the country. An initial assessment of the GPM-based multi-satellite IMERG precipitation estimates for the southwest monsoon season shows notable improvements over TMPA in capturing heavy rainfall over India. The recently released IMERG shows promising results to help improve modeling of hydrological extremes (e.g., floods and landslides) using satellite observations.

Comparative Study of Monsoon Rainfall Variability over India and the Odisha State

Directory of Open Access Journals (Sweden)

K C Gouda

2017-10-01

Full Text Available Indian summer monsoon (ISM plays an important role in the weather and climate system over India. The rainfall during monsoon season controls many sectors from agriculture, food, energy, and water, to the management of disasters. Being a coastal province on the eastern side of India, Odisha is one of the most important states affected by the monsoon rainfall and associated hydro-meteorological systems. The variability of monsoon rainfall is highly unpredictable at multiple scales both in space and time. In this study, the monsoon variability over the state of Odisha is studied using the daily gridded rainfall data from India Meteorological Department (IMD. A comparative analysis of the behaviour of monsoon rainfall at a larger scale (India, regional scale (Odisha, and sub-regional scale (zones of Odisha is carried out in terms of the seasonal cycle of monsoon rainfall and its interannual variability. It is seen that there is no synchronization in the seasonal monsoon category (normal/excess/deficit when analysed over large (India and regional (Odisha scales. The impact of El Niño, La Niña, and the Indian Ocean Dipole (IOD on the monsoon rainfall at both scales (large scale and regional scale is analysed and compared. The results show that the impact is much more for rainfall over India, but it has no such relation with the rainfall over Odisha. It is also observed that there is a positive (negative relation of the IOD with the seasonal monsoon rainfall variability over Odisha (India. The correlation between the IAV of monsoon rainfall between the large scale and regional scale was found to be 0.46 with a phase synchronization of 63%. IAV on a sub-regional scale is also presented.

Rainfall Distributions in Sri Lanka in Time and Space: An Analysis Based on Daily Rainfall Data

Directory of Open Access Journals (Sweden)

T. P. Burt

2014-09-01

Full Text Available Daily rainfall totals are analyzed for the main agro-climatic zones of Sri Lanka for the period 1976–2006. The emphasis is on daily rainfall rather than on longer-period totals, in particular the number of daily falls exceeding given threshold totals. For one station (Mapalana, where a complete daily series is available from 1950, a longer-term perspective on changes over half a century is provided. The focus here is particularly on rainfall in March and April, given the sensitivity of agricultural decisions to early southwest monsoon rainfall at the beginning of the Yala cultivation season but other seasons are also considered, in particular the northeast monsoon. Rainfall across Sri Lanka over three decades is investigated in relation to the main atmospheric drivers known to affect climate in the region: sea surface temperatures in the Pacific and Indian Oceans, of which the former are shown to be more important. The strong influence of El Niño and La Niña phases on various aspects of the daily rainfall distribution in Sri Lanka is confirmed: positive correlations with Pacific sea-surface temperatures during the north east monsoon and negative correlations at other times. It is emphasized in the discussion that Sri Lanka must be placed in its regional context and it is important to draw on regional-scale research across the Indian subcontinent and the Bay of Bengal.

Wheat yield vulnerability: relation to rainfall and suggestions for adaptation

Directory of Open Access Journals (Sweden)

Khalid Tafoughalti

2018-04-01

Full Text Available Wheat production is of paramount importance in the region of Meknes, which is mainly produced under rainfed conditions. It is the dominant cereal, the greater proportion being the soft type. During the past few decades, rainfall flaws have caused a number of cases of droughts. These flaws have seriously affecting wheat production. The main objective of this study is the assessment of rainfall variability at monthly, seasonal and annual scales and to determine their impact on wheat yields. To reduce this impact we suggested some mechanisms of adaptation. 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 to evaluate the impact of rainfall on wheat yields. Data 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 soft wheat and hard wheat are strongly correlated with the period of January to March than with the whole growing-season. While they are adversely correlated with the mid-spring. This investigation concluded that synchronizing appropriate adaptation with the period of January to March was crucial to achieving success yield of wheat.

Vegetation responses to season of fire in an aseasonal, fire-prone fynbos shrubland

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Tineke Kraaij

2017-08-01

Full Text Available Season of fire has marked effects on floristic composition in fire-prone Mediterranean-climate shrublands. In these winter-rainfall systems, summer-autumn fires lead to optimal recruitment of overstorey proteoid shrubs (non-sprouting, slow-maturing, serotinous Proteaceae which are important to the conservation of floral diversity. We explored whether fire season has similar effects on early establishment of five proteoid species in the eastern coastal part of the Cape Floral Kingdom (South Africa where rainfall occurs year-round and where weather conducive to fire and the actual incidence of fire are largely aseasonal. We surveyed recruitment success (ratio of post-fire recruits to pre-fire parents of proteoids after fires in different seasons. We also planted proteoid seeds into exclosures, designed to prevent predation by small mammals and birds, in cleared (intended to simulate fire fynbos shrublands at different sites in each of four seasons and monitored their germination and survival to one year post-planting (hereafter termed ‘recruitment’. Factors (in decreasing order of importance affecting recruitment success in the post-fire surveys were species, pre-fire parent density, post-fire age of the vegetation at the time of assessment, and fire season, whereas rainfall (for six months post-fire and fire return interval (>7 years had little effect. In the seed-planting experiment, germination occurred during the cooler months and mostly within two months of planting, except for summer-plantings, which took 2–3 months longer to germinate. Although recruitment success differed significantly among planting seasons, sites and species, significant interactions occurred among the experimental factors. In both the post-fire surveys and seed planting experiment, recruitment success in relation to fire- or planting season varied greatly within and among species and sites. Results of these two datasets were furthermore inconsistent, suggesting

Vegetation responses to season of fire in an aseasonal, fire-prone fynbos shrubland.

Science.gov (United States)

Kraaij, Tineke; Cowling, Richard M; van Wilgen, Brian W; Rikhotso, Diba R; Difford, Mark

2017-01-01

Season of fire has marked effects on floristic composition in fire-prone Mediterranean-climate shrublands. In these winter-rainfall systems, summer-autumn fires lead to optimal recruitment of overstorey proteoid shrubs (non-sprouting, slow-maturing, serotinous Proteaceae) which are important to the conservation of floral diversity. We explored whether fire season has similar effects on early establishment of five proteoid species in the eastern coastal part of the Cape Floral Kingdom (South Africa) where rainfall occurs year-round and where weather conducive to fire and the actual incidence of fire are largely aseasonal. We surveyed recruitment success (ratio of post-fire recruits to pre-fire parents) of proteoids after fires in different seasons. We also planted proteoid seeds into exclosures, designed to prevent predation by small mammals and birds, in cleared (intended to simulate fire) fynbos shrublands at different sites in each of four seasons and monitored their germination and survival to one year post-planting (hereafter termed 'recruitment'). Factors (in decreasing order of importance) affecting recruitment success in the post-fire surveys were species, pre-fire parent density, post-fire age of the vegetation at the time of assessment, and fire season, whereas rainfall (for six months post-fire) and fire return interval (>7 years) had little effect. In the seed-planting experiment, germination occurred during the cooler months and mostly within two months of planting, except for summer-plantings, which took 2-3 months longer to germinate. Although recruitment success differed significantly among planting seasons, sites and species, significant interactions occurred among the experimental factors. In both the post-fire surveys and seed planting experiment, recruitment success in relation to fire- or planting season varied greatly within and among species and sites. Results of these two datasets were furthermore inconsistent, suggesting that proteoid

Phlebotomus argentipes seasonal patterns in India and Nepal.

Science.gov (United States)

Picado, Albert; Das, Murari Lal; Kumar, Vijay; Dinesh, Diwakar S; Rijal, Suman; Singh, Shri P; Das, Pradeep; Coosemans, Marc; Boelaert, Marleen; Davies, Clive

2010-03-01

The current control of Phebotomus argentipes (Annandale and Brunetti), the vector of Leishmania donovani (Laveran and Mesnil), on the Indian subcontinent is base on indoor residual spraying. The efficacy of this method depends, among other factors, on the timing and number of spraying rounds, which depend on the P. argentipes seasonality. To describe P. argentipes' seasonal patterns, six visceral leishmaniasis (VL) endemic villages, three in Muzaffarpur and three in Sunsari districts in India and Nepal, respectively, were selected based on accessibility and VL incidence. Ten houses per cluster with the highest P. argentipes density were monitored monthly for 15-16 mo using Center for Disease Control and Prevention light traps. Minimum and maximum temperature and rainfall data for the months January 2006 through December 2007 were collected from the nearest available weather stations. Backwards stepwise regression was used to generate the minimal adequate model for explaining the monthly variation in P. argentipes populations. The seasonality of P. argentipes is similar in India and Nepal, with two annual density peaks around May and October. Monthly P. argentipes density is positively associated with temperature and negatively associated with rainfall in both study sites. The multivariate climate model explained 57% of the monthly vectorial abundance. Vector control programs against P. argentipes (i.e., indoor residual spraying) should take into account the seasonal described here when implementing and monitoring interventions. Monitoring simple meteorological variables (i.e., temperature, rainfall) may allow prediction of VL epidemics on the Indian subcontinent.

Nonstationary modeling of a long record of rainfall and temperature over Rome

Science.gov (United States)

Villarini, Gabriele; Smith, James A.; Napolitano, Francesco

2010-10-01

A long record (1862-2004) of seasonal rainfall and temperature from the Rome observatory of Collegio Romano are modeled in a nonstationary framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Modeling analyses are used to characterize nonstationarities in rainfall and related climate variables. It is shown that the GAMLSS models are able to represent the magnitude and spread in the seasonal time series with parameters which are a smooth function of time. Covariate analyses highlight the role of seasonal and interannual variability of large-scale climate forcing, as reflected in three teleconnection indexes (Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Mediterranean Index), for modeling seasonal rainfall and temperature over Rome. In particular, the North Atlantic Oscillation is a significant predictor during the winter, while the Mediterranean Index is a significant predictor for almost all seasons.

Study of Climate Change Impact to Local Rainfall Distribution in Lampung Provinces

Directory of Open Access Journals (Sweden)

Tumiar Katarina Manik

2016-08-01

Full Text Available Global warming which leads to climate change has potential affect to Indonesia agriculture activities and production. Analyzing rainfall pattern and distribution is important to investigate the impact of global climate change to local climate. This study using rainfall data from 1976-2010 from both lowland and upland area of Lampung Province. The results show that rainfall tends to decrease since the 1990s which related to the years with El Nino event. Monsoonal pattern- having rain and dry season- still excist in Lampung; however, since most rain fell below the average, it could not meet crops water need. Farmers conclude that dry seasons were longer and seasonal pattern has been changed. Global climate change might affect Lampung rainfall distribution through changes on sea surface temperature which could intensify the El Nino effect. Therefore, watching the El Nino phenomena and how global warming affects it, is important in predicting local climate especially the rainfall distribution in order to prevent significant loss in agriculture productivities.

Characterisation of Seasonal Rainfall for Cropping Schedules ...

African Journals Online (AJOL)

El Nino-South Oscillation (ENSO) phenomenon occurs in the Equatorial Eastern Pacific Ocean and has been noted to account significantly for rainfall variability in many parts of the world, particularly tropical regions. This variability is very important in rainfed crop production and needs to be well understood. Thirty years of ...

Soil Moisture and Turgidity of Selected Robusta Coffee Clones on Alluvial Plain with Seasonal Rainfall Pattern

Directory of Open Access Journals (Sweden)

Rudy Erwiyono

2005-08-01

Full Text Available Observation on the seasonal variations of hydrological condition and turgidity of selected Robusta coffee clones has been carried out in Kaliwining Experimental Station, Indonesian Coffee and Cocoa Research Institute in Jember. The aim was to evaluate the effect of hydrological variation on the coffee plants and the degree of soil moisture effect on plant performance. Experimental site overlays on alluvial plain, + 45 m a.s.l., 8o 15’ South with D rainfall type. Observation was conducted by survey method at the experimental plots of organic fertilizer and nitogen treatments on selected Robusta coffee clones derived from rooted cuttings, i.e. BP 436, BP 42, BP 936 and BP 358. Observation was only conducted at the experimental blocks of organic matter trials of 20 l/tree/year at nitrogen (Urea application of locally recommanded rate during the subsequent years of 1999 to 2001. Parameters observed included plant turgidity and soil moisture content of three different depths, i.e. 0—20, 20—40 and 40—60 cm and the weather. Observation was carried out in five replicates designed as blocks of barn manure treatment and N-fertilizer of recommended rate as basal fertilizer. The results showed that meteorological condition and soil moisture of experimental site through the years have seasonal patterns following the seasonal pattern of rainfall. Compared to other meteorological characteristics, relative humidity dominantly determined evaporation and plant turgidity. Plant turgi-dity was not only determined by soil moisture condition, but also atmospheric demand. When relative humidity (RH was relatively high, plant turgidity was relatively stable although soil moisture of surface layers was very low, and the reversal when soil moisture content was high plant turgidity was controlled by atmospheric demand (relative humidity. With a 3—4 dry month period, relative turgidity of the coffee plants was relatively stable above 82%, except when soil

Linking Vital Rates of Landbirds on a Tropical Island to Rainfall and Vegetation Greenness.

Directory of Open Access Journals (Sweden)

James F Saracco

Full Text Available Remote tropical oceanic islands are of high conservation priority, and they are exemplified by range-restricted species with small global populations. Spatial and temporal patterns in rainfall and plant productivity may be important in driving dynamics of these species. Yet, little is known about environmental influences on population dynamics for most islands and species. Here we leveraged avian capture-recapture, rainfall, and remote-sensed habitat data (enhanced vegetation index [EVI] to assess relationships between rainfall, vegetation greenness, and demographic rates (productivity, adult apparent survival of three native bird species on Saipan, Northern Mariana Islands: rufous fantail (Rhipidura rufifrons, bridled white-eye (Zosterops conspicillatus, and golden white-eye (Cleptornis marchei. Rainfall was positively related to vegetation greenness at all but the highest rainfall levels. Temporal variation in greenness affected the productivity of each bird species in unique ways. Predicted productivity of rufous fantail was highest when dry and wet season greenness values were high relative to site-specific 5-year seasonal mean values (i.e., relative greenness; while the white-eye species had highest predicted productivity when relative greenness contrasted between wet and dry seasons. Survival of rufous fantail and bridled white eye was positively related to relative dry-season greenness and negatively related to relative wet-season greenness. Bridled white-eye survival also showed evidence of a positive response to overall greenness. Our results highlight the potentially important role of rainfall regimes in affecting population dynamics of species on oceanic tropical islands. Understanding linkages between rainfall, vegetation, and animal population dynamics will be critical for developing effective conservation strategies in this and other regions where the seasonal timing, extent, and variability of rainfall is expected to change in the

James Madison and a Shift in Precipitation Seasonality

Science.gov (United States)

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

2001-12-01

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

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

Science.gov (United States)

Saxena, Rani; Mathur, Prasoon

2018-03-01

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

Mapping monthly rainfall erosivity in Europe.

Science.gov (United States)

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

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

Science.gov (United States)

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

2014-12-01

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

Rainfall-driven epidemic cholera: hydrologic controls on water-borne disease and multi-season projections

Science.gov (United States)

Righetto, L.; Bertuzzo, E.; Mari, L.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2012-12-01

Following the acknowledgement of a clear correlation between rainfall events and cholera resurgence, that was observed in Haiti starting from May 2011, we use a multi-variate Poisson generator to produce rainfall inputs, with which we force spatially explicit models of cholera spreading. Our models consist of ODE systems of equations, describing a network of human communities (divided in Susceptible, Infected and Recovered individuals) connected by river transport of pathogens and human mobility. We perform an a posteriori analysis -- from the beginning of the epidemic until December 2011 -- to assess the model reliability in predicting cholera cases and in testing control measures -- involving vaccination and sanitation campaigns. We then run a multi-seasonal prediction of the course of the epidemic until December 2015, to investigate further resurgences of cholera in the region and to evaluate, again, the effect of policies which may bring to the eradication of the disease in Haiti. We conclude that mathematical models may represent a key information tool for policy makers, as a way to preliminarly assess the possible future course of an epidemic and to test intervention policies to be deployed. Effect of intervention policies on the predicted course of the epidemic between 28/05-31/12/2011 (blue lines: simulations with the observed rainfall pattern; red lines/shaded range: median/25th-75th percentile range of simulations with generated rainfall). A) Effect of a reduction of the 20% of the contact rate , applied in one month starting from the 1st of June (dashed blue/red lines) or the 1st of July (dotted blue/red lines). B) A) Effect of a vaccination of 4 million individuals, implemented in one month starting from the 1st of June (dashed blue/red lines) or the 1st of July (dotted blue/red lines). C) Number of new cases in the period 28/05-31/12/2011 as a function of the reduction of the contact rate . D) Number of new cases in the period 28/05-31/12/2011 as a

A distinction between summer rainy season and summer monsoon season over the Central Highlands of Vietnam

Science.gov (United States)

Ngo-Thanh, Huong; Ngo-Duc, Thanh; Nguyen-Hong, Hanh; Baker, Peter; Phan-Van, Tan

2018-05-01

The daily rainfall data at 13 stations over the Central Highlands (CH) Vietnam were collected for the period 1981-2014. Two different sets of criteria using daily observed rainfall and 850 hPa daily reanalysis wind data were applied to determine the onset (retreat) dates of the summer rainy season (RS) and summer monsoon (SM) season, respectively. Over the study period, the mean RS and SM onset dates were April 20 and May 13 with standard deviations of 17.4 and 17.8 days, respectively. The mean RS and SM retreat dates were November 1 and September 30 with standard deviations of 17.9 and 10.2 days, respectively . The year-to-year variations of the onset dates and the rainfall amount within the RS and SM season were closely linked with the preceding winter and spring sea surface temperature in the central-eastern and western Pacific. It was also found that the onset dates were significantly correlated with the RS and SM rainfall amount.

Statistical Analysis of 30 Years Rainfall Data: A Case Study

Science.gov (United States)

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.

Performance of High Resolution Satellite Rainfall Products over Data Scarce Parts of Eastern Ethiopia

Directory of Open Access Journals (Sweden)

Shimelis B. Gebere

2015-09-01

Full Text Available Accurate estimation of rainfall in mountainous areas is necessary for various water resource-related applications. Though rain gauges accurately measure rainfall, they are rarely found in mountainous regions and satellite rainfall data can be used as an alternative source over these regions. This study evaluated the performance of three high-resolution satellite rainfall products, the Tropical Rainfall Measuring Mission (TRMM 3B42, the Global Satellite Mapping of Precipitation (GSMaP_MVK+, and the Precipitation Estimation from Remotely-Sensed Information using Artificial Neural Networks (PERSIANN at daily, monthly, and seasonal time scales against rain gauge records over data-scarce parts of Eastern Ethiopia. TRMM 3B42 rain products show relatively better performance at the three time scales, while PERSIANN did much better than GSMaP. At the daily time scale, TRMM correctly detected 88% of the rainfall from the rain gauge. The correlation at the monthly time scale also revealed that the TRMM has captured the observed rainfall better than the other two. For Belg (short rain and Kiremt (long rain seasons, the TRMM did better than the others by far. However, during Bega (dry season, PERSIANN showed a relatively good estimate. At all-time scales, noticing the bias, TRMM tends to overestimate, while PERSIANN and GSMaP tend to underestimate the rainfall. The overall result suggests that monthly and seasonal TRMM rainfall performed better than daily rainfall. It has also been found that both GSMaP and PERSIANN performed better in relatively flat areas than mountainous areas. Before the practical use of TRMM, the RMSE value needs to be improved by considering the topography of the study area or adjusting the bias.

Congo Basin rainfall climatology: can we believe the climate models?

Science.gov (United States)

Washington, Richard; James, Rachel; Pearce, Helen; Pokam, Wilfried M; Moufouma-Okia, Wilfran

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models.

Meta-heuristic ant colony optimization technique to forecast the amount of summer monsoon rainfall: skill comparison with Markov chain model

Science.gov (United States)

Chaudhuri, Sutapa; Goswami, Sayantika; Das, Debanjana; Middey, Anirban

2014-05-01

Forecasting summer monsoon rainfall with precision becomes crucial for the farmers to plan for harvesting in a country like India where the national economy is mostly based on regional agriculture. The forecast of monsoon rainfall based on artificial neural network is a well-researched problem. In the present study, the meta-heuristic ant colony optimization (ACO) technique is implemented to forecast the amount of summer monsoon rainfall for the next day over Kolkata (22.6°N, 88.4°E), India. The ACO technique belongs to swarm intelligence and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. ACO technique takes inspiration from the foraging behaviour of some ant species. The ants deposit pheromone on the ground in order to mark a favourable path that should be followed by other members of the colony. A range of rainfall amount replicating the pheromone concentration is evaluated during the summer monsoon season. The maximum amount of rainfall during summer monsoon season (June—September) is observed to be within the range of 7.5-35 mm during the period from 1998 to 2007, which is in the range 4 category set by the India Meteorological Department (IMD). The result reveals that the accuracy in forecasting the amount of rainfall for the next day during the summer monsoon season using ACO technique is 95 % where as the forecast accuracy is 83 % with Markov chain model (MCM). The forecast through ACO and MCM are compared with other existing models and validated with IMD observations from 2008 to 2012.

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

Directory of Open Access Journals (Sweden)

Carolien Toté

2015-02-01

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

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

Science.gov (United States)

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

2015-01-01

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

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

Science.gov (United States)

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

The response of ungulates to rainfall along the riverbeds of the Southern Kalahari

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M. G. L Mills

1984-12-01

Full Text Available The responses of springbok Antidorcas marsupialis, gemsbok Oryx gazella, blue wildebeest Connochaetes taurinus and red hartebeest Alcelaphus buselaphus to rainfall along the riverbeds of the southern Kalahari are analysed. Springbok reacted most rapidly to rainfall along the riverbeds and, by browsing in dry times, maintained a fairly stable presence throughout the year, although the actual number present in any one year was dependent on annual rainfall. Gemsbok responded more slowly to rainfall and reached their highest numbers in years of high rainfall when the grasses were tall and mature, after which they rapidly departed from the riverbeds. Red hartebeest also reached their highest numbers during the rainy season, but departed slightly more slowly than gemsbok. In dry years, they too, failed to come into the riverbeds. Blue wildebeest in the vicinity of the riverbeds tended to be more sedentary than the other species. The presence of potable artificial water appeared to be more important for wildebeest than for the other species and, although rainfall was undoubtedly an important factor in regulating their numbers along the riverbeds, they depended to a greater extent on breeding success and mortality factors, than on emigration and immigration. The overall seasonal pattern of ungulate abundance along the riverbeds in the southern Kalahari was one of wet season concentrations and dry season dispersion.

Seasonal forecasting of Bangladesh summer monsoon rainfall using ...

Indian Academy of Sciences (India)

In this paper, the development of a statistical forecasting method for summer ... 2008 summer monsoon rainfall based on the model were also found to be in good agreement with the ..... nificant on the basis of a one-tailed test of Student's.

Sensitivity of peak flow to the change of rainfall temporal pattern due to warmer climate

Science.gov (United States)

Fadhel, Sherien; Rico-Ramirez, Miguel Angel; Han, Dawei

2018-05-01

The widely used design storms in urban drainage networks has different drawbacks. One of them is that the shape of the rainfall temporal pattern is fixed regardless of climate change. However, previous studies have shown that the temporal pattern may scale with temperature due to climate change, which consequently affects peak flow. Thus, in addition to the scaling of the rainfall volume, the scaling relationship for the rainfall temporal pattern with temperature needs to be investigated by deriving the scaling values for each fraction within storm events, which is lacking in many parts of the world including the UK. Therefore, this study analysed rainfall data from 28 gauges close to the study area with a 15-min resolution as well as the daily temperature data. It was found that, at warmer temperatures, the rainfall temporal pattern becomes less uniform, with more intensive peak rainfall during higher intensive times and weaker rainfall during less intensive times. This is the case for storms with and without seasonal separations. In addition, the scaling values for both the rainfall volume and the rainfall fractions (i.e. each segment of rainfall temporal pattern) for the summer season were found to be higher than the corresponding results for the winter season. Applying the derived scaling values for the temporal pattern of the summer season in a hydrodynamic sewer network model produced high percentage change of peak flow between the current and future climate. This study on the scaling of rainfall fractions is the first in the UK, and its findings are of importance to modellers and designers of sewer systems because it can provide more robust scenarios for flooding mitigation in urban areas.

Monthly Rainfall Erosivity: Conversion Factors for Different Time Resolutions and Regional Assessments

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Panos Panagos

2016-03-01

Full Text Available As a follow up and an advancement of the recently published Rainfall Erosivity Database at European Scale (REDES and the respective mean annual R-factor map, the monthly aspect of rainfall erosivity has been added to REDES. Rainfall erosivity is crucial to be considered at a monthly resolution, for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices as well as natural hazard protection (landslides and flood prediction. We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland or former data density was not satisfactory (Austria, France, and Spain. The different time resolutions (from 5 to 60 min of high temporal data require a conversion of monthly R-factor based on a pool of stations with available data at all time resolutions. Because the conversion factors show smaller monthly variability in winter (January: 1.54 than in summer (August: 2.13, applying conversion factors on a monthly basis is suggested. The estimated monthly conversion factors allow transferring the R-factor to the desired time resolution at a European scale. The June to September period contributes to 53% of the annual rainfall erosivity in Europe, with different spatial and temporal patterns depending on the region. The study also investigated the heterogeneous seasonal patterns in different regions of Europe: on average, the Northern and Central European countries exhibit the largest R-factor values in summer, while the Southern European countries do so from October to January. In almost all countries (excluding Ireland, United Kingdom and North France, the seasonal variability of rainfall erosivity is high. Very few areas (mainly located in Spain and France show the largest from February to April. The average monthly erosivity density is very large in August (1.67 and July (1.63, while very small in January and February (0.37. This study addresses

On the determination of trends in rainfall

African Journals Online (AJOL)

2008-02-19

Feb 19, 2008 ... it was decided to start from the inherent distribution of rainfall and develop a method for determining temporal .... first log-transformed to stabilise the variance of the time series ... the Kolmogorov-Zurbenko filter had a very high probability of ... seasonality, the SKT test and a t-test adjusted for seasonality.

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

Science.gov (United States)

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

Tropical Atlantic Contributions to Strong Rainfall Variability Along the Northeast Brazilian Coast

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G. A. Hounsou-gbo

2015-01-01

Full Text Available Tropical Atlantic (TA Ocean-atmosphere interactions and their contributions to strong variability of rainfall along the Northeast Brazilian (NEB coast were investigated for the years 1974–2008. The core rainy seasons of March-April and June-July were identified for Fortaleza (northern NEB; NNEB and Recife (eastern NEB; ENEB, respectively. Lagged linear regressions between sea surface temperature (SST and pseudo wind stress (PWS anomalies over the entire TA and strong rainfall anomalies at Fortaleza and Recife show that the rainfall variability of these regions is differentially influenced by the dynamics of the TA. When the Intertropical Convergence Zone is abnormally displaced southward a few months prior to the NNEB rainy season, the associated meridional mode increases humidity and precipitation during the rainy season. Additionally, this study shows predictive effect of SST, meridional PWS, and barrier layer thickness, in the Northwestern equatorial Atlantic, on the NNEB rainfall. The dynamical influence of the TA on the June-July ENEB rainfall variability shows a northwestward-propagating area of strong, positively correlated SST from the southeastern TA to the southwestern Atlantic warm pool (SAWP offshore of Brazil. Our results also show predictive effect of SST, zonal PWS, and mixed layer depth, in the SAWP, on the ENEB rainfall.

Effect of rainfall on cropping pattern in mid Himalayan region ...

African Journals Online (AJOL)

The analysis of effect of rainfall during the last 20 years is needed to evaluate cropping pattern in the rain-fed region. In this study, trends in annual, seasonal and monthly rainfall of district of Himachal Pradesh in India over the past 20 years were examined. The annual rainfall varies from 863.3 to 1470.0 mm. During the ...

Seasonal streamflow prediction by a combined climate-hydrologic system for river basins of Taiwan

Science.gov (United States)

Kuo, Chun-Chao; Gan, Thian Yew; Yu, Pao-Shan

2010-06-01

SummaryA combined, climate-hydrologic system with three components to predict the streamflow of two river basins of Taiwan at one season (3-month) lead time for the NDJ and JFM seasons was developed. The first component consists of the wavelet-based, ANN-GA model (Artificial Neural Network calibrated by Genetic Algorithm) which predicts the seasonal rainfall by using selected sea surface temperature (SST) as predictors, given that SST are generally predictable by climate models up to 6-month lead time. For the second component, three disaggregation models, Valencia and Schaake (VS), Lane, and Canonical Random Cascade Model (CRCM), were tested to compare the accuracy of seasonal rainfall disaggregated by these three models to 3-day time scale rainfall data. The third component consists of the continuous rainfall-runoff model modified from HBV (called the MHBV) and calibrated by a global optimization algorithm against the observed rainfall and streamflow data of the Shihmen and Tsengwen river basins of Taiwan. The proposed system was tested, first by disaggregating the predicted seasonal rainfall of ANN-GA to rainfall of 3-day time step using the Lane model; then the disaggregated rainfall data was used to drive the calibrated MHBV to predict the streamflow for both river basins at 3-day time step up to a season's lead time. Overall, the streamflow predicted by this combined system for the NDJ season, which is better than that of the JFM season, will be useful for the seasonal planning and management of water resources of these two river basins of Taiwan.

Long term spatial and temporal rainfall trends and homogeneity analysis in Wainganga basin, Central India

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Arun Kumar Taxak

2014-08-01

Full Text Available Gridded rainfall data of 0.5×0.5° resolution (CRU TS 3.21 was analysed to study long term spatial and temporal trends on annual and seasonal scales in Wainganga river basin located in Central India during 1901–2012. After testing the presence of autocorrelation, Mann–Kendall (Modified Mann–Kendall test was applied to non-auto correlated (auto correlated series to detect the trends in rainfall data. Theil and Sen׳s slope estimator test was used for finding the magnitude of change over a time period. For detecting the most probable change year, Pettitt–Mann–Whitney test was applied. The Rainfall series was then divided into two partial duration series for finding changes in trends before and after the change year. Arc GIS was used to explore spatial patterns of the trends over the entire basin. Though most of the grid points shows a decreasing trend in annual rainfall, only seven grids has a significant decreasing trend during 1901–2012. On the basis of seasonal trend analysis, non-significant increasing trend is observed only in post monsoon season while seven grid points show significant decreasing trend in monsoon rainfall and non-significant in pre-monsoon and winter rainfall over the last 112 years. During the study period, overall a 8.45% decrease in annual rainfall is estimated. The most probable year of change was found to be 1948 in annual and monsoonal rainfall. There is an increasing rainfall trend in the basin during the period 1901–1948, which is reversed during the period 1949–2012 resulting in decreasing rainfall trend in the basin. Homogeneous trends in annual and seasonal rainfall over a grid points is exhibited in the basin by van Belle and Hughes׳ homogeneity trend test.

Vegetation responses to season of fire in an aseasonal, fire-prone fynbos shrubland

OpenAIRE

Tineke Kraaij; Richard M. Cowling; Brian W. van Wilgen; Diba R. Rikhotso; Mark Difford

2017-01-01

Season of fire has marked effects on floristic composition in fire-prone Mediterranean-climate shrublands. In these winter-rainfall systems, summer-autumn fires lead to optimal recruitment of overstorey proteoid shrubs (non-sprouting, slow-maturing, serotinous Proteaceae) which are important to the conservation of floral diversity. We explored whether fire season has similar effects on early establishment of five proteoid species in the eastern coastal part of the Cape Floral Kingdom (South A...

Rainfall trends in the Brazilian Amazon Basin in the past eight decades

Science.gov (United States)

Satyamurty, Prakki; de Castro, Aline Anderson; Tota, Julio; da Silva Gularte, Lucia Eliane; Manzi, Antonio Ocimar

2010-01-01

Rainfall series at 18 stations along the major rivers of the Brazilian Amazon Basin, having data since 1920s or 1930s, are analyzed to verify if there are appreciable long-term trends. Annual, rainy-season, and dry-season rainfalls are individually analyzed for each station and for the region as a whole. Some stations showed positive trends and some negative trends. The trends in the annual rainfall are significant at only six stations, five of which reporting increasing trends (Barcelos, Belem, Manaus, Rio Branco, and Soure stations) and just one (Itaituba station) reporting decreasing trend. The climatological values of rainfall before and after 1970 show significant differences at six stations (Barcelos, Belem, Benjamin Constant, Iaurete, Itaituba, and Soure). The region as a whole shows an insignificant and weak downward trend; therefore, we cannot affirm that the rainfall in the Brazilian Amazon basin is experiencing a significant change, except at a few individual stations. Subregions with upward and downward trends are interspersed in space from the far eastern Amazon to western Amazon. Most of the seasonal trends follow the annual trends, thus, indicating a certain consistency in the datasets and analysis.

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

Science.gov (United States)

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.

Contribution of tropical cyclones to global rainfall

Science.gov (United States)

Khouakhi, Abdou; Villarini, Gabriele; Vecchi, Gabriel; Smith, James

2016-04-01

Rainfall associated with tropical cyclones (TCs) can have both devastating and beneficial impacts in different parts of the world. In this work, daily precipitation and historical six-hour best track TC datasets are used to quantify the contribution of TCs to global rainfall. We select 18607 rain gauge stations with at least 25 complete (at least 330 measurements per year) years between 1970 and 2014. We consider rainfall associated with TCs if the center of circulation of the storm passed within a given distance from the rain gauge and within a given time window. Spatial and temporal sensitivity analyses are performed with varying time windows (same day, ±1 day) and buffer radii (400 km and 500 km) around each rain gauge. Results highlight regional differences in TC-induced rainfall. The highest TC-induced precipitation totals (400 to 600+ mm/year) are prevalent along eastern Asia, western and northeastern Australia, and in the western Pacific islands. Stations along the southeast of the U.S. coast and surrounding the Gulf of Mexico receive up to 200 mm/year of TC rainfall. The highest annual fractional contributions of TCs to total rainfall (from 35 to 50%) are recorded in stations located in northwestern Australia, southeastern China, the northern Philippines and the southern Mexico peninsula. Seasonally, the highest proportions (40 to 50%) are recorded along eastern Australia and Mauritius in winter, and in eastern Asia and Mexico in summer and autumn. Analyses of the relative contribution of TCs to extreme rainfall using annual maximum (AM) and peaks-over-threshold (POT) approaches indicate notable differences among regions. The highest TC-AM rainfall proportions (45 to 60%) are found in stations located in Japan, eastern China, the Philippines, eastern and western Australia. Substantial contributions (25 to 40% of extreme rainfall) are also recorded in stations located along the U.S. East Coast, the Gulf of Mexico, and the Mexico peninsula. We find similar

Monsoon Rainfall and Landslides in Nepal

Science.gov (United States)

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

2009-12-01

A large number of human settlements on the Nepal Himalayas are situated either on old landslide mass or on landslide-prone areas. As a result, a great number of people are affected by large- and small-scale landslides all over the Himalayas especially during monsoon periods. In Nepal, only in the half monsoon period (June 10 to August 15), 70, 50 and 68 people were killed from landslides in 2007, 2008 and 2009, respectively. In this context, this paper highlights monsoon rainfall and their implications in the Nepal Himalaya. In Nepal, monsoon is major source of rainfall in summer and approximately 80% of the annual total rainfall occurs from June to September. The measured values of mean annual precipitation in Nepal range from a low of approximately 250 mm at area north of the Himalaya to many areas exceeding 6,000 mm. The mean annual rainfall varying between 1500 mm and 2500 mm predominate over most of the country. In Nepal, the daily distribution of precipitation during rainy season is also uneven. Sometime 10% of the total annual precipitation can occur in a single day. Similarly, 50% total annual rainfall also can occur within 10 days of monsoon. This type of uneven distribution plays an important role in triggering many landslides in Nepal. When spatial distribution of landslides was evaluated from record of more than 650 landslides, it is found that more landslides events were concentrated at central Nepal in the area of high mean annual rainfall. When monsoon rainfall and landslide relationship was taken into consideration, it was noticed that a considerable number of landslides were triggered in the Himalaya by continuous rainfall of 3 to 90 days. It has been noticed that continuous rainfall of few days (5 days or 7 days or 10 days) are usually responsible for landsliding in the Nepal Himalaya. Monsoon rains usually fall with interruptions of 2-3 days and are generally characterized by low intensity and long duration. Thus, there is a strong role of

Inter-Seasonal and Annual Co-Variation of Smallholder Production Portfolios, Volumes and Incomes with Rainfall and Flood Levels in the Amazon Estuary: Implications for Building Livelihood Resilience to Increasing Variability of Hydro-Climatic Regimes

Science.gov (United States)

Vogt, N. D.; Fernandes, K.; Pinedo-Vasquez, M.; Brondizio, E. S.; Almeida, O.; Rivero, S.; Rabelo, F. R.; Dou, Y.; Deadman, P.

2014-12-01

In this paper we investigate inter-seasonal and annual co-variations of rainfall and flood levels with Caboclo production portfolios, and proportions of it they sell and consume, in the Amazon Estuary from August 2012 to August 2014. Caboclos of the estuary maintain a diverse and flexible land-use portfolio, with a shift in dominant use from agriculture to agroforestry and forestry since WWII (Vogt et al., 2014). The current landscape is configured for acai, shrimp and fish production. In the last decade the frequency of wet seasons with anomalous flood levels and duration has increased primarily from changes in rainfall and discharge from upstream basins. Local rainfall, though with less influence on extreme estuarine flood levels, is reported to be more sporadic and intense in wet season and variable in both wet and dry seasons, for yet unknown reasons. The current production portfolio and its flexibility are felt to build resilience to these increases in hydro-climatic variability and extreme events. What is less understood, for time and costliness of daily measures at household levels, is how variations in flood and rainfall levels affect shifts in the current production portfolio of estuarine Caboclos, and the proportions of it they sell and consume. This is needed to identify what local hydro-climatic thresholds are extreme for current livelihoods, that is, that most adversely affect food security and income levels. It is also needed identify the large-scale forcings driving those extreme conditions to build forecasts for when they will occur. Here we present results of production, rainfall and flood data collected daily in households from both the North and South Channel of the Amazon estuary over last two years to identify how they co-vary, and robustness of current production portfolio under different hydro-climatic conditions.

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

Science.gov (United States)

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 Rainfall Distribution In Owerri And Enugu, Nigeria Using ...

African Journals Online (AJOL)

The precipitation concentration index (PCI) of Owerri and Enugu for 1974 to 2011 was computed to characterise the rainfall distribution for both locations. The PCI was estimated on an annual and seasonal scale. The seasonal estimation was based on the categorisation of the seasons in eastern Nigeria into long wet ...

The Predictability of Dry-Season Precipitation in Tropical West Africa

Science.gov (United States)

Knippertz, P.; Davis, J.; Fink, A. H.

2012-04-01

Precipitation during the boreal winter dry season in tropical West Africa is rare but occasionally connected to high-impacts for the local population. Previous work has shown that these events are usually connected to a trough over northwestern Africa, an extensive cloud plume on its eastern side, unusual precipitation at the northern and western fringes of the Sahara, and reduced surface pressure over the southern Sahara and Sahel, which allows an inflow of moist southerlies from the Gulf of Guinea to feed the unusual dry-season rainfalls. These results also suggest that the extratropical influence enhances the predictability of these events on the synoptic timescale. Here we further investigate this question for the 11 dry seasons (November-March) 1998/99-2008/09 using rainfall estimates from TRMM (Tropical Rainfall Measuring Mission) and GPCP (Global Precipitation Climatology Project), and operational ensemble predictions from the European Centre for Medium-Range Forecasts (ECMWF). All fields are averaged over the study area 7.5-15°N, 10°W-10°E that spans most of southern West Africa. For each 0000 UTC analysis time, the daily precipitation estimates are accumulated to pentads and compared with 120-hour predictions starting at the same time. Compared to TRMM, the ensemble mean shows a weak positive bias, whereas there is a substantial negative bias with regard to GPCP. Temporal correlations reach a high value of 0.8 for both datasets, showing similar synoptic variability despite the differences in total amount. Standard probabilistic evaluation methods such as relative operating characteristic (ROC) diagrams indicate remarkably good reliability, resolution and skill, particularly for lower precipitation thresholds. Not surprisingly, forecasts cluster at low probabilities for higher thresholds, but the reliability and ROC score are still reasonably high. The results show that global ensemble prediction systems are capable to predict dry-season rainfall events

Potential of deterministic and geostatistical rainfall interpolation under high rainfall variability and dry spells: case of Kenya's Central Highlands

Science.gov (United States)

Kisaka, M. Oscar; Mucheru-Muna, M.; Ngetich, F. K.; Mugwe, J.; Mugendi, D.; Mairura, F.; Shisanya, C.; Makokha, G. L.

2016-04-01

Drier parts of Kenya's Central Highlands endure persistent crop failure and declining agricultural productivity. These have, in part, attributed to high temperatures, prolonged dry spells and erratic rainfall. Understanding spatial-temporal variability of climatic indices such as rainfall at seasonal level is critical for optimal rain-fed agricultural productivity and natural resource management in the study area. However, the predominant setbacks in analysing hydro-meteorological events are occasioned by either lack, inadequate, or inconsistent meteorological data. Like in most other places, the sole sources of climatic data in the study region are scarce and only limited to single stations, yet with persistent missing/unrecorded data making their utilization a challenge. This study examined seasonal anomalies and variability in rainfall, drought occurrence and the efficacy of interpolation techniques in the drier regions of eastern Kenyan. Rainfall data from five stations (Machang'a, Kiritiri, Kiambere and Kindaruma and Embu) were sourced from both the Kenya Meteorology Department and on-site primary recording. Owing to some experimental work ongoing, automated recording for primary dailies in Machang'a have been ongoing since the year 2000 to date; thus, Machang'a was treated as reference (for period of record) station for selection of other stations in the region. The other stations had data sets of over 15 years with missing data of less than 10 % as required by the world meteorological organization whose quality check is subject to the Centre for Climate Systems Modeling (C2SM) through MeteoSwiss and EMPA bodies. The dailies were also subjected to homogeneity testing to evaluate whether they came from the same population. Rainfall anomaly index, coefficients of variance and probability were utilized in the analyses of rainfall variability. Spline, kriging and inverse distance weighting interpolation techniques were assessed using daily rainfall data and

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

Science.gov (United States)

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

2018-01-01

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

Spatial dependence of extreme rainfall

Science.gov (United States)

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

2017-05-01

This study aims to model the spatial extreme daily rainfall process using the max-stable model. The max-stable model is used to capture the dependence structure of spatial properties of extreme rainfall. Three models from max-stable are considered namely Smith, Schlather and Brown-Resnick models. The methods are applied on 12 selected rainfall stations in Kelantan, Malaysia. Most of the extreme rainfall data occur during wet season from October to December of 1971 to 2012. This period is chosen to assure the available data is enough to satisfy the assumption of stationarity. The dependence parameters including the range and smoothness, are estimated using composite likelihood approach. Then, the bootstrap approach is applied to generate synthetic extreme rainfall data for all models using the estimated dependence parameters. The goodness of fit between the observed extreme rainfall and the synthetic data is assessed using the composite likelihood information criterion (CLIC). Results show that Schlather model is the best followed by Brown-Resnick and Smith models based on the smallest CLIC's value. Thus, the max-stable model is suitable to be used to model extreme rainfall in Kelantan. The study on spatial dependence in extreme rainfall modelling is important to reduce the uncertainties of the point estimates for the tail index. If the spatial dependency is estimated individually, the uncertainties will be large. Furthermore, in the case of joint return level is of interest, taking into accounts the spatial dependence properties will improve the estimation process.

Inter-annual rainfall variability and droughts occurrence during ...

African Journals Online (AJOL)

This study examined the trends of rainfall and the intensity of drought during sowing season and mid-season of rice farming calendar in the rainforest belt of Nigeria using data spanning 52 years (1961-2012) for five synoptic weather stations. The trends were investigated using simple linear regression and second order ...

Mapping monthly rainfall erosivity in Europe

DEFF Research Database (Denmark)

Ballabio, C; Meusburger, K; Klik, A

2017-01-01

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...... 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...... 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...

Species biogeography predicts drought responses in a seasonally dry tropical forest

Science.gov (United States)

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

Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model

Directory of Open Access Journals (Sweden)

Dongkyun Kim

2013-01-01

Full Text Available Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP stochastic rainfall simulation model were regionalized across the contiguous United States. Three thousand four hundred forty-four National Climate Data Center (NCDC rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between the observed and MBLRP-generated precipitation time series. These statistics included the mean, variance, probability of zero rainfall and autocorrelation at 1-, 3-, 12- and 24-hour accumulation intervals. The Ordinary Kriging interpolation technique was used to generate maps of the six MBLRP model parameters for each of the 12 months of the year. All parameters had clear to discernible regional tendencies; except for one related to rain cell duration distribution. Parameter seasonality was not obvious and it was more apparent in some locations than in others, depending on the seasonality of the rainfall statistics. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the observed rainfall statistics for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The boundaries of the expected residual, with 95% confidence, between the observed rainfall statistics and the simulated rainfall statistics based on the map parameters were approximately ±0.064 mm hr-1, ±1.63 mm2 hr-2, ±0.16, and ±0.030 for the mean, variance, lag-1 autocorrelation and probability of zero rainfall at hourly accumulation levels, respectively. The estimated parameter values were also used to estimate the storm and rain cell characteristics.

Spatial and Temporal Variability of Rainfall over the South-West Coast of Bangladesh

Directory of Open Access Journals (Sweden)

Md. Sarwar Hossain

2014-04-01

Full Text Available This study examined the spatial and temporal rainfall variability from the 1940s to 2007 in the south west coastal region of Bangladesh. Time series statistical tests were applied to examine the spatial and temporal trends in three time segments (1948–1970, 1971–1990 and 1991–2007 and four seasons (Pre-monsoon; Monsoon; Post-Monsoon and Winter, during the period 1948–2007. Eight weather stations were divided into two zones: exposed (exposed to sea and interior (distant to sea. Overall, rainfall increased during the period 1948–2007, while the trends intensified during post-1990s. Post-monsoon and winter rainfall was observed to follow significant positive trends at most weather stations during the time period 1948–2007. The rate of change was found in exposed zone and interior zone are +12.51 and +4.86 mm/year, respectively, over post monsoon and +0.9 and +1.86 mm/year, respectively, over winter. These trends intensified both in the exposed zone (+45.81 mm/year and the interior zone (+27.09 mm/year 1990 onwards. Winter rainfall does not exhibit significant change (p > 0.1 over the exterior or interior zone, though individual stations like Jessore, Satkhira and Bhola show significant negative trends after 1990s. Although the trends were observed to weaken in the monsoon and pre-monsoon seasons, they are not significant. Moreover, an 11-year cyclicity was found within these two seasons, whilst no cyclicity was observed in the post-monsoon and winter seasons. Sequential Mann Kendal test reveals that the changes in two zones rainfall trends are started around mid-80s, where step change found only for fours season in Khulna stations and also for winter seasons in all weather stations. These changes may have a detrimental effect on rain-fed agriculture in Bangladesh. The application of palaeo-environmental techniques, threshold determination and rainfall analysis across the whole country could be useful to support adaptation planning of

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

Directory of Open Access Journals (Sweden)

V. A. Bell

2017-09-01

Full Text Available 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�

Predictability of the intra-seasonal rainfall characteristics variables over South Africa

CSIR Research Space (South Africa)

Phakula, S

2015-09-01

Full Text Available for the homogeneous rainfall regions. Keywords: Retro-active validation, Forecast skill, Area-averaged ROC scores, Reliability diagrams. Introduction Southern Africa is a region of significant rainfall variability on a range of temporal and spacial scales... are evaluated using retro-actively generated hindcasts through canonical correlation analysis (CCA). Retro-active forecast validation is a robust method to assess forecast model performance and give unbiased skill levels (Landman et al., 2001). Two...

Diagnostics of Rainfall Anomalies in the Nordeste During the Global Weather Experiment

Science.gov (United States)

Sikdar, D. M.

1984-01-01

The relationship of the daily variability of large-scale pressure, cloudiness and upper level wind patterns over the Brazil-Atlantic sector during March/April 1979 to rainfall anomalies in northern Nordeste was investigated. The experiment divides the rainy season (March/April) of 1979 into wet and dry days, then composites bright cloudiness, sea level pressure, and upper level wind fields with respect to persistent rainfall episodes. Wet and dry anomalies are analyzed along with seasonal mean conditions.

Monsoon rainfall behaviour in recent times on local/regional scale in India

International Nuclear Information System (INIS)

Singh, Surender; Rao, V.U.M.; Singh, Diwan

2002-08-01

An attempt has been made here to investigate the local/regional monsoon rainfall behaviour in the meteorological sub-division no. 13 comprising the areas of Haryana, Delhi and Chandigarh in India. The monthly monsoon rainfall data of 30 years (1970-99) of different locations in the region were used for the investigation. All locations except Delhi received more rainfall in monsoon season during the decade (1990-99) showing general increasing trend in the rainfall behaviour in recent times. The mean monsoon rainfall at various locations ranged between 324.8 mm at Sirsa and 974.9 mm at Chandigarh. The major amount of monsoon rainfall occurred during the month of July and August in the entire region. Monthly mean rainfall ranged between 37.5 to 144.9 mm (June), 130.6 to 298.2 mm (July), 92.6 to 313.6 mm (August) and 44.0 to 149.4mm (September) at different locations. All the locations in the region exhibited overall increasing trend in monsoon rainfall over the period under study. All locations in the region received their lowest monsoon rainfall in the year 1987 which was a drought year and the season's rainfall ranged between 56.1 mm (Sirsa) and 290.0 mm (Delhi) during this year. Many of the locations observed clusters of fluctuations in their respective monsoon rainfall. The statistical summaries of historical data series (1970-99) gave rainfall information on various time scale. Such information acquires value through its influence on the decision making of the ultimate users. (author)

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

Science.gov (United States)

Brienen, Roel J W; Zuidema, Pieter A

2005-11-01

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

Incident rainfall in Rome and its relation to biodeterioration of buildings

Energy Technology Data Exchange (ETDEWEB)

Caneva, G; Gori, E; Danin, A [Instituto Centrale per il Restauro, Rome (Italy)

1992-06-01

A discussion is presented of the intensity and distribution of incident rainfall in Rome, and the degree of lithobiont cover of building walls. During all seasons the rainfall shows a significant peak in the south and the southeast exposures, where the highest cover of lithobionts is found. The results show the role of incident rainfall in the climatic conditions of Rome as the main driving factor for the growth of lithobionts on walls where rainfall is their principal source of water. 31 refs., 4 figs., 2 tabs.

Decadal variability in snow depth anomaly over Eurasia and its association with all India summer monsoon rainfall and seasonal circulations

International Nuclear Information System (INIS)

Singh, G.P.

2003-05-01

The Historical Soviet Daily Snow Depth (HSDSD) version II data set has been used in the computation of winter and spring snow depth anomalies over west (25 deg. E to 70 deg. E, 35 deg. N to 65 deg. N) and east (70 deg. E to 160 deg. E, 35 deg. N to 65 deg. N) Eurasia. It is noticed that winter snow depth anomaly over east Eurasia is positively correlated while west Eurasia is negatively correlated with subsequent Indian summer monsoon rainfall (ISMR). The DJF snow depth anomaly shows highest and inverse correlation coefficient (CC) with ISMR over a large area of west Eurasia in a recent period of study i.e. 1975-1995. On the basis of standardised winter (mean of December, January and February) snow depth anomaly over west Eurasia, the years 1966, 1968, 1979 and 1986 are identified as high snow years and the years 1961 and 1975 as low snow years. The characteristics of seasonal monsoon circulation features have been studied in detail during contrasting years of less (more) snow depth in winter/spring seasons followed by excess (deficient) rainfall over India using National Center for Environmental Prediction (NCEP) / National Center for Atmospheric Research (NCAR) reanylised data for the period 1948-1995. The composite difference of temperature, wind, stream function and velocity potential during the years of high and low snow years at upper and lower levels have been studied in detail. The temperature at lower level shows maximum cooling up to 6 deg. C during DJF and this cooling persists up to 500hPa by 2 deg. C which gives rise to anomalous cyclonic circulation over the Caspian Sea and this may be one of the causes of the weakening of the summer monsoon circulation over Indian sub-continent. The stream function difference fields show westerly dominated over Arabian Sea at upper level in weak monsoon years. Velocity potential difference field shows complete phase reversal in the dipole structure from the deficient to excess Indian summer monsoon rainfall. (author)

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

Energy Technology Data Exchange (ETDEWEB)

Ye, Sheng [Institute of Hydrology and Water Resources, School of Civil Engineering, Zhejiang University, Hangzhou, China; Li, Hong-Yi [Pacific Northwest National Laboratory, Richland, Washington; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland, Washington; Guo, Jiali [College of Civil and Hydropower Engineering, China Three Gorges University, Yichang, China; State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China; Ran, Qihua [Institute of Hydrology and Water Resources, School of Civil Engineering, Zhejiang University, Hangzhou, China; Demissie, Yonas [Department of Civil and Environmental Engineering, Washington State University Tri-Cities, Richland, Washington; Sivapalan, Murugesu [Department of Geography and Geographic Information Science, University of Illinois at Urbana–Champaign, Champaign, Illinois; Department of Civil and Environmental Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois

2017-07-01

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

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

Science.gov (United States)

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

2005-01-01

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

Seasonal forecasting of fire over Kalimantan, Indonesia

Science.gov (United States)

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.

Statistical downscaling of rainfall: a non-stationary and multi-resolution approach

Science.gov (United States)

Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir

2016-05-01

A novel downscaling technique is proposed in this study whereby the original rainfall and reanalysis variables are first decomposed by wavelet transforms and rainfall is modelled using the semi-parametric additive model formulation of Generalized Additive Model in Location, Scale and Shape (GAMLSS). The flexibility of the GAMLSS model makes it feasible as a framework for non-stationary modelling. Decomposition of a rainfall series into different components is useful to separate the scale-dependent properties of the rainfall as this varies both temporally and spatially. The study was conducted at the Onkaparinga river catchment in South Australia. The model was calibrated over the period 1960 to 1990 and validated over the period 1991 to 2010. The model reproduced the monthly variability and statistics of the observed rainfall well with Nash-Sutcliffe efficiency (NSE) values of 0.66 and 0.65 for the calibration and validation periods, respectively. It also reproduced well the seasonal rainfall over the calibration (NSE = 0.37) and validation (NSE = 0.69) periods for all seasons. The proposed model was better than the tradition modelling approach (application of GAMLSS to the original rainfall series without decomposition) at reproducing the time-frequency properties of the observed rainfall, and yet it still preserved the statistics produced by the traditional modelling approach. When downscaling models were developed with general circulation model (GCM) historical output datasets, the proposed wavelet-based downscaling model outperformed the traditional downscaling model in terms of reproducing monthly rainfall for both the calibration and validation periods.

Nitrogen budget of 15 N-Labelled urea applied to dry land wheat as affected by seasonal rainfall

International Nuclear Information System (INIS)

Abdel-Monem, M.A.; Ryan, J.; Christianson, B.

1999-01-01

Field trial was conducted at two locations of the semi-arid region of Morocco with an objective of estimating the N balance for the applied urea to wheat under two different agroecological zones. N-15 labelled urea was applied in microplots (1 m x 1 m) at tillering stage at rates of 0,40,80, and 120 kg/ha. Soil and plant samples were analyzed for N-15 excess. An average of 45% increase in grain yield of wheat was due to fertilization with 60 kg N/ha. Recovery of N-15 labelled N ranged between 28.8 and 45.1% for the rate of 40 kg N/ha. Results suggested that efficiency of the applied fertilizer is governed by seasonal rainfall and soil properties

Evapotranspiration seasonality across the Amazon Basin

Science.gov (United States)

Eiji Maeda, Eduardo; Ma, Xuanlong; Wagner, Fabien Hubert; Kim, Hyungjun; Oki, Taikan; Eamus, Derek; Huete, Alfredo

2017-06-01

Evapotranspiration (ET) of Amazon forests is a main driver of regional climate patterns and an important indicator of ecosystem functioning. Despite its importance, the seasonal variability of ET over Amazon forests, and its relationship with environmental drivers, is still poorly understood. In this study, we carry out a water balance approach to analyse seasonal patterns in ET and their relationships with water and energy drivers over five sub-basins across the Amazon Basin. We used in situ measurements of river discharge, and remotely sensed estimates of terrestrial water storage, rainfall, and solar radiation. We show that the characteristics of ET seasonality in all sub-basins differ in timing and magnitude. The highest mean annual ET was found in the northern Rio Negro basin (˜ 1497 mm year-1) and the lowest values in the Solimões River basin (˜ 986 mm year-1). For the first time in a basin-scale study, using observational data, we show that factors limiting ET vary across climatic gradients in the Amazon, confirming local-scale eddy covariance studies. Both annual mean and seasonality in ET are driven by a combination of energy and water availability, as neither rainfall nor radiation alone could explain patterns in ET. In southern basins, despite seasonal rainfall deficits, deep root water uptake allows increasing rates of ET during the dry season, when radiation is usually higher than in the wet season. We demonstrate contrasting ET seasonality with satellite greenness across Amazon forests, with strong asynchronous relationships in ever-wet watersheds, and positive correlations observed in seasonally dry watersheds. Finally, we compared our results with estimates obtained by two ET models, and we conclude that neither of the two tested models could provide a consistent representation of ET seasonal patterns across the Amazon.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

2011-12-01

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

A Statistical Model for Seasonal Rainfall Forecasting over the ...

African Journals Online (AJOL)

In a preliminary step, in order to identify the most influential rainfall predictor, a correlation matrix and step-wise regression of 10 predictors with different lags were analysed. The influence of the southern Indian Ocean Sea Surface Temperature was identified as the most influential predictor for the highland of Eritrea.

Effect Of Seasonal Rainfall And Other Environmental Changes, On ...

African Journals Online (AJOL)

Background: The last study on snail population density in relation to rainfall pattern in Kigungu canoe landing and recreational sites on Lake Victoria shore was earlier carried out about fifteen years ago. This study also reviewed the influence of other environmental factors on the snails\\' infection rate. Objective: To reassess ...

Long-range forecast of monthly rainfall over India during summer monsoon season using SST in the north Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Sadhuram, Y.

only SS T. Utilizing the rainfall data of Pa r tha - sarathy et al. 6 and SSTA data (5 ? 5 d e- gree grids) of Kaplan et al. 8 , it is found that the SSTA over the AS du r ing winter (DJF ? 1/0 year) in the region 15 ? 20 ?N; 60 ? 70 ?E... and b ). The corr e lations are almost zero du r ing April and May, which is not shown. SSTA during fall in the CEIO is strongly and positively corr e lated with the seasonal and monthly rai n fall. It is w eak during other months (Figure 1 c...

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

Science.gov (United States)

Fishman, R.

2013-12-01

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

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

Science.gov (United States)

Liu, Maofeng

Rainfall and associated flood hazards are one of the major threats of tropical cyclones (TCs) to coastal and inland regions. The interaction of TCs with extratropical systems can lead to enhanced precipitation over enlarged areas through extratropical transition (ET). To achieve a comprehensive understanding of rainfall and ET associated with TCs, this thesis conducts weather-scale analyses by focusing on individual storms and climate-scale analyses by focusing on seasonal predictability and changing properties of climatology under global warming. The temporal and spatial rainfall evolution of individual storms, including Hurricane Irene (2011), Hurricane Hanna (2008), and Hurricane Sandy (2012), is explored using the Weather Research and Forecast (WRF) model and a variety of hydrometeorological datasets. ET and Orographic mechanism are two key players in the rainfall distribution of Irene over regions experiencing most severe flooding. The change of TC rainfall under global warming is explored with the Forecast-oriented Low Ocean Resolution (FLOR) climate model under representative concentration pathway (RCP) 4.5 scenario. Despite decreased TC frequency, FLOR projects increased landfalling TC rainfall over most regions of eastern United States, highlighting the risk of increased flood hazards. Increased storm rain rate is an important player of increased landfalling TC rainfall. A higher atmospheric resolution version of FLOR (HiFLOR) model projects increased TC rainfall at global scales. The increase of TC intensity and environmental water vapor content scaled by the Clausius-Clapeyron relation are two key factors that explain the projected increase of TC rainfall. Analyses on the simulation, prediction, and projection of the ET activity with FLOR are conducted in the North Atlantic. FLOR model exhibits good skills in simulating many aspects of present-day ET climatology. The 21st-century-projection under RCP4.5 scenario demonstrates the dominant role of ET

Ecosystem and Community Responses to Rainfall Manipulations in Shrublands Depends on Dominant Vegetation Cover

Science.gov (United States)

Esch, E. H.; Lipson, D.; Kim, J. B.; Cleland, E. E.

2014-12-01

Southern California is predicted to face decreasing precipitation with increased interannual variability in the coming century. Native shrublands in this area are increasingly invaded by exotic annual grasses, though invasion dynamics can vary by rainfall scenario, with wet years generally associated with high invasion pressure. Interplay between rainfall and invasion scenarios can influence carbon stocks and community composition. Here we asked how invasion alters ecosystem and community responses in drought versus high rainfall scenarios, as quantified by community identity, biomass production, and the normalized difference vegetation index (NDVI). To do this, we performed a rainfall manipulation experiment with paired plots dominated either by native shrubs or exotic herbaceous species, subjected to treatments of 50%, 100%, or 150% of ambient rainfall. The study site was located in a coastal sage scrub ecosystem, with patches dominated by native shrubs and exotic grasses located in San Diego County, USA. During two growing seasons, we found that native, herbaceous biomass production was significantly affected by rainfall treatment (p<0.05 for both years), though was not affected by dominant community composition. Photosynthetic biomass production of shrub species also varied by treatment (p=0.035). Exotic biomass production showed a significant interaction between dominant community composition and rainfall treatment, and both individual effects (p<0.001 for all). NDVI showed similar results, but also indicated the importance of rainfall timing on overall biomass production between years. Community composition data showed certain species, of both native and exotic identities, segregating by treatment. These results indicate that exotic species are more sensitive to rainfall, and that increased rainfall may promote greater carbon storage in annual dominated communities when compared to shrub dominated communities in high rainfall years, but with drought, this

The influence of seasonal rainfall upon Sahel vegetation

DEFF Research Database (Denmark)

Proud, Simon Richard; Rasmussen, Laura Vang

2011-01-01

Throughout the Sahelian region of Africa, vegetation growth displays substantial inter-annual variation, causing widespread concern in the region as rain-fed agriculture and pastoralism are a means of sustenance for the predominantly rural population. Previously proposed factors behind variations...... yields, carbon storage and landscape changes without the need to resort to rainfall estimates that are sometimes of low accuracy. In addition, it may be possible to apply the results to other dry land regions worldwide....

Indonesian Rainfall Characteristic Based on the EAR and WPR Data Analysis

Science.gov (United States)

Hermawan, Eddy

2010-05-01

As one of the most real product of the joint research between RISH (Research Institute for Sustainable Humanosphere) of Kyoto University, Japan with the National Institute of Aeronautics and Space (LAPAN), is being applied the Equatorial Atmosphere Radar (EAR) at Kototabang, Bukittinggi, West Sumatera that has already operated since June, 2001. The other one, since March 2007, has also operated the other radar that called as WPR (Wind Profiling Radar) at Pontianak and Biak station under the JAMSTEC (Japan Marine Science Technology), Japan. Those radars give a good chance for the Indonesian young scientist to apply those data in applicable research for many people. One of them is the behavior of Indonesian rainfall variability over Kototabang, Pontianak, and Biak, respectively. This is very important, since rainfall is one of the most important parameter that has direct effect to daily living, not only in wet season (suspected related to flooding) or dry season (suspected related to drought) than normal condition. We understood that until now, no many significant result obtained from those data, especially from WPR, not only since that data is still new one, but also related well to the limitation of the other suppport data, facility (hardware and software), also the man power (reseracher) working on that data analysis. Based on this condition, the main purpose of this study is to investigate the Indonesian rainfall behavior, especially over Kototabang, Pontianak, and Biak, respectively. The others are we would like to investigate the pattern of zonal wind variation along the Indian Ocean passing away to Indonesia region, to investigate the MJO (Madden Julian Oscillation) phenomenon, and to investigate the relationship or correlation between rainfall and zonal wind variation. The results show that in the wet season (DJF=December-January-February), Kototabang and surrounded area is dominated by the Westerly wind that mostly contains of water vapor. While, in the dry

Correlations of Rainfall and Forest Type with Papilionid Assemblages in Assam in Northeast India

Directory of Open Access Journals (Sweden)

Kamini Kusum Barua

2010-01-01

Full Text Available No comprehensive community studies have been done on the butterflies of the tropical monsoon forests of the East Himalayan region. We described the Papilionidae at one site within the continuous moist deciduous forest belt of Northeast India and their variation with season and forest type. We surveyed 20 permanent line transects, varying with respect to canopy openness and observed levels of disturbance. A total sample effort of 131 days during the dry and wet seasons of a two-year study resulted in 18,373 individuals identified from 28 Papilionidae species. Constrained canonical correspondence ordination was used to examine the effects of season, forest type, rainfall, year, altitude, and geographical position on the species assemblages. Results showed that rainfall, forest type, and season accounted for most variance in papilionid abundance. Rainfall was strongly correlated with the abundance of some species. Nine species were associated with gaps, 16 species were restricted to closed forest, and three species were encountered in both gaps and closed forest. Six species with narrow geographic range were found only in closed forest. The results confirm the strong seasonality of continental Southeast Asian butterfly assemblages.

Introducing a rainfall compound distribution model based on weather patterns sub-sampling

Directory of Open Access Journals (Sweden)

F. Garavaglia

2010-06-01

Full Text Available This paper presents a probabilistic model for daily rainfall, using sub-sampling based on meteorological circulation. We classified eight typical but contrasted synoptic situations (weather patterns for France and surrounding areas, using a "bottom-up" approach, i.e. from the shape of the rain field to the synoptic situations described by geopotential fields. These weather patterns (WP provide a discriminating variable that is consistent with French climatology, and allows seasonal rainfall records to be split into more homogeneous sub-samples, in term of meteorological genesis.

First results show how the combination of seasonal and WP sub-sampling strongly influences the identification of the asymptotic behaviour of rainfall probabilistic models. Furthermore, with this level of stratification, an asymptotic exponential behaviour of each sub-sample appears as a reasonable hypothesis. This first part is illustrated with two daily rainfall records from SE of France.

The distribution of the multi-exponential weather patterns (MEWP is then defined as the composition, for a given season, of all WP sub-sample marginal distributions, weighted by the relative frequency of occurrence of each WP. This model is finally compared to Exponential and Generalized Pareto distributions, showing good features in terms of robustness and accuracy. These final statistical results are computed from a wide dataset of 478 rainfall chronicles spread on the southern half of France. All these data cover the 1953–2005 period.

Intense rainfalls prediction models for the state of Mato Grosso, Brazil

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Sidney Pereira

2011-12-01

Full Text Available Rain intensity data are necessary to increase security of hydraulic projects. The objective of this study was to determine the relationships among intensity-duration-frequency (IDF and Bell’s model for the State of Mato Grosso, Brazil. The equations were obtained by disaggregation of 24 h rainfall data from 136 rain stations available in the National Water Agency (ANA data base. Employing Gumbel distribution, the rainfalls were estimated for each time duration and for the return periods of 2, 5, 10, 25, 50 and 100 years, and thereafter for each season. The coefficients of IDF relationships and Bell’s models were adjusted by the minimum square method, for all seasons evaluated. The coefficients of determination and Willmott agreement index exceeded 0.98 and 0.85, respectively, for all stations, which classifies the adjustment of the rainfall models as great.

Modeling and forecasting rainfall patterns of southwest monsoons in North-East India as a SARIMA process

Science.gov (United States)

Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

2018-02-01

Weather forecasting is an important issue in the field of meteorology all over the world. The pattern and amount of rainfall are the essential factors that affect agricultural systems. India experiences the precious Southwest monsoon season for four months from June to September. The present paper describes an empirical study for modeling and forecasting the time series of Southwest monsoon rainfall patterns in the North-East India. The Box-Jenkins Seasonal Autoregressive Integrated Moving Average (SARIMA) methodology has been adopted for model identification, diagnostic checking and forecasting for this region. The study has shown that the SARIMA (0, 1, 1) (1, 0, 1)4 model is appropriate for analyzing and forecasting the future rainfall patterns. The Analysis of Means (ANOM) is a useful alternative to the analysis of variance (ANOVA) for comparing the group of treatments to study the variations and critical comparisons of rainfall patterns in different months of the season.

Rainfall erosivity in Europe.

Science.gov (United States)

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

An Assessment of Satellite-Derived Rainfall Products Relative to Ground Observations over East Africa

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Margaret Wambui Kimani

2017-05-01

Full Text Available Accurate and consistent rainfall observations are vital for climatological studies in support of better agricultural and water management decision-making and planning. In East Africa, accurate rainfall estimation with an adequate spatial distribution is limited due to sparse rain gauge networks. Satellite rainfall products can potentially play a role in increasing the spatial coverage of rainfall estimates; however, their performance needs to be understood across space–time scales and factors relating to their errors. This study assesses the performance of seven satellite products: Tropical Applications of Meteorology using Satellite and ground-based observations (TAMSAT, African Rainfall Climatology And Time series (TARCAT, Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS, Tropical Rainfall Measuring Mission (TRMM-3B43, Climate Prediction Centre (CPC Morphing technique (CMORPH, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR, CPC Merged Analysis of Precipitation (CMAP, and Global Precipitation Climatology Project (GPCP, using locally developed gridded (0.05° rainfall data for 15 years (1998–2012 over East Africa. The products’ assessments were done at monthly and yearly timescales and were remapped to the gridded rain gauge data spatial scale during the March to May (MAM and October to December (OND rainy seasons. A grid-based statistical comparison between the two datasets was used, but only pixel values located at the rainfall stations were considered for validation. Additionally, the impact of topography on the performance of the products was assessed by analyzing the pixels in areas of highest negative bias. All the products could substantially replicate rainfall patterns, but their differences are mainly based on retrieving high rainfall amounts, especially of localized orographic types. The products exhibited systematic errors, which

Impacts of the ENSO Modoki and other Tropical Indo-Pacific Climate-Drivers on African Rainfall.

Science.gov (United States)

Preethi, B; Sabin, T P; Adedoyin, J A; Ashok, K

2015-11-16

The study diagnoses the relative impacts of the four known tropical Indo-Pacific drivers, namely, El Niño Southern Oscillation (ENSO), ENSO Modoki, Indian Ocean Dipole (IOD), and Indian Ocean Basin-wide mode (IOBM) on African seasonal rainfall variability. The canonical El Niño and El Niño Modoki are in general associated with anomalous reduction (enhancement) of rainfall in southern (northern) hemispheric regions during March-May season. However, both the El Niño flavours anomalously reduce the northern hemispheric rainfall during June-September. Interestingly, during boreal spring and summer, in many regions, the Indian Ocean drivers have influences opposite to those from tropical Pacific drivers. On the other hand, during the October-December season, the canonical El Niño and/or positive IOD are associated with an anomalous enhancement of rainfall in the Eastern Africa, while the El Niño Modoki events are associated with an opposite impact. In addition to the Walker circulation changes, the Indo-Pacific drivers influence the African rainfall through modulating jet streams. During boreal summer, the El Niño Modoki and canonical El Niño (positive IOD) tend to weaken (strengthen) the tropical easterly jet, and result in strengthening (weakening) and southward shift of African easterly jet. This anomalously reduces (enhances) rainfall in the tropical north, including Sahelian Africa.

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

Science.gov (United States)

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

2017-08-01

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

Contribution of landfalling tropical system rainfall to the hydroclimate of the eastern U.S. Corn Belt 1981–2012

Directory of Open Access Journals (Sweden)

Olivia Kellner

2016-09-01

Landfalling tropical system rainfall accounts for approximately 20% of the observed monthly rainfall during the tropical storm season (June–November across the eastern U.S. Corn Belt (1981–2012. Correlation between the annual number of landfalling tropical systems and annual yield by state results in no relationship, but correlation of August monthly observed rainfall by climate division to crop reporting district annual yields has a weak to moderate, statistically significant correlation in Ohio districts 30–60 and Indiana CRD 90. ANOVA analysis suggests that landfalling tropical rainfall may actually reduce yields in some state's climate divisions/crop reporting districts while increasing yield in others. Results suggest that there is a balance between landfalling tropical storms providing sufficient rainfall or too much rainfall to be of benefit to crops. Findings aim to provide information to producers, crop advisers, risk managers and commodity groups so that seasonal hurricane forecasts can potentially be utilized in planning for above or below normal precipitation during phenologically important portions of the growing season.

In-stream Physical Heterogeneity, Rainfall Aided Flushing, and Discharge on Stream Water Quality.

Science.gov (United States)

Gomes, Pattiyage I A; Wai, Onyx W H

2015-08-01

Implications of instream physical heterogeneity, rainfall-aided flushing, and stream discharge on water quality control have been investigated in a headwater stream of a climatic region that has contrasting dry and wet seasons. Dry (low flow) season's physical heterogeneity showed a positive correlation with good water quality. However, in the wet season, physical heterogeneity showed minor or no significance on water quality variations. Furthermore, physical heterogeneity appeared to be more complementary with good water quality subsequent to rainfall events. In many cases stream discharge was a reason for poor water quality. For the dry season, graywater inputs to the stream could be held responsible. In the wet season, it was probably the result of catchment level disturbances (e.g., regulation of ephemeral freshwater paths). Overall, this study revealed the importance of catchment-based approaches on water quality improvement in tandem with in-stream approaches framed on a temporal scale.

What rainfall events trigger landslides on the West Coast US?

Science.gov (United States)

Biasutti, Michela; Seager, Richard; Kirschbaum, Dalia

2016-04-01

A dataset of landslide occurrences compiled by collating google news reports covers 9 full years of data. We show that, while this compilation cannot provide consistent and widespread monitoring everywhere, it is adequate to capture the distribution of events in the major urban areas of the West Coast US and it can be used to provide a quantitative relationship between landslides and rainfall events. The case of the Seattle metropolitan area is presented as an example. The landslide dataset shows a clear seasonality in landslide occurrence, corresponding to the seasonality of rainfall, modified by the accumulation of soil moisture as winter progresses. Interannual variability of landslide occurrences is also linked to interannual variability of monthly rainfall. In most instances, landslides are clustered on consecutive days or at least within the same pentad and correspond to days of large rainfall accumulation at the regional scale. A joint analysis of the landslide data and of the high-resolution PRISM daily rainfall accumulation shows that on days when landslides occurred, the distribution of rainfall was shifted, with rainfall accumulation higher than 10mm/day being more common. Accumulations above 50mm/day much increase the probability of landslides, including the possibility of a major landslide event (one with multiple landslides in a day). The synoptic meteorological conditions associated with these major events show a mid-tropospheric ridge to the south of the target area steering a surface low and bringing enhanced precipitable water towards the Pacific North West. The interaction of the low-level flow with the local orography results in instances of a strong Puget Sound Convergence Zone, with widespread rainfall accumulation above 30mm/day and localized maxima as high as 100mm/day or more.

Parametric study on the effect of rainfall pattern to slope stability

OpenAIRE

Hakim Sagitaningrum Fathiyah; Bahsan Erly

2017-01-01

Landslide in Indonesia usually occurs during the rainy seasons. Previous studies showed that rainfall infiltration has a great effect on the factor of safety (FS) of slopes. This research focused on the effect of rainfall pattern on the FS of unsaturated slope with different slope angle i.e.: 30°, 45°, and 60°. Three different rainfall patterns, which are normal, advanced, and delayed were considered in the analysis. The effects of low or high hydraulic conductivity of the soil are also obser...

The Spatial Scaling of Global Rainfall Extremes

Science.gov (United States)

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

2013-12-01

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

Soybean Yield along the Texas Gulf Coast during Periods of Variable Rainfall as Influenced by Soybean Cultivar and Planting Date

Directory of Open Access Journals (Sweden)

W. J. Grichar

2011-01-01

Full Text Available Soybeans (Glycine max can be planted along the upper Texas Gulf Coast from mid-March through May to take advantage of early season rains and to complete harvest before hurricane season and fall rains become a problem. When average to above average rainfall was received in May through July, yields were greater with the early April to mid-April planting; however, under high rainfall conditions throughout the season, the mid-April to early May planting produced the highest yields, with yields of over 4000 kg/ha. When rainfall was below normal, late March to early April plantings produced the greatest yields. When rainfall was above average, soybeans took longer to reach harvestability regardless of cultivar or plant dates, while under drought conditions the interval between planting and harvest was reduced. However, when planting was delayed, there was a greater risk of detrimental late-season effects from southern green stink bug (Nezara viridula or the brown stink bug (Euschistus heros.

Bias adjustment and advection interpolation of long-term high resolution radar rainfall series

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Nielsen, Jesper Ellerbæk; Rasmussen, Michael R.

2014-01-01

It is generally acknowledged that in order to apply radar rainfall data for hydrological proposes adjustment against ground observations are crucial. Traditionally, radar reflectivity is transformed into rainfall rates applying a fixed reflectivity – rainfall rate relationship even though...... this is known to depend on the changing drop size distribution of the specific rain. This creates a transient bias between the radar rainfall and the ground observations due to seasonal changes of the drop size distribution as well as other atmospheric effects and effects related to the radar observational...

Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

Science.gov (United States)

Mandal, S.; Choudhury, B. U.

2015-07-01

Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

Rainfall over the African continent from the 19th through the 21st century

Science.gov (United States)

Nicholson, Sharon E.; Funk, Chris; Fink, Andreas H.

2018-06-01

Most of the African continent is semi-arid and hence prone to extreme variations in rainfall from year to year. The extreme droughts that have plagued the Sahel and eastern Africa are particularly well known. This article uses a markedly expanded and updated rainfall data set to examine rainfall variability in 13 sectors that cover most of the continent. Annual rainfall is presented for each sector; the March-to-May and October-November seasons are also examined for equatorial sectors. In each case, the article includes the longest and most comprehensive precipitation gauge series ever published. All time series cover at least a century and most cover roughly one and one-half centuries or more. Although towards the end of the 20th century there was a widespread trend towards more arid conditions, few significant trends are evident over the entire period of record. The largest were downward trends in the Sahel and western sectors of North Africa. In those regions, an abrupt reduction in rainfall occurred around 1968, but a synchronous change occurred many other parts of Africa. A recovery did occur in the Sahel, but to varying degrees across the east-west expanse of the region. Noteworthy is that the west-to-east rainfall gradient across the region appears to have weakened in recent decades. For the continent as a whole, another change began in the 1980s decade, with more arid conditions persisting at the continental scale until early in the twenty-first century. No other such period of dry conditions occurred within the roughly one and one-half centuries evaluated here. A notable change also occurred at the seasonal level. During the period 1980 to 1998 rainfall during March-to-May was well below the long-term mean throughout most of the area from 20° N to 35° S. At the same time rainfall was above the long-term mean in most of eastern sectors within this latitude span, indicating a change in the seasonality of rainfall of a large part of Africa.

The time series variations of tritium concentration in precipitation and its relationships to the rainfall-inducing air mass

International Nuclear Information System (INIS)

Shimada, Jun

1978-01-01

The author measured the tritium concentration in precipitation of Tokyo for every ten-day period from August 1972 to May 1974. Judging from the daily synoptic weather chart, the rainfall-inducing air masses in Japan were classified into five types; polar maritime air mass (Pm), polar continental air mass (Pc), tropical maritime air mass (Tm), tropical continental air mass (Tc), and equatorial maritime air mass (Em). And the precipitation for every ten-day period sampled for tritium measurement were classified into these five types. Based on this classification, it is confirmed that there exist clear difference in the tritium concentration between the rainfall from the continental air mass and ones from the maritime air mass. It is characteristic that the tritium concentration in rainfall induced by equatorial maritime air mass such as typhoon in summer and early fall season is very low whereas the tritium concentration in rainfall and snowfall induced directly by the polar continental air mass in late winter season is very high. The regional difference of the tritium concentration in intermonthly precipitation could considerably be explained by this synoptic meteological classification of rainfall-inducing air mass. In spite of these regional difference of tritium concentration in precipitation, use of the tritium concentration of Tokyo as a representative value of Japan may be allowed because of the similarities of the changing pattern and annual mean tritium concentration. The time series variations of tritium concentration in precipitation of Tokyo from August 1972 to December 1977, Tsukuba from December 1976 to April 1978, and Nagaoka from April 1977 to March 1978 are listed. (author)

Detection of Anomalies and Changes of Rainfall in the Yellow River Basin, China, through Two Graphical Methods

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Hao Wu

2017-12-01

Full Text Available This study aims to reveal rainfall anomalies and changes over the Yellow River Basin due to the fragile ecosystem and rainfall-related disasters. Common trend analyses relate to overall trends in mean values. Therefore, we used two graphical methods: the quantile perturbation method (QPM was used to investigate anomalies over time in extreme rainfall, and the partial trend method (PTM was used to analyze rainfall changes at different intensities. A nonparametric bootstrap procedure is proposed in order to identify significant PTM indices. The QPM indicated prevailing positive anomalies in extreme daily rainfall 50 years ago and in the middle reaches during the 1970s and 1980s. The PTM detected significant decreases in annual rainfall mainly in the latter half of the middle reaches, two-thirds of which occurred in high and heavy rainfall. Most stations in the middle and lower reaches showed significant decreases in rainy days. Daily rainfall intensity had a significant increase at 13 stations, where rainy days were generally decreasing. The combined effect of these opposing changes explains the prevailing absence of change in annual rainfall, and the observed decreases in annual rainfall can be attributed to the decreasing number of rainy days. The changes in rainy days and rainfall intensity were dominated by the wet season and dry season, respectively.

Decadal variability in snow depth anomaly over Eurasia and its association with all India summer monsoon rainfall and seasonal circulations

CERN Document Server

Singh, G P

2003-01-01

The Historical Soviet Daily Snow Depth (HSDSD) version II data set has been used in the computation of winter and spring snow depth anomalies over west (25 deg. E to 70 deg. E, 35 deg. N to 65 deg. N) and east (70 deg. E to 160 deg. E, 35 deg. N to 65 deg. N) Eurasia. It is noticed that winter snow depth anomaly over east Eurasia is positively correlated while west Eurasia is negatively correlated with subsequent Indian summer monsoon rainfall (ISMR). The DJF snow depth anomaly shows highest and inverse correlation coefficient (CC) with ISMR over a large area of west Eurasia in a recent period of study i.e. 1975-1995. On the basis of standardised winter (mean of December, January and February) snow depth anomaly over west Eurasia, the years 1966, 1968, 1979 and 1986 are identified as high snow years and the years 1961 and 1975 as low snow years. The characteristics of seasonal monsoon circulation features have been studied in detail during contrasting years of less (more) snow depth in winter/spring seasons f...

Seasonality in cholera dynamics : a rainfall-driven model explains the wide range of patterns of an infectious disease in endemic areas

Science.gov (United States)

Baracchini, Theo; Pascual, Mercedes; King, Aaron A.; Bouma, Menno J.; Bertuzzo, Enrico; Rinaldo, Andrea

2015-04-01

An explanation for the spatial variability of seasonal cholera patterns has remained an unresolved problem in tropical medicine te{pascual_2002}. Previous studies addressing the role of climate drivers in disease dynamics have focused on interannual variability and modelled seasonality as given te{king_nature}. Explanations for seasonality have relied on complex environmental interactions that vary with spatial location (involving regional hydrological models te{bertuzzo_2012}, river discharge, sea surface temperature, and plankton blooms). Thus, no simple and unified theory based on local climate variables has been formulated te{emch_2008}, leaving our understanding of seasonal variations of cholera outbreaks in different regions of the world incomplete. Through the analysis of a unique historical dataset containing 50 years of monthly meteorological, demographic and epidemiological records, we propose a mechanistic, SIR-based stochastic model for the population dynamics of cholera driven by local rainfall and temperature that is able to capture the full range of seasonal patterns in this large estuarine region, which encompasses the variety of patterns worldwide. Parameter inference was implemented via new statistical methods that allow the computation of maximum-likelihood estimates for partially observed Markov processes through sequential Monte-Carlo te{ionides_2011}. Such a model may provide a unprecedented opportunity to gain insights on the conditions and factors responsible for endemicity around the globe, and therefore, to also revise our understanding of the ecology of Vibrio cholerae. Results indicate that the hydrological regime is a decisive driver determining the seasonal dynamics of cholera. It was found that rainfall and longer water residence times tend to buffer the propagation of the disease in wet regions due to a dilution effect, while also enhancing cholera incidence in dry regions. This indicates that overall water levels matter and appear

Seasonal variations in hospital admissions for mania

DEFF Research Database (Denmark)

Medici, Clara Reece; Vestergaard, Claus Høstrup; Hadzi-Pavlovic, Dusan

2016-01-01

in summer. Higher admission rates were associated with more sunshine, more ultraviolet radiation, higher temperature and less snow but were unassociated with rainfall. We did not find a secular trend in the seasonal pattern. Finally, neither gender nor admission status impacted on the overall seasonal...

Ajustement statistique des simulations climatiques : l'exemple des précipitations saisonnières de l'Amérique tropicaleStatistical adjustment of simulated climate: example of seasonal rainfall of tropical America.

Science.gov (United States)

Moron, Vincent; Navarra, Antonio

2000-05-01

This study presents the skill of the seasonal rainfall of tropical America from an ensemble of three 34-year general circulation model (ECHAM 4) simulations forced with observed sea surface temperature between 1961 and 1994. The skill gives a first idea of the amount of potential predictability if the sea surface temperatures are perfectly known some time in advance. We use statistical post-processing based on the leading modes (extracted from Singular Value Decomposition of the covariance matrix between observed and simulated rainfall fields) to improve the raw skill obtained by simple comparison between observations and simulations. It is shown that 36-55 % of the observed seasonal variability is explained by the simulations on a regional basis. Skill is greatest for Brazilian Nordeste (March-May), but also for northern South America or the Caribbean basin in June-September or northern Amazonia in September-November for example.

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

Science.gov (United States)

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.

Statistical evaluation of rainfall time series in concurrence with agriculture and water resources of Ken River basin, Central India (1901-2010)

Science.gov (United States)

Meshram, Sarita Gajbhiye; Singh, Sudhir Kumar; Meshram, Chandrashekhar; Deo, Ravinesh C.; Ambade, Balram

2017-12-01

Trend analysis of long-term rainfall records can be used to facilitate better agriculture water management decision and climate risk studies. The main objective of this study was to identify the existing trends in the long-term rainfall time series over the period 1901-2010 utilizing 12 hydrological stations located at the Ken River basin (KRB) in Madhya Pradesh, India. To investigate the different trends, the rainfall time series data were divided into annual and seasonal (i.e., pre-monsoon, monsoon, post-monsoon, and winter season) sub-sets, and a statistical analysis of data using the non-parametric Mann-Kendall (MK) test and the Sen's slope approach was applied to identify the nature of the existing trends in rainfall series for the Ken River basin. The obtained results were further interpolated with the aid of the Quantum Geographic Information System (GIS) approach employing the inverse distance weighted approach. The results showed that the monsoon and the winter season exhibited a negative trend in rainfall changes over the period of study, and this was true for all stations, although the changes during the pre- and the post-monsoon seasons were less significant. The outcomes of this research study also suggest significant decreases in the seasonal and annual trends of rainfall amounts in the study period. These findings showing a clear signature of climate change impacts on KRB region potentially have implications in terms of climate risk management strategies to be developed during major growing and harvesting seasons and also to aid in the appropriate water resource management strategies that must be implemented in decision-making process.

Temporal and spatial variations of rainfall erosivity in Southern Taiwan

Science.gov (United States)

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.

Prediction of meteorological parameters - 3: Rainfall and droughts

International Nuclear Information System (INIS)

Njau, E.C.

1990-11-01

We describe two new methods by which rainfall and hence meteorological droughts at any location on the earth may be predicted. The first method is based upon well supported observations that rainfall distribution at a given location during any local sunspot-related temperature/heat cycle is approximately similar to the distribution during another cycle associated with approximately similar sunspot cycle provided that the two temperature/heat cycles involved are immediately preceded by approximately similar sunspot cycles. The second method is based upon the fact that rainfall belts or patterns seem to be closely related to certain spatial and time-dependent temperature/heat patterns in the earth-atmosphere system. Reasonable predictions of these temperature/heat patterns may be made, and hence the associated rainfall patterns or belts may correspondingly be predicted. Specific examples are given to illustrate the two prediction methods. (author). 12 refs, 11 figs, 1 tab

Predictability of rainy season onset and cessation in east Africa

Science.gov (United States)

Joseph, B.-M.

2012-04-01

PREDICTABILITY OF RAINY SEASONS ONSET AND CESSATION IN EAST AFRICA Boyard-Micheau Joseph, joseph.boyard-micheau@u-bourgogne.fr Camberlin Pierre, Kenya and northern Tanzania mainly display bimodal rainfall regimes, which are controlled by the annual migration of the Intertropical Convergence Zone on both sides of the equator. In the low-income, semi-arid areas, food security is highly dependent on cereal yields (maize, millet and sorghum). Vulnerability is aggravated by the fact that these crops are mostly rainfed, and rely on the performance of the two, relatively brief rainy seasons. This performance depends on a combination of several rainy season characteristics, or rainfall descriptors, such as the onset and cessation dates of the rains, the frequency of rainy days, their intensity and the occurrence of wet/dry spells. The prediction of these descriptors some time (>15 days) before the real onset of the rainy season can be seen as a useful tool to help in the establishment of agricultural adaptation strategies. The main objective consists to understand linkages between regional variability of these rainfall descriptors and global modes of the climate system, in order to set up efficient predictive tools based on Model Output Statistics (MOS). The rainfall descriptors are computed from daily rainfall data collected for the period 1961-2001 from the Kenya Meteorological Department, the IGAD Climate Prediction and Application Center and the Tanzania Meteorological Agency. An initial spatial coherence analysis assesses the potential predictability of each descriptor, permitting eventually to eliminate those which are not spatially coherent, on the assumption that low spatial coherence denotes low potential predictability. Rainfall in East Africa simulated by a 24-ensemble member of the ECHAM 4.5 atmospheric general circulation model is compared with observations, to test the reproducibility of the rainfall descriptors. Canonical Correlation Analysis is next used to

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

Science.gov (United States)

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.

Dry-season retreat and dietary shift of the dart-poison frog Dendrobates tinctorius (Anura: Dendrobatidae)

NARCIS (Netherlands)

Born, M.; Bongers, F.; Poelman, E.H.; Sterck, F.J.

2010-01-01

Dry-season retreat and dietary shift of the dart-poison frog Delldrobates tillCtOrillS (Anura: Dendrobatidae). Seasonal rainfall affects tropical forest dynamics and behavior of species that are part of these ecosystems. TIle positive correlation between amphibian ac tivity pattems and rainfall has

Seasonal changes of fructans in dimorphic roots of Ichthyothere terminalis (Spreng.) Blake (Asteraceae) growing in Cerrado.

Science.gov (United States)

de Almeida, Lorrayne Veloso; Ferri, Pedro Henrique; Seraphin, José Carlos; de Moraes, Moemy Gomes

2017-11-15

Cerrado is a floristically rich savanna in Brazil, whose vegetation consists of a physiognomic mosaic, influenced by rainfall seasonality. In the dry season rainfall is substantially lower and reduces soil water supply, mainly for herbs and subshrubs. Climatic seasonal variations may well define phenological shifts and induce fluctuations of plant reserve pools. Some Cerrado native species have thickened underground organs that bear buds and store reserves, as adaptive features to enable plant survival following environmental stresses. Asteraceae species accumulate fructans in storage organs, which are not only reserve, but also protecting compounds against the effects of cold and drought. Ichthyothere terminalis is one Asteraceae species abundant in cerrado rupestre, with underground organs consisting of thickened orthogravitropic and diagravitropic roots. The objectives of this study were to analyze how abiotic environmental factors and plant phenology influence fructan dynamics in field grown plants, and verify if fructan metabolism differs in both root types for one year. I. terminalis accumulates inulin-type fructans in 10-40% of the dry mass in both root types. Fructan dynamics have similar patterns described for other Asteraceae species, exhibiting a proportional increase of polysaccharides with the senescence of the aerial organs. Multivariate analyzes showed that, as rainfall decreased, environmental factors had a stronger influence on metabolite levels than phenological shifts in both root types. Only slight differences were found in fructan dynamics between orthogravitropic and diagravitropic roots, suggesting they may have similar fructan metabolism regulation. However, these small differences may reflect distinct microclimatic conditions in both root types and also represent the influence of sink strength. Copyright © 2017 Elsevier B.V. All rights reserved.

Rainfall Downscaling Conditional on Upper-air Variables: Assessing Rainfall Statistics in a Changing Climate

Science.gov (United States)

Langousis, Andreas; Deidda, Roberto; Marrocu, Marino; Kaleris, Vassilios

2014-05-01

Due to its intermittent and highly variable character, and the modeling parameterizations used, precipitation is one of the least well reproduced hydrologic variables by both Global Climate Models (GCMs) and Regional Climate Models (RCMs). This is especially the case at a regional level (where hydrologic risks are assessed) and at small temporal scales (e.g. daily) used to run hydrologic models. In an effort to remedy those shortcomings and assess the effect of climate change on rainfall statistics at hydrologically relevant scales, Langousis and Kaleris (2013) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables. The developed downscaling scheme was tested using atmospheric data from the ERA-Interim archive (http://www.ecmwf.int/research/era/do/get/index), and daily rainfall measurements from western Greece, and was proved capable of reproducing several statistical properties of actual rainfall records, at both annual and seasonal levels. This was done solely by conditioning rainfall simulation on a vector of atmospheric predictors, properly selected to reflect the relative influence of upper-air variables on ground-level rainfall statistics. In this study, we apply the developed framework for conditional rainfall simulation using atmospheric data from different GCM/RCM combinations. This is done using atmospheric data from the ENSEMBLES project (http://ensembleseu.metoffice.com), and daily rainfall measurements for an intermediate-sized catchment in Italy; i.e. the Flumendosa catchment. Since GCM/RCM products are suited to reproduce the local climatology in a statistical sense (i.e. in terms of relative frequencies), rather than ensuring a one-to-one temporal correspondence between observed and simulated fields (i.e. as is the case for ERA-interim reanalysis data), we proceed in three steps: a) we use statistical tools to establish a linkage between ERA-Interim upper-air atmospheric forecasts and

Using Seasonal Climate Forecasts to Guide Disaster Management: The Red Cross Experience during the 2008 West Africa Floods

Directory of Open Access Journals (Sweden)

Arame Tall

2012-01-01

Full Text Available In 2008, the seasonal forecast issued at the Seasonal Climate Outlook Forum for West Africa (PRESAO announced a high risk of above-normal rainfall for the July–September rainy season. With probabilities for above-normal rainfall of 0.45, this forecast indicated noteworthy increases in the risk of heavy rainfall. When this information reached the International Federation of Red Cross and Red Crescent Societies (IFRC West and Central Africa Office, it led to significant changes in the organization’s flood response operations. The IFRC regional office requested funds in advance of anticipated floods, prepositioned disaster relief items in strategic locations across West Africa to benefit up to 9,500 families, updated its flood contingency plans, and alerted vulnerable communities and decision-makers across the region. This forecast-based preparedness resulted in a decrease in the number of lives, property, and livelihoods lost to floods, compared to just one year prior in 2007 when similar floods claimed above 300 lives in the region. This article demonstrates how a science-based early warning informed decisions and saved lives by triggering action in anticipation of forecast events. It analyses what it took to move decision-makers to action, based on seasonal climate information, and to overcome traditional barriers to the uptake of seasonal climate information in the region, providing evidence that these barriers can be overcome. While some institutional, communication and technical barriers were addressed in 2008, many challenges remain. Scientists and humanitarians need to build more common ground.

Combined effect of MJO, ENSO and IOD on the intraseasonal variability of northeast monsoon rainfall over south peninsular India

Science.gov (United States)

Sreekala, P. P.; Rao, S. Vijaya Bhaskara; Rajeevan, K.; Arunachalam, M. S.

2018-02-01

The present study has examined the combined effect of MJO, ENSO and IOD on the intraseasonal and interannual variability of northeast monsoon rainfall over south peninsular India. The study has revealed that the intraseasonal variation of daily rainfall over south peninsular India during NEM season is associated with various phases of eastward propagating MJO life cycle. Positive rainfall anomaly over south peninsular India and surrounding Indian Ocean (IO) is observed during the strong MJO phases 2, 3 and 4; and negative rainfall anomaly during the strong MJO phases 5,6,7,8 and 1. Above normal (below normal) convection over south peninsular India and suppressed convection over east Indian and West Pacific Ocean, high pressure (low pressure) anomaly over West Pacific Ocean, Positive (negative) SST anomalies over equatorial East and Central Pacific Ocean and easterly wind anomaly (westerly anomaly) over equatorial Indian Ocean are the observed features during the first three MJO (5, 6, 7) phases and all these features are observed in the excess (drought) NEMR composite. This suggests that a similar mode of physical mechanism is responsible for the intraseasonal and interannual variability of northeast monsoon rainfall. The number of days during the first three phases (last four phases) of MJO, where the enhanced convection and positive rainfall anomaly is over Indian Ocean (East Indian ocean and West Pacific Ocean), is more (less) during El Nino and IOD years and less during La Nina and NIOD years and vice versa. The observed excess (deficit) rainfall anomaly over west IO and south peninsular India and deficit (excess) rainfall anomaly over east IO including Bay of Bengal and West Pacific Ocean suggest that the more (less) number of first three phases during El Nino and IOD (La Nina and Negative IOD) is due to the interaction between eastward moving MJO and strong easterlies over equatorial IO present during El Nino and IOD years. This interaction would inhibit the

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

Science.gov (United States)

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

2017-12-01

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

Estimation of potential rainfall recharge in the pothwar area

International Nuclear Information System (INIS)

Afzal, M.; Yaseen, M.

2015-01-01

Groundwater recharge is complex phenomenon to understand and describe because it cannot be seen with open eyes. We have to depend some theoretical assumptions to understand this complicated hidden natural underground water movement process. There are many factors affecting and controlling the water movement in soil profile. Groundwater use in district chakwal is of a fundamental importance to meet the rapidly expanding drinking and agricultural water requirements. The man factors contributing to groundwater recharge in chakwal are rainfall, evapotranspiration and geology. due to the semi arid climatic conditions of the area, this resource is almost the only key to economic development. There are a number of dug wells in the area where water is getting stored during rainy season. source and processes of recharge in humid areas are different compared with semi-arid areas. Due to the main resource of available water in the area, the potential groundwater recharge estimation could be good exercise to visulize the amount of rainwater entering the ground. For groundwater recharge estimation there are a number of simple and advanced techniques available. In the present study simple methods were used to estimate potential recharge due to available limited resources. Rainfall runoff, gravimetric and water table fluctuation methods were used to quantify rainfall recharge during the monsoon season. The average potential recharge estimated was 60% of the rainfall of 148 mm. Rainfall runoff and gravimetric methods were found to be comparable for short period potential recharge estimation while water table fluctuation method gives actual recharge and require longer period data. Potential recharge values were higher for area having grassland type vegetation and low for area covering shrubs and tick vegetation. (author)

Detecting changes in rainfall pattern and seasonality index vis-`a-vis ...

Indian Academy of Sciences (India)

index vis-`a-vis increasing water scarcity in Maharashtra ... in the district scale are identified by trend analysis of rainfall time series. ... for better disaster management and water resource ..... productivity and irrigation water supply in the con-.

Seasonal prediction of Indian summer monsoon rainfall in NCEP CFSv2: forecast and predictability error

Science.gov (United States)

Pokhrel, Samir; Saha, Subodh Kumar; Dhakate, Ashish; Rahman, Hasibur; Chaudhari, Hemantkumar S.; Salunke, Kiran; Hazra, Anupam; Sujith, K.; Sikka, D. R.

2016-04-01

A detailed analysis of sensitivity to the initial condition for the simulation of the Indian summer monsoon using retrospective forecast by the latest version of the Climate Forecast System version-2 (CFSv2) is carried out. This study primarily focuses on the tropical region of Indian and Pacific Ocean basin, with special emphasis on the Indian land region. The simulated seasonal mean and the inter-annual standard deviations of rainfall, upper and lower level atmospheric circulations and Sea Surface Temperature (SST) tend to be more skillful as the lead forecast time decreases (5 month lead to 0 month lead time i.e. L5-L0). In general spatial correlation (bias) increases (decreases) as forecast lead time decreases. This is further substantiated by their averaged value over the selected study regions over the Indian and Pacific Ocean basins. The tendency of increase (decrease) of model bias with increasing (decreasing) forecast lead time also indicates the dynamical drift of the model. Large scale lower level circulation (850 hPa) shows enhancement of anomalous westerlies (easterlies) over the tropical region of the Indian Ocean (Western Pacific Ocean), which indicates the enhancement of model error with the decrease in lead time. At the upper level circulation (200 hPa) biases in both tropical easterly jet and subtropical westerlies jet tend to decrease as the lead time decreases. Despite enhancement of the prediction skill, mean SST bias seems to be insensitive to the initialization. All these biases are significant and together they make CFSv2 vulnerable to seasonal uncertainties in all the lead times. Overall the zeroth lead (L0) seems to have the best skill, however, in case of Indian summer monsoon rainfall (ISMR), the 3 month lead forecast time (L3) has the maximum ISMR prediction skill. This is valid using different independent datasets, wherein these maximum skill scores are 0.64, 0.42 and 0.57 with respect to the Global Precipitation Climatology Project

Rainfall Climatology over Asir Region, Saudi Arabia

Science.gov (United States)

Sharif, H.; Furl, C.; Al-Zahrani, M.

2012-04-01

Arid and semi-arid lands occupy about one-third of the land surface of the earth and support about one-fifth of the world population. The Asir area in Saudi Arabia is an example of these areas faced with the problem of maintaining sustainable water resources. This problem is exacerbated by the high levels of population growth, land use changes, increasing water demand, and climate variability. In this study, the characteristics of decade-scale variations in precipitation are examined in more detail for Asir region. The spatio-temporal distributions of rainfall over the region are analyzed. The objectives are to identify the sensitivity, magnitude, and range of changes in annual and seasonal evapotranspiration resulting from observed decade-scale precipitation variations. An additional objective is to characterize orographic controls on the space-time variability of rainfall. The rainfall data is obtained from more than 30 rain gauges spread over the region.

Rainfall and Development of Zika Virus

African Journals Online (AJOL)

2017-11-01

Nov 1, 2017 ... between rainfall and incidence of arbovirus disease such as dengue is well demonstrated (2). For Zika virus an infection, a similar observation can be expected. A recent report from Thailand can also show the expected pattern of the prevalence of Zika virus infection in the areas with high rainfall (3).

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

Science.gov (United States)

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

Seasonal Scale Convective-Stratiform Pricipitation Variabilities at Tropics

Science.gov (United States)

S, Sreekanth T.

begin{center} Large Seasonal Scale Convective-Stratiform Pricipitation Variabilities at Tropics Sreekanth T S*, Suby Symon*, G. Mohan Kumar (1) and V Sasi Kumar (2) *Centre for Earth Science Studies, Akkulam, Thiruvananthapuram (1) D-330, Swathi Nagar, West Fort, Thiruvananthapuram 695023 (2) 32. NCC Nagar Peroorkada, Thiruvananthapuram ABSTRACT This study investigates the variabilities of convective and stratiform rainfall from 2011 to 2013 at a tropical coastal station in three seasons viz Pre-Monsoon (March-May), Monsoon (June-September) and Post-Monsoon (October-December). Understanding the climatological variability of these two dominant forms of precipitation and their implications in the total rainfall were the main objectives of this investigation. Variabilities in the frequency & duration of events, rain rate & total number of rain drops distribution in different events and the accumulated amount of rain water were analysed. Based on the ground & radar observations from optical & impact disdrometers, Micro Rain Radar and Atmospheric Electric Field Mill, precipitation events were classified into convective and stratiform in three seasons. Classification was done by the method followed by Testud et al (2001) and as an additional information electrical behaviour of clouds from Atmospheric Electric Field Mill is also used. Events which could not be included in both types were termed as 'mixed precipitation' and were included separately. Diurnal variability of the total rainfall in each seasons were also examined. For both convective and stratiform rainfall there exist distinct day-night differences. During nocturnal hours convective rain draged more attention. In all seasons almost 70% of rain duration and 60% of rain events of convective origin were confined to nocturnal hours. But stratiform rain was not affected by diurnal variations greatly because night time occurrences of stratiform duration and events were less than 50%. Also in Monsoon above 35% of

Positive response of Indian summer rainfall to Middle East dust

KAUST Repository

Jin, Qinjian

2014-06-02

Using observational and reanalyses data, we investigated the impact of dust aerosols over the Middle East and the Arabian Sea (AS) on the Indian summer monsoon (ISM) rainfall. Satellite and aerosol reanalysis data show extremely heavy aerosol loading, mainly mineral dust, over the Middle East and AS during the ISM season. Multivariate empirical orthogonal function analyses suggest an aerosol-monsoon connection. This connection may be attributed to dust-induced atmospheric heating centered over the Iranian Plateau (IP), which enhances the meridional thermal contrast and strengthens the ISM circulation and rainfall. The enhanced circulation further transports more dust to the AS and IP, heating the atmosphere (positive feedback). The aerosols over the AS and the Arabian Peninsula have a significant correlation with rainfall over central and eastern India about 2 weeks later. This finding highlights the nonlocal radiative effect of dust on the ISM circulation and rainfall and may improve ISM rainfall forecasts. © 2014. American Geophysical Union. All Rights Reserved.

Positive response of Indian summer rainfall to Middle East dust

KAUST Repository

Jin, Qinjian; Wei, Jiangfeng; Yang, Zong-Liang

2014-01-01

Using observational and reanalyses data, we investigated the impact of dust aerosols over the Middle East and the Arabian Sea (AS) on the Indian summer monsoon (ISM) rainfall. Satellite and aerosol reanalysis data show extremely heavy aerosol loading, mainly mineral dust, over the Middle East and AS during the ISM season. Multivariate empirical orthogonal function analyses suggest an aerosol-monsoon connection. This connection may be attributed to dust-induced atmospheric heating centered over the Iranian Plateau (IP), which enhances the meridional thermal contrast and strengthens the ISM circulation and rainfall. The enhanced circulation further transports more dust to the AS and IP, heating the atmosphere (positive feedback). The aerosols over the AS and the Arabian Peninsula have a significant correlation with rainfall over central and eastern India about 2 weeks later. This finding highlights the nonlocal radiative effect of dust on the ISM circulation and rainfall and may improve ISM rainfall forecasts. © 2014. American Geophysical Union. All Rights Reserved.

Seasonality in the dung beetle community in a Brazilian tropical dry forest: Do small changes make a difference?

Science.gov (United States)

Medina, Anderson Matos; Lopes, Priscila Paixão

2014-01-01

Dung beetle (Coleoptera: Scarabaeoidea: Scarabaeinae) activity is influenced by rainfall seasonality. We hypothesized that rainfall might also play a major role in regulating the community structure of this group. In this study, we describe seasonal changes in the richness, composition, and structure of the Scarabaeinae community in a Brazilian tropical dry forest. A fragment of arboreal Caatinga was sampled using baited pitfall traps during the early dry season (EDS), late dry season (LDS), early wet season (EWS), and middle wet season (MWS). We compared the dung beetle community in each season in relationship to species richness, rank-dominance, curves, and composition. We collected 1352 Scarabaeinae individuals , belonging to 15 species. Dichotomius aff. laevicollis Felsche (Coleoptera: Scarabaeidae) was the dominant species, representing 73.89% of the individuals. There were no seasonal changes in the rank dominance curves; all had a single dominant species and a few species with low abundance, typical for arid areas. Estimated richness was highest in MWS, followed by EWS. Dry-season samples (EDS and LDS) had lower richness, with no significant difference between the dry seasons. Although species richness increased as the habitat became wetter, the difference between the wet and dry seasons was small, which differs completely from the findings of other studies in Neotropical dry forests, where almost all species cease activities in the dry season. Species composition changes were found in non-metric multidimensional scaling and sustained by analysis of similarity. All the seasons had pairwise differences in composition, with the exception of EDS and MWS, which indicates that the dung beetle community in this fragment requires more than three months of drought to trigger changes in species composition; this is probably due to small changes in the forest canopy. There was no difference in composition between EDS and MWS. As in other tropical dry forests, although

Forecasting Andean rainfall and crop yield from the influence of El Nino on Pleiades visibility

Science.gov (United States)

Orlove; Chiang; Cane

2000-01-06

Farmers in drought-prone regions of Andean South America have historically made observations of changes in the apparent brightness of stars in the Pleiades around the time of the southern winter solstice in order to forecast interannual variations in summer rainfall and in autumn harvests. They moderate the effect of reduced rainfall by adjusting the planting dates of potatoes, their most important crop. Here we use data on cloud cover and water vapour from satellite imagery, agronomic data from the Andean altiplano and an index of El Nino variability to analyse this forecasting method. We find that poor visibility of the Pleiades in June-caused by an increase in subvisual high cirrus clouds-is indicative of an El Nino year, which is usually linked to reduced rainfall during the growing season several months later. Our results suggest that this centuries-old method of seasonal rainfall forecasting may be based on a simple indicator of El Nino variability.

Rainfall estimation with TFR model using Ensemble Kalman filter

Science.gov (United States)

Asyiqotur Rohmah, Nabila; Apriliani, Erna

2018-03-01

Rainfall fluctuation can affect condition of other environment, correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, which caused climate change. Meanwhile, the forests as carbon sinks that help keep the carbon cycle and climate change mitigation. Climate change caused by rainfall intensity deviations can affect the economy of a region, and even countries. It encourages research on rainfall associated with an area of forest. In this study, the mathematics model that used is a model which describes the global temperatures, forest cover, and seasonal rainfall called the TFR (temperature, forest cover, and rainfall) model. The model will be discretized first, and then it will be estimated by the method of Ensemble Kalman Filter (EnKF). The result shows that the more ensembles used in estimation, the better the result is. Also, the accurateness of simulation result is influenced by measurement variable. If a variable is measurement data, the result of simulation is better.

Influence of rainfall on the trophic status of a brazilian semiarid reservoir - doi: 10.4025/actascibiolsci.v35i4.18261

Directory of Open Access Journals (Sweden)

Francisco Ítalo Barbosa Chaves

2013-07-01

Full Text Available This study evaluated the trophic conditions of the reservoir located in the urban perimeter of the town General Sampaio, semiarid region of the Ceará State, Brazil and its relationship with seasonal variation in rainfall between 2010 and 2011. It was obtained data for Secchi disk transparency, total phosphorus, and chlorophyll a to calculate the Trophic State Index (TSI, as well as rainfall data. The Trophic State Index (TSI proposed by Carlson (1977 and modified by Toledo Junior (1990 was used to test the influence of the seasonal variation in rainfall on hydrological variables and on trophic conditions of the reservoir in 2010 and 2011. There was seasonal variability in variables analyzed between climatic periods (rainy and dry and trophic conditions determined through the trophic index indicated conditions ranging from oligotrophic to eutrophic during the two years analyzed in this reservoir. Under these circumstances, one may conclude that the trophic status is related to seasonal fluctuations in the hydrology of the system controlled by rainfall, which is a common feature of semiarid regions.

Real-time prediction of rain-triggered lahars: incorporating seasonality and catchment recovery

Science.gov (United States)

Jones, Robbie; Manville, Vern; Peakall, Jeff; Froude, Melanie J.; Odbert, Henry M.

2017-12-01

Rain-triggered lahars are a significant secondary hydrological and geomorphic hazard at volcanoes where unconsolidated pyroclastic material produced by explosive eruptions is exposed to intense rainfall, often occurring for years to decades after the initial eruptive activity. Previous studies have shown that secondary lahar initiation is a function of rainfall parameters, source material characteristics and time since eruptive activity. In this study, probabilistic rain-triggered lahar forecasting models are developed using the lahar occurrence and rainfall record of the Belham River valley at the Soufrière Hills volcano (SHV), Montserrat, collected between April 2010 and April 2012. In addition to the use of peak rainfall intensity (PRI) as a base forecasting parameter, considerations for the effects of rainfall seasonality and catchment evolution upon the initiation of rain-triggered lahars and the predictability of lahar generation are also incorporated into these models. Lahar probability increases with peak 1 h rainfall intensity throughout the 2-year dataset and is higher under given rainfall conditions in year 1 than year 2. The probability of lahars is also enhanced during the wet season, when large-scale synoptic weather systems (including tropical cyclones) are more common and antecedent rainfall and thus levels of deposit saturation are typically increased. The incorporation of antecedent conditions and catchment evolution into logistic-regression-based rain-triggered lahar probability estimation models is shown to enhance model performance and displays the potential for successful real-time prediction of lahars, even in areas featuring strongly seasonal climates and temporal catchment recovery.

Real-time prediction of rain-triggered lahars: incorporating seasonality and catchment recovery

Directory of Open Access Journals (Sweden)

R. Jones

2017-12-01

Full Text Available Rain-triggered lahars are a significant secondary hydrological and geomorphic hazard at volcanoes where unconsolidated pyroclastic material produced by explosive eruptions is exposed to intense rainfall, often occurring for years to decades after the initial eruptive activity. Previous studies have shown that secondary lahar initiation is a function of rainfall parameters, source material characteristics and time since eruptive activity. In this study, probabilistic rain-triggered lahar forecasting models are developed using the lahar occurrence and rainfall record of the Belham River valley at the Soufrière Hills volcano (SHV, Montserrat, collected between April 2010 and April 2012. In addition to the use of peak rainfall intensity (PRI as a base forecasting parameter, considerations for the effects of rainfall seasonality and catchment evolution upon the initiation of rain-triggered lahars and the predictability of lahar generation are also incorporated into these models. Lahar probability increases with peak 1 h rainfall intensity throughout the 2-year dataset and is higher under given rainfall conditions in year 1 than year 2. The probability of lahars is also enhanced during the wet season, when large-scale synoptic weather systems (including tropical cyclones are more common and antecedent rainfall and thus levels of deposit saturation are typically increased. The incorporation of antecedent conditions and catchment evolution into logistic-regression-based rain-triggered lahar probability estimation models is shown to enhance model performance and displays the potential for successful real-time prediction of lahars, even in areas featuring strongly seasonal climates and temporal catchment recovery.

Experimental and model analysis of evapotranspiration and percolation losses in present and future rainfall scenarios in seasonally dry tropics

Science.gov (United States)

Lima, J. D.; Gondim, P. S.; Silva, R. A.; Gomes, C. A.; Souza, E. S.; Vico, G.; Soares, W. A.; Feng, X.; Montenegro, S. M.; Antonino, A. C.; Porporato, A.

2013-12-01

Evapotranspiration losses with their link to the surface energy balance are a major determinant of the ecohydrological conditions of vegetation, especially in semi-arid ecosystems and crops. Grassland ecosystems account for approximately 32% of global natural vegetation, and cover 170 million ha in Brazil, with 2.5 million ha in the Pernambuco State of the semiarid-NE Brazil. The water balance (WB) and Bowen ratio - energy balance (EB) methods were used in conjunction to lysimeters and eddy covariance methods to come up with reliable estimates for water fluxes in the conditions of extreme seasonal and interannual variability of NE Brazil. The SiSPAT (Simple Soil-Plant-Atmosphere Transfer Model) model was also used to help quantify the seasonal and diurnal variations in energy and water vapour exchanges over grasslands. The ET estimates were obtained with WB and EB methods during the wet and dry season in a grassland in NE Brazil, using a rain gauge, a pyranometer, a net radiometer and sensors for measuring air temperature and relative humidity at two levels, as well as automated sensors for measuring soil water content at depths of 0.10, 0.20, 0.30 and 0.40 m. During the dry period, the low stored soil water limited the grass production and LAI, and as a consequence most of the net radiation (62%) was consumed in sensible heat flux (H) compared to during the wet period (52%). In both seasons, the water flow in the lower limit of soil (z = 0.30 m) occurred only in the downward direction, losing 23.68 mm by drainage in wet period and only 0.19 mm in dry period. The best results for evapotranspiration were obtained with the EB method and the SiSPAT model. These results were then used to estimate the hydrologic partitioning in future climatic conditions where seasonal and interannual rainfall variability is predicted to increase.

Description of rainfall variability in Br hat -samhita of Varâha-mihira

OpenAIRE

Iyengar, RN

2004-01-01

Br hat -samhita of Varâha-mihira (5–6th century AD) provides valuable information on the approach in ancient India towards monsoon rainfall, including its measurement and forecasting. In this context, we come across a description of the expected amount of total seasonal rainfall depending on the first rains under the 27 naks atras of Indian astronomy. This provides a rough statistical picture of what might have been the rainfall and its variability in the region around Ujjain, where Varâha-mi...

Validation of satellite daily rainfall estimates in complex terrain of Bali Island, Indonesia

Science.gov (United States)

Rahmawati, Novi; Lubczynski, Maciek W.

2017-11-01

Satellite rainfall products have different performances in different geographic regions under different physical and climatological conditions. In this study, the objective was to select the most reliable and accurate satellite rainfall products for specific, environmental conditions of Bali Island. The performances of four spatio-temporal satellite rainfall products, i.e., CMORPH25, CMORPH8, TRMM, and PERSIANN, were evaluated at the island, zonation (applying elevation and climatology as constraints), and pixel scales, using (i) descriptive statistics and (ii) categorical statistics, including bias decomposition. The results showed that all the satellite products had low accuracy because of spatial scale effect, daily resolution and the island complexity. That accuracy was relatively lower in (i) dry seasons and dry climatic zones than in wet seasons and wet climatic zones; (ii) pixels jointly covered by sea and mountainous land than in pixels covered by land or by sea only; and (iii) topographically diverse than uniform terrains. CMORPH25, CMORPH8, and TRMM underestimated and PERSIANN overestimated rainfall when comparing them to gauged rain. The CMORPH25 had relatively the best performance and the PERSIANN had the worst performance in the Bali Island. The CMORPH25 had the lowest statistical errors, the lowest miss, and the highest hit rainfall events; it also had the lowest miss rainfall bias and was relatively the most accurate in detecting, frequent in Bali, ≤ 20 mm day-1 rain events. Lastly, the CMORPH25 coarse grid better represented rainfall events from coastal to inlands areas than other satellite products, including finer grid CMORPH8.

Evolution of rainfall in the Sahel

International Nuclear Information System (INIS)

Diallo, M.A.

1995-09-01

In this note, a number of main meteorological stations has been chosen to analyse the rainfall during the last 30 years in the Sahel (1961 to 1990). Reliable climatological data have been used for this study. The concerned area is limited by the 200 mm isohyet in the north and 600 mm isohyet in the south in the Sahel countries (Senegal, Mauritania, Mali, Burkina Faso, Niger and Chad). The evolution of rainfall has pointed out some similar and significant aspects for all stations studied. Established criteria have been used to characterize the annual rainfall and to determine the years with good rainfall and years of drought in the Sahel. (author). 6 refs, 3 figs

Flowering phenology in the arid winter rainfall region of southern Africa

Directory of Open Access Journals (Sweden)

M. Struck

1994-10-01

Full Text Available The impact of physical factors on the flowering phenology of a succulent karroid community in the winter rainfall region of the northwestern Cape, South Africa, based upon a three year study on permanent plots, is examined, (in the permanent plots, flowering of the shrubby species extended over a period of 4 to 4'/i> months each year, while blooming ot the therophytes peaked m the first half of the flowering season. Species composition and numbers of individuals in the therophytes and geophytes offering flowers varied greatly according to the pattern and amount of seasonal precipitation. Despite these variations a consistent flowering sequence between the years was observed. Possible relations between the flowering phenology and the climatic variables are discussed in detail. The present data suggest that the onset of flowering is determined indirectly by the first drop in temperature in autumn, indicating the beginning of the rainy season and presumably the start of the growing period, and/or by the increase of temperatures in the beginning of spring. The pattern and amount of rainfall within a given season mainly influenced the duration of anthesis and the number of flowers produced.

TIME SERIES CHARACTERISTIC ANALYSIS OF RAINFALL, LAND USE AND FLOOD DISCHARGE BASED ON ARIMA BOX-JENKINS MODEL

Directory of Open Access Journals (Sweden)

Abror Abror

2014-01-01

Full Text Available Indonesia located in tropic area consists of wet season and dry season. However, in last few years, in river discharge in dry season is very little, but in contrary, in wet season, frequency of flood increases with sharp peak and increasingly great water elevation. The increased flood discharge may occur due to change in land use or change in rainfall characteristic. Both matters should get clarity. Therefore, a research should be done to analyze rainfall characteristic, land use and flood discharge in some watershed area (DAS quantitatively from time series data. The research was conducted in DAS Gintung in Parakankidang, DAS Gung in Danawarih, DAS Rambut in Cipero, DAS Kemiri in Sidapurna and DAS Comal in Nambo, located in Tegal Regency and Pemalang Regency in Central Java Province. This research activity consisted of three main steps: input, DAS system and output. Input is DAS determination and selection and searching secondary data. DAS system is early secondary data processing consisting of rainfall analysis, HSS GAMA I parameter, land type analysis and DAS land use. Output is final processing step that consisting of calculation of Tadashi Tanimoto, USSCS effective rainfall, flood discharge, ARIMA analysis, result analysis and conclusion. Analytical calculation of ARIMA Box-Jenkins time series used software Number Cruncher Statistical Systems and Power Analysis Sample Size (NCSS-PASS version 2000, which result in time series characteristic in form of time series pattern, mean square errors (MSE, root mean square ( RMS, autocorrelation of residual and trend. Result of this research indicates that composite CN and flood discharge is proportional that means when composite CN trend increase then flood discharge trend also increase and vice versa. Meanwhile, decrease of rainfall trend is not always followed with decrease in flood discharge trend. The main cause of flood discharge characteristic is DAS management characteristic, not change in

Rainforest-initiated wet season onset over the southern Amazon.

Science.gov (United States)

Wright, Jonathon S; Fu, Rong; Worden, John R; Chakraborty, Sudip; Clinton, Nicholas E; Risi, Camille; Sun, Ying; Yin, Lei

2017-08-08

Although it is well established that transpiration contributes much of the water for rainfall over Amazonia, it remains unclear whether transpiration helps to drive or merely responds to the seasonal cycle of rainfall. Here, we use multiple independent satellite datasets to show that rainforest transpiration enables an increase of shallow convection that moistens and destabilizes the atmosphere during the initial stages of the dry-to-wet season transition. This shallow convection moisture pump (SCMP) preconditions the atmosphere at the regional scale for a rapid increase in rain-bearing deep convection, which in turn drives moisture convergence and wet season onset 2-3 mo before the arrival of the Intertropical Convergence Zone (ITCZ). Aerosols produced by late dry season biomass burning may alter the efficiency of the SCMP. Our results highlight the mechanisms by which interactions among land surface processes, atmospheric convection, and biomass burning may alter the timing of wet season onset and provide a mechanistic framework for understanding how deforestation extends the dry season and enhances regional vulnerability to drought.

Rainfall Variability, Wetland Persistence, and Water–Carbon Cycle Coupling in the Upper Zambezi River Basin in Southern Africa

Directory of Open Access Journals (Sweden)

Lauren E. L. Lowman

2018-05-01

Full Text Available The Upper Zambezi River Basin (UZRB delineates a complex region of topographic, soil and rainfall gradients between the Congo rainforest and the Kalahari Desert. Satellite imagery shows permanent wetlands in low-lying convergence zones where surface–groundwater interactions are vigorous. A dynamic wetland classification based on MODIS Nadir BRDF-Adjusted Reflectance is developed to capture the inter-annual and seasonal changes in areal extent due to groundwater redistribution and rainfall variability. Simulations of the coupled water–carbon cycles of seasonal wetlands show nearly double rates of carbon uptake as compared to dry areas, at increasingly lower water-use efficiencies as the dry season progresses. Thus, wetland extent and persistence into the dry season is key to the UZRB’s carbon sink and water budget. Whereas groundwater recharge governs the expansion of wetlands in the rainy season under large-scale forcing, wetland persistence in April–June (wet–dry transition months is tied to daily morning fog and clouds, and by afternoon land–atmosphere interactions (isolated convection. Rainfall suppression in July–September results from colder temperatures, weaker regional circulations, and reduced instability in the lower troposphere, shutting off moisture recycling in the dry season despite high evapotranspiration rates. The co-organization of precipitation and wetlands reflects land–atmosphere interactions that determine wetland seasonal persistence, and the coupled water and carbon cycles.

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

Science.gov (United States)

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

2015-04-01

To improve the level skill of Global Climate Models (GCMs) and Regional Climate Models (RCMs) in reproducing the statistics of rainfall at a basin level and at hydrologically relevant temporal scales (e.g. daily), two types of statistical approaches have been suggested. One is the statistical correction of climate model rainfall outputs using historical series of precipitation. The other is the use of stochastic models of rainfall to conditionally simulate precipitation series, based on large-scale atmospheric predictors produced by climate models (e.g. geopotential height, relative vorticity, divergence, mean sea level pressure). The latter approach, usually referred to as statistical rainfall downscaling, aims at reproducing the statistical character of rainfall, while accounting for the effects of large-scale atmospheric circulation (and, therefore, climate forcing) on rainfall statistics. While promising, statistical rainfall downscaling has not attracted much attention in recent years, since the suggested approaches involved complex (i.e. subjective or computationally intense) identification procedures of the local weather, in addition to demonstrating limited success in reproducing several statistical features of rainfall, such as seasonal variations, the distributions of dry and wet spell lengths, the distribution of the mean rainfall intensity inside wet periods, and the distribution of rainfall extremes. In an effort to remedy those shortcomings, Langousis and Kaleris (2014) developed a statistical framework for simulation of daily rainfall intensities conditional on upper air variables, which accurately reproduces the statistical character of rainfall at multiple time-scales. Here, we study the relative performance of: a) quantile-quantile (Q-Q) correction of climate model rainfall products, and b) the statistical downscaling scheme of Langousis and Kaleris (2014), in reproducing the statistical structure of rainfall, as well as rainfall extremes, at a

Regimes of seasonal air-sea interaction and implications for performance of forced simulations

Energy Technology Data Exchange (ETDEWEB)

Wu, Renguang [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); Kirtman, Ben P. [Center for Ocean-Land-Atmosphere Studies, Calverton, MD (United States); George Mason University, School of Computational Sciences, Fairfax, VA (United States)

2007-09-15

Sea surface temperature (SST) anomalies can induce anomalous convection through surface evaporation and low-level moisture convergence. This SST forcing of the atmosphere is indicated in a positive local rainfall-SST correlation. Anomalous convection can feedback on SST through cloud-radiation and wind-evaporation effects and wind-induced oceanic mixing and upwelling. These atmospheric feedbacks are reflected in a negative local rainfall-SST tendency correlation. As such, the simultaneous rainfall-SST and rainfall-SST tendency correlations can indicate the nature of local air-sea interactions. Based on the magnitude of simultaneous rainfall-SST and rainfall-SST tendency correlations, the present study identifies three distinct regimes of local air-sea interactions. The relative importance of SST forcing and atmospheric forcing differs in these regimes. In the equatorial central-eastern Pacific and, to a smaller degree, in the western equatorial Indian Ocean, SST forcing dominates throughout the year and the surface heat flux acts mainly as a damping term. In the tropical Indo-western Pacific Ocean regions, SST forcing and atmospheric forcing dominate alternatively in different seasons. Atmospheric forcing dominates in the local warm/rainy season. SST forcing dominates with a positive wind-evaporation feedback during the transition to the cold/dry season. SST forcing also dominates during the transition to the warm/rainy season but with a negative cloud-radiation feedback. The performance of atmospheric general circulation model simulations forced by observed SST is closely linked to the regime of air-sea interaction. The forced simulations have good performance when SST forcing dominates. The performance is low or poor when atmospheric forcing dominates. (orig.)

Rainfall Stochastic models

Science.gov (United States)

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

Real-time Extremely Heavy Rainfall Forecast and Warning over Rajasthan During the Monsoon Season (2016)

Science.gov (United States)

Srivastava, Kuldeep; Pradhan, D.

2018-01-01

Two events of extremely heavy rainfall occurred over Rajasthan during 7-9 August 2016 and 19-21 August 2016. Due to these events, flooding occurred over east Rajasthan and affected the normal life of people. A low-pressure area lying over northwest Madhya Pradesh on 7 August 2016 moved north-westward and lay near east Rajasthan and adjoining northwest Madhya Pradesh on 8 and 9 August 2016. Under the influence of this low-pressure system, Chittorgarh district and adjoining areas of Rajasthan received extremely heavy rainfall of 23 cm till 0300 UTC of 8 August 2016 and 34 cm on 0300 UTC of 9 August 2016. A deep depression lying over extreme south Uttar Pradesh and adjoining northeast Madhya Pradesh on 19 August 2016 moved westward and gradually weakened into a depression on 20 August 2016. It further weakened into a low-pressure area and lay over east Rajasthan on 21 and 22 August 2016. Under the influence of this deep depression, Jhalawar received 31 cm and Baran received 25 cm on 19 August. On 20 August 2016, extremely heavy rainfall (EHR) occurred over Banswara (23.5 cm), Pratapgarh (23.2 cm) and Chittorgarh (22.7 cm) districts. In this paper, the performance of the National Centers for Environmental Prediction (NCEP) global forecast system (GFS) model for real-time forecast and warning of heavy to very heavy/EHR that occurred over Rajasthan during 7-9 August 2016 and 19-21 August 2016 has been examined. The NCEP GFS forecast rainfall (Day 1, Day 2 and Day 3) was compared with the corresponding observed gridded rainfall. Based on the predictions given by the NCEP GFS model for heavy rainfall and with their application in real-time rainfall forecast and warnings issued by the Regional Weather Forecasting Center in New Delhi, it is concluded that the model has predicted the wind pattern and EHR event associated with the low-pressure system very accurately on day 1 and day 2 forecasts and with small errors in intensity and space for day 3.

Variation in Annual Rainfall Data of Forty Years (1978-2017) for ...

African Journals Online (AJOL)

PROF HORSFALL

2018-04-07

Apr 7, 2018 ... differences between the two means of the equal-length time scales revealed variability of ... intensities within the Southern part of Nigeria, is ..... Assessing Seasonal Rainfall Variability in Guinea. Savanna Part of Nigeria.

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

Science.gov (United States)

Chooi Tan, Kok

2018-04-01

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

Runoff and Sediment Production under the Similar Rainfall Events in Different Aggregate Sizes of an Agricultural Soil

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S. F. Eslami

2016-09-01

Full Text Available Introduction: Soil erosion by water is the most serious form of land degradation throughout the world, particularly in arid and semi-arid regions. In these areas, soils are weakly structured and are easily disrupted by raindrop impacts. Soil erosion is strongly affected by different factors such as rainfall characteristics, slope properties, vegetation cover, conservation practices, and soil erodibility. Different physicochemical soil properties such texture, structure, infiltration rate, organic matter, lime and exchangeable sodium percentage can affect the soil erodibility as well as soil erosion. Soil structure is one of the most important properties influencing runoff and soil loss because it determines the susceptibility of the aggregates to detach by either raindrop impacts or runoff shear stress. Many soil properties such as particle size distribution, organic matter, lime, gypsum, and exchangeable sodium percentage (ESP can affect the soil aggregation and the stability. Aggregates size distribution and their stability can be changed considerably because of agricultural practices. Information about variations of runoff and sediment in the rainfall events can be effective in modeling runoff as well as sediment. Thus, the study was conducted to determine runoff and sediment production of different aggregate sizes in the rainfall event scales. Materials and Methods: Toward the objective of the study, five aggregate classes consist of 0.25-2, 2-4.75, 4.75-5.6, 5.6-9.75, and 9.75-12.7 mm were collected from an agricultural sandy clay loam (0-30 cm using the related sieves in the field. Physicochemical soil analyses were performed in the aggregate samples using conventional methods in the lab. The aggregate samples were separately filed into fifteen flumes with a dimension of 50 cm × 100 cm and 15-cm in depth. The aggregate flumes were fixed on a steel plate with 9% slope and were exposed to the simulated rainfalls for investigating runoff and

Significant Features of Warm Season Water Vapor Flux Related to Heavy Rainfall and Draught in Japan

Science.gov (United States)

Nishiyama, Koji; Iseri, Yoshihiko; Jinno, Kenji

2009-11-01

In this study, our objective is to reveal complicated relationships between spatial water vapor inflow patterns and heavy rainfall activities in Kyushu located in the western part of Japan, using the outcomes of pattern recognition of water vapor inflow, based on the Self-Organizing Map. Consequently, it could be confirmed that water vapor inflow patterns control the distribution and the frequency of heavy rainfall depending on the direction of their fluxes and the intensity of Precipitable water. Historically serious flood disasters in South Kyushu in 1993 were characterized by high frequency of the water vapor inflow patterns linking to heavy rainfall. On the other hand, severe draught in 1994 was characterized by inactive frontal activity that do not related to heavy rainfall.

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.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Application of Artificial Neural Networks to Rainfall Forecasting in Queensland, Australia

Institute of Scientific and Technical Information of China (English)

John ABBOT; Jennifer MAROHASY

2012-01-01

In this study,the application of artificial intelligence to monthly and seasonal rainfall forecasting in Queensland,Australia,was assessed by inputting recognized climate indices,monthly historical rainfall data,and atmospheric temperatures into a prototype stand-alone,dynamic,recurrent,time-delay,artificial neural network.Outputs,as monthly rainfall forecasts 3 months in advance for the period 1993 to 2009,were compared with observed rainfall data using time-series plots,root mean squared error (RMSE),and Pearson correlation coefficients.A comparison of RMSE values with forecasts generated by the Australian Bureau of Meteorology's Predictive Ocean Atmosphere Model for Australia (POAMA)-1.5 general circulation model (GCM) indicated that the prototype achieved a lower RMSE for 16 of the 17 sites compared.The application of artificial neural networks to rainfall forecasting was reviewed.The prototype design is considered preliminary,with potential for significant improvement such as inclusion of output from GCMs and experimentation with other input attributes.

Parametric study on the effect of rainfall pattern to slope stability

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Hakim Sagitaningrum Fathiyah

2017-01-01

Full Text Available Landslide in Indonesia usually occurs during the rainy seasons. Previous studies showed that rainfall infiltration has a great effect on the factor of safety (FS of slopes. This research focused on the effect of rainfall pattern on the FS of unsaturated slope with different slope angle i.e.: 30°, 45°, and 60°. Three different rainfall patterns, which are normal, advanced, and delayed were considered in the analysis. The effects of low or high hydraulic conductivity of the soil are also observed. The analyses were conducted with SEEP/W for the seepage and SLOPE/W for the slope stability. It is found that the lowest FS for gentle slope is reached under the application of advanced rainfall pattern and the lowest FS for steep slope is reached under the application of delayed rainfall pattern. Reduction of FS is known to be the largest for gentle slope rather than steep slope due to negative pore water pressure reduction and the rising of ground water level. The largest FS reduction caused by rainfall was achieved for gentle slope under advanced rainfall pattern.

Impact of climate change on mid-twenty-first century growing seasons in Africa

Energy Technology Data Exchange (ETDEWEB)

Cook, Kerry H.; Vizy, Edward K. [The University of Texas at Austin, Department of Geological Sciences, Jackson School of Geosciences, Austin, TX (United States)

2012-12-15

Changes in growing seasons for 2041-2060 across Africa are projected using a regional climate model at 90-km resolution, and confidence in the predictions is evaluated. The response is highly regional over West Africa, with decreases in growing season days up to 20% in the western Guinean coast and some regions to the east experiencing 5-10% increases. A longer growing season up to 30% in the central and eastern Sahel is predicted, with shorter seasons in parts of the western Sahel. In East Africa, the short rains (boreal fall) growing season is extended as the Indian Ocean warms, but anomalous mid-tropospheric moisture divergence and a northward shift of Sahel rainfall severely curtails the long rains (boreal spring) season. Enhanced rainfall in January and February increases the growing season in the Congo basin by 5-15% in association with enhanced southwesterly moisture transport from the tropical Atlantic. In Angola and the southern Congo basin, 40-80% reductions in austral spring growing season days are associated with reduced precipitation and increased evapotranspiration. Large simulated reductions in growing season over southeastern Africa are judged to be inaccurate because they occur due to a reduction in rainfall in winter which is over-produced in the model. Only small decreases in the actual growing season are simulated when evapotranspiration increases in the warmer climate. The continent-wide changes in growing season are primarily the result of increased evapotranspiration over the warmed land, changes in the intensity and seasonal cycle of the thermal low, and warming of the Indian Ocean. (orig.)

Amplified melt and flow of the Greenland ice sheet driven by late-summer cyclonic rainfall

DEFF Research Database (Denmark)

Doyle, Samuel H.; Hubbard, Alun; van de Wal, Roderik S.W.

2015-01-01

and meteorological variables from the western margin of the Greenland ice sheet during a week of warm, wet cyclonic weather in late August and early September 2011. We find that extreme surface runoff from melt and rainfall led to a widespread acceleration in ice flow that extended 140 km into the ice-sheet interior....... We suggest that the late-season timing was critical in promoting rapid runoff across an extensive bare ice surface that overwhelmed a subglacial hydrological system in transition to a less-efficient winter mode. Reanalysis data reveal that similar cyclonic weather conditions prevailed across southern...

Spatial variability and rainfall characteristics of Kerala

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

Geographical regions of covariability in precipitation over the Kerala state are exposed using factor analysis. The results suggest that Kerala can be divided into three unique rainfall regions, each region having a similar covariance structure of annual rainfall. Stations north of 10◦N (north. Kerala) fall into one group and they ...

Statistical Seasonal Rainfall Forecast in the Neuquén River Basin (Comahue Region, Argentina

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Marcela Hebe González

2015-05-01

Full Text Available A detailed statistical analysis was performed at the Neuquén river basin using precipitation data for 1980–2007. The hydrological year begins in March with a maximum in June associated with rainfall and another relative maximum in October derived from snow-break. General features of the rainy season and the excess or deficits thereof are analyzed using standardized precipitation index (SPI for a six-month period in the basin. The SPI has a significant cycle of 14.3 years; the most severe excess (SPI greater than 2 has a return period of 25 years, while the most severe droughts (SPI less than −2 have a return period of 10 years. The SPI corresponding to the rainy season (April–September (SPI9 has no significant trend and is used to classify wet/dry years. In order to establish the previous circulation patterns associated with interannual SPI9 variability, the composite fields of wet and dry years are compared. There is a tendency for wet (dry periods to take place during El Niño (La Niña years, when there are positive anomalies of precipitable water over the basin, when the zonal flow over the Pacific Ocean is weakened (intensified and/or when there are negative pressure anomalies in the southern part of the country and Antarctic sea. Some prediction schemes using multiple linear regressions were performed. One of the models derived using the forward stepwise method explained 42% of the SPI9 variance and retained two predictors related to circulation over the Pacific Ocean: one of them shows the relevance of the intensity of zonal flow in mid-latitudes, and the other is because of the influence of low pressure near the Neuquén River basin. The cross-validation used to prove model efficiency showed a correlation of 0.41 between observed and estimated SPI9; there was a probability of detection of wet (dry years of 80% (65% and a false alarm relation of 25% in both cases.

Spatial and Temporal Variability of Rainfall in the Gandaki River Basin of Nepal Himalaya

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Jeeban Panthi

2015-03-01

Full Text Available Landslides, floods, and droughts are recurring natural disasters in Nepal related to too much or too little water. The summer monsoon contributes more than 80% of annual rainfall, and rainfall spatial and inter-annual variation is very high. The Gandaki River, one of the three major rivers of Nepal and one of the major tributaries of the Ganges River, covers all agro-ecological zones in the central part of Nepal. Time series tests were applied for different agro-ecological zones of the Gandaki River Basin (GRB for rainfall trends of four seasons (pre-monsoon, monsoon, post-monsoon and winter from 1981 to 2012. The non-parametric Mann-Kendall and Sen’s methods were used to determine the trends. Decadal anomalies relative to the long-term average were analyzed using the APHRODITE precipitation product. Trends in number of rainy days and timing of the monsoon were also analyzed. We found that the post-monsoon, pre-monsoon and winter rainfalls are decreasing significantly in most of the zones but monsoon rainfall is increasing throughout the basin. In the hill region, the annual rainfall is increasing but the rainy days do not show any trend. There is a tendency toward later departure of monsoon from Nepal, indicating an increase in its duration. These seasonally and topographically variable trends may have significant impacts for the agriculture and livestock smallholders that form the majority of the population in the GRB.

Seasonal distribution and interactions between plankton and microplastics in a tropical estuary

Science.gov (United States)

Lima, A. R. A.; Barletta, M.; Costa, M. F.

2015-11-01

The seasonal migration of a salt wedge and rainfall were the major factors influencing the spatiotemporal distribution of ichthyoplankton and microplastics along the main channel of the Goiana Estuary, NE Brazil. The most abundant taxa were the clupeids Rhinosardinia bahiensis and Harengula clupeola, followed by the achirid Trinectes maculatus (78.7% of the catch). Estuarine and mangrove larvae (e.g. Anchovia clupeoides, Gobionellus oceanicus), as well as microplastics were ubiquitous. During drier months, the salt wedge reaches the upper estuary and marine larvae (e.g. Cynoscion acoupa) migrated upstream until the zones of coastal waters influence. However, the meeting of waterfronts in the middle estuary forms a barrier that retains the microplastics in the upper and lower estuary most part of the year. During the late dry season, a bloom of zooplankton was followed by a bloom of fish larvae (12.74 ind. 100 m-3) and fish eggs (14.65 ind. 100 m-3) at the lower estuary. During the late rainy season, the high freshwater inflow flushed microplastics, together with the biota, seaward. During this season, a microplastic maximum (14 items 100 m-3) was observed, followed by fish larvae maximum (14.23 ind. 100 m-3) in the lower estuary. In contrast to fish larvae, microplastics presented positive correlation with high rainfall rates, being more strictly associated to flushing out/into the estuary than to seasonal variation in environmental variables. Microplastics represented half of fish larvae density. Comparable densities in the water column increase the chances of interaction between microplastics and fish larvae, including the ingestion of smaller fragments, whose shape and colour are similar to zooplankton prey.

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

Science.gov (United States)

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

Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall

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Elena Tarnavsky

2013-12-01

Full Text Available This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR. Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions.

Modeling seasonal water balance based on catchments' hedging strategy on evapotranspiration for climate seasonality

Science.gov (United States)

Wu, S.; Zhao, J.; Wang, H.

2017-12-01

This paper develops a seasonal water balance model based on the hypothesis that natural catchments utilize hedging strategy on evapotranspiration for climate seasonality. According to the monthly aridity index, one year is split into wet season and dry season. A seasonal water balance model is developed by analogy to a two-stage reservoir operation model, in which seasonal rainfall infiltration, evapotranspiration and saturation-excess runoff is corresponding to the inflow, release and surplus of the catchment system. Then the optimal hedging between wet season and dry season evapotranspiration is analytically derived with marginal benefit principle. Water budget data sets of 320 catchments in the United States covering the period from 1980 to 2010 are used to evaluate the performance of this model. The Nash-Sutcliffe Efficiency coefficient for evapotranspiration is higher than 0.5 in 84% of the study catchments; while the runoff is 87%. This paper validates catchments' hedging strategy on evapotranspiration for climate seasonality and shows its potential application for seasonal water balance, which is valuable for water resources planning and management.

Non-parametric characterization of long-term rainfall time series

Science.gov (United States)

Tiwari, Harinarayan; Pandey, Brij Kishor

2018-03-01

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

New spatial and temporal indices of Indian summer monsoon rainfall

Science.gov (United States)

Dwivedi, Sanjeev; Uma, R.; Lakshmi Kumar, T. V.; Narayanan, M. S.; Pokhrel, Samir; Kripalani, R. H.

2018-02-01

The overall yearly seasonal performance of Indian southwest monsoon rainfall (ISMR) for the whole Indian land mass is presently expressed by the India Meteorological Department (IMD) by a single number, the total quantum of rainfall. Any particular year is declared as excess/deficit or normal monsoon rainfall year on the basis of this single number. It is well known that monsoon rainfall also has high interannual variability in spatial and temporal scales. To account for these aspects in ISMR, we propose two new spatial and temporal indices. These indices have been calculated using the 115 years of IMD daily 0.25° × 0.25° gridded rainfall data. Both indices seem to go in tandem with the in vogue seasonal quantum index. The anomaly analysis indicates that the indices during excess monsoon years behave randomly, while for deficit monsoon years the phase of all the three indices is the same. Evaluation of these indices is also studied with respect to the existing dynamical indices based on large-scale circulation. It is found that the new temporal indices have better link with circulation indices as compared to the new spatial indices. El Nino and Southern Oscillation (ENSO) especially over the equatorial Pacific Ocean still have the largest influence in both the new indices. However, temporal indices have much better remote influence as compared to that of spatial indices. Linkages over the Indian Ocean regions are very different in both the spatial and temporal indices. Continuous wavelet transform (CWT) analysis indicates that the complete spectrum of oscillation of the QI is shared in the lower oscillation band by the spatial index and in the higher oscillation band by the temporal index. These new indices may give some extra dimension to study Indian summer monsoon variability.

Seasonal habitat selection by African buffalo Syncerus caffer in the Savuti–Mababe–Linyanti ecosystem of northern Botswana

Directory of Open Access Journals (Sweden)

Keoikantse Sianga

2017-05-01

Full Text Available This study aimed to establish seasonal movement and habitat selection patterns of African buffalo Syncerus caffer in relation to a detailed habitat map and according to seasonal changes in forage quality and quantity in the Savuti–Mababe–Linyanti ecosystem (Botswana. Two buffalo were collared in November 2011 and another in October 2012. All three buffalo had greater activities in the mopane–sandveld woodland mosaic during the wet season, which provided high-quality leafy grasses and ephemeral water for drinking, but moved to permanent water and reliable forage of various wetlands (swamps and floodplains and riverine woodlands during the dry season. Wetlands had higher grass greenness, height and biomass than woodlands during the dry season. Buffalo had similar wet season concentration areas in the 2011–2012 and 2012–2013 wet seasons and similar dry season concentration areas over the 2012 and 2013 dry seasons. However, their dry season location of collaring in 2011 differed dramatically from their 2012 and 2013 dry season concentration areas, possibly because of the exceptionally high flood levels in 2011, which reduced accessibility to their usual dry season concentration areas. The study demonstrates that extremely large and heterogeneous landscapes are needed to conserve buffalo in sandy, dystrophic ecosystems with variable rainfall. Conservation implications: This study emphasises the importance of large spatial scale available for movement, which enables adaptation to changing conditions between years and seasons.

Soil water storage, rainfall and runoff relationships in a tropical dry forest catchment

Science.gov (United States)

Farrick, Kegan K.; Branfireun, Brian A.

2014-12-01

In forested catchments, the exceedance of rainfall and antecedent water storage thresholds is often required for runoff generation, yet to our knowledge these threshold relationships remain undescribed in tropical dry forest catchments. We, therefore, identified the controls of streamflow activation and the timing and magnitude of runoff in a tropical dry forest catchment near the Pacific coast of central Mexico. During a 52 day transition phase from the dry to wet season, soil water movement was dominated by vertical flow which continued until a threshold soil moisture content of 26% was reached at 100 cm below the surface. This satisfied a 162 mm storage deficit and activated streamflow, likely through lateral subsurface flow pathways. High antecedent soil water conditions were maintained during the wet phase but had a weak influence on stormflow. We identified a threshold value of 289 mm of summed rainfall and antecedent soil water needed to generate >4 mm of stormflow per event. Above this threshold, stormflow response and magnitude was almost entirely governed by rainfall event characteristics and not antecedent soil moisture conditions. Our results show that over the course of the wet season in tropical dry forests the dominant controls on runoff generation changed from antecedent soil water and storage to the depth of rainfall.

Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

Science.gov (United States)

Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

2017-12-01

This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

Spatio-temporal trends of rainfall across Indian river basins

Science.gov (United States)

Bisht, Deepak Singh; Chatterjee, Chandranath; Raghuwanshi, Narendra Singh; Sridhar, Venkataramana

2018-04-01

Daily gridded high-resolution rainfall data of India Meteorological Department at 0.25° spatial resolution (1901-2015) was analyzed to detect the trend in seasonal, annual, and maximum cumulative rainfall for 1, 2, 3, and 5 days. The present study was carried out for 85 river basins of India during 1901-2015 and pre- and post-urbanization era, i.e., 1901-1970 and 1971-2015, respectively. Mann-Kendall ( α = 0.05) and Theil-Sen's tests were employed for detecting the trend and percentage of change over the period of time, respectively. Daily extreme rainfall events, above 95 and 99 percentile threshold, were also analyzed to detect any trend in their magnitude and number of occurrences. The upward trend was found for the majority of the sub-basins for 1-, 2-, 3-, and 5-day maximum cumulative rainfall during the post-urbanization era. The magnitude of extreme threshold events is also found to be increasing in the majority of the river basins during the post-urbanization era. A 30-year moving window analysis further revealed a widespread upward trend in a number of extreme threshold rainfall events possibly due to urbanization and climatic factors. Overall trends studied against intra-basin trend across Ganga basin reveal the mixed pattern of trends due to inherent spatial heterogeneity of rainfall, therefore, highlighting the importance of scale for such studies.

Rainfall Modification by Urban Areas: New Perspectives from TRMM

Science.gov (United States)

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.

Rainfall simulators - innovations seeking rainfall uniformity and automatic flow rate measurements

Science.gov (United States)

Bauer, Miroslav; Kavka, Petr; Strouhal, Luděk; Dostál, Tomáš; Krása, Josef

2016-04-01

single pressure operating mode, which is ensured by the pressure probe controlled electromagnetic valve. Previous experiments implied the need of automatic continuous measurements of selected variables. To this end the control unit was equipped with a datalogger. In a several seconds time step it collects the values of water pressure, nozzle-valves operation, control point rainfall intensity from a tipping bucket rain gauge, topsoil moisture from several Theta ML2x probes and most recently the plot outlet runoff rate. For a continuous runoff rate measurement a 0,4-foot HS-flume was constructed and equipped with S18U ultrasonic sensor. Assemble setting was optimised both in flow rate laboratory flume and in laboratory rainfall simulator. Namely the rating curves for particular flume bottom slopes were derived. Employment of the flume in the terrain is scheduled for the experimental season 2016, but laboratory results already show sufficient measurement accuracy and are promising in terms of experimental campaigns simplification. The abovementioned activities have been supported by the research grants SGS14/180/OHK1/3T/11, QJ1530181, QJ1520265 and QJ1330118.

Spatial Distribution of Annual and Monthly Rainfall Erosivity in the Jaguarí River Basin

Directory of Open Access Journals (Sweden)

Lucas Machado Pontes

2017-11-01

Full Text Available ABSTRACT The Jaguarí River Basin forms the main water supply sources for the São Paulo Metropolitan Region and other cities in the state. Since the kinetic energy of rainfall is the driving force of water erosion, the main cause of land and water degradation, we tested the hypothesis of correlation between the erosive potential of rainfall (erosivity and geographical coordinates and altitude for the purpose of predicting the spatial and temporal distribution of the rainfall erosivity index (EI30 in the basin. An equation was used to estimate the (EI30 in accordance with the average monthly and total annual rainfall at rainfall stations with data available for the study area. In the regression kriging technique, the deterministic part was modeled using multiple linear regression between the dependent variable (EI30 and environmental predictor variables: latitude, longitude, and altitude. From the result of equations and the maps generated, a direct correlation between erosivity and altitude could be observed. Erosivity has a markedly seasonal behavior in accordance with the rainy season from October to March. This season concentrates 86 % of the estimated EI30 values, with monthly maximum values of up to 2,342 MJ mm ha-1 h-1 month-1 between December and January, and minimum of 34 MJ mm ha-1 h-1 month-1 in August. The highest values were found in the Mantiqueira Range region (annual average of up to 12,000 MJ mm ha-1 h-1, a region that should be prioritized in soil and water conservation efforts. From this validation, good precision and accuracy of the model was observed for the long period of the annual average, which is the main factor used in soil loss prediction models.

Solar activity and rainfall pattern in Tamil Nadu during the Northeast monsoon

International Nuclear Information System (INIS)

Reddy, R.S.; Mukherjee, B.K.; Ramana Murty, Bh.V.

1976-01-01

An attempt is made to examine the association, of any, between the rainfall, in Tamil Nadu and sunspot activity and if so, whether similar periodicities are also present in the sunspot activity. The daily relative sunspot numbers for the period Oct.-Dec. during 1961-70 and the daily sunspot means for the period Oct.-Dec. 1889-1938, as well as the rainfall series for the period Oct.-Nov., during 1961-70 have been analysed by power spectrum. An anti-phase relation was noticed between the rainfall and the sunspot activity. The 15-day periodicity in the rainfall was significant. The sunspot activity also showed similar periodicities as rainfall. The 30-day periodicity in the sunspot activity was significant. (author)

Solar activity and rainfall pattern in Tamil Nadu during the Northeast monsoon

Energy Technology Data Exchange (ETDEWEB)

Reddy, R S; Mukherjee, B K; Ramana Murty, Bh V [Indian Inst. of Tropical Meteorology, Pune

1976-12-01

An attempt is made to examine the association, of any, between the rainfall, in Tamil Nadu and sunspot activity and if so, whether similar periodicities are also present in the sunspot activity. The daily relative sunspot numbers for the period Oct.-Dec. during 1961-70 and the daily sunspot means for the period Oct.-Dec. 1889-1938, as well as the rainfall series for the period Oct.-Nov., during 1961-70 have been analysed by power spectrum. An anti-phase relation was noticed between the rainfall and the sunspot activity. The 15-day periodicity in the rainfall was significant. The sunspot activity also showed similar periodicities as rainfall. The 30-day periodicity in the sunspot activity was significant.

Rainfall simulation for environmental application

Energy Technology Data Exchange (ETDEWEB)

Shriner, D.S.; Abner, C.H.; Mann, L.K.

1977-08-01

Rain simulation systems have been designed for field and greenhouse studies which have the capability of reproducing the physical and chemical characteristics of natural rainfall. The systems permit the simulation of variations in rainfall and droplet size similar to that of natural precipitation. The systems are completely automatic and programmable, allowing unattended operation for periods of up to one week, and have been used to expose not only vegetation but also soils and engineering materials, making them versatile tools for studies involving simulated precipitation.

Causes and Model Skill of the Persistent Intense Rainfall and Flooding in Paraguay during the Austral Summer 2015-2016

Science.gov (United States)

Doss-Gollin, J.; Munoz, A. G.; Pastén, M.

2017-12-01

During the austral summer 2015-16 severe flooding displaced over 150,000 people on the Paraguay River system in Paraguay, Argentina, and Southern Brazil. This flooding was out of phase with the typical seasonal cycle of the Paraguay River, and was driven by repeated intense rainfall events in the Lower Paraguay River basin. Using a weather typing approach within a diagnostic framework, we show that enhanced moisture inflow from the low-level jet and local convergence associated with baroclinic systems favored the development of mesoscale convective activity and enhanced precipitation. The observed circulation patterns were made more likely by the cross-timescale interactions of multiple climate mechanisms including the strong, mature El Niño event and an active Madden-Julien Oscillation in phases four and five. We also perform a comparison of the rainfall predictability using seasonal forecasts from the Latin American Observatory of Climate Events (OLE2) and sub-seasonal forecasts produced by the ECMWF. We find that the model output precipitation field exhibited limited skill at lead times beyond the synoptic timescale, but that a Model Output Statistics (MOS) approach, in which the leading principal components of the observed rainfall field are regressed on the leading principal components of model-simulated rainfall fields, substantially improves spatial representation of rainfall forecasts. Possible implications for flood preparedness are briefly discussed.

Assessing the simulation and prediction of rainfall associated with the MJO in the POAMA seasonal forecast system

Energy Technology Data Exchange (ETDEWEB)

Marshall, Andrew G. [Centre for Australian Weather and Climate Research, CSIRO Marine and Atmospheric Research, Hobart, (Australia); Hudson, Debra; Wheeler, Matthew C.; Hendon, Harry H.; Alves, Oscar [Centre for Australian Weather and Climate Research, Bureau of Meteorology, Melbourne (Australia)

2011-12-15

We assess the ability of the Predictive Ocean Atmosphere Model for Australia (POAMA) to simulate and predict weekly rainfall associated with the MJO using a 27-year hindcast dataset. After an initial 2-week atmospheric adjustment, the POAMA model is shown to simulate well, both in pattern and in intensity, the weekly-mean rainfall variation associated with the evolution of the MJO over the tropical Indo-Pacific. The simulation is most realistic in December-February (austral summer) and least realistic in March-May (austral autumn). Regionally, the most problematic area is the Maritime Continent, which is a common problem area in other models. Coupled with our previous demonstration of the ability of POAMA to predict the evolution of the large-scale structure of the MJO for up to about 3 weeks, this ability to simulate the regional rainfall evolution associated with the MJO translates to enhanced predictability of rainfall regionally throughout much of the tropical Indo-Pacific when the MJO is present in the initial conditions during October-March. We also demonstrate enhanced prediction skill of rainfall at up to 3 weeks lead time over the north-east Pacific and north Atlantic, which are areas of pronounced teleconnections excited by the MJO-modulation of tropical Indo-Pacific rainfall. Failure to simulate and predict the modulation of rainfall in such places as the Maritime Continent and tropical Australia by the MJO indicates, however, there is still much room for improvement of the prediction of the MJO and its teleconnections. (orig.)

Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

KAUST Repository

Srinivas, C. V.

2015-09-11

This study examines the ability of the Advanced Research WRF (ARW) regional model to simulate Indian summer monsoon (ISM) rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000–2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP) global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25° IMD (India Meteorological Department) rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid) of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast) with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative) and above-normal onset (June positive) phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over northeast, east and

Simulation of the Indian summer monsoon onset-phase rainfall using a regional model

Directory of Open Access Journals (Sweden)

C. V. Srinivas

2015-09-01

Full Text Available This study examines the ability of the Advanced Research WRF (ARW regional model to simulate Indian summer monsoon (ISM rainfall climatology in different climate zones during the monsoon onset phase in the decade 2000–2009. The initial and boundary conditions for ARW are provided from the NCEP/NCAR Reanalysis Project (NNRP global reanalysis. Seasonal onset-phase rainfall is compared with corresponding values from 0.25° IMD (India Meteorological Department rainfall and NNRP precipitation data over seven climate zones (perhumid, humid, dry/moist, subhumid, dry/moist, semiarid and arid of India to see whether dynamical downscaling using a regional model yields advantages over just using large-scale model predictions. Results show that the model could simulate the onset phase in terms of progression and distribution of rainfall in most zones (except over the northeast with good correlations and low error metrics. The observed mean onset dates and their variability over different zones are well reproduced by the regional model over most climate zones. It has been found that the ARW performed similarly to the reanalysis in most zones and improves the onset time by 1 to 3 days in zones 4 and 7, in which the NNRP shows a delayed onset compared to the actual IMD onset times. The variations in the onset-phase rainfall during the below-normal onset (June negative and above-normal onset (June positive phases are well simulated. The slight underestimation of onset-phase rainfall in the northeast zone could be due to failure in resolving the wide extent of topographic variations and the associated multiscale interactions in that zone. Spatial comparisons showed improvement of pentad rainfall in both space and quantity in ARW simulations over NNRP data, as evident from a wider eastward distribution of pentad rainfall over the Western Ghats, central and eastern India, as in IMD observations. While NNRP under-represented the high pentad rainfall over

Rainfall characteristics and their implications for rain-fed agriculture : a case study in the Upper Zambezi River Basin

NARCIS (Netherlands)

Beyer, M.; Wallner, M.; Bahlmann, L.; Thiemig, V.; Dietrich, J.; Billib, M.

2016-01-01

This study investigates rainfall characteristics in the Upper Zambezi River Basin and implications for rain-fed agriculture. Seventeen indices describing the character of each rainy season were calculated using a bias-corrected version of TRMM-B42 v6 rainfall estimate for 1998–2010. These were

Characterization of the rainy season in Burkina Faso and it's representation by regional climate models

Energy Technology Data Exchange (ETDEWEB)

Ibrahim, B.; Karambiri, H. [Institut International d' Ingenierie de l' Eau et de l' Environnement (2iE), Ouagadougou 01 (Burkina Faso); Polcher, J. [Laboratoire de Meteorologie Dynamique du CNRS, Institut Pierre Simon Laplace, Paris Cedex 05 (France); Rockel, B. [Helmholtz-Zentrum Geesthacht Institute of Coastal Research/Group Regional Atmospheric Modeling, Geesthacht (Germany)

2012-09-15

West African monsoon is one of the most challenging climate components to model. Five regional climate models (RCMs) were run over the West African region with two lateral boundary conditions, ERA-Interim re-analysis and simulations from two general circulation models (GCMs). Two sets of daily rainfall data were generated from these boundary conditions. These simulated rainfall data are analyzed here in comparison to daily rainfall data collected over a network of ten synoptic stations in Burkina Faso from 1990 to 2004. The analyses are based on a description of the rainy season throughout a number of it's characteristics. It was found that the two sets of rainfall data produced with the two driving data present significant biases. The RCMs generally produce too frequent low rainfall values (between 0.1 and 5 mm/day) and too high extreme rainfalls (more than twice the observed values). The high frequency of low rainfall events in the RCMs induces shorter dry spells at the rainfall thresholds of 0.1-1 mm/day. Altogether, there are large disagreements between the models on the simulate season duration and the annual rainfall amounts but most striking are their differences in representing the distribution of rainfall intensity. It is remarkable that these conclusions are valid whether the RCMs are driven by re-analysis or GCMs. In none of the analyzed rainy season characteristics, a significant improvement of their representation can be found when the RCM is forced by the re-analysis, indicating that these deficiencies are intrinsic to the models. (orig.)

Rainfall prediction methodology with binary multilayer perceptron neural networks

Science.gov (United States)

Esteves, João Trevizoli; de Souza Rolim, Glauco; Ferraudo, Antonio Sergio

2018-05-01

Precipitation, in short periods of time, is a phenomenon associated with high levels of uncertainty and variability. Given its nature, traditional forecasting techniques are expensive and computationally demanding. This paper presents a soft computing technique to forecast the occurrence of rainfall in short ranges of time by artificial neural networks (ANNs) in accumulated periods from 3 to 7 days for each climatic season, mitigating the necessity of predicting its amount. With this premise it is intended to reduce the variance, rise the bias of data and lower the responsibility of the model acting as a filter for quantitative models by removing subsequent occurrences of zeros values of rainfall which leads to bias the and reduces its performance. The model were developed with time series from ten agriculturally relevant regions in Brazil, these places are the ones with the longest available weather time series and and more deficient in accurate climate predictions, it was available 60 years of daily mean air temperature and accumulated precipitation which were used to estimate the potential evapotranspiration and water balance; these were the variables used as inputs for the ANNs models. The mean accuracy of the model for all the accumulated periods were 78% on summer, 71% on winter 62% on spring and 56% on autumn, it was identified that the effect of continentality, the effect of altitude and the volume of normal precipitation, have an direct impact on the accuracy of the ANNs. The models have peak performance in well defined seasons, but looses its accuracy in transitional seasons and places under influence of macro-climatic and mesoclimatic effects, which indicates that this technique can be used to indicate the eminence of rainfall with some limitations.

Movement response patterns of livestock to rainfall variability in the ...

African Journals Online (AJOL)

Livestock movement patterns indicated that forage is the motivation for winter movements and water is the motivation for summer. The movement followed a predictable ... The latter can be considered as a 'key resource' area to sustain animal numbers through critical periods of low rainfall. Overall, seasonal movement ...

Rainfall and temperature scenarios for Bangladesh for the middle of ...

Indian Academy of Sciences (India)

mean surface air temperature projection for Bangladesh is experimentally obtained for 2050 and 2060. This work discloses that simulated ... seasonal and annual rainfall, and mean surface air temperature in Bangladesh. The projected change ... already being felt in South Asia and will continue to intensify (Haq et al 1998; ...

SEASONAL PREDICTION OF PRECIPITATION OVER NIGERIA

African Journals Online (AJOL)

DEPT OF AGRICULTURAL ENGINEERING

nificant difference between the means of predicted and observed seasonal rainfall amount for all ... and the Gulf of Guinea in the north, east, west ... from the northern part to the southern part of ... and Savanna regions of Nigeria than the other.

Rainfall effects on rare annual plants

Science.gov (United States)

Levine, J.M.; McEachern, A.K.; Cowan, C.

2008-01-01

Variation in climate is predicted to increase over much of the planet this century. Forecasting species persistence with climate change thus requires understanding of how populations respond to climate variability, and the mechanisms underlying this response. Variable rainfall is well known to drive fluctuations in annual plant populations, yet the degree to which population response is driven by between-year variation in germination cueing, water limitation or competitive suppression is poorly understood.We used demographic monitoring and population models to examine how three seed banking, rare annual plants of the California Channel Islands respond to natural variation in precipitation and their competitive environments. Island plants are particularly threatened by climate change because their current ranges are unlikely to overlap regions that are climatically favourable in the future.Species showed 9 to 100-fold between-year variation in plant density over the 5–12 years of censusing, including a severe drought and a wet El Niño year. During the drought, population sizes were low for all species. However, even in non-drought years, population sizes and per capita growth rates showed considerable temporal variation, variation that was uncorrelated with total rainfall. These population fluctuations were instead correlated with the temperature after the first major storm event of the season, a germination cue for annual plants.Temporal variation in the density of the focal species was uncorrelated with the total vegetative cover in the surrounding community, suggesting that variation in competitive environments does not strongly determine population fluctuations. At the same time, the uncorrelated responses of the focal species and their competitors to environmental variation may favour persistence via the storage effect.Population growth rate analyses suggested differential endangerment of the focal annuals. Elasticity analyses and life table response

Evaluate Hydrologic Response on Spatiotemporal Characteristics of Rainfall Using High Resolution Radar Rainfall Data and WRF-Hydro Model

Science.gov (United States)

Gao, S.; Fang, N. Z.

2017-12-01

A previously developed Dynamic Moving Storm (DMS) generator is a multivariate rainfall model simulating the complex nature of precipitation field: spatial variability, temporal variability, and storm movement. Previous effort by the authors has investigated the sensitivity of DMS parameters on corresponding hydrologic responses by using synthetic storms. In this study, the DMS generator has been upgraded to generate more realistic precipitation field. The dependence of hydrologic responses on rainfall features was investigated by dissecting the precipitation field into rain cells and modifying their spatio-temporal specification individually. To retrieve DMS parameters from radar rainfall data, rain cell segmentation and tracking algorithms were respectively developed and applied on high resolution radar rainfall data (1) to spatially determine the rain cells within individual radar image and (2) to temporally analyze their dynamic behavior. Statistics of DMS parameters were established by processing a long record of rainfall data (10 years) to keep the modification on real storms within the limit of regional climatology. Empirical distributions of the DMS parameters were calculated to reveal any preferential pattern and seasonality. Subsequently, the WRF-Hydro model forced by the remodeled and modified precipitation was used for hydrologic simulation. The study area was the Upper Trinity River Basin (UTRB) watershed, Texas; and two kinds of high resolution radar data i.e. the Next-Generation Radar (NEXRAD) level III Digital Hybrid Reflectivity (DHR) product and Multi-Radar Multi-Sensor (MRMS) precipitation rate product, were utilized to establish parameter statistics and to recreate/remodel historical events respectively. The results demonstrated that rainfall duration is a significant linkage between DMS parameters and their hydrologic impacts—any combination of spatiotemporal characteristics that keep rain cells longer over the catchment will produce higher

Intra-seasonal and Inter-annual variability of Bowen Ratio over rain-shadow region of North peninsular India

Science.gov (United States)

Morwal, S. B.; Narkhedkar, S. G.; Padmakumari, B.; Maheskumar, R. S.; Deshpande, C. G.; Kulkarni, J. R.

2017-05-01

Intra-seasonal and inter-annual variability of Bowen Ratio (BR) have been studied over the rain-shadow region of north peninsular India during summer monsoon season. Daily grid point data of latent heat flux (LHF), sensible heat flux (SHF) from NCEP/NCAR Reanalysis for the period 1970-2014 have been used to compute daily area-mean BR. Daily grid point rainfall data at a resolution of 0.25° × 0.25° from APHRODITE's Water Resources for the available period 1970-2007 have been used to study the association between rainfall and BR. The study revealed that BR rapidly decreases from 4.1 to 0.29 in the month of June and then remains nearly constant at the same value (≤0.1) in the rest of the season. High values of BR in the first half of June are indicative of intense thermals and convective clouds with higher bases. Low values of BR from July to September period are indicative of weak thermals and convective clouds with lower bases. Intra-seasonal and inter-annual variability of BR is found to be inversely related to precipitation over the region. BR analysis indicates that the land surface characteristics of the study region during July-September are similar to that over oceanic regions as far as intensity of thermals and associated cloud microphysical properties are concerned. Similar variation of BR is found in El Nino and La Nina years. During June, an increasing trend is observed in SHF and BR and decreasing trend in LHF from 1976 to 2014. Increasing trend in the SHF is statistically significant.

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

Science.gov (United States)

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

2008-12-01

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

Disturbance Driven Rainfall in O`ahu, Hawai`i (1990-2010)

Science.gov (United States)

Longman, R. J.; Elison Timm, O.; Giambelluca, T. W.; Kaiser, L.; Newman, A. J.; Arnold, J.; Clark, M. P.

2017-12-01

Trade wind orographic rainfall is the most prevalent synoptic weather pattern in Hawai`i and provides a year-round source of moisture to the windward areas across the Island chain. Significant contributions to total and extreme precipitation have also been linked to one of four atmospheric disturbance situations that include: cold fronts, Kona storms, upper-tropospheric disturbances (upper level lows), and tropical systems. The primary objective of this research is to determine how these disturbance types contribute to total wet-season rainfall (RF) on the Island of O`ahu, Hawai`i and to identify any significant changes in the frequency of occurrence and or the intensity of these events. Atmospheric fronts that occurred in the Hawai`i region (17-26°N, 150-165°W) were extracted from a global dataset and combined with a Kona low and upper level low dataset to create a daily categorical weather classification time series (1990-2010). Mean rainfall was extracted from gridded daily O`ahu RF maps. Results show that the difference between a wet and dry year is predominantly explained by the RF contributions from disturbance events (r2 = 0.57, p cold fronts that cross the Island. During the wettest season on record, disturbances accounted for 48% of the total RF, while during the driest season they accounted for only 6% of the total RF. The event-based RF analysis also compared the RF intensity in the absence of disturbance events with the average RF intensity on days when atmospheric fronts are present but do not cross the island. The results show that non-crossing fronts reduce the average RF intensity. A possible explanation is that these events are too far away to produce RF, but close enough to disrupt normal trade wind flow, thus limiting orographic RF on the island. This new event-based RF analysis has important implications for the projection of regional climate change in Hawai`i. Our results suggest that if storm tracks were to shift poleward, O`ahu wet season

Ecophysiological and phenological strategies in seasonally-dry ecosystems: an ecohydrological approach

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Vico, Giulia; Manzoni, Stefano; Thompson, Sally; Molini, Annalisa; Porporato, Amilcare

2015-04-01

Seasonally-dry climates are particularly challenging for vegetation, as they are characterized by prolonged dry periods and often marked inter-annual variability. During the dry season plants face predictable physiological stress due to lack of water, whereas the inter-annual variability in rainfall timing and amounts requires plants to develop flexible adaptation strategies. The variety of strategies observed across seasonally-dry (Mediterranean and tropical) ecosystems is indeed wide - ranging from near-isohydric species that adjust stomatal conductance to avoid drought, to anisohydric species that maintain gas exchange during the dry season. A suite of phenological strategies are hypothesized to be associated to ecophysiological strategies. Here we synthetize current knowledge on ecophysiological and phenological adaptations through a comprehensive ecohydrological model linking a soil water balance to a vegetation carbon balance. Climatic regimes are found to select for different phenological strategies that maximize the long-term plant carbon uptake. Inter-annual variability of the duration of the wet season allows coexistence of different drought-deciduous strategies. In contrast, short dry seasons or access to groundwater favour evergreen species. Climatic changes causing more intermittent rainfall and/or shorter wet seasons are predicted to favour drought-deciduous species with opportunistic water use.

Assessment of the Growing Season Regime Region of Tanzania ...

African Journals Online (AJOL)

The growing period for most crops continues beyond the rainy season and, to a greater or lesser extent, crops often mature on moisture reserves stored in the soil profile. When the rains start early the season is likely to be· longer, however, early rainfall (November) over unimodal areas is variable (Mhita and Nassib, 1988).

The Use of Rainfall Variability in Flood Countermeasure Planning

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Iis Catur Wulan Dhari

2017-09-01

Full Text Available One of the impacts of climate change is the unpredictable shifting of seasons and rainfall patterns which caused flooding. Rejoso Watershed in Pasuruan Regency is one of the watersheds that suffer from flooding almost every year due to watershed degradation characterized by land conversion and changes in the hydrological behavior including the extreme rainfall pattern. This research was aimed to investigate the effect of rainfall variability on runoff and floodwater level profile along the river channel to provide technical and non-technical recommendation for handling flood problems. The hydrological analysis was performed using HEC-HMS version 4.0 software and the hydraulic analysis was conducted using HEC-RAS version 5.0.3 software. Several variations of extreme rainfall pattern were applied in the rainfall-runoff calculation to determine the representative flood discharges that will be used as input to the hydraulic simulation for evaluating the characteristics of flood water level. The result of the research shows that rainfall with the same depth yet varies in duration and starting time generate different flood hydrographs. Rejoso River could not store flood discharge with return period of 2 years with peak discharge of 201.46 m3/s that causing overflow along the stream. The recommendation to handle flood problems is by normalization, which could reduce the overtopping at several river reaches of 4,927 m, while the combination of normalization and embankment could reduce 7,843 m from the existing river length of 12,396 m.

Parameterization of a bucket model for soil-vegetation-atmosphere modeling under seasonal climatic regimes

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N. Romano

2011-12-01

Full Text Available We investigate the potential impact of accounting for seasonal variations in the climatic forcing and using different methods to parameterize the soil water content at field capacity on the water balance components computed by a bucket model (BM. The single-layer BM of Guswa et al. (2002 is employed, whereas the Richards equation (RE based Soil Water Atmosphere Plant (SWAP model is used as a benchmark model. The results are analyzed for two differently-textured soils and for some synthetic runs under real-like seasonal weather conditions, using stochastically-generated daily rainfall data for a period of 100 years. Since transient soil-moisture dynamics and climatic seasonality play a key role in certain zones of the World, such as in Mediterranean land areas, a specific feature of this study is to test the prediction capability of the bucket model under a condition where seasonal variations in rainfall are not in phase with the variations in plant transpiration. Reference is made to a hydrologic year in which we have a rainy period (starting 1 November and lasting 151 days where vegetation is basically assumed in a dormant stage, followed by a drier and rainless period with a vegetation regrowth phase. Better agreement between BM and RE-SWAP intercomparison results are obtained when BM is parameterized by a field capacity value determined through the drainage method proposed by Romano and Santini (2002. Depending on the vegetation regrowth or dormant seasons, rainfall variability within a season results in transpiration regimes and soil moisture fluctuations with distinctive features. During the vegetation regrowth season, transpiration exerts a key control on soil water budget with respect to rainfall. During the dormant season of vegetation, the precipitation regime becomes an important climate forcing. Simulations also highlight the occurrence of bimodality in the probability distribution of soil moisture during the season when plants are

Developing a savanna burning emissions abatement methodology for tussock grasslands in high rainfall regions of northern Australia

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Jeremy Russell-Smith

2014-06-01

Full Text Available Fire-prone tropical savanna and grassland systems are a significant source of atmospheric emissions of greenhouse gases.  In recent years, substantial research has been directed towards developing accounting methodologies for savanna burning emissions to be applied in Australia’s National Greenhouse Gas Inventory, as well as for commercial carbon trading purposes.  That work has focused on woody savanna systems.  Here, we extend the methodological approach to include tussock grasslands and associated Melaleuca-dominated open woodlands (<10% foliage cover in higher rainfall (>1,000 mm/annum regions of northern Australia.  Field assessments under dry season conditions focused on deriving fuel accumulation, fire patchiness and combustion relationships for key fuel types: fine fuels − grass and litter; coarse woody fuels − twigs <6 mm diameter; heavy woody fuels − >6 mm diameter; and shrubs.  In contrast with previous savanna burning assessments, fire treatments undertaken under early dry season burning conditions resulted in negligible patchiness and very substantial consumption of fine fuels.  In effect, burning in the early dry season provides no benefits in greenhouse gas emissions and emissions reductions in tussock grasslands can be achieved only through reducing the extent of burning.  The practical implications of reduced burning in higher rainfall northern Australian grassland systems are discussed, indicating that there are significant constraints, including infrastructural, cultural and woody thickening issues.  Similar opportunities and constraints are observed in other international contexts, but especially project implementation challenges associated with legislative, political and governance issues.

Seasonality of fire weather strongly influences fire regimes in South Florida savanna-grassland landscapes.

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William J Platt

Full Text Available Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature. We used nonparametric cluster analyses of a 17-year (1993-2009 data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires over a 13-year period with fire records (1997-2009. Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with

Seasonality of Fire Weather Strongly Influences Fire Regimes in South Florida Savanna-Grassland Landscapes

Science.gov (United States)

Platt, William J.; Orzell, Steve L.; Slocum, Matthew G.

2015-01-01

Fire seasonality, an important characteristic of fire regimes, commonly is delineated using seasons based on single weather variables (rainfall or temperature). We used nonparametric cluster analyses of a 17-year (1993–2009) data set of weather variables that influence likelihoods and spread of fires (relative humidity, air temperature, solar radiation, wind speed, soil moisture) to explore seasonality of fire in pine savanna-grassland landscapes at the Avon Park Air Force Range in southern Florida. A four-variable, three-season model explained more variation within fire weather variables than models with more seasons. The three-season model also delineated intra-annual timing of fire more accurately than a conventional rainfall-based two-season model. Two seasons coincided roughly with dry and wet seasons based on rainfall. The third season, which we labeled the fire season, occurred between dry and wet seasons and was characterized by fire-promoting conditions present annually: drought, intense solar radiation, low humidity, and warm air temperatures. Fine fuels consisting of variable combinations of pyrogenic pine needles, abundant C4 grasses, and flammable shrubs, coupled with low soil moisture, and lightning ignitions early in the fire season facilitate natural landscape-scale wildfires that burn uplands and across wetlands. We related our three season model to fires with different ignition sources (lightning, military missions, and prescribed fires) over a 13-year period with fire records (1997–2009). Largest wildfires originate from lightning and military ignitions that occur within the early fire season substantially prior to the peak of lightning strikes in the wet season. Prescribed ignitions, in contrast, largely occur outside the fire season. Our delineation of a pronounced fire season provides insight into the extent to which different human-derived fire regimes mimic lightning fire regimes. Delineation of a fire season associated with timing of

Rainfall declines over Queensland from 1951-2007 and links to the Subtropical Ridge and the SAM

International Nuclear Information System (INIS)

Cottrill, D A; Ribbe, J

2010-01-01

Much of southern and eastern Australia including Queensland have experienced rainfall declines over recent decades affecting agricultural production and accelerating water infrastructure development. Rainfall declines from southern Australia have now been directly related to changes in the Southern Annular Mode (SAM) and the subtropical ridge. In southern and coastal Queensland, the rainfall declines have occurred mostly in the austral summer and autumn. Observations from this region reveal the rainfall decline is correlated to an increase in the mean sea level pressure (MSLP) at many stations. The largest increases in MSLP are over southeast Queensland and coastal regions, where some of the largest rainfall declines occur. This study indicates the subtropical ridge as one of the main factors in the rainfall decline over this region. SAM is also likely to be important, although its seasonal influence, apart from winter, is harder to determine.

Thermodynamic ocean-atmosphere Coupling and the Predictability of Nordeste rainfall

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Chang, P.; Saravanan, R.; Giannini, A.

2003-04-01

The interannual variability of rainfall in the northeastern region of Brazil, or Nordeste, is known to be very strongly correlated with sea surface temperature (SST) variability, of Atlantic and Pacific origin. For this reason the potential predictability of Nordeste rainfall is high. The current generation of state-of-the-art atmospheric models can replicate the observed rainfall variability with high skill when forced with the observed record of SST variability. The correlation between observed and modeled indices of Nordeste rainfall, in the AMIP-style integrations with two such models (NSIPP and CCM3) analyzed here, is of the order of 0.8, i.e. the models explain about 2/3 of the observed variability. Assuming that thermodynamic, ocean-atmosphere heat exchange plays the dominant role in tropical Atlantic SST variability on the seasonal to interannual time scale, we analyze its role in Nordeste rainfall predictability using an atmospheric general circulation model coupled to a slab ocean model. Predictability experiments initialized with observed December SST show that thermodynamic coupling plays a significant role in enhancing the persistence of SST anomalies, both in the tropical Pacific and in the tropical Atlantic. We show that thermodynamic coupling is sufficient to provide fairly accurate forecasts of tropical Atlantic SST in the boreal spring that are significantly better than the persistence forecasts. The consequences for the prediction of Nordeste rainfall are analyzed.

Developing Methods For Linking Surficial Aquifers With Localized Rainfall Data

Science.gov (United States)

Lafrenz, W. B.; van Gaalen, J. F.

2008-12-01

Water level hydrographs of the surficial aquifer can be evaluated to identify both the cause and consequence of water supply development. Rainfall, as a source of direct recharge and as a source of delayed or compounded recharge, is often the largest influence on surficial aquifer water level responses. It is clear that proximity of the rain gauge to the observation well is a factor in the degree of correlation, but in central Florida, USA, rainfall patterns change seasonally, with latitude, and with distance from the coast . Thus, for a location in central Florida, correlation of rain events with observed hydrograph responses depends on both distance and direction from an observation well to a rain gauge. In this study, we examine the use of extreme value analysis as a method of selecting the best rainfall data set for describing a given surficial aquifer monitor well. A surficial aquifer monitor well with a substantial suite of data is compared to a series of rainfall data sets from gauges ranging from meters to tens of kilometers in distance from the monitor well. The gauges vary in a wide range of directions from the monitor well in an attempt to identify both a method for rainfall gauge selection to be associated with the monitor well. Each rainfall gauge is described by a correlation coefficient with respect to the surficial aquifer water level data.

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

Science.gov (United States)

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%.

Seasonal drivers of the epidemiology of arthropod-borne viruses in Australia.

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Jemma L Geoghegan

2014-11-01

Full Text Available Arthropod-borne viruses are a major cause of emerging disease with significant public health and economic impacts. However, the factors that determine their activity and seasonality are not well understood. In Australia, a network of sentinel cattle herds is used to monitor the distribution of several such viruses and to define virus-free regions. Herein, we utilize these serological data to describe the seasonality, and its drivers, of three economically important animal arboviruses: bluetongue virus, Akabane virus and bovine ephemeral fever virus. Through epidemiological time-series analyses of sero-surveillance data of 180 sentinel herds between 2004-2012, we compared seasonal parameters across latitudes, ranging from the tropical north (-10°S to the more temperate south (-40°S. This analysis revealed marked differences in seasonality between distinct geographic regions and climates: seasonality was most pronounced in southern regions and gradually decreased as latitude decreased toward the Equator. Further, we show that both the timing of epidemics and the average number of seroconversions have a strong geographical component, which likely reflect patterns of vector abundance through co-varying climatic factors, especially temperature and rainfall. Notably, despite their differences in biology, including insect vector species, all three viruses exhibited very similar seasonality. By revealing the factors that shape spatial and temporal distributions, our study provides a more complete understanding of arbovirus seasonality that will enable better risk predictions.

Hydrological Responses to Changes in the Rainfall Regime are Less Pronounced in Forested Basins: an Analysis of Southern Brazil, 1975-2010

Science.gov (United States)

Chagas, V. B. P.; Chaffe, P. L. B.

2017-12-01

It is unknown to what extent the hydrological responses to changes in the rainfall regime vary across forested and non-forested landscapes. Southern Brazil is approximately 570000 km² and was naturally covered mostly by tropical and subtropical forests. In the last century, a large proportion of forests were replaced by agricultural activities. The rainfall regime has also changed substantially in the last decades. The annual rainfall, number and magnitude of extreme events, and number of non-rainy days have increased in most of the area. In this study, we investigated the changes in the regime of 142 streamflow gauges and 674 rainfall gauges in Southern Brazil, from 1975 to 2010. The changes in the regime were analyzed for forested basins (i.e., with more than 50% forest coverage) and non-forested basins (i.e., with less than 20% forest coverage). The area of the river basins ranged from 100 to 60000 km². We analyzed a total of six signatures that represent the regime, including annual averages, seasonality, floods, and droughts. The statistical trends of the signatures were calculated using the Mann-Kendall test and the Sen's slope. The results showed that the majority of basins with opposing signal trends for mean annual streamflow and rainfall are non-forested basins (i.e., basins with higher anthropogenic impacts). Forested basins had a lower correlation between trends in the streamflow and rainfall trends for the seasonality and the average duration of drought events. There was a lower variability in the annual maximum 1-day streamflow trends in the forested basins. Additionally, despite a decrease in the 31-day rainfall minima and an increase in the seasonality, in forested basins the 7-day streamflow minima increases were substantially larger than in non-forested basins. In summary, the forested basins were less responsive to the changes in the precipitation 1-day maxima, seasonality, number of dry days, and 31-day minima.

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

Science.gov (United States)

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.

Diagnosing observed characteristics of the wet season across Africa to identify deficiencies in climate model simulations

Science.gov (United States)

Dunning, C.; Black, E.; Allan, R. P.

2017-12-01

The seasonality of rainfall over Africa plays a key role in determining socio-economic impacts for agricultural stakeholders, influences energy supply from hydropower, affects the length of the malaria transmission season and impacts surface water supplies. Hence, failure or delays of these rains can lead to significant socio-economic impacts. Diagnosing and interpreting interannual variability and long-term trends in seasonality, and analysing the physical driving mechanisms, requires a robust definition of African precipitation seasonality, applicable to both observational datasets and model simulations. Here we present a methodology for objectively determining the onset and cessation of multiple wet seasons across the whole of Africa. Compatibility with known physical drivers of African rainfall, consistency with indigenous methods, and generally strong agreement between satellite-based rainfall data sets confirm that the method is capturing the correct seasonal progression of African rainfall. Application of this method to observational datasets reveals that over East Africa cessation of the short rains is 5 days earlier in La Nina years, and the failure of the rains and subsequent humanitarian disaster is associated with shorter as well as weaker rainy seasons over this region. The method is used to examine the representation of the seasonality of African precipitation in CMIP5 model simulations. Overall, atmosphere-only and fully coupled CMIP5 historical simulations represent essential aspects of the seasonal cycle; patterns of seasonal progression of the rainy season are captured, for the most part mean model onset/ cessation dates agree with mean observational dates to within 18 days. However, unlike the atmosphere-only simulations, the coupled simulations do not capture the biannual regime over the southern West African coastline, linked to errors in Gulf of Guinea Sea Surface Temperature. Application to both observational and climate model datasets, and

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

Science.gov (United States)

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

Significant influences of global mean temperature and ENSO on extreme rainfall over Southeast Asia

Science.gov (United States)

Villafuerte, Marcelino, II; Matsumoto, Jun

2014-05-01

Along with the increasing concerns on the consequences of global warming, and the accumulating records of disaster related to heavy rainfall events in Southeast Asia, this study investigates whether a direct link can be detected between the rising global mean temperature, as well as the El Niño-Southern Oscillation (ENSO), and extreme rainfall over the region. The maximum likelihood modeling that allows incorporating covariates on the location parameter of the generalized extreme value (GEV) distribution is employed. The GEV model is fitted to annual and seasonal rainfall extremes, which were taken from a high-resolution gauge-based gridded daily precipitation data covering a span of 57 years (1951-2007). Nonstationarities in extreme rainfall are detected over the central parts of Indochina Peninsula, eastern coasts of central Vietnam, northwest of the Sumatra Island, inland portions of Borneo Island, and on the northeastern and southwestern coasts of the Philippines. These nonstationarities in extreme rainfall are directly linked to near-surface global mean temperature and ENSO. In particular, the study reveals that a kelvin increase in global mean temperature anomaly can lead to an increase of 30% to even greater than 45% in annual maximum 1-day rainfall, which were observed pronouncedly over central Vietnam, southern coast of Myanmar, northwestern sections of Thailand, northwestern tip of Sumatra, central portions of Malaysia, and the Visayas island in central Philippines. Furthermore, a pronounced ENSO influence manifested on the seasonal maximum 1-day rainfall; a northward progression of 10%-15% drier condition over Southeast Asia as the El Niño develops from summer to winter is revealed. It is important therefore, to consider the results obtained here for water resources management as well as for adaptation planning to minimize the potential adverse impact of global warming, particularly on extreme rainfall and its associated flood risk over the region

The impact of Indian Ocean high pressure system on rainfall and stream flow

International Nuclear Information System (INIS)

Rehman, S.; Nasir, H.; Zia, S.S.; Ansari, W.A.; Salam, K.; Tayyab, N.

2012-01-01

Centre of Action approach is very useful in getting insight of rainfall and stream flow variability of specific region. Hameed et al. showed that Inter-annual variability of Gulf Stream north wall is influenced by low Icelandic pressure system and has more statistically significant correlation than North Atlantic Oscillation (NAO) with longitude of Icelandic low. This study also aims to explore possible relationships between rainfall and stream flow in Collie river catchment in Southwest Western Australia (SWWA) with Indian Ocean high pressure dynamics. The relationship between rainfall and stream flow with Indian Ocean high pressure system have been investigated using correlation analysis for early winter season (MJJA), lag correlation for MJJA versus SOND rainfall and stream flow are also calculated and found significant at 95% confidence level. By investigating the relationship between COA indices with rainfall and stream flow over the period 1976-2008, significant correlations suggests that rainfall and stream flow in Collie river basin is strongly influenced by COA indices. Multiple correlations between rainfall and stream flow with Indian Ocean high pressure (IOHPS and IOHLN) is 0.7 and 0.6 respectively. Centers of Action (COA) indices explain 51% and 36% of rainfall and stream flow respectively. The correlation between rainfall and stream flow with IOHPS is -0.4 and -0.3 whereas, with IOHLN is -0.47 and -0.52 respectively. (author)

Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria

Directory of Open Access Journals (Sweden)

S. O

2017-12-01

Full Text Available The Global Precipitation Measurement (GPM Integrated Multi-satellite Retrievals for GPM (IMERG products provide quasi-global (60° N–60° S precipitation estimates, beginning March 2014, from the combined use of passive microwave (PMW and infrared (IR satellites comprising the GPM constellation. The IMERG products are available in the form of near-real-time data, i.e., IMERG Early and Late, and in the form of post-real-time research data, i.e., IMERG Final, after monthly rain gauge analysis is received and taken into account. In this study, IMERG version 3 Early, Late, and Final (IMERG-E,IMERG-L, and IMERG-F half-hourly rainfall estimates are compared with gauge-based gridded rainfall data from the WegenerNet Feldbach region (WEGN high-density climate station network in southeastern Austria. The comparison is conducted over two IMERG 0.1°  ×  0.1° grid cells, entirely covered by 40 and 39 WEGN stations each, using data from the extended summer season (April–October for the first two years of the GPM mission. The entire data are divided into two rainfall intensity ranges (low and high and two seasons (warm and hot, and we evaluate the performance of IMERG, using both statistical and graphical methods. Results show that IMERG-F rainfall estimates are in the best overall agreement with the WEGN data, followed by IMERG-L and IMERG-E estimates, particularly for the hot season. We also illustrate, through rainfall event cases, how insufficient PMW sources and errors in motion vectors can lead to wide discrepancies in the IMERG estimates. Finally, by applying the method of Villarini and Krajewski (2007, we find that IMERG-F half-hourly rainfall estimates can be regarded as a 25 min gauge accumulation, with an offset of +40 min relative to its nominal time.

Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria

Science.gov (United States)

O, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Juergen; Tan, Jackson; Petersen, Walter A.

2017-12-01

The Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) products provide quasi-global (60° N-60° S) precipitation estimates, beginning March 2014, from the combined use of passive microwave (PMW) and infrared (IR) satellites comprising the GPM constellation. The IMERG products are available in the form of near-real-time data, i.e., IMERG Early and Late, and in the form of post-real-time research data, i.e., IMERG Final, after monthly rain gauge analysis is received and taken into account. In this study, IMERG version 3 Early, Late, and Final (IMERG-E,IMERG-L, and IMERG-F) half-hourly rainfall estimates are compared with gauge-based gridded rainfall data from the WegenerNet Feldbach region (WEGN) high-density climate station network in southeastern Austria. The comparison is conducted over two IMERG 0.1° × 0.1° grid cells, entirely covered by 40 and 39 WEGN stations each, using data from the extended summer season (April-October) for the first two years of the GPM mission. The entire data are divided into two rainfall intensity ranges (low and high) and two seasons (warm and hot), and we evaluate the performance of IMERG, using both statistical and graphical methods. Results show that IMERG-F rainfall estimates are in the best overall agreement with the WEGN data, followed by IMERG-L and IMERG-E estimates, particularly for the hot season. We also illustrate, through rainfall event cases, how insufficient PMW sources and errors in motion vectors can lead to wide discrepancies in the IMERG estimates. Finally, by applying the method of Villarini and Krajewski (2007), we find that IMERG-F half-hourly rainfall estimates can be regarded as a 25 min gauge accumulation, with an offset of +40 min relative to its nominal time.

Sensitivity of Horn of Africa Rainfall to Regional Sea Surface Temperature Forcing

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Zewdu T. Segele

2015-05-01

Full Text Available The Abdus Salam International Center for Theoretical Physics (ICTP version 4.4 Regional Climate Model (RegCM4 is used to investigate the rainfall response to cooler/warmer sea surface temperature anomaly (SSTA forcing in the Indian and Atlantic Oceans. The effect of SSTA forcing in a specific ocean basin is identified by ensemble, averaging 10 individual simulations in which a constant or linearly zonally varying SSTA is prescribed in individual basins while specifying the 1971–2000 monthly varying climatological sea surface temperature (SST across the remaining model domain. The nonlinear rainfall response to SSTA amplitude also is investigated by separately specifying +1K, +2K, and +4K SSTA forcing in the Atlantic and Indian Oceans. The simulation results show that warm SSTs over the entire Indian Ocean produce drier conditions across the larger Blue Nile catchment, whereas warming ≥ +2K generates large positive rainfall anomalies exceeding 10 mm·day−1 over drought prone regions of Northeastern Ethiopia. However, the June–September rainy season tends to be wetter (drier when the SST warming (cooling is limited to either the Northern or Southern Indian Ocean. Wet rainy seasons generally are characterized by deepening of the monsoon trough, east of 40°E, intensification of the Mascarene high, strengthening of the Somali low level jet and the tropical easterly jet, enhanced zonal and meridional vertically integrated moisture fluxes, and steeply vertically decreasing moist static energy. The opposite conditions hold for dry monsoon seasons.

Extreme rainfall and snowfall alter responses of soil respiration to nitrogen fertilization: a 3-year field experiment.

Science.gov (United States)

Chen, Zengming; Xu, Yehong; Zhou, Xuhui; Tang, Jianwu; Kuzyakov, Yakov; Yu, Hongyan; Fan, Jianling; Ding, Weixin

2017-08-01

Extreme precipitation is predicted to be more frequent and intense accompanying global warming and may have profound impacts on soil respiration (Rs) and its components, that is, autotrophic (Ra) and heterotrophic (Rh) respiration. However, how natural extreme rainfall or snowfall events affect these fluxes are still lacking, especially under nitrogen (N) fertilization. In this study, extreme rainfall and snowfall events occurred during a 3-year field experiment, allowing us to examine their effects on the response of Rs, Rh, and Ra to N supply. In normal rainfall years of 2011/2012 and 2012/2013, N fertilization significantly stimulated Rs by 23.9% and 10.9%, respectively. This stimulation was mainly due to the increase of Ra because of N-induced increase in plant biomass. In the record wet year of 2013/2014, however, Rs was independent on N supply because of the inhibition effect of the extreme rainfall event. Compared with those in other years, Rh and Ra were reduced by 36.8% and 59.1%, respectively, which were likely related to the anoxic stress on soil microbes and decreased photosynthates supply. Although N supply did not affect annual Rh, the response ratio (RR) of Rh flux to N fertilization decreased firstly during growing season, increased in nongrowing season and peaked during spring thaw in each year. Nongrowing season Rs and Rh contributed 5.5-16.4% to their annual fluxes and were higher in 2012/2013 than other years due to the extreme snowfall inducing higher soil moisture during spring thaw. The RR of nongrowing season Rs and Rh decreased in years with extreme snowfall or rainfall compared to those in normal years. Overall, our results highlight the significant effects of extreme precipitation on responses of Rs and its components to N fertilization, which should be incorporated into models to improve the prediction of carbon-climate feedbacks. © 2017 John Wiley & Sons Ltd.

Multisite rainfall downscaling and disaggregation in a tropical urban area

Science.gov (United States)

Lu, Y.; Qin, X. S.

2014-02-01

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

Diurnal Variation of Rainfall Associated with Tropical Depression in South China and its Relationship to Land-Sea Contrast and Topography

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Yuchun Zhao

2013-12-01

Full Text Available Convective precipitation associated with tropical depression (TD is one primary type of post-flooding season rainfall in South China (SC. Observations of the Tropical Rainfall Measuring Mission (TRMM satellite have shown specific diurnal features of convective rainfall in South China, which is somewhat different from that in other seasons or regions of China. Convective precipitation is usually organized into a rainfall band along the southeastern coast of South China in the early morning hours. The rainfall band develops and intensifies quickly in the morning, then moves inland in the afternoon and, finally, diminishes at night. The daily convective rainfall along the coast is much more than that in the inland region, and heavy rainfall is often found along the coast. A long-duration heavy rainfall event associated with tropical depression “Fitow” during the period from 28 August to 6 September 2001, is selected in this study to explore the diurnal feature of convective rainfall and its formation mechanism. Modeling results of the 10-day heavy rainfall event are compared with both rain-gauge observation and satellite-retrieved rainfall. Total precipitation and its spatial distribution, as well as diurnal variations are reasonably simulated and agree well with observations. Further analysis reveals that the development and movement of convective precipitation is mainly related to the land and sea breezes. The anomalous height-latitudinal circulation in the morning-to-noon hours is completely reversed in the afternoon-to-late-evening hours, with the convective rainfall swinging back and forth, following its updraft branch. Sensitivity experiments show that the afternoon convective rainfall in the inland region of SC is caused by the diurnal variation of solar radiation forcing. The mountain range along the coast and the complex topography in the inland region of SC plays a critical role in the enhancement of diurnal convective rainfall

Seasonal variation of physicochemical factor and fecal pollution in the Hansan-Geojeman area, Korea

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Young Cheol Park

2016-06-01

Full Text Available Abstract The seasonal variation of fecal coliforms (FCs and physicochemical factors was determined in seawaters of the Hansan-Geojeman area, including a designated area for oyster, and in inland pollution sources of its drainage basin. The mean daily loads of FCs in inland pollution sources ranged from 1.2 × 109 to 3.1 × 1011 most probable number (MPN/day; however, the pollutants could not be reached at the designated area. FC concentrations of seawaters were closely related to season, rainfall, and inland contaminants, however, within the regulation limit of various countries for shellfish. The highest concentrations for chemical oxygen demand (COD and chlorophyll-a in seawaters were shown in the surface layer during August with high rainfall, whereas the lowest for dissolved oxygen (DO in the bottom layer of the same month. Therefore, it indicates that the concentrations of FC, COD, DO, and chlorophyll-a of seawaters were closely related to season and rainfall.

Deformation responses of slow moving landslides to seasonal rainfall in the Northern Apennines, measured by InSAR

Science.gov (United States)

Bayer, Benedikt; Simoni, Alessandro; Mulas, Marco; Corsini, Alessandro; Schmidt, David

2018-05-01

Slow moving landslides are widespread geomorphological features in the Northern Apennines of Italy where they represent one of the main landscape forming processes. The lithology of the Northern Apennines fold and thrust belt is characterized by alternations of sandstone, siltstone and clayshales, also known as flysch, and clay shales with a chaotic block in matrix fabric, which are often interpreted as tectonic or sedimentary mélanges. While flysch rocks with a high pelitic fraction host earthslides that occasionally evolve into flow like movements, earthflows are the dominant landslide type in chaotic clay shales. In the present work, we document the kinematic response to rainfall of landslides in these different lithologies using radar interferometry. The study area includes three river catchments in the Northern Apennines. Here, the Mediterranean climate is characterized by two wet seasons during autumn and spring respectively, separated by dry summers and winters with moderate precipitation. We use SAR imagery from the X-band satellite COSMO SkyMed and from the C-band satellite Sentinel 1 to retrieve spatial displacement measurements between 2009 and 2016 for 25 landslides in our area of interest. We also document detailed temporal and spatial deformation signals for eight representative landslides, although the InSAR derived deformation signal is only well constrained by our dataset during the years 2013 and 2015. In spring 2013, long enduring rainfalls struck the study area and numerous landslide reactivations were documented by the regional authorities. During 2013, we measured higher displacement rates on the landslides in pelitic flysch formations compared to the earthflows in the clay shales. Slower mean velocities were measured on most landslides during 2015. We analyse the temporal deformation signal of our eight representative landslides and compare the temporal response to precipitation. We show that earthslides in pelitic flysch formations

Linking seasonal climate forecasts with crop models in Iberian Peninsula

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Capa, Mirian; Ines, Amor; Baethgen, Walter; Rodriguez-Fonseca, Belen; Han, Eunjin; Ruiz-Ramos, Margarita

2015-04-01

Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast. This study evaluates two methods for disaggregating seasonal climate forecasts into daily weather data: 1) a stochastic weather generator (CondWG), and 2) a forecast tercile resampler (FResampler). Both methods were used to generate 100 (with FResampler) and 110 (with CondWG) weather series/sequences for three scenarios of seasonal rainfall forecasts. Simulated wheat yield is computed with the crop model CERES-wheat (Ritchie and Otter, 1985), which is included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at two locations in northeastern Spain where the crop model was calibrated and validated with independent field data. Once simulated yields were obtained, an assessment of farmer's gross margin for different seasonal climate forecasts was accomplished to estimate production risks under different climate scenarios. This methodology allows farmers to assess the benefits and risks of a seasonal weather forecast in IP prior to the crop growing season. The results of this study may have important implications on both, public (agricultural planning) and private (decision support to farmers, insurance companies) sectors. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Hoogenboom, G. et al., 2010. The Decision

Relationships between Indian summer monsoon rainfall and ice cover over selected oceanic regions

Digital Repository Service at National Institute of Oceanography (India)

Gopinathan, C.K.

The variations in oceanic ice cover at selected polar regions during 1973 to 1987 have been analysed in relation to the seasonal Indian summer monsoon rainfall. The ice cover over the Arctic regions in June has negative relationship (correlation...

Monthly Rainfall Erosivity: Conversion Factors for Different Time Resolutions and Regional Assessments

DEFF Research Database (Denmark)

Panagos, Panos; Borrelli, Pasquale; Spinoni, Jonathan

2016-01-01

, for the optimization of land management (seasonal variation of vegetation cover and agricultural support practices) as well as natural hazard protection (landslides and flood prediction). We expanded REDES by 140 rainfall stations, thus covering areas where monthly R-factor values were missing (Slovakia, Poland...

Modeling Daily Rainfall Conditional on Atmospheric Predictors: An application to Western Greece

Science.gov (United States)

Langousis, Andreas; Kaleris, Vassilios

2013-04-01

1979 - 30 September 1993. The developed model is found to accurately reproduce several statistics of actual rainfall timeseries, including the distribution of annual rainfall totals, the seasonal means, variances and wet-day fractions (i.e. seasonality), the alternation of wet and dry intervals (i.e. rainfall intermittency), and the empirical distribution of dry and wet spell lengths (i.e. the clustered nature of rainfall). The suggested approach is expected to serve as a useful tool for the stochastic simulation of rainfall timeseries conditional on GCM outputs, at a regional level, and at temporal scales suitable to run hydrological models and perform hydrologic impact studies. Acknowledgments: The research project is implemented within the framework of the Action «Supporting Postdoctoral Researchers» of the Operational Program "Education and Lifelong Learning" (Action's Beneficiary: General Secretariat for Research and Technology), and is co-financed by the European Social Fund (ESF) and the Greek State.

Effect of rainfall and under-canopy vegetation on the ability to ...

African Journals Online (AJOL)

The combined effects of seasonal variation in rainfall and the presence or absence of under-canopy vegetation on soil moisture content may have a negative or positive impact on the ability to debark eucalypts. A study was initiated to investigate these interactions on the ability to debark Eucalyptus grandis x E.

Markov chain analysis of the rainfall patterns of five geographical locations in the south eastern coast of Ghana

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Meshach Tettey

2017-08-01

Full Text Available Abstract This study develops an objective rainfall pattern assessment through Markov chain analysis using daily rainfall data from 1980 to 2010, a period of 30 years, for five cities or towns along the south eastern coastal belt of Ghana; Cape Coast, Accra, Akuse, Akatsi and Keta. Transition matrices were computed for each town and each month using the conditional probability of rain or no rain on a particular day given that it rained or did not rain on the previous day. The steady state transition matrices and the steady state probability vectors were also computed for each town and each month. It was found that, the rainy or dry season pattern observed using the monthly steady state rainfall vectors tended to reflect the monthly rainfall time series trajectory. Overall, the probability of rain on any day was low to average: Keta 0.227, Akuse 0.382, Accra 0.467, Cape Coast, 0.50 and Akatsi 0.50. In particular, for Accra, the rainy season was observed to be in the months of May to June and September to October. We also determined that the probability of rainfall generally tended to increase from east to west along the south eastern coast of Ghana.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

2017-12-01

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

Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM for Rainfall Variability over the Pacific Slope and Coast of Ecuador

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Bolívar Erazo

2018-02-01

Full Text Available A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC. A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965–2015. This product is compared with the Global Precipitation Climatology Centre (GPCC dataset, the Climatic Research Unit–University of East Anglia (CRU dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7 dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7% but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of −28%. The average RMSE and Rbias of 68.7 and −2.8% of TRMM are comparable with the GPCC (69.8 and 5.7% and CRU (102.3 and −2.3% products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event over the EPSC and specifically towards the center-south of the EPSC (Guayas basin but present underestimations for the moderate El Niño of 2002–2003 event and the weak 2009–2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.

FROM RAINFALL DATA

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Sisuru Sendanayake

2015-01-01

Full Text Available There are many correlations developed to predict incident solar radiation at a givenlocation developed based on geographical and meteorological parameters. However, allcorrelations depend on accurate measurement and availability of weather data such assunshine duration, cloud cover, relative humidity, maximum and minimumtemperatures etc, which essentially is a costly exercise in terms of equipment andlabour. Sri Lanka being a tropical island of latitudinal change of only 30 along thelength of the country, the meteorological factors govern the amount of incidentradiation. Considering the cloud formation and wind patterns over Sri Lanka as well asthe seasonal rainfall patterns, it can be observed that the mean number of rainy dayscan be used to predict the monthly average daily global radiation which can be used forcalculations in solar related activities conveniently.

A numerical investigation of vapor intrusion--the dynamic response of contaminant vapors to rainfall events.

Science.gov (United States)

Shen, Rui; Pennell, Kelly G; Suuberg, Eric M

2012-10-15

The U.S. government and various agencies have published guidelines for field investigation of vapor intrusion, most of which suggest soil gas sampling as an integral part of the investigation. Contaminant soil gas data are often relatively more stable than indoor air vapor concentration measurements, but meteorological conditions might influence soil gas values. Although a few field and numerical studies have considered some temporal effects on soil gas vapor transport, a full explanation of the contaminant vapor concentration response to rainfall events is not available. This manuscript seeks to demonstrate the effects on soil vapor transport during and after different rainfall events, by applying a coupled numerical model of fluid flow and vapor transport. Both a single rainfall event and seasonal rainfall events were modeled. For the single rainfall event models, the vapor response process could be divided into three steps: namely, infiltration, water redistribution, and establishment of a water lens atop the groundwater source. In the infiltration step, rainfall intensity was found to determine the speed of the wetting front and wash-out effect on the vapor. The passage of the wetting front led to an increase of the vapor concentration in both the infiltration and water redistribution steps and this effect is noted at soil probes located 1m below the ground surface. When the mixing of groundwater with infiltrated water was not allowed, a clean water lens accumulated above the groundwater source and led to a capping effect which can reduce diffusion rates of contaminant from the source. Seasonal rainfall with short time intervals involved superposition of the individual rainfall events. This modeling results indicated that for relatively deeper soil that the infiltration wetting front could not flood, the effects were damped out in less than a month after rain; while in the long term (years), possible formation of a water lens played a larger role in determining

Erosivity factor in the Universal Soil Loss Equation estimated from Finnish rainfall data

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Maximilian Posch

1993-07-01

Full Text Available Continuous rainfall data recorded for many years at 8 stations in Finland were used to estimate rainfall erosivity, a quantity needed for soil loss predictions with the Universal Soil Loss Equation (USLE. The obtained erosivity values were then used to determine the 2 parameters of a power-law function describing the relationship between daily precipitation and erosivity. This function is of importance in erosion modeling at locations where no breakpoint rainfall data are available. The parameters of the power-law were estimated both by linear regression of the log-transformed data and by non-linear least-square fitting of the original data. Results indicate a considerable seasonal (monthly variation of the erosivity, whereas the spatial variation over Finland is rather small.

Water policy reform in Australia: lessons from the Victorian seasonal water market

OpenAIRE

Brennan, Donna C.

2006-01-01

The nature of the seasonal water market is examined using a theoretical model and empirical evidence from the Victorian market. Drivers of the seasonal opportunity cost of water include the underlying nature of investment in the industry made in the context of risky entitlement yields; and the timing and nature of information regarding seasonal water availability and rainfall. Seasonal water markets facilitate the reallocation of water availability according to this short-run opportunity cost...

Factors influencing long-term and seasonal waterbird abundance ...

African Journals Online (AJOL)

... influence waterbird communities include rainfall quantity and distribution, waterbird movement, breeding and moulting; anthropogenic drivers include activities such as fishing and agriculture. Results suggest that seasonal variations in resource availability influenced the waterbird community composition and abundance, ...

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

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Francyregis A Nunes

2011-12-01

abundance (R2=0.68. A similar negative linear correlation was found for species occurrences against rainfall (R2=0.71, and for mean number of species per pitfall trap against rainfall (R2=0.71. However, some species showed equal abundance, occurrence and mean number of individuals per pitfall trap in both seasons, while others showed a much higher abundance and occurrence during the rainy season. Pitfall trapping as a method to sample ground-foraging ant assemblage of the Caatinga biome and potential factors responsible for lower pitfall trap performance during rainy season are discussed. Rev. Biol. Trop. 59 (4: 1637-1650. Epub 2011 December 01.

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

Science.gov (United States)

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 (pARIMA) model. The model is further evaluated using 24 months rainfall data yielding r=0.79 (regression slope=0.8; pARIMA 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.

Rainfall and flow of the Riozinho do Rôla Basin on Western Amazon

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Maria Lúcia Hall de Souza

2013-04-01

Full Text Available The present study was conducted to analyze the factors influencing the hydrological behavior of the Riozinho do Rôla hydrographic basin, and was based on descriptive analysis tools. Fourteen pluviometers were set up in order to conduct a representative analysis of the rainfall in the basin. Residents of the area voluntarily participated in collection of the rainfall data in the years 2007 and 2008; the residents were trained to collect the data before the pluviometers were installed. ArcGis 9.2 software was used to outline and calculate the area of the Thiessen polygons, and both arithmetic and Thiessen precipitation means were calculated using Excel software. The average precipitation values were 1,428 mm and 1,450 mm, as calculated using the arithmetic mean and Thiessen method, respectively. Using data from the Agência Nacional de Águas (ANA, the rainfall and flow rate in the basin were calculated for the period from 1998 to 2005. The seasonality of precipitation is reflected in the temporary flow rate activity, which reached a peak of 1,276.9 m³/s during the flood period and 4.1 m³/s during periods of the dry season. This behavior is fundamentally related to natural and social aspects of the basin, such as the occurrence of a hydrographic network with characteristics of a headwater associated with a hydrological regime marked by high seasonality; the low permeability of the soils in the basin; and the intensification of deforestation in the region in order to develop livestock as a privileged form of land use.

Soil Infiltration Characteristics in Agroforestry Systems and Their Relationships with the Temporal Distribution of Rainfall on the Loess Plateau in China.

Science.gov (United States)

Wang, Lai; Zhong, Chonggao; Gao, Pengxiang; Xi, Weimin; Zhang, Shuoxin

2015-01-01

Many previous studies have shown that land use patterns are the main factors influencing soil infiltration. Thus, increasing soil infiltration and reducing runoff are crucial for soil and water conservation, especially in semi-arid environments. To explore the effects of agroforestry systems on soil infiltration and associated properties in a semi-arid area of the Loess Plateau in China, we compared three plant systems: a walnut (Juglans regia) monoculture system (JRMS), a wheat (Triticum aestivum) monoculture system (TAMS), and a walnut-wheat alley cropping system (JTACS) over a period of 11 years. Our results showed that the JTACS facilitated infiltration, and its infiltration rate temporal distribution showed a stronger relationship coupled with the rainfall temporal distribution compared with the two monoculture systems during the growing season. However, the effect of JTACS on the infiltration capacity was only significant in shallow soil layer, i.e., the 0-40 cm soil depth. Within JTACS, the speed of the wetting front's downward movement was significantly faster than that in the two monoculture systems when the amount of rainfall and its intensity were higher. The soil infiltration rate was improved, and the two peaks of soil infiltration rate temporal distribution and the rainfall temporal distribution coupled in rainy season in the alley cropping system, which has an important significance in soil and water conservation. The results of this empirical study provide new insights into the sustainability of agroforestry, which may help farmers select rational planting patterns in this region, as well as other regions with similar climatic and environmental characteristics throughout the world.

Soil Infiltration Characteristics in Agroforestry Systems and Their Relationships with the Temporal Distribution of Rainfall on the Loess Plateau in China.

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Lai Wang

Full Text Available Many previous studies have shown that land use patterns are the main factors influencing soil infiltration. Thus, increasing soil infiltration and reducing runoff are crucial for soil and water conservation, especially in semi-arid environments. To explore the effects of agroforestry systems on soil infiltration and associated properties in a semi-arid area of the Loess Plateau in China, we compared three plant systems: a walnut (Juglans regia monoculture system (JRMS, a wheat (Triticum aestivum monoculture system (TAMS, and a walnut-wheat alley cropping system (JTACS over a period of 11 years. Our results showed that the JTACS facilitated infiltration, and its infiltration rate temporal distribution showed a stronger relationship coupled with the rainfall temporal distribution compared with the two monoculture systems during the growing season. However, the effect of JTACS on the infiltration capacity was only significant in shallow soil layer, i.e., the 0-40 cm soil depth. Within JTACS, the speed of the wetting front's downward movement was significantly faster than that in the two monoculture systems when the amount of rainfall and its intensity were higher. The soil infiltration rate was improved, and the two peaks of soil infiltration rate temporal distribution and the rainfall temporal distribution coupled in rainy season in the alley cropping system, which has an important significance in soil and water conservation. The results of this empirical study provide new insights into the sustainability of agroforestry, which may help farmers select rational planting patterns in this region, as well as other regions with similar climatic and environmental characteristics throughout the world.

First study on infestation of Excorallana berbicensis (Isopoda: Corallanidae on six fishes in a reservoir in Brazilian Amazon during dry and rainy seasons

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Huann Carllo Gentil-Vasconcelos

2015-11-01

Full Text Available We analyzed the infestation levels of Excorallana berbicensis on Acestrorhynchus falcirostris, Ageneiosus ucayalensis, Geophagus proximus, Hemiodus unimaculatus, Psectrogasterfalcata and Serrasalmus gibbus in a reservoir in the Araguari River basin, northern Brazil, during the dry and rainy seasons. For P. falcata, the infestation levels due to E. berbicensis were greater during the rainy season. For all the species studied, the peak parasite prevalence was in the month of highest rainfall levels and there were two peaks of parasite abundance: one in the month with highest rainfall level and the other in the month of transition from the rainy season to the dry season. In these hosts, around 70% of the E. berbicensis specimens were collected during the rainy season. The body conditions of the hosts also did not suffer any seasonal influence. Despite the differences in seasonal rainfall levels, there was no fluctuation in transparency, turbidity, pH, electric conductivity, temperature and dissolved oxygen levels in the water, due to the stability of these parameters during the seasonal cycle investigated in this artificial Amazon ecosystem. This was the first report on the seasonality of infestation by E. berbicensis associated with fish.

Assessment of GloSea4 seasonal forecasts for SADC and the global oceans

CSIR Research Space (South Africa)

Landman, WA

2012-10-01

Full Text Available totals during the austral spring (SON), mid-summer (DJF) and autumn (MAM) seasons in the region, and by testing for monthly sea-surface temperature anomalies during mid-summer. The model’s ability to simulate the region’s intra-seasonal rainfall and low...

Diagnosing the Atmospheric/Oceanic Phenomena Associated with the Onset, Demise and Mid-Summer Drought of the Rainy Season in Mesoamerica

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Groenen, D.; Bourassa, M. A.

2017-12-01

The rainfall in Mesoamerica (Mexico and Central America) has influences from two bodies of water, interesting topography, and complex wind patterns, which complicates weather forecasting. Knowing the approximate onset and demise of the rainy season is critical for the optimal growth and development of key crops in this region such as coffee, bananas, rice, and maize. This study compares three methods to calculate the onset/demise dates of the individual years' rainy season, using area-averaged rainfall data (7-28 °N/77-109 °W) from two datasets. After these onset/demise dates are obtained using rainfall data, the atmospheric and oceanic phenomena associated with the timing is analyzed using MERRA-2 reanalysis data. The objective is to link the large-scale phenomena to the individual years' onset/demise dates, as well as link the weather phenomena to the interannual variability of the onset/demise dates. In addition, the broad scale rainy season will be connected with regional onset/demise dates on the scale of 400km. Linking the broad scale rainfall regimes to the regional regimes will allow a more cohesive view of the dynamics related to rainfall variability in the Mesoamerican region. A smoothing method will be used to analyze the timing and intensity of the mid-summer drought (MSD), a minimum in rainfall typically occurring during July and August. The goal of this research is to link the physical and dynamical mechanisms that cause the Mesoamerican rainy season and mid-summer drought (MSD) in order to better understand the predictability of Mesoamerican rainfall and ensure the health and safety of key crops.

Seasonal Variation of Diurnal Cycle of Rainfall in the Eastern Equatorial Indian Ocean

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RameshKumar, M.R.; Pednekar, S.; Katsumata, M.; Antony, M.K.; Kuroda, Y.; Unnikrishnan, A.S.

The diurnal cycle of rainfall over the eastern equatorial Indian Ocean is studied for the period 23rd October 2001 to 31st October 2003 using the hourly data from the Triton buoy positioned at 1.5°S and 90°E. An analysis of the active and weak...

Multiple Time-Scale Monitoring to Address Dynamic Seasonality and Storm Pulses of Stream Water Quality in Mountainous Watersheds

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Hyun-Ju Lee

2015-11-01

Full Text Available Rainfall variability and extreme events can amplify the seasonality and storm pulses of stream water chemistry in mountainous watersheds under monsoon climates. To establish a monitoring program optimized for identifying potential risks to stream water quality arising from rainfall variability and extremes, we examined water chemistry data collected on different timescales. At a small forested watershed, bi-weekly sampling lasted over two years, in comparison to three other biweekly sampling sites. In addition, high-frequency continuous measurements of pH, electrical conductivity, and turbidity were conducted in tandem with automatic water sampling at 2 h intervals during eight rainfall events. Biweekly monitoring showed that during the summer monsoon period, electrical conductivity (EC, dissolved oxygen (DO, and dissolved ion concentrations generally decreased, but total suspended solids (TSS slightly increased. A noticeable variation from the usual seasonal pattern was that DO levels substantially decreased during an extended drought. Bi-hourly storm event samplings exhibited large changes in the concentrations of TSS and particulate and dissolved organic carbon (POC; DOC during intense rainfall events. However, extreme fluctuations in sediment export during discharge peaks could be detected only by turbidity measurements at 5 min intervals. Concomitant measurements during rainfall events established empirical relationships between turbidity and TSS or POC. These results suggest that routine monitoring based on weekly to monthly sampling is valid only in addressing general seasonal patterns or long-lasting phenomena such as drought effects. We propose an “adaptive” monitoring scheme that combines routine monitoring for general seasonal patterns and high-frequency instrumental measurements of water quality components exhibiting rapid responses pulsing during intense rainfall events.

Interannual rainfall variability in the Amazon basin and sea-surface temperatures in the equatorial Pacific and the tropical Atlantic Oceans

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Ronchail, Josyane; Cochonneau, Gérard; Molinier, Michel; Guyot, Jean-Loup; Chaves, Adriana Goretti De Miranda; Guimarães, Valdemar; de Oliveira, Eurides

2002-11-01

Rainfall variability in the Amazon basin is studied in relation to sea-surface temperatures (SSTs) in the equatorial Pacific and the northern and southern tropical Atlantic during the 1977-99 period, using the HiBAm original rainfall data set and complementary cluster and composite analyses.The northeastern part of the basin, north of 5 °S and east of 60 °W, is significantly related with tropical SSTs: a rainier wet season is observed when the equatorial Pacific and the northern (southern) tropical Atlantic are anomalously cold (warm). A shorter and drier wet season is observed during El Niño events and negative rainfall anomalies are also significantly associated with a warm northern Atlantic in the austral autumn and a cold southern Atlantic in the spring. The northeastern Amazon rainfall anomalies are closely related with El Niño-southern oscillation during the whole year, whereas the relationships with the tropical Atlantic SST anomalies are mainly observed during the autumn. A time-space continuity is observed between El Niño-related rainfall anomalies in the northeastern Amazon, those in the northern Amazon and south-eastern Amazon, and those in northern South America and in the Nordeste of Brazil.A reinforcement of certain rainfall anomalies is observed when specific oceanic events combine. For instance, when El Niño and cold SSTs in the southern Atlantic are associated, very strong negative anomalies are observed in the whole northern Amazon basin. Nonetheless, the comparison of the cluster and the composite analyses results shows that the rainfall anomalies in the northeastern Amazon are not always associated with tropical SST anomalies.In the southern and western Amazon, significant tropical SST-related rainfall anomalies are very few and spatially variable. The precipitation origins differ from those of the northeastern Amazon: land temperature variability, extratropical perturbations and moisture advection are important rainfall factors, as well

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

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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.

A space-time hybrid hourly rainfall model for derived flood frequency analysis

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U. Haberlandt

2008-12-01

Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.

First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in

A Numerical Investigation of Vapor Intrusion — the Dynamic Response of Contaminant Vapors to Rainfall Events

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Shen, Rui; Pennell, Kelly G.; Suuberg, Eric M.

2013-01-01

The U.S. government and various agencies have published guidelines for field investigation of vapor intrusion, most of which suggest soil gas sampling as an integral part of the investigation. Contaminant soil gas data are often relatively more stable than indoor air vapor concentration measurements, but meteorological conditions might influence soil gas values. Although a few field and numerical studies have considered some temporal effects on soil gas vapor transport, a full explanation of the contaminant vapor concentration response to rainfall events is not available. This manuscript seeks to demonstrate the effects on soil vapor transport during and after different rainfall events, by applying a coupled numerical model of fluid flow and vapor transport. Both a single rainfall event and seasonal rainfall events were modeled. For the single rainfall event models, the vapor response process could be divided into three steps: namely, infiltration, water redistribution, and establishment of a water lens atop the groundwater source. In the infiltration step, rainfall intensity was found to determine the speed of the wetting front and wash-out effect on the vapor. The passage of the wetting front led to an increase of the vapor concentration in both the infiltration and water redistribution steps and this effect is noted at soil probes located 1 m below the ground surface. When the mixing of groundwater with infiltrated water was not allowed, a clean water lens accumulated above the groundwater source and led to a capping effect which can reduce diffusion rates of contaminant from the source. Seasonal rainfall with short time intervals involved superposition of the individual rainfall events. This modeling results indicated that for relatively deeper soil that the infiltration wetting front could not flood, the effects were damped out in less than a month after rain; while in the long term (years), possible formation of a water lens played a larger role in

Determination of Areas Susceptible to Landsliding Using Spatial Patterns of Rainfall from Tropical Rainfall Measuring Mission Data, Rio de Janeiro, Brazil

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Renato Fontes Guimarães

2017-10-01

Full Text Available Spatial patterns of shallow landslide initiation reflect both spatial patterns of heavy rainfall and areas susceptible to mass movements. We determine the areas most susceptible to shallow landslide occurrence through the calculation of critical soil cohesion and spatial patterns of rainfall derived from TRMM (Tropical Rainfall Measuring Mission data for Paraty County, State of Rio de Janeiro, Brazil. Our methodology involved: (a creating the digital elevation model (DEM and deriving attributes such as slope and contributing area; (b incorporating spatial patterns of rainfall derived from TRMM into the shallow slope stability model SHALSTAB; and (c quantitative assessment of the correspondence of mapped landslide scars to areas predicted to be most prone to shallow landsliding. We found that around 70% of the landslide scars occurred in less than 10% of the study area identified as potentially unstable. The greatest concentration of landslides occurred in areas where the root strength of vegetation is an important contribution to slope stability in regions of orographically-enhanced rainfall on the coastal topographic flank. This approach helps quantify landslide hazards in areas with similar geomorphological characteristics, but different spatial patterns of rainfall.

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

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

2017-09-01

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

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

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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.

Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

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Pattanaik, D.R. [India Meteorological Department (IMD), New Delhi (India); Kumar, Arun [Climate Prediction Center, National Centre for Environmental Prediction (NCEP)/NWS/NOAA, Camp Springs, MD (United States)

2010-03-15

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction's (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS's hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50 E-110 E and 10 S-35 N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon

Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

Science.gov (United States)

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

Rainfall variability and drought characteristics in two agro-climatic zones: An assessment of climate change challenges in Africa.

Science.gov (United States)

Ayanlade, Ayansina; Radeny, Maren; Morton, John F; Muchaba, Tabitha

2018-07-15

This paper examines drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' climate change perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations. Consequently, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability (p) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62≤p≥0.8 in all the stations, though, the p-values for 10day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days 0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided to farmers, at a subsidized price by the government, for them to cope with the current condition of climate change. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Trend Analysis of Droughts during Crop Growing Seasons of Nigeria

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Mohammed Sanusi Shiru

2018-03-01

Full Text Available This study assesses the impacts of recent climate changes on drought-affected areas and the occurrence of droughts during different cropping seasons of Nigeria using the standardized precipitation evapotranspiration index (SPEI. The crop growing seasons are considered because the droughts for those periods are more destructive to national agricultural production. The Mann–Kendall test and binary logistic regression were used to quantify the trends in drought-affected areas and the occurrence of crop droughts with different areal extents, respectively. Gauge-based gridded rainfall and temperature data for the period 1961–2010 with spatial resolutions of 0.5° were used. Results showed an increase in the areal extent of droughts during some of the cropping seasons. The occurrences of droughts, particularly moderate droughts with smaller areal extents, were found to increase for all of the seasons. The SPEI values calculated decreased mostly in the regions where rainfall was decreasing. That is, the recent changes in climate were responsible for the increase in the occurrences of droughts with smaller areal extents. These trends in climate indicate that the occurrence of larger areal extent droughts may happen more frequently in Nigeria in the future.

Rainfall mediations in the spreading of epidemic cholera

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Righetto, L.; Bertuzzo, E.; Mari, L.; Schild, E.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2013-10-01

Following the empirical evidence of a clear correlation between rainfall events and cholera resurgence that was observed in particular during the recent outbreak in Haiti, a spatially explicit model of epidemic cholera is re-examined. Specifically, we test a multivariate Poisson rainfall generator, with parameters varying in space and time, as a driver of enhanced disease transmission. The relevance of the issue relates to the key insight that predictive mathematical models may provide into the course of an ongoing cholera epidemic aiding emergency management (say, in allocating life-saving supplies or health care staff) or in evaluating alternative management strategies. Our model consists of a set of dynamical equations (SIRB-like i.e. subdivided into the compartments of Susceptible, Infected and Recovered individuals, and including a balance of Bacterial concentrations in the water reservoir) describing a connected network of human communities where the infection results from the exposure to excess concentrations of pathogens in the water. These, in turn, are driven by rainfall washout of open-air defecation sites or cesspool overflows, hydrologic transport through waterways and by mobility of susceptible and infected individuals. We perform an a posteriori analysis (from the beginning of the epidemic in October 2010 until December 2011) to test the model reliability in predicting cholera cases and in testing control measures, involving vaccination and sanitation campaigns, for the ongoing epidemic. Even though predicting reliably the timing of the epidemic resurgence proves difficult due to rainfall inter-annual variability, we find that the model can reasonably quantify the total number of reported infection cases in the selected time-span. We then run a multi-seasonal prediction of the course of the epidemic until December 2015, to investigate conditions for further resurgences and endemicity of cholera in the region with a view to policies which may bring to

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

Science.gov (United States)

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.

Seasonal dynamics of snail populations in coastal Kenya: Model calibration and snail control

Science.gov (United States)

Gurarie, D.; King, C. H.; Yoon, N.; Wang, X.; Alsallaq, R.

2017-10-01

A proper snail population model is important for accurately predicting Schistosoma transmission. Field data shows that the overall snail population and that of shedding snails have a strong pattern of seasonal variation. Because human hosts are infected by the cercariae released from shedding snails, the abundance of the snail population sets ultimate limits on human infection. For developing a predictive dynamic model of schistosome infection and control strategies we need realistic snail population dynamics. Here we propose two such models based on underlying environmental factors and snail population biology. The models consist of two-stage (young-adult) populations with resource-dependent reproduction, survival, maturation. The key input in the system is seasonal rainfall which creates snail habitats and resources (small vegetation). The models were tested, calibrated and validated using dataset collected in Msambweni (coastal Kenya). Seasonal rainfall in Msambweni is highly variable with intermittent wet - dry seasons. Typical snail patterns follow precipitation peaks with 2-4-month time-lag. Our models are able to reproduce such seasonal variability over extended period of time (3-year study). We applied them to explore the optimal seasonal timing for implementing snail control.

Radar rainfall estimation for the identification of debris-flow precipitation thresholds

Science.gov (United States)

Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

2014-05-01

variogram) of the triggering rainfall. These results show that weather radar has the potential to effectively increase the accuracy of rainfall thresholds for debris flow occurrence. However, these benefits may only be achieved if the same monitoring instrumentation is used both to derive the rainfall thresholds and for use of thresholds for real-time identification of debris flows occurrence. References Nikolopoulos, E.I., Borga M., Crema S., Marchi L, Marra F. & Guzzetti F., 2014. Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris-flow occurrence. Geomorphology (conditionally accepted) Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C., and Guzzetti, F., 2012. Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy, Geomorphology, 139-140, 79-90, 2012.

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

Science.gov (United States)

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.

The seasonal influence of climate and environment on yellow fever transmission across Africa.

Science.gov (United States)

Hamlet, Arran; Jean, Kévin; Perea, William; Yactayo, Sergio; Biey, Joseph; Van Kerkhove, Maria; Ferguson, Neil; Garske, Tini

2018-03-01

Yellow fever virus (YFV) is a vector-borne flavivirus endemic to Africa and Latin America. Ninety per cent of the global burden occurs in Africa where it is primarily transmitted by Aedes spp, with Aedes aegypti the main vector for urban yellow fever (YF). Mosquito life cycle and viral replication in the mosquito are heavily dependent on climate, particularly temperature and rainfall. We aimed to assess whether seasonal variations in climatic factors are associated with the seasonality of YF reports. We constructed a temperature suitability index for YFV transmission, capturing the temperature dependence of mosquito behaviour and viral replication within the mosquito. We then fitted a series of multilevel logistic regression models to a dataset of YF reports across Africa, considering location and seasonality of occurrence for seasonal models, against the temperature suitability index, rainfall and the Enhanced Vegetation Index (EVI) as covariates alongside further demographic indicators. Model fit was assessed by the Area Under the Curve (AUC), and models were ranked by Akaike's Information Criterion which was used to weight model outputs to create combined model predictions. The seasonal model accurately captured both the geographic and temporal heterogeneities in YF transmission (AUC = 0.81), and did not perform significantly worse than the annual model which only captured the geographic distribution. The interaction between temperature suitability and rainfall accounted for much of the occurrence of YF, which offers a statistical explanation for the spatio-temporal variability in transmission. The description of seasonality offers an explanation for heterogeneities in the West-East YF burden across Africa. Annual climatic variables may indicate a transmission suitability not always reflected in seasonal interactions. This finding, in conjunction with forecasted data, could highlight areas of increased transmission and provide insights into the occurrence of

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

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

2017-08-01

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

Analysis on the influence of rainfall and mine water ratio against pH in East pit 3 West Banko coal mine

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Rochyani Neny

2017-01-01

Full Text Available In the coal mining area, the pH of mine water is found tend to low and acids. In order to increase the pH, it is important to consider the treatment of acid mine drainage using lime, due the indicators of pollution. This work is focused on the influence of rainfall volume on the pH of acid mine drainage. This research conducted using a ratio of mine water and rainfall water that varies in the 9 (nine conditions, respectively: 1: 1, 1: 2, 1: 3, 1: 4 and 1: 5 and 5: 4, 5: 3 , 5: 2 and 5: 1. The results were then measured and tested with statistical analysis. The ratio of rainfall and mine water showed a significant effect on the pH. The higher of the rainfall lead to increase pH. This condition will affect the water neutralization process using lime where there are some possible differences on dose of lime needed to neutralized the acid mine drainage in the rainy season and dry season.

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

Science.gov (United States)

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

2018-01-01

simulations forced using the bias corrected rainfall (distribution mapping and modified power transformation methods that used the proposed daily correction factors) was similar to those simulated by the IMD rainfall. The results demonstrate that the methods and the time scales used for bias correction of RCM rainfall data have a larger impact on the accuracy of the daily rainfall and consequently the simulated streamflow. The analysis suggests that the distribution mapping with daily correction factors can be preferred for adjusting RCM rainfall data irrespective of seasons or climate zones for realistic simulation of streamflow.

Topographic relationships for design rainfalls over Australia

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Johnson, F.; Hutchinson, M. F.; The, C.; Beesley, C.; Green, J.

2016-02-01

for most of the Australian continent, extreme rainfall is closely aligned with elevation, but in areas with high topographic relief the impacts of topography on rainfall extremes are more complex. The interpolated extreme rainfall statistics, using no data transformation, have been used by the Australian Bureau of Meteorology to produce new IDF data for the Australian continent. The comprehensive methods presented for the evaluation of gridded design rainfall statistics will be useful for similar studies, in particular the importance of balancing the need for a continentally-optimum solution that maintains sufficient definition at the local scale.

Evaluating the MSG satellite Multi-Sensor Precipitation Estimate for extreme rainfall monitoring over northern Tunisia

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Saoussen Dhib

2017-06-01

Full Text Available Knowledge and evaluation of extreme precipitation is important for water resources and flood risk management, soil and land degradation, and other environmental issues. Due to the high potential threat to local infrastructure, such as buildings, roads and power supplies, heavy precipitation can have an important social and economic impact on society. At present, satellite derived precipitation estimates are becoming more readily available. This paper aims to investigate the potential use of the Meteosat Second Generation (MSG Multi-Sensor Precipitation Estimate (MPE for extreme rainfall assessment in Tunisia. The MSGMPE data combine microwave rain rate estimations with SEVIRI thermal infrared channel data, using an EUMETSAT production chain in near real time mode. The MPE data can therefore be used in a now-casting mode, and are potentially useful for extreme weather early warning and monitoring. Daily precipitation observed across an in situ gauge network in the north of Tunisia were used during the period 2007–2009 for validation of the MPE extreme event data. As a first test of the MSGMPE product's performance, very light to moderate rainfall classes, occurring between January and October 2007, were evaluated. Extreme rainfall events were then selected, using a threshold criterion for large rainfall depth (>50 mm/day occurring at least at one ground station. Spatial interpolation methods were applied to generate rainfall maps for the drier summer season (from May to October and the wet winter season (from November to April. Interpolated gauge rainfall maps were then compared to MSGMPE data available from the EUMETSAT UMARF archive or from the GEONETCast direct dissemination system. The summation of the MPE data at 5 and/or 15 min time intervals over a 24 h period, provided a basis for comparison. The MSGMPE product was not very effective in the detection of very light and light rain events. Better results were obtained for the slightly

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

Science.gov (United States)

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

2015-12-01

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

Rainfall Variability across the Agneby Watershed at the Agboville Outlet in Côte d’Ivoire, West Africa

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Akissi Bienve Pélagie Kouakou

2016-12-01

Full Text Available This study analyzes, at local and regional scales, the rainfall variability across the Agneby watershed at the Agboville outlet over the period 1950–2013. Daily rainfall data from 14 rain gauges are used. The methods used are based, firstly, on the rainfall index which aims to characterize the inter-annual and decadal variability of rainfall and, secondly, on the moving average to determine the dynamics of the mean seasonal cycle of the precipitations. Furthermore, the Pettitt test and the Hubert segmentation are applied to detect change-point in the rainfall series. At the basin scale, analysis of rainfall signals composites has shown that the rainfall deficit was more pronounced after the leap of monsoon. Dry years were characterized by an early monsoon demise which is remarkable after 1968. Moreover, the years after 1969 presented a shift of the peaks in precipitation for about 12 days. These peaks were reached early. The rainfall signal showed that the rainfall deficit for the period after 1968, relatively to the period before, was 10% in June against 36% in October for the average rainfall in the Agneby basin. At the local scale, the deficit of the peaks depends on the location. These rainfall deficits were 23% against 36.3% in June for the Agboville and Bongouanou rain gauges, respectively.

Seasonal variation in human reproduction: environmental factors.

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Bronson, F H

1995-06-01

Almost all human populations exhibit seasonal variation in births, owing mostly to seasonal variation in the frequency of conception. This review focuses on the degree to which environmental factors like nutrition, temperature and photoperiod contribute to these seasonal patterns by acting directly on the reproductive axis. The reproductive strategy of humans is basically that of the apes: Humans have the capacity to reproduce continuously, albeit slowly, unless inhibited by environmental influences. Two, and perhaps three, environmental factors probably act routinely as seasonal inhibitors in some human populations. First, it seems likely that ovulation is regulated seasonally in populations experiencing seasonal variation in food availability. More specifically, it seems likely that inadequate food intake or the increased energy expenditure required to obtain food, or both, can delay menarche, suppress the frequency of ovulation in the nonlactating adult, and prolong lactational amenorrhea in these populations on a seasonal basis. This action is most easily seen in tropical subsistence societies where food availability often varies greatly owing to seasonal variation in rainfall; hence births in these populations often correlate with rainfall. Second, it seems likely that seasonally high temperatures suppress spermatogenesis enough to influence the incidence of fertilization in hotter latitudes, but possibly only in males wearing clothing that diminishes scrotal cooling. Since most of our knowledge about this phenomenon comes from temperate latitudes, the sensitivity of spermatogenesis in both human and nonhuman primates to heat in the tropics needs further study. It is quite possible that high temperatures suppress ovulation and early embryo survival seasonally in some of these same populations. Since we know less than desired about the effect of heat stress on ovulation and early pregnancy in nonhuman mammals, and nothing at all about it in humans or any of the

Accuracy of rainfall measurement for scales of hydrological interest

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S. J. Wood

2000-01-01

Full Text Available The dense network of 49 raingauges over the 135 km2 Brue catchment in Somerset, England is used to examine the accuracy of rainfall estimates obtained from raingauges and from weather radar. Methods for data quality control and classification of precipitation types are first described. A super-dense network comprising eight gauges within a 2 km grid square is employed to obtain a 'true value' of rainfall against which the 2 km radar grid and a single 'typical gauge' estimate can be compared. Accuracy is assessed as a function of rainfall intensity, for different periods of time-integration (15 minutes, 1 hour and 1 day and for two 8-gauge networks in areas of low and high relief. In a similar way, the catchment gauge network is used to provide the 'true catchment rainfall' and the accuracy of a radar estimate (an area-weighted average of radar pixel values and a single 'typical gauge' estimate of catchment rainfall evaluated as a function of rainfall intensity. A single gauge gives a standard error of estimate for rainfall in a 2 km square and over the catchment of 33% and 65% respectively, at rain rates of 4 mm in 15 minutes. Radar data at 2 km resolution give corresponding errors of 50% and 55%. This illustrates the benefit of using radar when estimating catchment scale rainfall. A companion paper (Wood et al., 2000 considers the accuracy of rainfall estimates obtained using raingauge and radar in combination. Keywords: rainfall, accuracy, raingauge, radar

Dry-season retreat and dietary shift of the dart-poison frog Dendrobates tinctorius (Anura: Dendrobatidae

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Marga Born

2010-07-01

Full Text Available Seasonal rainfall affects tropical forest dynamics and behaviorof species that are part of these ecosystems. The positive correlation between amphibian activity patterns and rainfall has been demonstrated repeatedly. Members of Dendrobatidae, a clade of Neotropical dart-poison frogs, are well known for their habitat use and behavior during the rainy season, but their behavior during the dry season has received little attention. We studied habitat use and diet of the dendrobatid frog Dendrobates tinctorius in French Guiana during the rainy and dry seasons. Unlike many other dendrobatid frogs, D. tinctorius does not maintain territories for the entire rainy season. Both sexes colonize recently formed canopy-gaps and stay in these forest patches for only a few weeks. The frogs inthese patches consume a great diversity of prey, consisting of ants, beetles, wasps, insect larvae, and mites. During the dry season, frogs move to retreat sites in mature forest, such as palm bracts and tree holes. The frogs are less active and consume fewer prey items in the dry season, and they consume fewer wasps and insect larvae, but more termites. Ants are the most common prey items during both the wet and dry seasons. We discuss the effects of shifts in seasonal habitat use on the territorial behavior of dendrobatid frogs.

Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia.

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Aragão, Luiz Eduardo O C; Malhi, Yadvinder; Barbier, Nicolas; Lima, Andre; Shimabukuro, Yosio; Anderson, Liana; Saatchi, Sassan

2008-05-27

Understanding the interplay between climate and land-use dynamics is a fundamental concern for assessing the vulnerability of Amazonia to climate change. In this study, we analyse satellite-derived monthly and annual time series of rainfall, fires and deforestation to explicitly quantify the seasonal patterns and relationships between these three variables, with a particular focus on the Amazonian drought of 2005. Our results demonstrate a marked seasonality with one peak per year for all variables analysed, except deforestation. For the annual cycle, we found correlations above 90% with a time lag between variables. Deforestation and fires reach the highest values three and six months, respectively, after the peak of the rainy season. The cumulative number of hot pixels was linearly related to the size of the area deforested annually from 1998 to 2004 (r2=0.84, p=0.004). During the 2005 drought, the number of hot pixels increased 43% in relation to the expected value for a similar deforested area (approx. 19000km2). We demonstrated that anthropogenic forcing, such as land-use change, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region even with decreased deforestation rates. We may expect that the ongoing deforestation, currently based on slash and burn procedures, and the use of fires for land management in Amazonia will intensify the impact of droughts associated with natural climate variability or human-induced climate change and, therefore, a large area of forest edge will be under increased risk of fires.

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

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

2014-01-01

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

Effects of extreme rainfall events on the distribution of selected emerging contaminants in surface and groundwater: The Guadalete River basin (SW, Spain).

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Corada-Fernández, Carmen; Candela, Lucila; Torres-Fuentes, Nivis; Pintado-Herrera, Marina G; Paniw, Maria; González-Mazo, Eduardo

2017-12-15

This study is focused on the Guadalete River basin (SW, Spain), where extreme weather conditions have become common, with and alternation between periods of drought and extreme rainfall events. Combined sewer overflows (CSOs) occur when heavy rainfall events exceed the capacity of the wastewater treatment plants (WWTP), as well as pollution episodes in parts of the basin due to uncontrolled sewage spills and the use of reclaimed water and sludge from the local WWTP. The sampling was carried out along two seasons and three campaigns during dry (March 2007) and extreme rainfall (April and December 2010) in the Guadalete River, alluvial aquifer and Jerez de la Frontera aquifer. Results showed minimum concentrations for synthetic surfactants in groundwater (contaminants increased in December 2010 as the heavy rainfall caused the river to overflow. In surface water, surfactant concentrations showed similar trends to groundwater observations. In addition to surfactants, pharmaceuticals and personal care products (PPCPs) were analyzed in the third campaign, 22 of which were detected in surface waters. Two fragrances (OTNE and galaxolide) and one analgesic/anti-inflammatory (ibuprofen) were the most abundant PPCPs (up to 6540, 2748 and 1747ng·L -1 , respectively). Regarding groundwater, most PPCPs were detected in Jerez de la Frontera aquifer, where a synthetic fragrance (OTNE) was predominant (up to 1285ng·L -1 ). Copyright © 2017 Elsevier B.V. All rights reserved.

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

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Ongoma, Victor; Chen, Haishan; Gao, Chujie

2018-02-01

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

The Relationship between El nino Southern Oscillation (ENSO) Phenomenon and Seasonal Precipitation Variability in Eastern Kenya with Special Reference to Katumani: Its Implication to Crop Production

International Nuclear Information System (INIS)

Kitheka, S.K

1999-01-01

Climatic variability has been defined as a major limitation to agricultural production in semi arid Kenya. The major difficulty to both farmers and research community, has been the inability to to predict seasonal rainfall prior to the season onset. Although several researches have attempted and made advances in predicting rainfall amount, solutions to the problem have not been achieved. This study has examined and related rainfall at Katumani with the El Nino-Southern Oscillation (ENSO) phenomenon. Rainfall variations during different phases of ENSO were established. Some advances in the early prediction of March-May and October -January rains for, both, the warm and cold phases of ENSO have been made. Crop production is closely related to the rainfall and therefore a need for revision of agronomic recommendation to tie them with rainfall variation

Micro-Physical characterisation of Convective & Stratiform Rainfall at Tropics

Science.gov (United States)

Sreekanth, T. S.

Large Micro-Physical characterisation of Convective & Stratiform Rainfall at Tropics begin{center} begin{center} Sreekanth T S*, Suby Symon*, G. Mohan Kumar (1) , and V Sasi Kumar (2) *Centre for Earth Science Studies, Akkulam, Thiruvananthapuram (1) D-330, Swathi Nagar, West Fort, Thiruvananthapuram 695023 (2) 32. NCC Nagar, Peroorkada, Thiruvananthapuram ABSTRACT Micro-physical parameters of rainfall such as rain drop size & fall speed distribution, mass weighted mean diameter, Total no. of rain drops, Normalisation parameters for rain intensity, maximum & minimum drop diameter from different rain intensity ranges, from both stratiform and convective rain events were analysed. Convective -Stratiform classification was done by the method followed by Testud et al (2001) and as an additional information electrical behaviour of clouds from Atmospheric Electric Field Mill was also used. Events which cannot be included in both types are termed as 'mixed precipitation' and identified separately. For the three years 2011, 2012 & 2013, rain events from both convective & stratiform origin are identified from three seasons viz Pre-Monsoon (March-May), Monsoon (June-September) and Post-Monsoon (October-December). Micro-physical characterisation was done for each rain events and analysed. Ground based and radar observations were made and classification of stratiform and convective rainfall was done by the method followed by Testud et al (2001). Radar bright band and non bright band analysis was done for confimation of stratifom and convective rain respectievely. Atmospheric electric field data from electric field mill is also used for confirmation of convection during convective events. Statistical analyses revealed that the standard deviation of rain drop size in higher rain rates are higher than in lower rain rates. Normalised drop size distribution is ploted for selected events from both forms. Inter relations between various precipitation parameters were analysed in three

Rainfall and topo-edaphic influences on woody community phenology in South African savannas

CSIR Research Space (South Africa)

Shackleton, CM

1999-03-01

Full Text Available the limiting periods, i.e. at Stockholm. the start and cessation of the rainy season. This was Fatubarin, A. (1985) Observations on the phenology of not reflected in the data presented here with respect to the woody plants and grasses in a savanna ecosystem... of temperature on evaporative demand (Bate, Furniss & Pendle, 1982).∗ Current address: Environmentek, CSIR, P.O. Box At a gross scale, annual rainfall is a coarse index of395, Pretoria 0001, South Africa. e-mail: csh- ackle@csir.co.za. seasonal plant available...

Using high resolution aridity and drainage position data to better predict rainfall-runoff relationships in complex upland topography

Science.gov (United States)

Metzen, D.; Sheridan, G. J.; Benyon, R. G.; Lane, P. N. J.

2015-12-01

In topographically complex terrain, the interaction of aspect-dependent solar exposure and drainage-position-dependent flow accumulation results in energy and water partitioning that is highly spatially variable. Catchment scale rainfall-runoff relationships are dependent on these smaller scale spatial patterns. However, there remains considerable uncertainty as to how to represent this smaller scale variability within lumped parameter, catchment scale rainfall-runoff models. In this study we aim to measure and represent the key interactions between aridity and drainage position in complex terrain to inform the development of simple catchment-scale hydrologic model parameters. Six measurement plots were setup on opposing slopes in an east-west facing eucalypt forest headwater catchment. The field sites are spanning three drainage positions with two contrasting aridity indices each, while minimizing variations in other factors, e.g. geology and weather patterns. Sapflow, soil water content (SWC) and throughfall were continuously monitored on two convergent hillslopes with similar size (1.3 and 1.6ha) but contrasting aspects (north and south). Soil depth varied from 0.6m at the topslope to >2m at the bottomslope positions. Maximum tree heights ranged from 16.2m to 36.9m on the equator-facing slope and from 30.1m to 45.5m on the pole-facing slope, with height decreasing upslope on both aspects. Two evapotranspiration (ET) patterns emerged in relation to aridity and drainage position. On the equator-facing slope (AI~ 2.1), seasonal understorey and overstorey ET patterns were in sync, whereas on the pole-facing slope (AI~1.5) understorey ET showed larger seasonal fluctuations than overstorey ET. Seasonal ET patterns and competition between soil evaporation and root water uptake lead to distinct differences in profile SWC across the sites, likely caused by depletion from different depths. Topsoil water content on equator-facing slopes was generally lower and responded

Hydrology in a mediterranean mountain environment. The Vallcebre research catchment (north eastern Spain) II. Rainfall-runoff relationships and runoff processes

International Nuclear Information System (INIS)

Latron, J.; Solar, M.; Nord, G.; Llorens, P.; Gallart, F.

2009-01-01

Hydrological response and runoff processes have been studied in the Vallcebre research basins (North Eastern Spain) for almost 20 years. Results obtained allowed to build a more complete perceptual model of the hydrological functioning of Mediterranean mountains basins. On a seasonal and monthly scale, there was no simple relationship between rainfall and runoff depths. Monthly rainfall and runoff values revealed the existence of a threshold in the relationship between rainfall and runoff depths. At the event scale, the storm-flow coefficient had a clear seasonal pattern. The effect of the water table position on how rainfall and runoff volumes relate was observed. Examination of soil water potential and water table dynamics during representative floods helped to identify 3 types of characteristic hydrological behaviour during the year. Under dry conditions, runoff was generated essentially as infiltration excess runoff in low permeable areas, whereas saturation excess runoff dominated during wetting-up and wet conditions. During wetting-up transition, saturated areas resulted from the development of scattered perched water tables, whereas in wet conditions they were linked to the rise of the shallow water table. (Author) 8 refs.

Heterogeneity of Dutch rainfall

NARCIS (Netherlands)

Witter, J.V.

1984-01-01

Rainfall data for the Netherlands have been used in this study to investigate aspects of heterogeneity of rainfall, in particular local differences in rainfall levels, time trends in rainfall, and local differences in rainfall trend. The possible effect of urbanization and industrialization on the

Impacts of Seasonal Patterns of Climate on Recurrent Fluctuations in Tourism Demand: Evidence from Aruba

NARCIS (Netherlands)

Ridderstaat, J.R.; Oderber, M.; Croes, R.; Nijkamp, P.; Martens, P.

2014-01-01

This study estimates the effect of seasonal patterns of pull and push climate elements (rainfall, temperature, wind, and cloud coverage) on recurrent fluctuations in tourism demand from the United States (USA) and Venezuela to Aruba. The seasonal patterns were first isolated from the series using

Vulnerability assessment of Central-East Sardinia (Italy to extreme rainfall events

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A. Bodini

2010-01-01

Full Text Available In Sardinia (Italy, the highest frequency of extreme events is recorded in the Central-East area (3–4 events per year. The presence of high and steep mountains near the sea on the central and south-eastern coast, causes an East-West precipitation gradient in autumn especially, due to hot and moist currents coming from Africa. Soil structure and utilization make this area highly vulnerable to flash flooding and landslides. The specific purpose of this work is to provide a description of the heavy rainfall phenomenon on a statistical basis. The analysis mainly focuses on i the existence of trends in heavy rainfall and ii the characterization of the distribution of extreme events. First, to study possible trends in extreme events a few indices have been analyzed by the linear regression test. The analysis has been carried out at annual and seasonal scales. Then, extreme values analysis has been carried out by fitting a Generalized Pareto Distribution (GPD to the data. As far as trends are concerned, different results are obtained at the two temporal scales: significant trends are obtained at the seasonal scale which are masked at the annual scale. By combining trend analysis and GPD analysis, the vulnerability of the study area to the occurrence of heavy rainfall has been characterized. Therefore, this work might support the improvement of land use planning and the application of suitable prevention systems. Future work will consider the extension of the analysis to all Sardinia and the application of statistical methods taking into account the spatial correlation of extreme events.

Detecting trends in 10-day rainfall amounts at five sites in the state ofSão Paulo, Brazil

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Gabriel Constantino Blain

2014-09-01

Full Text Available The temporal distribution of the rainfall events within a crop growing season plays a crucial role on the crop yield. In this way, the main goal of this study was to evaluate the presence of climate trends in the 10-day rainfall totalsobtained from five weather stations in the State of São Paulo, Brazil (1951-2012.The autocorrelation function, the Run test and the Durbin-Watson test indicateda lack of significant serial correlation in theseseries. The wavelet analysis revealed no conclusive evidence of periodicities in the temporal variability of this variable. According to the Mann-Kendall test, most of the 10-day rainfall amounts obtained from the five weather stations shows no significant trends. However, for the locations of States Campinas, Pindorama and Ribeirão Preto, the significant decreasing trends observed during the 2nd and 3rd ten days of October suggests a possible change in the climatic patterns of these locations, which may be linked to a delay in the return of the rainy season.

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

Science.gov (United States)

Worku, Gebrekidan; Teferi, Ermias; Bantider, Amare; Dile, Yihun T.

2018-02-01

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies.

Estimation of typhoon rainfall in GaoPing River: A Multivariate Maximum Entropy Method

Science.gov (United States)

Pei-Jui, Wu; Hwa-Lung, Yu

2016-04-01

The heavy rainfall from typhoons is the main factor of the natural disaster in Taiwan, which causes the significant loss of human lives and properties. Statistically average 3.5 typhoons invade Taiwan every year, and the serious typhoon, Morakot in 2009, impacted Taiwan in recorded history. Because the duration, path and intensity of typhoon, also affect the temporal and spatial rainfall type in specific region , finding the characteristics of the typhoon rainfall type is advantageous when we try to estimate the quantity of rainfall. This study developed a rainfall prediction model and can be divided three parts. First, using the EEOF(extended empirical orthogonal function) to classify the typhoon events, and decompose the standard rainfall type of all stations of each typhoon event into the EOF and PC(principal component). So we can classify the typhoon events which vary similarly in temporally and spatially as the similar typhoon types. Next, according to the classification above, we construct the PDF(probability density function) in different space and time by means of using the multivariate maximum entropy from the first to forth moment statistically. Therefore, we can get the probability of each stations of each time. Final we use the BME(Bayesian Maximum Entropy method) to construct the typhoon rainfall prediction model , and to estimate the rainfall for the case of GaoPing river which located in south of Taiwan.This study could be useful for typhoon rainfall predictions in future and suitable to government for the typhoon disaster prevention .

A comparison of methods for determining soil water availability in two sites in Panama with similar rainfall but distinct tree communities

Science.gov (United States)

Thomas A. Kursar; Bettina M. J. Engelbrecht; Melvin T. Tyree

2005-01-01

Plant productivity, distribution and diversity in tropical rain forests correlate with water availability. Water availability is determined by rainfall and also by the available water capacity of the soil. However, while rainfall is recognized as important, linkages between plant distribution and differences among soils in available water capacity have not been...

Rainfall Erosivity in Europe

DEFF Research Database (Denmark)

Panagos, Panos; Ballabio, Cristiano; Borrelli, Pasquale

2015-01-01

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 Rfactor 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...

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

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

2017-12-01

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

Estimating seasonal herbage production of a semi-arid grassland ...

African Journals Online (AJOL)

The relation between above-ground phytomass production and three independent variables, namely, seasonal rainfall, evapotranspiration (Et) and veld condition, were investigated using fourteen years' data (1977-1991) from the dry Themeda-Cymbopogon grassveld of the central Orange Free State. The data showed that ...

Seasonal precipitation patterns along pathways of South American low-level jets and aerial rivers

Science.gov (United States)

Poveda, Germán.; Jaramillo, Liliana; Vallejo, Luisa F.

2014-01-01

We study the seasonal dynamics of the eastern Pacific (CHOCO) and Caribbean low-level jets (LLJ), and aerial rivers (AR) acting on tropical and subtropical South America. Using the ERA-Interim reanalysis (1979-2012), we show that the convergence of both LLJs over the eastern Pacific-western Colombia contributes to the explanation of the region's world-record rainfall. Diverse variables involved in the transport and storage of moisture permit the identification of an AR over northern South America involving a midtropospheric easterly jet that connects the Atlantic and Pacific Oceans across the Andes, with stronger activity in April to August. Other major seasonal AR pathways constitute part of a large gyre originating over the tropical North Atlantic, veering to the southeast over the eastern Andes and reaching regions of northern Argentina and southeastern Brazil. We illustrate the distribution of average seasonal precipitation along the LLJs and AR pathways with data from the Tropical Rainfall Measuring Mission (1998-2011), combined with considerations of CAPE, topography, and land cover. In addition, the theory of the biotic pump of atmospheric moisture (BiPAM) is tested at seasonal time scales, and found to hold in 8 out of 12 ARs, and 22 out of 32 forest-covered tracks (64% in distance) along the ARs. Deviations from BiPAM's predictions of rainfall distribution are explained by the effects of topography, orography, and land cover types different from forests. Our results lend a strong observational support to the BiPAM theory at seasonal time scales over South American forested flat lands.

Nitrogen transformations in response to temperature and rainfall manipulation in oak savanna: A global change experiment

Science.gov (United States)

Wellman, R. L.; Boutton, T. W.; Tjoelker, M. G.; Volder, A.; Briske, D. D.

2013-12-01

Increasing concentrations of greenhouse gases are projected to elevate global surface air temperatures by 1.1 to 6.4°C by the end of the century, and potentially magnify the intensity and variability of seasonal precipitation distribution. The mid-latitude grasslands of North America are predicted to experience substantial modification in precipitation regimes, with a shift towards drier summers and wetter spring and fall seasons. Despite these predictions, little is known concerning the effects of these global climate change drivers or their potential interactive effects on nitrogen (N) cycling processes. The purpose of this study is to quantify seasonal variation in rates of N-mineralization, nitrification, and N-losses via leaching in soil subjected to experimental warming and rainfall manipulation. Research was conducted at the Texas A&M Warming and Rainfall Manipulation (WaRM) Site in College Station where eight 9x18m rainout shelters and two unsheltered controls were established in post oak savanna in 2003. Replicate annual rainfall redistribution treatments (n = 4) are applied at the shelter level (long term mean vs. 40% of summer redistributed to fall and spring with same annual total). Warming treatments (ambient vs. 24-hr IR canopy warming of 1-3°C) were applied to planted monocultures of juniper and little bluestem, and a juniper-grass combination. Both juniper and little bluestem are key species within the post oak savanna region. Plots were sampled from the full factorial design during years six and seven of the WaRM experiment. Soil N-mineralization, nitrification, and N-losses via leaching were assessed quarterly for two years using the resin core incubation method. Rainfall, species composition, and time interacted significantly to influence both ammonification and nitrification. Highest rates of ammonification (0.115 mg NH4+ -N/ kg soil/day) occurred in grass monocultures during summer in the control rainfall plots, whereas highest rates of

Modeling Rainfall-Runoff Response to Land Use and Land Cover Change in Rwanda (1990–2016

Directory of Open Access Journals (Sweden)

Fidele Karamage

2017-02-01

Full Text Available Stormwater runoff poses serious environmental problems and public health issues in Rwanda, a tropical country that is increasingly suffering from severe floods, landslides, soil erosion and water pollution. Using the WetSpa Extension model, this study assessed the changes in rainfall runoff depth in Rwanda from 1990 to 2016 in response to precipitation and land use changes. Our results show that Rwanda has experienced a significant conversion of natural forest and grassland to cropland and built-up areas. During the period 1990–2016, 7090.02 km2 (64.5% and 1715.26 km2 (32.1% of forest and grassland covers were lost, respectively, while the cropland and built-up areas increased by 135.3% (8503.75 km2 and 304.3% (355.02 km2, respectively. According to our estimates, the land use change effect resulted in a national mean runoff depth increase of 2.33 mm/year (0.38%. Although precipitation change affected the inter-annual fluctuation of runoff, the long-term trend of runoff was dominated by land use change. The top five districts that experienced the annual runoff depth increase (all >3.8 mm/year are Rubavu, Nyabihu, Ngororero, Gakenke, and Musanze. Their annual runoff depths increased at a rate of >3.8 mm/year during the past 27 years, due to severe deforestation (ranging from 62% to 85% and cropland expansion (ranging from 123% to 293%. These areas require high priority in runoff control using terracing in croplands and rainwater harvesting systems such as dam/reservoirs, percolation tanks, storage tanks, etc. The wet season runoff was three times higher than the dry season runoff in Rwanda; appropriate rainwater management and reservation could provide valuable irrigation water for the dry season or drought years (late rainfall onsets or early rainfall cessations. It was estimated that a reservation of 30.5% (3.99 km3 of the runoff in the wet season could meet the cropland irrigation water gap during the dry season in 2016.