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

USGS Publications Warehouse

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

1994-01-01

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

Intra-seasonal rainfall characteristics and their importance to the seasonal prediction problem

NASA Astrophysics Data System (ADS)

Tennant, Warren J.; Hewitson, Bruce C.

2002-07-01

Daily station rainfall data in South Africa from 1936 to 1999 are combined into homogeneous rainfall regions using Ward's clustering method. Various rainfall characteristics are calculated for the summer season, defined as December to February. These include seasonal rainfall total, region-average number of station rain days exceeding 1 and 20 mm, region-average of periods between rain days at stations >1 and >20 mm, region-average of wet spell length (sequential days of station rainfall >1 and >20 mm), correlation of daily station rainfall within a region and correlation of seasonal station rainfall anomalies within a region.Rank-ordered rainfall characteristic data generally form an s-shaped curve, and significance testing of discontinuities in these curves suggests that normal rainfall conditions in South Africa consist of a combined middle three quintiles separated from the outer quintiles, rather than the traditional middle tercile.The relationships between the various rainfall characteristics show that seasons with a high total rainfall generally have a higher number of heavy rain days (>20 mm) and not necessarily an increase in light rain days. The length of the period between rain days has a low correlation to season totals, demonstrating that seasons with a high total rainfall may still contain prolonged dry periods. These additional rainfall characteristics are important to end-users, and the analysis undertaken here offers a valuable starting point for seeking physical relationships between rainfall characteristics and the general circulation. Preliminary studies show that the vertical mean wind is related to rainfall characteristics in South Africa. Given that general circulation models capture this part of the circulation adequately, seasonal forecasts of rainfall characteristics become plausible.

Characteristics of Atmospheric Pollutants Distribution and Removal Effect of Rainfall on Atmospheric Pollutants in Mining Cities

NASA Astrophysics Data System (ADS)

Wen-feng, Tang; You-biao, Hu

2018-05-01

This paper studies the characteristics of atmospheric pollutant (SO2, NO2, PM2.5 and PM10) and the effects of rainfall on the removal of atmospheric pollutants. The results show atmospheric pollutants concentration vary in different seasons and functional area: atmospheric pollutants concentration in summer and autumn is lower than that in winter and spring; the concentration of SO2 and NO2 in coal-chemical industry areas and light industrial areas is higher, the concentration difference of PM2.5 and PM10 in different functional areas is very small, the removal efficiency of rainfall on atmospheric pollutant is gradually improved with the increasing of daily rainfall, rainfall intensity and rainfall duration, the ability of rainfall to remove pollutants tends to be stable after daily rainfall and rainfall intensity exceeds 30mm and 20mm/h respectively, the effect of rainfall on the removal of PM2.5 was slightly worse than the effect of rainfall on other atmospheric pollutants, the rainfall duration should be 60min, 60min and 80min respectively when the effect of rainfall on NO2, PM10 and SO2 tends to be stable.

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

PubMed

Li, Yi; Shao, Ming-An

2008-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

Gouda, K. C.; Goswami, P.

2016-10-01

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

Can spatial patterns along climatic gradients predict ecosystem responses to climate change? Experimenting with reaction-diffusion simulations.

PubMed

Roitberg, Elena; Shoshany, Maxim

2017-01-01

Following a predicted decline in water resources in the Mediterranean Basin, we used reaction-diffusion equations to gain a better understanding of expected changes in properties of vegetation patterns that evolve along the rainfall transition between semi-arid and arid rainfall regions. Two types of scenarios were investigated: the first, a discrete scenario, where the potential consequences of climate change are represented by patterns evolving at discrete rainfall levels along a rainfall gradient. This scenario concerns space-for-time substitutions characteristic of the rainfall gradient hypothesis. The second, a continuous scenario, represents explicitly the effect of rainfall decline on patterns which evolved at different rainfall levels along the rainfall gradient prior to the climate change. The eccentricity of patterns that emerge through these two scenarios was found to decrease with decreasing rainfall, while their solidity increased. Due to their inverse modes of change, their ratio was found to be a highly sensitive indicator for pattern response to rainfall decline. An eccentricity ratio versus rainfall (ER:R) line was generalized from the results of the discrete experiment, where ERs above this line represent developed (recovered) patterns and ERs below this line represent degraded patterns. For the rainfall range of 1.2 to 0.8 mm/day, the continuous rainfall decline experiment with ERs that lie above the ER:R line, yielded patterns less affected by rainfall decline than would be expected according to the discrete representation of ecosystems' response. Thus, for this range, space-for-time substitution represents an overestimation of the consequences of the expected rainfall decline. For rainfall levels below 0.8 mm/day, eccentricity ratios from the discrete and continuous experiments practically converge to the same trend of pattern change along the ER:R line. Thus, the rainfall gradient hypothesis may be valid for regions characterized by this important rainfall range, which typically include desert fringe ecosystems.

Temporal rainfall estimation using input data reduction and model inversion

NASA Astrophysics Data System (ADS)

Wright, A. J.; Vrugt, J. A.; Walker, J. P.; Pauwels, V. R. N.

2016-12-01

Floods are devastating natural hazards. To provide accurate, precise and timely flood forecasts there is a need to understand the uncertainties associated with temporal rainfall and model parameters. The estimation of temporal rainfall and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of rainfall input to be considered when estimating model parameters and provides the ability to estimate rainfall from poorly gauged catchments. Current methods to estimate temporal rainfall distributions from streamflow are unable to adequately explain and invert complex non-linear hydrologic systems. This study uses the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia. The reduction of rainfall to DWT coefficients allows the input rainfall time series to be simultaneously estimated along with model parameters. The estimation process is conducted using multi-chain Markov chain Monte Carlo simulation with the DREAMZS algorithm. The use of a likelihood function that considers both rainfall and streamflow error allows for model parameter and temporal rainfall distributions to be estimated. Estimation of the wavelet approximation coefficients of lower order decomposition structures was able to estimate the most realistic temporal rainfall distributions. These rainfall estimates were all able to simulate streamflow that was superior to the results of a traditional calibration approach. It is shown that the choice of wavelet has a considerable impact on the robustness of the inversion. The results demonstrate that streamflow data contains sufficient information to estimate temporal rainfall and model parameter distributions. The extent and variance of rainfall time series that are able to simulate streamflow that is superior to that simulated by a traditional calibration approach is a demonstration of equifinality. The use of a likelihood function that considers both rainfall and streamflow error combined with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

Regional extreme rainfalls observed globally with 17 years of the Tropical Precipitation Measurement Mission

NASA Astrophysics Data System (ADS)

Takayabu, Yukari; Hamada, Atsushi; Mori, Yuki; Murayama, Yuki; Liu, Chuntao; Zipser, Edward

2015-04-01

While extreme rainfall has a huge impact upon human society, the characteristics of the extreme precipitation vary from region to region. Seventeen years of three dimensional precipitation measurements from the space-borne precipitation radar equipped with the Tropical Precipitation Measurement Mission satellite enabled us to describe the characteristics of regional extreme precipitation globally. Extreme rainfall statistics are based on rainfall events defined as a set of contiguous PR rainy pixels. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile in each 2.5degree x2.5degree horizontal resolution grid. First, regional extreme rainfall is characterized in terms of its intensity and event size. Regions of ''intense and extensive'' extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of ''intense but less extensive'' extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of ''extensive but less intense'' extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones. Secondly, regional extremes in terms of surface rainfall intensity and those in terms of convection height are compared. Conventionally, extremely tall convection is considered to contribute the largest to the intense rainfall. Comparing probability density functions (PDFs) of 99th percentiles in terms of the near surface rainfall intensity in each regional grid and those in terms of the 40dBZ echo top heights, it is found that heaviest precipitation in the region is not associated with tallest systems, but rather with systems with moderate heights. Interestingly, this separation of extremely heavy precipitation from extremely tall convection is found to be quite universal, irrespective of regions. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Thus it is demonstrated that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. Third, the size effect of rainfall events on the precipitation intensity is investigated. Comparisons of normalized PDFs of foot-print size rainfall intensity for different sizes of rainfall events show that footprint-scale extreme rainfall becomes stronger as the rainfall events get larger. At the same time, stratiform ratio in area as well as in rainfall amount increases with the size, confirming larger sized features are more organized systems. After all, it is statistically shown that organization of precipitation not only brings about an increase in extreme volumetric rainfall but also an increase in probability of the satellite footprint scale extreme rainfall.

Reduced precipitation over large water bodies in the Brazilian Amazon shown from TRMM data

NASA Astrophysics Data System (ADS)

Paiva, Rodrigo Cauduro Dias; Buarque, Diogo Costa; Clarke, Robin T.; Collischonn, Walter; Allasia, Daniel Gustavo

2011-02-01

Tropical Rainfall Measurement Mission (TRMM) data show lower rainfall over large water bodies in the Brazilian Amazon. Mean annual rainfall (P), number of wet days (rainfall > 2 mm) (W) and annual rainfall accumulated over 3-hour time intervals (P3hr) were computed from TRMM 3B42 data for 1998-2009. Reduced rainfall was marked over the Rio Solimões/Amazon, along most Amazon tributaries and over the Balbina reservoir. In a smaller test area, a heuristic argument showed that P and W were reduced by 5% and 6.5% respectively. Allowing for TRMM 3B42 spatial resolution, the reduction may be locally greater. Analyses of diurnal rainfall patterns showed that rainfall is lowest over large rivers during the afternoon, when most rainfall is convective, but at night and early morning the opposite occurs, with increased rainfall over rivers, although this pattern is less marked. Rainfall patterns reported from studies of smaller Amazonian regions therefore exist more widely.

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

USDA-ARS?s Scientific Manuscript database

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

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

NASA Astrophysics Data System (ADS)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

Estimation of Rainfall Erosivity via 1-Minute to Hourly Rainfall Data from Taipei, Taiwan

NASA Astrophysics Data System (ADS)

Huang, Ting-Yin; Yang, Ssu-Yao; Jan, Chyan-Deng

2017-04-01

Soil erosion is a natural process on hillslopes that threats people's life and properties, having a considerable environmental and economic implications for soil degradation, agricultural activity and water quality. The rainfall erosivity factor (R-factor) in the Universal Soil Loss Equation (USLE), composed of total kinetic energy (E) and the maximum 30-min rainfall intensity (I30), is widely used as an indicator to measure the potential risks of soil loss caused by rainfall at a regional scale. This R factor can represent the detachment and entrainment involved in climate conditions on hillslopes, but lack of 30-min rainfall intensity data usually lead to apply this factor more difficult in many regions. In recent years, fixed-interval, hourly rainfall data is readily available and widely used due to the development of automatic weather stations. Here we assess the estimations of R, E, and I30 based on 1-, 5-, 10-, 15-, 30-, 60-minute rainfall data, and hourly rainfall data obtained from Taipei weather station during 2004 to 2010. Results show that there is a strong correlation among R-factors estimated from different interval rainfall data. Moreover, the shorter time-interval rainfall data (e.g., 1-min) yields larger value of R-factor. The conversion factors of rainfall erosivity (ratio of values estimated from the resolution lower than 30-min rainfall data to those estimated from 60-min and hourly rainfall data, respectively) range from 1.85 to 1.40 (resp. from 1.89 to 1.02) for 60-min (resp. hourly) rainfall data as the time resolution increasing from 30-min to 1-min. This paper provides useful information on estimating R-factor when hourly rainfall data is only available.

Rainfall simulators in hydrological and geomorphological sciences: benefits, applications and future research directions

NASA Astrophysics Data System (ADS)

Iserloh, Thomas; Cerdà, Artemi; Fister, Wolfgang; Seitz, Steffen; Keesstra, Saskia; Green, Daniel; Gabriels, Donald

2017-04-01

Rainfall simulators are used extensively within the hydrological and geomorphological sciences and provide a useful investigative tool to understand many processes, such as: (i) plot-scale runoff, infiltration and erosion; (ii) irrigation and crop management, and; (iii) investigations into flooding within a laboratory setting. Although natural rainfall is desirable as it represents actual conditions in a given geographic location, data acquisition relying on natural rainfall is often hindered by its unpredictable nature. Furthermore, rainfall characteristics such as the intensity, duration, drop size distribution and kinetic energy cannot be spatially or temporally regulated or repeated between experimentation. Rainfall simulators provide a suitable method to overcome the issues associated with depending on potentially erratic and unpredictable natural rainfall as they allow: (i) multiple measurements to be taken quickly without waiting for suitable natural rainfall conditions; (ii) the simulation of spatially and/or temporally controlled rainfall patterns over a given plot area, and; (iii) the creation of a closed environment, allowing simplified measurement of input and output conditions. There is no standardisation of rainfall simulation and as such, rainfall simulators differ in their design, rainfall characteristics and research application. Although this impedes drawing meaningful comparisons between studies, this allows researchers to create a bespoke and tailored rainfall simulator for the specific research application. This paper summarises the rainfall simulators used in European research institutions (Universities of Trier, Valencia, Basel, Tuebingen, Wageningen, Loughborough and Ghent) to investigate a number of hydrological and geomorphological issues and includes details on the design specifications (such as the extent and characteristics of simulated rainfall), as well as a discussion of the purpose and application of the rainfall simulator.

TRMM rainfall estimative coupled with Bell (1969) methodology for extreme rainfall characterization

NASA Astrophysics Data System (ADS)

Schiavo Bernardi, E.; Allasia, D.; Basso, R.; Freitas Ferreira, P.; Tassi, R.

2015-06-01

The lack of rainfall data in Brazil, and, in particular, in Rio Grande do Sul State (RS), hinders the understanding of the spatial and temporal distribution of rainfall, especially in the case of the more complex extreme events. In this context, rainfall's estimation from remote sensors is seen as alternative to the scarcity of rainfall gauges. However, as they are indirect measures, such estimates needs validation. This paper aims to verify the applicability of the Tropical Rainfall Measuring Mission (TRMM) satellite information for extreme rainfall determination in RS. The analysis was accomplished at different temporal scales that ranged from 5 min to daily rainfall while spatial distribution of rainfall was investigated by means of regionalization. An initial test verified TRMM rainfall estimative against measured rainfall at gauges for 1998-2013 period considering different durations and return periods (RP). Results indicated that, for the RP of 2, 5, 10 and 15 years, TRMM overestimated on average 24.7% daily rainfall. As TRMM minimum time-steps is 3 h, in order to verify shorter duration rainfall, the TRMM data were adapted to fit Bell's (1969) generalized IDF formula (based on the existence of similarity between the mechanisms of extreme rainfall events as they are associated to convective cells). Bell`s equation error against measured precipitation was around 5-10%, which varied based on location, RP and duration while the coupled BELL+TRMM error was around 10-35%. However, errors were regionally distributed, allowing a correction to be implemented that reduced by half these values. These findings in turn permitted the use of TRMM+Bell estimates to improve the understanding of spatiotemporal distribution of extreme hydrological rainfall events.

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

PubMed

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

2014-09-01

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

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

PubMed Central

Nandargi, S.; Mulye, S. S.

2012-01-01

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

Censored rainfall modelling for estimation of fine-scale extremes

NASA Astrophysics Data System (ADS)

Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

2018-01-01

Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

Weak linkage between the heaviest rainfall and tallest storms.

PubMed

Hamada, Atsushi; Takayabu, Yukari N; Liu, Chuntao; Zipser, Edward J

2015-02-24

Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Warm season heavy rainfall events over the Huaihe River Valley and their linkage with wintertime thermal condition of the tropical oceans

NASA Astrophysics Data System (ADS)

Li, Laifang; Li, Wenhong; Tang, Qiuhong; Zhang, Pengfei; Liu, Yimin

2016-01-01

Warm season heavy rainfall events over the Huaihe River Valley (HRV) of China are amongst the top causes of agriculture and economic loss in this region. Thus, there is a pressing need for accurate seasonal prediction of HRV heavy rainfall events. This study improves the seasonal prediction of HRV heavy rainfall by implementing a novel rainfall framework, which overcomes the limitation of traditional probability models and advances the statistical inference on HRV heavy rainfall events. The framework is built on a three-cluster Normal mixture model, whose distribution parameters are sampled using Bayesian inference and Markov Chain Monte Carlo algorithm. The three rainfall clusters reflect probability behaviors of light, moderate, and heavy rainfall, respectively. Our analysis indicates that heavy rainfall events make the largest contribution to the total amount of seasonal precipitation. Furthermore, the interannual variation of summer precipitation is attributable to the variation of heavy rainfall frequency over the HRV. The heavy rainfall frequency, in turn, is influenced by sea surface temperature anomalies (SSTAs) over the north Indian Ocean, equatorial western Pacific, and the tropical Atlantic. The tropical SSTAs modulate the HRV heavy rainfall events by influencing atmospheric circulation favorable for the onset and maintenance of heavy rainfall events. Occurring 5 months prior to the summer season, these tropical SSTAs provide potential sources of prediction skill for heavy rainfall events over the HRV. Using these preceding SSTA signals, we show that the support vector machine algorithm can predict HRV heavy rainfall satisfactorily. The improved prediction skill has important implication for the nation's disaster early warning system.

Evaluating rainfall errors in global climate models through cloud regimes

NASA Astrophysics Data System (ADS)

Tan, Jackson; Oreopoulos, Lazaros; Jakob, Christian; Jin, Daeho

2017-07-01

Global climate models suffer from a persistent shortcoming in their simulation of rainfall by producing too much drizzle and too little intense rain. This erroneous distribution of rainfall is a result of deficiencies in the representation of underlying processes of rainfall formation. In the real world, clouds are precursors to rainfall and the distribution of clouds is intimately linked to the rainfall over the area. This study examines the model representation of tropical rainfall using the cloud regime concept. In observations, these cloud regimes are derived from cluster analysis of joint-histograms of cloud properties retrieved from passive satellite measurements. With the implementation of satellite simulators, comparable cloud regimes can be defined in models. This enables us to contrast the rainfall distributions of cloud regimes in 11 CMIP5 models to observations and decompose the rainfall errors by cloud regimes. Many models underestimate the rainfall from the organized convective cloud regime, which in observation provides half of the total rain in the tropics. Furthermore, these rainfall errors are relatively independent of the model's accuracy in representing this cloud regime. Error decomposition reveals that the biases are compensated in some models by a more frequent occurrence of the cloud regime and most models exhibit substantial cancellation of rainfall errors from different regimes and regions. Therefore, underlying relatively accurate total rainfall in models are significant cancellation of rainfall errors from different cloud types and regions. The fact that a good representation of clouds does not lead to appreciable improvement in rainfall suggests a certain disconnect in the cloud-precipitation processes of global climate models.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Estimating rainfall time series and model parameter distributions using model data reduction and inversion techniques

NASA Astrophysics Data System (ADS)

Wright, Ashley J.; Walker, Jeffrey P.; Pauwels, Valentijn R. N.

2017-08-01

Floods are devastating natural hazards. To provide accurate, precise, and timely flood forecasts, there is a need to understand the uncertainties associated within an entire rainfall time series, even when rainfall was not observed. The estimation of an entire rainfall time series and model parameter distributions from streamflow observations in complex dynamic catchments adds skill to current areal rainfall estimation methods, allows for the uncertainty of entire rainfall input time series to be considered when estimating model parameters, and provides the ability to improve rainfall estimates from poorly gauged catchments. Current methods to estimate entire rainfall time series from streamflow records are unable to adequately invert complex nonlinear hydrologic systems. This study aims to explore the use of wavelets in the estimation of rainfall time series from streamflow records. Using the Discrete Wavelet Transform (DWT) to reduce rainfall dimensionality for the catchment of Warwick, Queensland, Australia, it is shown that model parameter distributions and an entire rainfall time series can be estimated. Including rainfall in the estimation process improves streamflow simulations by a factor of up to 1.78. This is achieved while estimating an entire rainfall time series, inclusive of days when none was observed. It is shown that the choice of wavelet can have a considerable impact on the robustness of the inversion. Combining the use of a likelihood function that considers rainfall and streamflow errors with the use of the DWT as a model data reduction technique allows the joint inference of hydrologic model parameters along with rainfall.

High temporal resolution of extreme rainfall rate variability and the acoustic classification of rainfall

NASA Astrophysics Data System (ADS)

Nystuen, Jeffrey A.; Amitai, Eyal

2003-04-01

The underwater sound generated by raindrop splashes on a water surface is loud and unique allowing detection, classification and quantification of rainfall. One of the advantages of the acoustic measurement is that the listening area, an effective catchment area, is proportional to the depth of the hydrophone and can be orders of magnitude greater than other in situ rain gauges. This feature allows high temporal resolution of the rainfall measurement. A series of rain events with extremely high rainfall rates, over 100 mm/hr, is examined acoustically. Rapid onset and cessation of rainfall intensity are detected within the convective cells of these storms with maximum 5-s resolution values exceeding 1000 mm/hr. The probability distribution functions (pdf) for rainfall rate occurrence and water volume using the longer temporal resolutions typical of other instruments do not include these extreme values. The variance of sound intensity within different acoustic frequency bands can be used as an aid to classify rainfall type. Objective acoustic classification algorithms are proposed. Within each rainfall classification the relationship between sound intensity and rainfall rate is nearly linear. The reflectivity factor, Z, also has a linear relationship with rainfall rate, R, for each rainfall classification.

Predicting rainfall erosivity by momentum and kinetic energy in Mediterranean environment

NASA Astrophysics Data System (ADS)

Carollo, Francesco G.; Ferro, Vito; Serio, Maria A.

2018-05-01

Rainfall erosivity is an index that describes the power of rainfall to cause soil erosion and it is used around the world for assessing and predicting soil loss on agricultural lands. Erosivity can be represented in terms of both rainfall momentum and kinetic energy, both calculated per unit time and area. Contrasting results on the representativeness of these two variables are available: some authors stated that momentum and kinetic energy are practically interchangeable in soil loss estimation while other found that kinetic energy is the most suitable expression of rainfall erosivity. The direct and continuous measurements of momentum and kinetic energy by a disdrometer allow also to establish a relationship with rainfall intensity at the study site. At first in this paper a comparison between the momentum-rainfall intensity relationships measured at Palermo and El Teularet by an optical disdrometer is presented. For a fixed rainfall intensity the measurements showed that the rainfall momentum values measured at the two experimental sites are not coincident. However both datasets presented a threshold value of rainfall intensity over which the rainfall momentum assumes a quasi-constant value. Then the reliability of a theoretically deduced relationship, linking momentum, rainfall intensity and median volume diameter, is positively verified using measured raindrop size distributions. An analysis to assess which variable, momentum or kinetic energy per unit area and time, is the best predictor of erosivity in Italy and Spain was also carried out. This investigation highlighted that the rainfall kinetic energy per unit area and time can be substituted by rainfall momentum as index for estimating the rainfall erosivity, and this result does not depend on the site where precipitation occurs. Finally, rainfall intensity measurements and soil loss data collected from the bare plots equipped at Sparacia experimental area were used to verify the reliability of some rainfall erosivity indices and their ability to distinguish the type of involved soil erosion processes.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Constraining continuous rainfall simulations for derived design flood estimation

NASA Astrophysics Data System (ADS)

Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.

2016-11-01

Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.

Rainfall erosivity: An historical review

USDA-ARS?s Scientific Manuscript database

Rainfall erosivity is the capability of rainfall to cause soil loss from hillslopes by water. Modern definitions of rainfall erosivity began with the development of the Universal Soil Loss Equation (USLE), where rainfall characteristics were statistically related to soil loss from thousands of plot...

A new physically-based model considered antecedent rainfall for shallow landslide

NASA Astrophysics Data System (ADS)

Luo, Yu; He, Siming

2017-04-01

Rainfall is the most significant factor to cause landslide especially shallow landslide. In previous studies, rainfall intensity and duration are take part in the physically based model to determining the occurrence of the rainfall-induced landslides, but seldom considered the antecedent rainfall. In this study, antecedent rainfall is took into account to derive a new physically based model for shallow landslides prone area predicting at the basin scale. Based on the Rosso's equation of seepage flow considering the antecedent rainfall to construct the hillslope hydrology model. And then, the infinite slope stability theory is using to construct the slope stability model. At last, the model is apply in the Baisha river basin of Chengdu, Sichuan, China, and the results are compared with the one's from unconsidered antecedent rainfall. The results show that the model is simple, but has the capability of consider antecedent rainfall in the triggering mechanism of shallow landslide. Meanwhile, antecedent rainfall can make an obvious effect on shallow landslides, so in shallow landslide hazard assessment, the influence of the antecedent rainfall can't be ignored.

Investigation of summer monsoon rainfall variability in Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Mian Sabir; Lee, Seungho

2016-08-01

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

Probabilistic clustering of rainfall condition for landslide triggering

NASA Astrophysics Data System (ADS)

Rossi, Mauro; Luciani, Silvia; Cesare Mondini, Alessandro; Kirschbaum, Dalia; Valigi, Daniela; Guzzetti, Fausto

2013-04-01

Landslides are widespread natural and man made phenomena. They are triggered by earthquakes, rapid snow melting, human activities, but mostly by typhoons and intense or prolonged rainfall precipitations. In Italy mostly they are triggered by intense precipitation. The prediction of landslide triggered by rainfall precipitations over large areas is commonly based on the exploitation of empirical models. Empirical landslide rainfall thresholds are used to identify rainfall conditions for the possible landslide initiation. It's common practice to define rainfall thresholds by assuming a power law lower boundary in the rainfall intensity-duration or cumulative rainfall-duration space above which landslide can occur. The boundary is defined considering rainfall conditions associated to landslide phenomena using heuristic approaches, and doesn't consider rainfall events not causing landslides. Here we present a new fully automatic method to identify the probability of landslide occurrence associated to rainfall conditions characterized by measures of intensity or cumulative rainfall and rainfall duration. The method splits the rainfall events of the past in two groups: a group of events causing landslides and its complementary, then estimate their probabilistic distributions. Next, the probabilistic membership of the new event to one of the two clusters is estimated. The method doesn't assume a priori any threshold model, but simple exploits the real empirical distribution of rainfall events. The approach was applied in the Umbria region, Central Italy, where a catalogue of landslide timing, were obtained through the search of chronicles, blogs and other source of information in the period 2002-2012. The approach was tested using rain gauge measures and satellite rainfall estimates (NASA TRMM-v6), allowing in both cases the identification of the rainfall condition triggering landslides in the region. Compared to the other existing threshold definition methods, the prosed one (i) largely reduces the subjectivity in the choice of the threshold model and in how it is calculated, and (ii) it can be easier set-up in other study areas. The proposed approach can be conveniently integrated in existing early-warning system to improve the accuracy of the estimation of the real landslide occurrence probability associated to rainfall events and its uncertainty.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

SUB-PIXEL RAINFALL VARIABILITY AND THE IMPLICATIONS FOR UNCERTAINTIES IN RADAR RAINFALL ESTIMATES

EPA Science Inventory

Radar estimates of rainfall are subject to significant measurement uncertainty. Typically, uncertainties are measured by the discrepancies between real rainfall estimates based on radar reflectivity and point rainfall records of rain gauges. This study investigates how the disc...

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Ten-Year Climatology of Summertime Diurnal Rainfall Rate Over the Conterminous U.S.

NASA Technical Reports Server (NTRS)

Matsui, Toshihisa; Mocko, David; Lee, Myong-In; Tao, Wei-Kuo; Suarez, Max J.; Pielke, Roger A., Sr.

2010-01-01

Diurnal cycles of summertime rainfall rates are examined over the conterminous United States, using radar-gauge assimilated hourly rainfall data. As in earlier studies, rainfall diurnal composites show a well-defined region of rainfall propagation over the Great Plains and an afternoon maximum area over the south and eastern portion of the United States. Zonal phase speeds of rainfall in three different small domains are estimated, and rainfall propagation speeds are compared with background zonal wind speeds. Unique rainfall propagation speeds in three different regions can be explained by the evolution of latent-heat theory linked to the convective available potential energy, than by gust-front induced or gravity wave propagation mechanisms.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Rainfall thresholds for possible landslide occurrence in Italy

NASA Astrophysics Data System (ADS)

Peruccacci, Silvia; Brunetti, Maria Teresa; Gariano, Stefano Luigi; Melillo, Massimo; Rossi, Mauro; Guzzetti, Fausto

2017-08-01

The large physiographic variability and the abundance of landslide and rainfall data make Italy an ideal site to investigate variations in the rainfall conditions that can result in rainfall-induced landslides. We used landslide information obtained from multiple sources and rainfall data captured by 2228 rain gauges to build a catalogue of 2309 rainfall events with - mostly shallow - landslides in Italy between January 1996 and February 2014. For each rainfall event with landslides, we reconstructed the rainfall history that presumably caused the slope failure, and we determined the corresponding rainfall duration D (in hours) and cumulated event rainfall E (in mm). Adopting a power law threshold model, we determined cumulated event rainfall-rainfall duration (ED) thresholds, at 5% exceedance probability, and their uncertainty. We defined a new national threshold for Italy, and 26 regional thresholds for environmental subdivisions based on topography, lithology, land-use, land cover, climate, and meteorology, and we used the thresholds to study the variations of the rainfall conditions that can result in landslides in different environments, in Italy. We found that the national and the environmental thresholds cover a small part of the possible DE domain. The finding supports the use of empirical rainfall thresholds for landslide forecasting in Italy, but poses an empirical limitation to the possibility of defining thresholds for small geographical areas. We observed differences between some of the thresholds. With increasing mean annual precipitation (MAP), the thresholds become higher and steeper, indicating that more rainfall is needed to trigger landslides where the MAP is high than where it is low. This suggests that the landscape adjusts to the regional meteorological conditions. We also observed that the thresholds are higher for stronger rocks, and that forested areas require more rainfall than agricultural areas to initiate landslides. Finally, we observed that a 20% exceedance probability national threshold was capable of predicting all the rainfall-induced landslides with casualties between 1996 and 2014, and we suggest that this threshold can be used to forecast fatal rainfall-induced landslides in Italy. We expect the method proposed in this work to define and compare the thresholds to have an impact on the definition of new rainfall thresholds for possible landslide occurrence in Italy, and elsewhere.

Analysis of rainfall distribution in Kelantan river basin, Malaysia

NASA Astrophysics Data System (ADS)

Che Ros, Faizah; Tosaka, Hiroyuki

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

Narulita, Ida; Ningrum, Widya

2018-02-01

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

Rainfall pattern variability as climate change impact in The Wallacea Region

NASA Astrophysics Data System (ADS)

Pujiastuti, I.; Nurjani, E.

2018-04-01

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

Influence of rainfall microstructure on rainfall interception

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Gross rainfall amount and maximum rainfall intensity in 60-minute influence on interception loss of shrubs: a 10-year observation in the Tengger Desert.

PubMed

Zhang, Zhi-Shan; Zhao, Yang; Li, Xin-Rong; Huang, Lei; Tan, Hui-Juan

2016-05-17

In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics.

Heavy rainfall events and diarrhea incidence: the role of social and environmental factors.

PubMed

Carlton, Elizabeth J; Eisenberg, Joseph N S; Goldstick, Jason; Cevallos, William; Trostle, James; Levy, Karen

2014-02-01

The impact of heavy rainfall events on waterborne diarrheal diseases is uncertain. We conducted weekly, active surveillance for diarrhea in 19 villages in Ecuador from February 2004 to April 2007 in order to evaluate whether biophysical and social factors modify vulnerability to heavy rainfall events. A heavy rainfall event was defined as 24-hour rainfall exceeding the 90th percentile value (56 mm) in a given 7-day period within the study period. Mixed-effects Poisson regression was used to test the hypothesis that rainfall in the prior 8 weeks, water and sanitation conditions, and social cohesion modified the relationship between heavy rainfall events and diarrhea incidence. Heavy rainfall events were associated with increased diarrhea incidence following dry periods (incidence rate ratio = 1.39, 95% confidence interval: 1.03, 1.87) and decreased diarrhea incidence following wet periods (incidence rate ratio = 0.74, 95% confidence interval: 0.59, 0.92). Drinking water treatment reduced the deleterious impacts of heavy rainfall events following dry periods. Sanitation, hygiene, and social cohesion did not modify the relationship between heavy rainfall events and diarrhea. Heavy rainfall events appear to affect diarrhea incidence through contamination of drinking water, and they present the greatest health risks following periods of low rainfall. Interventions designed to increase drinking water treatment may reduce climate vulnerability.

Extreme rainfall-induced landslide changes based on landslide susceptibility in China, 1998-2015

NASA Astrophysics Data System (ADS)

Li, Weiyue; Liu, Chun; Hong, Yang

2017-04-01

Nowadays, landslide has been one of the most frequent and seriously widespread natural hazards all over the world. Rainfall, especially heavy rainfall is a trigger to cause the landslide occurrence, by increasing soil pore water pressures. In China, rainfall-induced landslides have risen up over to 90% of the total number. Rainfall events sometimes generate a trend of extremelization named rainfall extremes that induce the slope failure suddenly and severely. This study shows a method to simulate the rainfall-induced landslide spatio-temporal distribution on the basis of the landslide susceptibility index. First, the study on landslide susceptibility in China is introduced. We set the values of the index to the range between 0 and 1. Second, we collected TRMM 3B42 precipitation products spanning the years 1998-2015 and extracted the daily rainfall events greater than 50mm/day as extreme rainfall. Most of the rainfall duration time that may trigger a landslide has resulted between 3 hours and 45 hours. The combination of these two aspects can be exploited to simulate extreme rainfall-induced landslide distribution and illustrate the changes in 17 years. This study shows a useful tool to be part of rainfall-induced landslide simulation methodology for landslide early warning.

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

PubMed

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

2013-01-01

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

New Indices to Evaluate the Effects of Rainfall Pattern on Runoff and Soil Loss under Different Vegetation in the Loess Plateau, China.

NASA Astrophysics Data System (ADS)

Liu, J.; Gao, G.; Jiao, L.; Fu, B.

2016-12-01

The rainfall amount, density and duration were commonly used to evaluate the influences of rainfall on runoff and soil loss, which could completely express the information of rainfall, especially rainfall pattern. In this study, the peak zone of rainfall intensity (PZRI) and intra-event intermittency of rainfall (IERI) were developed to detect the effects of rainfall pattern on runoff and soil loss under different land cover types in the Loess Plateau of China. The runoff and soil loss of three vegetation types (Prunus armeniaca, Artemisia sacrorum and Andropogon yunnanensis) and bare land were measured from 2012 to 2015. The PZRI was significantly correlated with average rainfall intensity (I) and maximum rainfall intensity in 30 minutes (I30). The runoff coefficient (RC) and soil loss were not significantly correlated with I, but they were significantly affected by I30 and PZRI (p<0.05). The greater value of IERI indicated more proportion of PZRI in rainfall duration, and there was positive correlation between IERI and RC. It was showed that the RC was most correlated with PZRI, whereas the correlation between soil loss and I30 was most significant under all cover types. This indicated that the changes of rainfall pattern had more effects on runoff than soil loss. In addition, the position of PZRI in the rainfall profile had an important role on runoff and soil loss. RC and soil loss under bare land was most sensitive to the occurrence period of rainfall peak, followed by Prunus armeniaca, Artemisia sacrorum and Andropogon yunnanensis.

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

PubMed Central

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Spatial variability of extreme rainfall at radar subpixel scale

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

PubMed Central

Tao, Wanghai; Wu, Junhu; Wang, Quanjiu

2017-01-01

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

A comparison of methods to estimate future sub-daily design rainfall

NASA Astrophysics Data System (ADS)

Li, J.; Johnson, F.; Evans, J.; Sharma, A.

2017-12-01

Warmer temperatures are expected to increase extreme short-duration rainfall due to the increased moisture-holding capacity of the atmosphere. While attention has been paid to the impacts of climate change on future design rainfalls at daily or longer time scales, the potential changes in short duration design rainfalls have been often overlooked due to the limited availability of sub-daily projections and observations. This study uses a high-resolution regional climate model (RCM) to predict the changes in sub-daily design rainfalls for the Greater Sydney region in Australia. Sixteen methods for predicting changes to sub-daily future extremes are assessed based on different options for bias correction, disaggregation and frequency analysis. A Monte Carlo cross-validation procedure is employed to evaluate the skill of each method in estimating the design rainfall for the current climate. It is found that bias correction significantly improves the accuracy of the design rainfall estimated for the current climate. For 1 h events, bias correcting the hourly annual maximum rainfall simulated by the RCM produces design rainfall closest to observations, whereas for multi-hour events, disaggregating the daily rainfall total is recommended. This suggests that the RCM fails to simulate the observed multi-duration rainfall persistence, which is a common issue for most climate models. Despite the significant differences in the estimated design rainfalls between different methods, all methods lead to an increase in design rainfalls across the majority of the study region.

Predicting water table response to rainfall events, central Florida.

PubMed

van Gaalen, J F; Kruse, S; Lafrenz, W B; Burroughs, S M

2013-01-01

A rise in water table in response to a rainfall event is a complex function of permeability, specific yield, antecedent soil-water conditions, water table level, evapotranspiration, vegetation, lateral groundwater flow, and rainfall volume and intensity. Predictions of water table response, however, commonly assume a linear relationship between response and rainfall based on cumulative analysis of water level and rainfall logs. By identifying individual rainfall events and responses, we examine how the response/rainfall ratio varies as a function of antecedent water table level (stage) and rainfall event size. For wells in wetlands and uplands in central Florida, incorporating stage and event size improves forecasting of water table rise by more than 30%, based on 10 years of data. At the 11 sites studied, the water table is generally least responsive to rainfall at smallest and largest rainfall event sizes and at lower stages. At most sites the minimum amount of rainfall required to induce a rise in water table is fairly uniform when the water table is within 50 to 100 cm of land surface. Below this depth, the minimum typically gradually increases with depth. These observations can be qualitatively explained by unsaturated zone flow processes. Overall, response/rainfall ratios are higher in wetlands and lower in uplands, presumably reflecting lower specific yields and greater lateral influx in wetland sites. Pronounced depth variations in rainfall/response ratios appear to correlate with soil layer boundaries, where corroborating data are available. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

High-resolution stochastic generation of extreme rainfall intensity for urban drainage modelling applications

NASA Astrophysics Data System (ADS)

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

2016-04-01

Urban drainage response is highly dependent on the spatial and temporal structure of rainfall. Therefore, measuring and simulating rainfall at a high spatial and temporal resolution is a fundamental step to fully assess urban drainage system reliability and related uncertainties. This is even more relevant when considering extreme rainfall events. However, the current space-time rainfall models have limitations in capturing extreme rainfall intensity statistics for short durations. Here, we use the STREAP (Space-Time Realizations of Areal Precipitation) model, which is a novel stochastic rainfall generator for simulating high-resolution rainfall fields that preserve the spatio-temporal structure of rainfall and its statistical characteristics. The model enables a generation of rain fields at 102 m and minute scales in a fast and computer-efficient way matching the requirements for hydrological analysis of urban drainage systems. The STREAP model was applied successfully in the past to generate high-resolution extreme rainfall intensities over a small domain. A sub-catchment in the city of Luzern (Switzerland) was chosen as a case study to: (i) evaluate the ability of STREAP to disaggregate extreme rainfall intensities for urban drainage applications; (ii) assessing the role of stochastic climate variability of rainfall in flow response and (iii) evaluate the degree of non-linearity between extreme rainfall intensity and system response (i.e. flow) for a small urban catchment. The channel flow at the catchment outlet is simulated by means of a calibrated hydrodynamic sewer model.

Variability in rainfall at monitoring stations and derivation of a long-term rainfall intensity record in the Grand Canyon Region, Arizona, USA

USGS Publications Warehouse

Caster, Joshua J.; Sankey, Joel B.

2016-04-11

In this study, we examine rainfall datasets of varying temporal length, resolution, and spatial distribution to characterize rainfall depth, intensity, and seasonality for monitoring stations along the Colorado River within Marble and Grand Canyons. We identify maximum separation distances between stations at which rainfall measurements might be most useful for inferring rainfall characteristics at other locations. We demonstrate a method for applying relations between daily rainfall depth and intensity, from short-term high-resolution data to lower-resolution longer-term data, to synthesize a long-term record of daily rainfall intensity from 1950–2012. We consider the implications of our spatio-temporal characterization of rainfall for understanding local landscape change in sedimentary deposits and archaeological sites, and for better characterizing past and present rainfall and its potential role in overland flow erosion within the canyons. We find that rainfall measured at stations within the river corridor is spatially correlated at separation distances of tens of kilometers, and is not correlated at the large elevation differences that separate stations along the Colorado River from stations above the canyon rim. These results provide guidance for reasonable separation distances at which rainfall measurements at stations within the Grand Canyon region might be used to infer rainfall at other nearby locations along the river. Like other rugged landscapes, spatial variability between rainfall measured at monitoring stations appears to be influenced by canyon and rim physiography and elevation, with preliminary results suggesting the highest elevation landform in the region, the Kaibab Plateau, may function as an important orographic influence. Stations at specific locations within the canyons and along the river, such as in southern (lower) Marble Canyon and eastern (upper) Grand Canyon, appear to have strong potential to receive high-intensity rainfall that can generate runoff which may erode alluvium. The characterization of past and present rainfall variability in this study will be useful for future studies that evaluate more spatially continuous datasets in order to better understand the rainfall dynamics within this, and potentially other, deep canyons.

Application of Radar-Based Accumulated Rainfall Products for Early Detection of Heavy Rainfall Occurrence

NASA Astrophysics Data System (ADS)

Nishiyama, K.; Wakimizu, K.; Yokota, I.; Tsukahara, K.; Moriyama, T.

2016-12-01

In Japan, river and debris flow disasters have been frequently caused by heavy rainfall occurrence under the influence of the activity of a stationary front and associated inflow of a large amount of moisture into the front. However, it is very difficult to predict numerically-based heavy rainfall and associated landslide accurately. Therefore, the use of meteorological radar information is required for enhancing decision-making ability to urge the evacuation of local residents by local government staffs prior to the occurrence of the heavy rainfall disaster. It is also desirable that the local residents acquire the ability to determine the evacuation immediately after confirming radar information by themselves. Actually, it is difficult for untrained local residents and local government staffs to easily recognize where heavy rainfall occurs locally for a couple of hours. This reason is that the image of radar echoes is equivalent to instant electromagnetic distribution measured per a couple of minutes, and the distribution of the radar echoes moves together with the movement of a synoptic system. Therefore, in this study, considering that the movement of radar echoes also may stop in a specific area if stationary front system becomes dominant, radar-based accumulated rainfall information is defined here. The rainfall product is derived by the integration of radar intensity measured every ten minutes during previous 1 hours. Using this product, it was investigated whether and how the radar-based accumulated rainfall displayed at an interval of ten minutes can be applied for early detection of heavy rainfall occurrence. The results are summarized as follows. 1) Radar-based accumulated rainfall products could confirm that some of stationary heavy rainfall systems had already appeared prior to disaster occurrence, and clearly identify the movement of heavy rainfall area. 2) Moreover, accumulated area of rainfall could be visually and easily identified, compared with time-series (movie) of real-time radar-based rainfall intensity. Therefore, the accumulated rainfall distribution provides effective information for early detection of heavy rainfall causing disasters through the training of local residents and local government staffs who have no meteorologically-technical knowledge.

Derivation of critical rainfall thresholds for landslide in Sicily

NASA Astrophysics Data System (ADS)

Caracciolo, Domenico; Arnone, Elisa; Noto, Leonardo V.

2015-04-01

Rainfall is the primary trigger of shallow landslides that can cause fatalities, damage to properties and economic losses in many areas of the world. For this reason, determining the rainfall amount/intensity responsible for landslide occurrence is important, and may contribute to mitigate the related risk and save lives. Efforts have been made in different countries to investigate triggering conditions in order to define landslide-triggering rainfall thresholds. The rainfall thresholds are generally described by a functional relationship of power in terms of cumulated or intensity event rainfall-duration, whose parameters are estimated empirically from the analysis of historical rainfall events that triggered landslides. The aim of this paper is the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern Italy, by focusing particularly on the role of the antecedent wet conditions. The creation of the appropriate landslide-rainfall database likely represents one of main efforts in this type of analysis. For this work, historical landslide events occurred in Sicily from 1919 to 2001 were selected from the archive of the Sistema Informativo sulle Catastrofi Idrogeologiche, developed under the project Aree Vulnerabili Italiane. The corresponding triggering precipitations were screened from the raingauges network in Sicily, maintained by the Osservatorio delle Acque - Agenzia Regionale per i Rifiuti e le Acque. In particular, a detailed analysis was carried out to identify and reconstruct the hourly rainfall events that caused the selected landslides. A bootstrapping statistical technique has been used to determine the uncertainties associated with the threshold parameters. The rainfall thresholds at different exceedance probability levels, from 1% to 10%, were defined in terms of cumulated event rainfall, E, and rainfall duration, D. The role of rainfall prior to the damaging events was taken into account by including in the analysis the rainfall fallen 6, 15 and 30 days before each landslide. The antecedent rainfall turned out to be particularly important in triggering landslides. The rainfall thresholds obtained for the Sicily were compared with the regional curves proposed by various authors confirming a good agreement with these.

Rainfall and Sheet Power Equation for Interrill Erosion on Steep Hillslope

NASA Astrophysics Data System (ADS)

Shin, S.; Park, S.; Pierson, F. B.; Al-Hamdan, O. Z.; Williams, C. J.

2012-12-01

Splash and sheet erosion processes dominate on most undisturbed hillslopes of rangeland. Interrill soil erosion should consider the influence of both raindrop and sheet flow to work of soil particles detached by raindrop impact and transported by rainfall-disturbed sheet flow. Interrill erosion equations that combine the influence of both rainfall and runoff have been proposed by several researchers. However most approaches to modeling interrill erosion have been based on statistical relationships given the inherent complexity in derivation of broadly-applicable physically-based erosion parameters. In this study, a rainfall and sheet power equation to evaluate interrill sediment yields (Qs) was derived from the sum of rainfall power and sheet power expressed by rainfall intensity: Qs=a(cosθ/L){α sinθ ∑ I(t)^(11/9)+β tanθ^(1/2) ∑ (1-fr(t))^(5/3) I(t)^(5/3)}^b, where I(t) is rainfall intensity, θ is slope angle, fr(t) is infiltration rate, a, b, α, and β are coefficients, sinθ I(t)^(11/9) is the rainfall power term, and tanθ^(1/2) (1-fr(t))^(5/3) I(t)^(5/3) is the sheet power term. The rainfall power ratio and sheet power ratio decreased and increased with increased rainfall intensity, respectively. The sheet power term depended greatly on infiltration rate controlled by rainfall intensity, vegetation cover, and soil condition. The rainfall and sheet power equation assuming that α and β is 0 was evaluated using field data from plots on steep hillslopes and showed the better correlation with sediment yields than rainfall kinetic energy, runoff discharge, or interrill equations based on rainfall intensity and runoff discharge founded in the literature. This equation successfully explained physical processes for soil erosion that rainfall power is dominant under low rainfall and sheet power is dominant under heavy rainfall. Additional experimental data is needed to assess coefficients of the power equation to determine the relative quantities of rainfall power and sheet power and to evaluate the erosion efficiency of interactions between raindrop impact and sheet flow and soil erodibility. Acknowledgements: This work was supported by a grant (Code#'08 RTIP B-01) from Regional Technology Innovation Program funded by Ministry of Land, Transport and Maritime Affairs of Korean government.;

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Changes to Sub-daily Rainfall Patterns in a Future Climate

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

Duangdai, Eakkapong; Likasiri, Chulin

2017-03-01

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

Nonstationary Intensity-Duration-Frequency Curves for Drainge Infrastructure Coping with Climate Change

NASA Astrophysics Data System (ADS)

Kim, Byung Sik; Jeung, Se Jin; Lee, Dong Seop; Han, Woo Suk

2015-04-01

As the abnormal rainfall condition has been more and more frequently happen and serious by climate change and variabilities, the question whether the design of drainage system could be prepared with abnormal rainfall condition or not has been on the rise. Usually, the drainage system has been designed by rainfall I-D-F (Intensity-Duration-Frequency) curve with assumption that I-D-F curve is stationary. The design approach of the drainage system has limitation not to consider the extreme rainfall condition of which I-D-F curve is non-stationary by climate change and variabilities. Therefore, the assumption that the I-D-F curve is stationary to design drainage system maybe not available in the climate change period, because climate change has changed the characteristics of extremes rainfall event to be non-stationary. In this paper, design rainfall by rainfall duration and non-stationary I-D-F curve are derived by the conditional GEV distribution considering non-stationary of rainfall characteristics. Furthermore, the effect of designed peak flow with increase of rainfall intensity was analyzed by distributed rainfall-runoff model, S-RAT(Spatial Runoff Assessment Tool). Although there are some difference by rainfall duration, the traditional I-D-F curves underestimates the extreme rainfall events for high-frequency rainfall condition. As a result, this paper suggest that traditional I-D-F curves could not be suitable for the design of drainage system under climate change condition. Keywords : Drainage system, Climate Change, non-stationary, I-D-F curves This research was supported by a grant 'Development of multi-function debris flow control technique considering extreme rainfall event' [NEMA-Natural-2014-74] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of KOREA

The Eastern Pacific ITCZ during the Boreal Spring

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

Temporal and spatial variations of rainfall erosivity in Southern Taiwan

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Gross rainfall amount and maximum rainfall intensity in 60-minute influence on interception loss of shrubs: a 10-year observation in the Tengger Desert

PubMed Central

Zhang, Zhi-Shan; Zhao, Yang; Li, Xin-Rong; Huang, Lei; Tan, Hui-Juan

2016-01-01

In water-limited regions, rainfall interception is influenced by rainfall properties and crown characteristics. Rainfall properties, aside from gross rainfall amount and duration (GR and RD), maximum rainfall intensity and rainless gap (RG), within rain events may heavily affect throughfall and interception by plants. From 2004 to 2014 (except for 2007), individual shrubs of Caragana korshinskii and Artemisia ordosica were selected to measure throughfall during 210 rain events. Various rainfall properties were auto-measured and crown characteristics, i.e., height, branch and leaf area index, crown area and volume of two shrubs were also measured. The relative interceptions of C. korshinskii and A. ordosica were 29.1% and 17.1%, respectively. Rainfall properties have more contributions than crown characteristics to throughfall and interception of shrubs. Throughfall and interception of shrubs can be explained by GR, RI60 (maximum rainfall intensities during 60 min), RD and RG in deceasing importance. However, relative throughfall and interception of two shrubs have different responses to rainfall properties and crown characteristics, those of C. korshinskii were closely related to rainfall properties, while those of A. ordosica were more dependent on crown characteristics. We highlight long-term monitoring is very necessary to determine the relationships between throughfall and interception with crown characteristics. PMID:27184918

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

PubMed

Zhang, Zhengzhong; Shan, Lishan; Li, Yi

2018-01-01

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

Rainfall intensity effects on removal of fecal indicator bacteria from solid dairy manure applied over grass-covered soil

USDA-ARS?s Scientific Manuscript database

The rainfall-induced removal of pathogens and microbial indicators from land-applied manure with runoff and infiltration greatly contributes to the impairment of surface and groundwater resources. It has been assumed that rainfall intensity and changes in rainfall intensity during a rainfall event d...

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Towards combining GPM and MFG observations to monitor near real time heavy precipitation at fine scale over India and nearby oceanic regions

NASA Astrophysics Data System (ADS)

Mishra, Anoop; Rafiq, Mohammd

2017-12-01

This is the first attempt to merge highly accurate precipitation estimates from Global Precipitation Measurement (GPM) with gap free satellite observations from Meteosat to develop a regional rainfall monitoring algorithm to estimate heavy rainfall over India and nearby oceanic regions. Rainfall signature is derived from Meteosat observations and is co-located against rainfall from GPM to establish a relationship between rainfall and signature for various rainy seasons. This relationship can be used to monitor rainfall over India and nearby oceanic regions. Performance of this technique was tested by applying it to monitor heavy precipitation over India. It is reported that our algorithm is able to detect heavy rainfall. It is also reported that present algorithm overestimates rainfall areal spread as compared to rain gauge based rainfall product. This deficiency may arise from various factors including uncertainty caused by use of different sensors from different platforms (difference in viewing geometry from MFG and GPM), poor relationship between warm rain (light rain) and IR brightness temperature, and weak characterization of orographic rain from IR signature. We validated hourly rainfall estimated from the present approach with independent observations from GPM. We also validated daily rainfall from this approach with rain gauge based product from India Meteorological Department (IMD). Present technique shows a Correlation Coefficient (CC) of 0.76, a bias of -2.72 mm, a Root Mean Square Error (RMSE) of 10.82 mm, Probability of Detection (POD) of 0.74, False Alarm Ratio (FAR) of 0.34 and a Skill score of 0.36 with daily rainfall from rain gauge based product of IMD at 0.25° resolution. However, FAR reduces to 0.24 for heavy rainfall events. Validation results with rain gauge observations reveal that present technique outperforms available satellite based rainfall estimates for monitoring heavy rainfall over Indian region.

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

NASA Astrophysics Data System (ADS)

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

2009-09-01

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

Satellite-based high-resolution mapping of rainfall over southern Africa

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Drönner, Johannes; Nauss, Thomas

2017-06-01

A spatially explicit mapping of rainfall is necessary for southern Africa for eco-climatological studies or nowcasting but accurate estimates are still a challenging task. This study presents a method to estimate hourly rainfall based on data from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Rainfall measurements from about 350 weather stations from 2010-2014 served as ground truth for calibration and validation. SEVIRI and weather station data were used to train neural networks that allowed the estimation of rainfall area and rainfall quantities over all times of the day. The results revealed that 60 % of recorded rainfall events were correctly classified by the model (probability of detection, POD). However, the false alarm ratio (FAR) was high (0.80), leading to a Heidke skill score (HSS) of 0.18. Estimated hourly rainfall quantities were estimated with an average hourly correlation of ρ = 0. 33 and a root mean square error (RMSE) of 0.72. The correlation increased with temporal aggregation to 0.52 (daily), 0.67 (weekly) and 0.71 (monthly). The main weakness was the overestimation of rainfall events. The model results were compared to the Integrated Multi-satellitE Retrievals for GPM (IMERG) of the Global Precipitation Measurement (GPM) mission. Despite being a comparably simple approach, the presented MSG-based rainfall retrieval outperformed GPM IMERG in terms of rainfall area detection: GPM IMERG had a considerably lower POD. The HSS was not significantly different compared to the MSG-based retrieval due to a lower FAR of GPM IMERG. There were no further significant differences between the MSG-based retrieval and GPM IMERG in terms of correlation with the observed rainfall quantities. The MSG-based retrieval, however, provides rainfall in a higher spatial resolution. Though estimating rainfall from satellite data remains challenging, especially at high temporal resolutions, this study showed promising results towards improved spatio-temporal estimates of rainfall over southern Africa.

Assessment of landslide hazards induced by extreme rainfall event in Jammu and Kashmir Himalaya, northwest India

NASA Astrophysics Data System (ADS)

Kumar, Amit; Asthana, AKL; Priyanka, Rao Singh; Jayangondaperumal, R.; Gupta, Anil K.; Bhakuni, SS

2017-05-01

In the Indian Himalayan region (IHR), landslide-driven hazards have intensified over the past several decades primarily caused by the occurrence of heavy and extreme rainfall. However, little attention has been given to determining the cause of events triggered during pre- and post-Indian Summer Monsoon (ISM) seasons. In the present research, detailed geological, meteorological, and remote sensing investigations have been carried out on an extreme rainfall landslide event that occurred in Sadal village, Udhampur district, Jammu and Kashmir Himalaya, during September 2014. Toward the receding phase of the ISM (i.e., in the month of September 2014), an unusual rainfall event of 488.2 mm rainfall in 24 h took place in Jammu and Kashmir Himalaya in contrast to the normal rainfall occurrence. Geological investigations suggest that a planar weakness in the affected region is caused by bedding planes that consist of an alternate sequence of hard, compact sandstone and weak claystone. During this extreme rainfall event, the Sadal village was completely buried under the rock slides, as failure occurred along the planar weakness that dips toward the valley slope. Rainfall data analysis from the Tropical Rainfall Measuring Mission (TRMM) for the preceding years homogeneous time series (July-September) indicates that the years 2005, 2009, 2011, 2012, and 2014 (i.e., closely spaced and clustering heavy rainfall events) received heavy rainfalls during the withdrawal of the ISM; whereas the heaviest rainfall was received in the years 2003 and 2013 at the onset of the ISM in the study region. This suggests that no characteristic cyclicity exists for extreme rainfall events. However, we observe that either toward the onset of the ISM or its retreat, the extreme rainfall facilitates landslides, rockfall, and slope failures in northwestern Himalaya. The spatiotemporal distribution of landslides caused by extreme rainfall events suggests its confinement toward the windward side of the Himalayan front.

Statistical approaches for the definition of landslide rainfall thresholds and their uncertainty using rain gauge and satellite data

NASA Astrophysics Data System (ADS)

Rossi, M.; Luciani, S.; Valigi, D.; Kirschbaum, D.; Brunetti, M. T.; Peruccacci, S.; Guzzetti, F.

2017-05-01

Models for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (LS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the "ground" rainfall registered by rain gauges.

Statistical Approaches for the Definition of Landslide Rainfall Thresholds and their Uncertainty Using Rain Gauge and Satellite Data

NASA Technical Reports Server (NTRS)

Rossi, M.; Luciani, S.; Valigi, D.; Kirschbaum, D.; Brunetti, M. T.; Peruccacci, S.; Guzzetti, F.

2017-01-01

Models for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (LS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the 'ground' rainfall registered by rain gauges.

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

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

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

NASA Astrophysics Data System (ADS)

Licznar, Paweł; Deidda, Roberto

2014-05-01

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

Temporal and spatial characteristics of annual and seasonal rainfall in Malawi

NASA Astrophysics Data System (ADS)

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

2010-05-01

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

Analysis of extreme rainfall events using attributes control charts in temporal rainfall processes

NASA Astrophysics Data System (ADS)

Villeta, María; Valencia, Jose Luis; Saá-Requejo, Antonio; María Tarquis, Ana

2015-04-01

The impacts of most intense rainfall events on agriculture and insurance industry can be very severe. This research focuses in the analysis of extreme rainfall events throughout the use of attributes control charts, which constitutes a usual tool in Statistical Process Control (SPC) but unusual in climate studios. Here, series of daily precipitations for the years 1931-2009 within a Spanish region are analyzed, based on a new type of attributes control chart that takes into account the autocorrelation between the extreme rainfall events. The aim is to conclude if there exist or not evidence of a change in the extreme rainfall model of the considered series. After adjusting seasonally the precipitation series and considering the data of the first 30 years, a frequency-based criterion allowed fixing specification limits in order to discriminate between extreme observed rainfall days and normal observed rainfall days. The autocorrelation amongst maximum precipitation is taken into account by a New Binomial Markov Extended Process obtained for each rainfall series. These modelling of the extreme rainfall processes provide a way to generate the attributes control charts for the annual fraction of rainfall extreme days. The extreme rainfall processes along the rest of the years under study can then be monitored by such attributes control charts. The results of the application of this methodology show evidence of change in the model of extreme rainfall events in some of the analyzed precipitation series. This suggests that the attributes control charts proposed for the analysis of the most intense precipitation events will be of practical interest to agriculture and insurance sectors in next future.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Remote rainfall sensing for landslide hazard analysis

USGS Publications Warehouse

Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay

2001-01-01

Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

Statistical Analysis of 30 Years Rainfall Data: A Case Study

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Soil Texture Mediates the Response of Tree Cover to Rainfall Intensity in African Savannas

NASA Astrophysics Data System (ADS)

Case, M. F.; Staver, A. C.

2017-12-01

Global circulation models predict widespread shifts in the frequency and intensity of rainfall, even where mean annual rainfall does not change. Resulting changes in soil moisture dynamics could have major consequences for plant communities and ecosystems, but the direction of potential vegetation responses can be challenging to predict. In tropical savannas, where tree and grasses coexist, contradictory lines of evidence have suggested that tree cover could respond either positively or negatively to less frequent, more intense rainfall. Here, we analyzed remote sensing data and continental-scale soils maps to examine whether soil texture or fire could explain heterogeneous responses of savanna tree cover to intra-annual rainfall variability across sub-Saharan Africa. We find that tree cover generally increases with mean wet-season rainfall, decreases with mean wet-season rainfall intensity, and decreases with fire frequency. However, soil sand content mediates these relationships: the response to rainfall intensity switches qualitatively depending on soil texture, such that tree cover decreases dramatically with less frequent, more intense rainfall on clay soils but increases with rainfall intensity on sandy soils in semi-arid savannas. We propose potential ecohydrological mechanisms for this heterogeneous response, and emphasize that predictions of savanna vegetation responses to global change should account for interactions between soil texture and changing rainfall patterns.

Building rainfall thresholds for large-scales landslides by extracting occurrence time of landslides from seismic records

NASA Astrophysics Data System (ADS)

Yen, Hsin-Yi; Lin, Guan-Wei

2017-04-01

Understanding the rainfall condition which triggers mass moment on hillslope is the key to forecast rainfall-induced slope hazards, and the exact time of landslide occurrence is one of the basic information for rainfall statistics. In the study, we focused on large-scale landslides (LSLs) with disturbed area larger than 10 ha and conducted a string of studies including the recognition of landslide-induced ground motions and the analyses of different terms of rainfall thresholds. More than 10 heavy typhoons during the periods of 2005-2014 in Taiwan induced more than hundreds of LSLs and provided the opportunity to characterize the rainfall conditions which trigger LSLs. A total of 101 landslide-induced seismic signals were identified from the records of Taiwan seismic network. These signals exposed the occurrence time of landslide to assess rainfall conditions. Rainfall analyses showed that LSLs occurred when cumulative rainfall exceeded 500 mm. The results of rainfall-threshold analyses revealed that it is difficult to distinct LSLs from small-scale landslides (SSLs) by the I-D and R-D methods, but the I-R method can achieve the discrimination. Besides, an enhanced three-factor threshold considering deep water content was proposed as the rainfall threshold for LSLs.

Predicting watershed acidification under alternate rainfall conditions

USGS Publications Warehouse

Huntington, T.G.

1996-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Critical scales to explain urban hydrological response: an application in Cranbrook, London

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-Claire; Gaitan, Santiago; Ochoa Rodriguez, Susana; van de Giesen, Nick

2018-04-01

Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response.

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Garcia, Ricardo A. C.; Quaresma, Ivânia

2018-04-01

This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

How effective is the new generation of GPM satellite precipitation in characterizing the rainfall variability over Malaysia?

NASA Astrophysics Data System (ADS)

Mahmud, Mohd Rizaludin; Hashim, Mazlan; Reba, Mohd Nadzri Mohd

2017-08-01

We investigated the potential of the new generation of satellite precipitation product from the Global Precipitation Mission (GPM) to characterize the rainfall in Malaysia. Most satellite precipitation products have limited ability to precisely characterize the high dynamic rainfall variation that occurred at both time and scale in this humid tropical region due to the coarse grid size to meet the physical condition of the smaller land size, sub-continent and islands. Prior to the status quo, an improved satellite precipitation was required to accurately measure the rainfall and its distribution. Subsequently, the newly released of GPM precipitation product at half-hourly and 0.1° resolution served an opportunity to anticipate the aforementioned conflict. Nevertheless, related evidence was not found and therefore, this study made an initiative to fill the gap. A total of 843 rain gauges over east (Borneo) and west Malaysia (Peninsular) were used to evaluate the rainfall the GPM rainfall data. The assessment covered all critical rainy seasons which associated with Asian Monsoon including northeast (Nov. - Feb.), southwest (May - Aug.) and their subsequent inter-monsoon period (Mar. - Apr. & Sep. - Oct.). The ability of GPM to provide quantitative rainfall estimates and qualitative spatial rainfall patterns were analysed. Our results showed that the GPM had good capacity to depict the spatial rainfall patterns in less heterogeneous rainfall patterns (Spearman's correlation, 0.591 to 0.891) compared to the clustered one (r = 0.368 to 0.721). Rainfall intensity and spatial heterogeneity that is largely driven by seasonal monsoon has significant influence on GPM ability to resolve local rainfall patterns. In quantitative rainfall estimation, large errors can be primarily associated with the rainfall intensity increment. 77% of the error variation can be explained through rainfall intensity particularly the high intensity (> 35 mm d-1). A strong relationship between GPM rainfall and error was found from heavy ( 35 mm d-1) to violent rain (160 mm d-1). The output of this study provides reference regarding the performance of GPM data for respective hydrology studies in this region.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Rainfall simulation in education

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Sub-seasonal behaviour of Asian summer monsoon under a changing climate: assessments using CMIP5 models

NASA Astrophysics Data System (ADS)

Sooraj, K. P.; Terray, Pascal; Xavier, Prince

2016-06-01

Numerous global warming studies show the anticipated increase in mean precipitation with the rising levels of carbon dioxide concentration. However, apart from the changes in mean precipitation, the finer details of daily precipitation distribution, such as its intensity and frequency (so called daily rainfall extremes), need to be accounted for while determining the impacts of climate changes in future precipitation regimes. Here we examine the climate model projections from a large set of Coupled Model Inter-comparison Project 5 models, to assess these future aspects of rainfall distribution over Asian summer monsoon (ASM) region. Our assessment unravels a north-south rainfall dipole pattern, with increased rainfall over Indian subcontinent extending into the western Pacific region (north ASM region, NASM) and decreased rainfall over equatorial oceanic convergence zone over eastern Indian Ocean region (south ASM region, SASM). This robust future pattern is well conspicuous at both seasonal and sub-seasonal time scales. Subsequent analysis, using daily rainfall events defined using percentile thresholds, demonstrates that mean rainfall changes over NASM region are mainly associated with more intense and more frequent extreme rainfall events (i.e. above 95th percentile). The inference is that there are significant future changes in rainfall probability distributions and not only a uniform shift in the mean rainfall over the NASM region. Rainfall suppression over SASM seems to be associated with changes involving multiple rainfall events and shows a larger model spread, thus making its interpretation more complex compared to NASM. Moisture budget diagnostics generally show that the low-level moisture convergence, due to stronger increase of water vapour in the atmosphere, acts positively to future rainfall changes, especially for heaviest rainfall events. However, it seems that the dynamic component of moisture convergence, associated with vertical motion, shows a strong spatial and rainfall category dependency, sometimes offsetting the effect of the water vapour increase. Additionally, we found that the moisture convergence is mainly dominated by the climatological vertical motion acting on the humidity changes and the interplay between all these processes proves to play a pivotal role for regulating the intensities of various rainfall events in the two domains.

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

NASA Astrophysics Data System (ADS)

Zahmatkesh, Zahra; Karamouz, Mohammad; Nazif, Sara

2015-09-01

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

Detecting Climate Variability in Tropical Rainfall

NASA Astrophysics Data System (ADS)

Berg, W.

2004-05-01

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

Rainfall erosivity and rainfall return period in the experimental watershed of Aracruz, in the Coastal Plain of Espirito Santo, Brazil

USDA-ARS?s Scientific Manuscript database

The knowledge of the factors influencing water erosion is relevant to land management practices. Rainfall, expressed by rainfall erosivity, is very important among the factors affecting water erosion. Thus, the objective of this study was to determine rainfall erosivity and return period for the Coa...

Analysis of global oceanic rainfall from microwave data

NASA Technical Reports Server (NTRS)

Rao, M.

1978-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Modern proposal of methodology for retrieval of characteristic synthetic rainfall hyetographs

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Mesoscale Assimilation of TMI Rainfall Data with 4DVAR: Sensitivity Studies

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Pu, Zhaoxia

2003-01-01

Sensitivity studies are performed on the assimilation of TRMM (Tropical Rainfall Measurement Mission) Microwave Imager (TMI) derived rainfall data into a mesoscale model using a four-dimensional variational data assimilation (4DVAR) technique. A series of numerical experiments is conducted to evaluate the impact of TMI rainfall data on the numerical simulation of Hurricane Bonnie (1998). The results indicate that rainfall data assimilation is sensitive to the error characteristics of the data and the inclusion of physics in the adjoint and forward models. In addition, assimilating the rainfall data alone is helpful for producing a more realistic eye and rain bands in the hurricane but does not ensure improvements in hurricane intensity forecasts. Further study indicated that it is necessary to incorporate TMI rainfall data together with other types of data such as wind data into the model, in which case the inclusion of the rainfall data further improves the intensity forecast of the hurricane. This implies that proper constraints may be needed for rainfall assimilation.

Rainfall Morphology in Semi-Tropical Convergence Zones

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Ferrier, Brad S.; Ray, Peter S.

2000-01-01

Central Florida is the ideal test laboratory for studying convergence zone-induced convection. The region regularly experiences sea breeze fronts and rainfall-induced outflow boundaries. The focus of this study is the common yet poorly-studied convergence zone established by the interaction of the sea breeze front and an outflow boundary. Previous studies have investigated mechanisms primarily affecting storm initiation by such convergence zones. Few have focused on rainfall morphology yet these storms contribute a significant amount precipitation to the annual rainfall budget. Low-level convergence and mid-tropospheric moisture have both been shown to correlate with rainfall amounts in Florida. Using 2D and 3D numerical simulations, the roles of low-level convergence and mid-tropospheric moisture in rainfall evolution are examined. The results indicate that time-averaged, vertical moisture flux (VMF) at the sea breeze front/outflow convergence zone is directly and linearly proportional to initial condensation rates. This proportionality establishes a similar relationship between VMF and initial rainfall. Vertical moisture flux, which encompasses depth and magnitude of convergence, is better correlated to initial rainfall production than surface moisture convergence. This extends early observational studies which linked rainfall in Florida to surface moisture convergence. The amount and distribution of mid-tropospheric moisture determines how rainfall associated with secondary cells develop. Rainfall amount and efficiency varied significantly over an observable range of relative humidities in the 850- 500 mb layer even though rainfall evolution was similar during the initial or "first-cell" period. Rainfall variability was attributed to drier mid-tropospheric environments inhibiting secondary cell development through entrainment effects. Observationally, 850-500 mb moisture structure exhibits wider variability than lower level moisture, which is virtually always present in Florida. A likely consequence of the variability in 850-500 moisture is a stronger statistical correlation to rainfall, which observational studies have noted. The study indicates that vertical moisture flux forcing at convergence zones is critical in determining rainfall in the initial stage of development but plays a decreasing role in rainfall evolution as the system matures. The mid-tropospheric moisture (e.g. environment) plays an increasing role in rainfall evolution as the system matures. This suggests the need to improve measurements of magnitude/depth of convergence and mid-tropospheric moisture distribution. It also highlights the need for better parameterization of entrainment and vertical moisture distribution in larger-scale models.

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

PubMed

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

2015-05-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

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

NASA Astrophysics Data System (ADS)

Pan, Huali; Hu, Mingjian; Ou, Guoqiang

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

This article summarizes the results from an analysis conducted to investigate the spatio-temporal variability and trends in the rainfall over Ethiopia over a period of 31 years from 1980 to 2010. The data is mostly observed station data supplemented by bias-corrected AgMERRA climate data. Changes in annual and Belg (March-May) and Kiremt (June to September) season rainfalls and rainy days have been analysed over the entire Ethiopia. Rainfall is characterized by high temporal variability with coefficient of variation (CV, %) varying from 9 to 30% in the annual, 9 to 69% during the Kiremt season and 15-55% during the Belg season rainfall amounts. Rainfall variability increased disproportionately as the amount of rainfall declined from 700 to 100 mm or less. No significant trend was observed in the annual rainfall amounts over the country, but increasing and decreasing trends were observed in the seasonal rainfall amounts in some areas. A declining trend is also observed in the number of rainy days especially in Oromia, Benishangul-Gumuz and Gambella regions. Trends in seasonal rainfall indicated a general decline in the Belg season and an increase in the Kiremt season rainfall amounts. The increase in rainfall during the main Kiremt season along with the decrease in the number of rainy days leads to an increase in extreme rainfall events over Ethiopia. The trends in the 95th-percentile rainfall events illustrate that the annual extreme rainfall events are increasing over the eastern and south-western parts of Ethiopia covering Oromia and Benishangul-Gumuz regions. During the Belg season, extreme rainfall events are mostly observed over central Ethiopia extending towards the southern part of the country while during the Kiremt season, they are observed over parts of Oromia, (covering Borena, Guji, Bali, west Harerge and east Harerge), Somali, Gambella, southern Tigray and Afar regions. Changes in the intensity of extreme rainfall events are mostly observed over south-eastern parts of Ethiopia extending to the south-west covering Somali and Oromia regions. Similar trends are also observed in the greatest 3-, 5- and 10-day rainfall amounts. Changes in the consecutive dry and wet days showed that consecutive wet days during Belg and Kiremt seasons decreased significantly in many areas in Ethiopia while consecutive dry days increased. The consistency in the trends over large spatial areas confirms the robustness of the trends and serves as a basis for understanding the projected changes in the climate. These results were discussed in relation to their significance to agriculture.

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

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

Raingauge-Based Rainfall Nowcasting with Artificial Neural Network

NASA Astrophysics Data System (ADS)

Liong, Shie-Yui; He, Shan

2010-05-01

Rainfall forecasting and nowcasting are of great importance, for instance, in real-time flood early warning systems. Long term rainfall forecasting demands global climate, land, and sea data, thus, large computing power and storage capacity are required. Rainfall nowcasting's computing requirement, on the other hand, is much less. Rainfall nowcasting may use data captured by radar and/or weather stations. This paper presents the application of Artificial Neural Network (ANN) on rainfall nowcasting using data observed at weather and/or rainfall stations. The study focuses on the North-East monsoon period (December, January and February) in Singapore. Rainfall and weather data from ten stations, between 2000 and 2006, were selected and divided into three groups for training, over-fitting test and validation of the ANN. Several neural network architectures were tried in the study. Two architectures, Backpropagation ANN and Group Method of Data Handling ANN, yielded better rainfall nowcasting, up to two hours, than the other architectures. The obtained rainfall nowcasts were then used by a catchment model to forecast catchment runoff. The results of runoff forecast are encouraging and promising.With ANN's high computational speed, the proposed approach may be deliverable for creating the real-time flood early warning system.

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

NASA Astrophysics Data System (ADS)

Yulihastin, E.; Trismidianto

2018-05-01

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

Evolving Improvements to TRMM Ground Validation Rainfall Estimates

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

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

USGS Publications Warehouse

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

2015-01-01

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

A Metastatistical Approach to Satellite Estimates of Extreme Rainfall Events

NASA Astrophysics Data System (ADS)

Zorzetto, E.; Marani, M.

2017-12-01

The estimation of the average recurrence interval of intense rainfall events is a central issue for both hydrologic modeling and engineering design. These estimates require the inference of the properties of the right tail of the statistical distribution of precipitation, a task often performed using the Generalized Extreme Value (GEV) distribution, estimated either from a samples of annual maxima (AM) or with a peaks over threshold (POT) approach. However, these approaches require long and homogeneous rainfall records, which often are not available, especially in the case of remote-sensed rainfall datasets. We use here, and tailor it to remotely-sensed rainfall estimates, an alternative approach, based on the metastatistical extreme value distribution (MEVD), which produces estimates of rainfall extreme values based on the probability distribution function (pdf) of all measured `ordinary' rainfall event. This methodology also accounts for the interannual variations observed in the pdf of daily rainfall by integrating over the sample space of its random parameters. We illustrate the application of this framework to the TRMM Multi-satellite Precipitation Analysis rainfall dataset, where MEVD optimally exploits the relatively short datasets of satellite-sensed rainfall, while taking full advantage of its high spatial resolution and quasi-global coverage. Accuracy of TRMM precipitation estimates and scale issues are here investigated for a case study located in the Little Washita watershed, Oklahoma, using a dense network of rain gauges for independent ground validation. The methodology contributes to our understanding of the risk of extreme rainfall events, as it allows i) an optimal use of the TRMM datasets in estimating the tail of the probability distribution of daily rainfall, and ii) a global mapping of daily rainfall extremes and distributional tail properties, bridging the existing gaps in rain gauges networks.

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

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Bias correction of satellite-based rainfall data

NASA Astrophysics Data System (ADS)

Bhattacharya, Biswa; Solomatine, Dimitri

2015-04-01

Limitation in hydro-meteorological data availability in many catchments limits the possibility of reliable hydrological analyses especially for near-real-time predictions. However, the variety of satellite based and meteorological model products for rainfall provides new opportunities. Often times the accuracy of these rainfall products, when compared to rain gauge measurements, is not impressive. The systematic differences of these rainfall products from gauge observations can be partially compensated by adopting a bias (error) correction. Many of such methods correct the satellite based rainfall data by comparing their mean value to the mean value of rain gauge data. Refined approaches may also first find out a suitable time scale at which different data products are better comparable and then employ a bias correction at that time scale. More elegant methods use quantile-to-quantile bias correction, which however, assumes that the available (often limited) sample size can be useful in comparing probabilities of different rainfall products. Analysis of rainfall data and understanding of the process of its generation reveals that the bias in different rainfall data varies in space and time. The time aspect is sometimes taken into account by considering the seasonality. In this research we have adopted a bias correction approach that takes into account the variation of rainfall in space and time. A clustering based approach is employed in which every new data point (e.g. of Tropical Rainfall Measuring Mission (TRMM)) is first assigned to a specific cluster of that data product and then, by identifying the corresponding cluster of gauge data, the bias correction specific to that cluster is adopted. The presented approach considers the space-time variation of rainfall and as a result the corrected data is more realistic. Keywords: bias correction, rainfall, TRMM, satellite rainfall

Urban rainfall estimation employing commercial microwave links

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Starr, David O'C (Technical Monitor)

2001-01-01

A recent paper by Shepherd and Pierce (conditionally accepted to Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. A convective-mesoscale model with extensive land-surface processes is employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. Early analysis suggests that urban surface roughness (through turbulence and low-level convergence) may control timing and initial location of UHI-induced convection. The magnitude of the heat island appears to be closely linked to the total rainfall amount with minor impact on timing and location. The physical size of the city may predominantly impact on the location of UHI-induced rainfall anomaly. The UHI factor parameter space will be thoroughly investigated with respect to their effects on rainfall amount, location, and timing. This study extends prior numerical investigations of the impact of urban surfaces on meteorological processes, particularly rainfall development. The work also contains several novel aspects, including the application of a high-resolution (less than I km) cloud-mesoscale model to investigate urban-induce rainfall process; investigation of thermal magnitude of the UHI on rainfall process; and investigation of UHI physical size on rainfall processes.

How spatial and temporal rainfall variability affect runoff across basin scales: insights from field observations in the (semi-)urbanised Charlotte watershed

NASA Astrophysics Data System (ADS)

Ten Veldhuis, M. C.; Smith, J. A.; Zhou, Z.

2017-12-01

Impacts of rainfall variability on runoff response are highly scale-dependent. Sensitivity analyses based on hydrological model simulations have shown that impacts are likely to depend on combinations of storm type, basin versus storm scale, temporal versus spatial rainfall variability. So far, few of these conclusions have been confirmed on observational grounds, since high quality datasets of spatially variable rainfall and runoff over prolonged periods are rare. Here we investigate relationships between rainfall variability and runoff response based on 30 years of radar-rainfall datasets and flow measurements for 16 hydrological basins ranging from 7 to 111 km2. Basins vary not only in scale, but also in their degree of urbanisation. We investigated temporal and spatial variability characteristics of rainfall fields across a range of spatial and temporal scales to identify main drivers for variability in runoff response. We identified 3 ranges of basin size with different temporal versus spatial rainfall variability characteristics. Total rainfall volume proved to be the dominant agent determining runoff response at all basin scales, independent of their degree of urbanisation. Peak rainfall intensity and storm core volume are of secondary importance. This applies to all runoff parameters, including runoff volume, runoff peak, volume-to-peak and lag time. Position and movement of the storm with respect to the basin have a negligible influence on runoff response, with the exception of lag times in some of the larger basins. This highlights the importance of accuracy in rainfall estimation: getting the position right but the volume wrong will inevitably lead to large errors in runoff prediction. Our study helps to identify conditions where rainfall variability matters for correct estimation of the rainfall volume as well as the associated runoff response.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2000-10-01

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

The Effect of Rainfall Measurement Technique and Its Spatiotemporal Resolution on Discharge Predictions in the Netherlands

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Brauer, C.; Overeem, A.; Sassi, M.; Rios Gaona, M. F.

2014-12-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of these spatiotemporal resolutions on discharge simulations in lowland catchments by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in a freely draining lowland catchment and a polder with controlled water levels. We used rain gauge networks with automatic (hourly resolution but low spatial density) and manual gauges (high spatial density but daily resolution). Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. We also investigated the effect of spatiotemporal resolution with a high-resolution X-band radar data set for catchments with different sizes. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. When catchments are divided into sub-catchments, rainfall spatial variability can become more important, especially during convective rainfall events, leading to spatially varying catchment wetness and spatially varying contribution of quick flow routes. Improving rainfall measurements and their spatiotemporal resolution can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

A stationary criterion to identify the duration of efficient rainfalls to trigger shallow landslide

NASA Astrophysics Data System (ADS)

Vessia, G.; Parise, M.

2012-04-01

Even though rainfall is considered a well known trigger of natural slope instability, its effective role in initiating landsliding phenomena cannot be easily distinguished due to many time- and space- variable interactions among several factors (i.e. slope geometry, mechanical and hydraulic characters of superficial layers and the basin, etc.). A common approach to relate rainfall to the onset of shallow landslides is to plot effective rainfall intensity vs duration to draw intensity threshold lines. Since the earliest work by Caine (1980) on this topic, several researchers have tried to establish intensity thresholds by means of deterministic and probabilistic approaches from a number of worldwide and regional rainfall-landslide inventories. With respect to this intensity-duration threshold approach, information about rainfall-induced landslides are generally collected from chronicles or historical landslide time series, whilst no data about the hydraulic and geometric features of soils and rocks involved into the natural slope instability is commonly taken into account. On the contrary, rainfall heights at different time lag (even every 30 min) are available at different stations by rain gauges. As rain gauge measurements are concerned, these can suffer many problems such as temporary saturation, temporary lack of data transmission and anomalous geographical distribution of the rainfall. Recently, satellite data have been employed to quantify the rainfall event related to landslide occurrence but their correlation to the effective rainfall height at a site is not guaranteed yet. So far, rain gauge measures still represent the most used option. Moreover, the physical simplification introduced by such "rainfall based" approach on landslide prediction can be accepted due to the assumption that only shallow landslides are considered for drawing a regional intensity-duration threshold from the considered data. Starting from the above considerations, and within the framework of a nationwide project by CNR-IRPI, under funds from the National Civil Department, the authors propose in this article a new criterion to identify from rain gauge measures the duration of the rainfalls triggering shallow landslides. The new criterion represents an attempt to identify the duration of the "effective rainfall event" responsible for the landslide occurrence, as reported by newspaper clips and/or in real time web newspapers. At this regard, antecedent precipitations are not taken into account, since the model considers only that amount of rainfall that effectively triggers the slope failure. The model analyses the hourly rainfall time series for at least one month before occurrence of the shallow landslide, using a historical landslide archive covering the time range between 2002 and 2011 in the Lazio Region, central Italy. This archive was obtained by a procedure consisting of the following steps: i) critical scrutiny of chronicles, ii) identification of the landslide site, and iii) retrieval of the rainfall data from the nearest rain gauge station within the pluviometric network provided by the National Department of Civil Protection. The proposed method, for each reported landslide, uses the cumulative function of the rainfall heights and rainfall intensity calculated for different time lag. Then, in order to identify the beginning of the effective rainfall event, two conditions have to be satisfied: (1) the difference in rainfall intensity between two adjacent windows must be very low, and (2) the time series of lack of rainfall must be stationary. When these conditions are met, the initial time of the efficient rainfall necessary to trigger the landslide is established. Such criterion is statistically based according to the rainfall time distribution only. No assumption is needed on the probabilistic distributions of time series of rain/not rain. Such approach has been successfully applied to medium-to-long rainfalls, for which rain/not rain datasets are statistically significant. Very short rainfall durations (i.e. a few hours), due to the small number of data, are not suitable to this approach, but, on the other hand, their onset is generally easily recognizable by visual inspection of the height pluviometric trends.

Meteorology Assessment of Historic Rainfall for Los Alamos During September 2013

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

Bruggeman, David Alan; Dewart, Jean Marie

2016-02-12

DOE Order 420.1, Facility Safety, requires that site natural phenomena hazards be evaluated every 10 years to support the design of nuclear facilities. The evaluation requires calculating return period rainfall to determine roof loading requirements and flooding potential based on our on-site rainfall measurements. The return period rainfall calculations are done based on statistical techniques and not site-specific meteorology. This and future studies analyze the meteorological factors that produce the significant rainfall events. These studies provide the meteorology context of the return period rainfall events.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Validation of satellite-based rainfall in Kalahari

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Impacts of the seasonal distribution of rainfall on vegetation productivity across the Sahel

NASA Astrophysics Data System (ADS)

Zhang, Wenmin; Brandt, Martin; Tong, Xiaoye; Tian, Qingjiu; Fensholt, Rasmus

2018-01-01

Climate change in drylands has caused alterations in the seasonal distribution of rainfall including increased heavy-rainfall events, longer dry spells, and a shifted timing of the wet season. Yet the aboveground net primary productivity (ANPP) in drylands is usually explained by annual-rainfall sums, disregarding the influence of the seasonal distribution of rainfall. This study tested the importance of rainfall metrics in the wet season (onset and cessation of the wet season, number of rainy days, rainfall intensity, number of consecutive dry days, and heavy-rainfall events) for growing season ANPP. We focused on the Sahel and northern Sudanian region (100-800 mm yr-1) and applied daily satellite-based rainfall estimates (CHIRPS v2.0) and growing-season-integrated normalized difference vegetation index (NDVI; MODIS) as a proxy for ANPP over the study period: 2001-2015. Growing season ANPP in the arid zone (100-300 mm yr-1) was found to be rather insensitive to variations in the seasonal-rainfall metrics, whereas vegetation in the semi-arid zone (300-700 mm yr-1) was significantly impacted by most metrics, especially by the number of rainy days and timing (onset and cessation) of the wet season. We analysed critical breakpoints for all metrics to test if vegetation response to changes in a given rainfall metric surpasses a threshold beyond which vegetation functioning is significantly altered. It was shown that growing season ANPP was particularly negatively impacted after > 14 consecutive dry days and that a rainfall intensity of ˜ 13 mm day-1 was detected for optimum growing season ANPP. We conclude that the number of rainy days and the timing of the wet season are seasonal-rainfall metrics that are decisive for favourable vegetation growth in the semi-arid Sahel and need to be considered when modelling primary productivity from rainfall in the drylands of the Sahel and elsewhere.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

Li, S.; Elison Timm, O.

2017-12-01

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

Implications of climate change on landslide hazard in Central Italy.

PubMed

Alvioli, Massimiliano; Melillo, Massimo; Guzzetti, Fausto; Rossi, Mauro; Palazzi, Elisa; von Hardenberg, Jost; Brunetti, Maria Teresa; Peruccacci, Silvia

2018-07-15

The relation between climate change and its potential effects on the stability of slopes remains an open issue. For rainfall induced landslides, the point consists in determining the effects of the projected changes in the duration and amounts of rainfall that can initiate slope failures. We investigated the relationship between fine-scale climate projections obtained by downscaling and the expected modifications in landslide occurrence in Central Italy. We used rainfall measurements taken by 56 rain gauges in the 9-year period 2003-2011, and the RainFARM technique to generate downscaled synthetic rainfall fields from regional climate model projections for the 14-year calibration period 2002-2015, and for the 40-year projection period 2010-2049. Using a specific algorithm, we extracted a number of rainfall events, i.e. rainfall periods separated by dry periods of no or negligible amount of rain, from the measured and the synthetic rainfall series. Then, we used the selected rainfall events to forcethe Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model TRIGRS v. 2.1. We analyzed the results in terms of variations (or lack of variations) in the rainfall thresholds for the possible initiation of landslides, in the probability distribution of landslide size (area), and in landslide hazard. Results showed that the downscaled rainfall fields obtained by RainFARM can be used to single out rainfall events, and to force the slope stability model. Results further showed that while the rainfall thresholds for landslide occurrence are expected to change in future scenarios, the probability distribution of landslide areas are not. We infer that landslide hazard in the study area is expected to change in response to the projected variations in the rainfall conditions. We expect our results to contribute to regional investigations of the expected impact of projected climate variations on slope stability conditions and on landslide hazards. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

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

PubMed

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

2017-10-15

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

Encounter risk analysis of rainfall and reference crop evapotranspiration in the irrigation district

NASA Astrophysics Data System (ADS)

Zhang, Jinping; Lin, Xiaomin; Zhao, Yong; Hong, Yang

2017-09-01

Rainfall and reference crop evapotranspiration are random but mutually affected variables in the irrigation district, and their encounter situation can determine water shortage risks under the contexts of natural water supply and demand. However, in reality, the rainfall and reference crop evapotranspiration may have different marginal distributions and their relations are nonlinear. In this study, based on the annual rainfall and reference crop evapotranspiration data series from 1970 to 2013 in the Luhun irrigation district of China, the joint probability distribution of rainfall and reference crop evapotranspiration are developed with the Frank copula function. Using the joint probability distribution, the synchronous-asynchronous encounter risk, conditional joint probability, and conditional return period of different combinations of rainfall and reference crop evapotranspiration are analyzed. The results show that the copula-based joint probability distributions of rainfall and reference crop evapotranspiration are reasonable. The asynchronous encounter probability of rainfall and reference crop evapotranspiration is greater than their synchronous encounter probability, and the water shortage risk associated with meteorological drought (i.e. rainfall variability) is more prone to appear. Compared with other states, there are higher conditional joint probability and lower conditional return period in either low rainfall or high reference crop evapotranspiration. For a specifically high reference crop evapotranspiration with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is increased with the decrease in frequency. For a specifically low rainfall with a certain frequency, the encounter risk of low rainfall and high reference crop evapotranspiration is decreased with the decrease in frequency. When either the high reference crop evapotranspiration exceeds a certain frequency or low rainfall does not exceed a certain frequency, the higher conditional joint probability and lower conditional return period of various combinations likely cause a water shortage, but the water shortage is not severe.

Runoff process in the Miyake-jima Island after Eruption in 2000

NASA Astrophysics Data System (ADS)

Tagata, Satoshi; Itoh, Takahiro; Miyamoto, Kuniaki; Ishizuka, Tadanori

2014-05-01

Hydrological environment in a basin can be changed completely due to volcanic eruption. Huge volume of tephra was yielded due to eruptions in 2000 in the Miyake-jima Island, Japan. Hydrological monitoring was conducted at four observation sites with several hundred m2 in a basin. Those were decided by the distribution of thickness and the grain size of the tephra. Rainfall intensity was measured by a tipping bucket type raingauge and flow discharge was calculated by the over flow depth in a flow gauging weir in the monitoring. However, the runoff rate did not relate to the grain size of tephra and the thickness of tephra deposition, according to measured data of rainfall intensity and runoff discharge. Supposing that if total runoff in one rainfall event is equal to the summation of rainfall over a threshold, the value of the threshold must be the loss rainfall intensity, the value of the threshold corresponds to the infiltration for the rainfall intensity. The relationships between loss rainfall intensity and the antecedent precipitation are calculated using measured rainfall and runoff data in every rainfall event, focusing on that the antecedent precipitation before occurrence of surface runoff approximately corresponds to the water contents under the slope surface. In present study, the results obtained through data analyses are summarized as follows: (1) There are some values for the threshold values, and the loss rainfall intensity approaches to some constant value if the value of the antecedent precipitation increases. The constant value corresponds to the saturated infiltration. (2) The loss rainfall intensity must be vertical unsaturated infiltration, and observed data for water runoff can express that the runoff is given by the excess rainfall intensity more than the loss rainfall intensity. (3) There are two antecedent times for rainfall with several hours and several days, and the saturation ratio before antecedent time at four observation sites can be predicted in the range from sixty to ninety percentages by the water retention curve.

Sensitivity of Rainfall Extremes Under Warming Climate in Urban India

NASA Astrophysics Data System (ADS)

Ali, H.; Mishra, V.

2017-12-01

Extreme rainfall events in urban India halted transportation, damaged infrastructure, and affected human lives. Rainfall extremes are projected to increase under the future climate. We evaluated the relationship (scaling) between rainfall extremes at different temporal resolutions (daily, 3-hourly, and 30 minutes), daily dewpoint temperature (DPT) and daily air temperature at 850 hPa (T850) for 23 urban areas in India. Daily rainfall extremes obtained from Global Surface Summary of Day Data (GSOD) showed positive regression slopes for most of the cities with median of 14%/K for the period of 1979-2013 for DPT and T850, which is higher than Clausius-Clapeyron (C-C) rate ( 7%). Moreover, sub-daily rainfall extremes are more sensitive to both DPT and T850. For instance, 3-hourly rainfall extremes obtained from Tropical Rainfall Measurement Mission (TRMM 3B42 V7) showed regression slopes more than 16%/K aginst DPT and T850 for the period of 1998-2015. Half-hourly rainfall extremes from the Integrated Multi-satellitE Retrievals (IMERGE) of Global precipitation mission (GPM) also showed higher sensitivity against changes in DPT and T850. The super scaling of rainfall extremes against changes in DPT and T850 can be attributed to convective nature of precipitation in India. Our results show that urban India may witness non-stationary rainfall extremes, which, in turn will affect stromwater designs and frequency and magniture of urban flooding.

Design and development of surface rainfall forecast products on GRAPES_MESO model

NASA Astrophysics Data System (ADS)

Zhili, Liu

2016-04-01

In this paper, we designed and developed the surface rainfall forecast products using medium scale GRAPES_MESO model precipitation forecast products. The horizontal resolution of GRAPES_MESO model is 10km*10km, the number of Grids points is 751*501, vertical levels is 26, the range is 70°E－145.15°E, 15°N－64.35 °N. We divided the basin into 7 major watersheds. Each watersheds was divided into a number of sub regions. There were 95 sub regions in all. Tyson polygon method is adopted in the calculation of surface rainfall. We used 24 hours forecast precipitation data of GRAPES_MESO model to calculate the surface rainfall. According to the site of information and boundary information of the 95 sub regions, the forecast surface rainfall of each sub regions was calculated. We can provide real-time surface rainfall forecast products every day. We used the method of fuzzy evaluation to carry out a preliminary test and verify about the surface rainfall forecast product. Results shows that the fuzzy score of heavy rain, rainstorm and downpour level forecast rainfall were higher, the fuzzy score of light rain level was lower. The forecast effect of heavy rain, rainstorm and downpour level surface rainfall were better. The rate of missing and empty forecast of light rainfall level surface rainfall were higher, so it's fuzzy score were lower.

Convective rainfall estimation from digital GOES-1 infrared data

NASA Technical Reports Server (NTRS)

Sickler, G. L.; Thompson, A. H.

1979-01-01

An investigation was conducted to determine the feasibility of developing and objective technique for estimating convective rainfall from digital GOES-1 infrared data. The study area was a 240 km by 240 km box centered on College Station, Texas (Texas A and M University). The Scofield and Oliver (1977) rainfall estimation scheme was adapted and used with the digital geostationary satellite data. The concept of enhancement curves with respect to rainfall approximation is discussed. Raingage rainfall analyses and satellite-derived rainfall estimation analyses were compared. The correlation for the station data pairs (observed versus estimated rainfall amounts) for the convective portion of the storm was 0.92. It was demonstrated that a fairly accurate objective rainfall technique using digital geostationary infrared satellite data is feasible. The rawinsonde and some synoptic data that were used in this investigation came from NASA's Atmospheric Variability Experiment, AVE 7.

A Diagnosis of Rainfall over South America during the 1997/98 El Niño Event. Part I: Validation of NCEP-NCAR Reanalysis Rainfall Data.

NASA Astrophysics Data System (ADS)

Brahmananda Rao, V.; Santo, Clóvis E.; Franchito, Sergio H.

2002-03-01

A comparison between the National Centers for Environmental Predictions-National Center for Atmospheric Research (NCEP-NCAR) reanalysis rainfall data and the Agência Nacional de Energia Elétrica (ANEEL) rain gauge data over Brazil is made. It is found that over northeast Brazil, NCEP-NCAR rainfall is overestimated. But over south and southeast Brazil, the correlation between the two datasets is highly significant showing the utility of NCEP-NCAR rainfall data. Over other parts of Brazil the validity of NCEP-NCAR rainfall data is questionable. A detailed comparison between NCEP-NCAR rainfall data over northwest South America and rain gauge data showed that NCEP-NCAR rainfall data are useful despite important differences between the characteristics in the two data sources. NCEP-NCAR reanalysis data seem to have difficulty in correctly reproducing the strength and orientation of the South Atlantic convergence zone.

Two Distinct Modes in One-Day Rainfall Event during MC3E Field Campaign: Analyses of Disdrometer Observations and WRF-SBM Simulation

NASA Technical Reports Server (NTRS)

Iguchi, Takamichi; Matsui, Toshihisa; Tokay, Ali; Kollias, Pavlos; Tao, Wei-Kuo

2012-01-01

A unique microphysical structure of rainfall is observed by the surface laser optical Particle Size and Velocity (Parsivel) disdrometers on 25 April 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E). According to the systematic differences in rainfall rate and bulk effective droplet radius, the sampling data can be divided into two groups; the rainfall mostly from the deep convective clouds has relatively high rainfall rate and large bulk effective droplet radius, whereas the reverse is true for the rainfall from the shallow wrm clouds. The Weather Research and Forecasting model coupled with spectral bin microphysics (WRF-SBM) successfully reproduces the two distinct modes in the observed rainfall microphysical structure. The results show that the up-to-date model can demonstrate how the cloud physics and the weather condition on the day are involved in forming the unique rainfall characteristic.

Darfur: rainfall and conflict

NASA Astrophysics Data System (ADS)

Kevane, Michael; Gray, Leslie

2008-07-01

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

Tropical cyclone rainfall area controlled by relative sea surface temperature

PubMed Central

Lin, Yanluan; Zhao, Ming; Zhang, Minghua

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

On storm movement and its applications

NASA Astrophysics Data System (ADS)

Niemczynowicz, Janusz

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

Two distinct modes in one-day rainfall event during MC3E field campaign: Analyses of disdrometer observations and WRF-SBM simulation

NASA Astrophysics Data System (ADS)

Iguchi, Takamichi; Matsui, Toshihisa; Tokay, Ali; Kollias, Pavlos; Tao, Wei-Kuo

2012-12-01

A unique microphysical structure of rainfall is observed by the surface laser optical Particle Size and Velocity (Parsivel) disdrometers on 25 April 2011 during Midlatitude Continental Convective Clouds Experiment (MC3E). According to the systematic differences in rainfall rate and bulk effective droplet radius, the sampling data can be divided into two groups; the rainfall mostly from the deep convective clouds has relatively high rainfall rate and large bulk effective droplet radius, whereas the reverse is true for the rainfall from the shallow warm clouds. The Weather Research and Forecasting model coupled with spectral bin microphysics (WRF-SBM) successfully reproduces the two distinct modes in the observed rainfall microphysical structure. The results show that the up-to-date model can demonstrate how the cloud physics and the weather condition on the day are involved in forming the unique rainfall characteristic.

Estimation of the fractional coverage of rainfall in climate models

NASA Technical Reports Server (NTRS)

Eltahir, E. A. B.; Bras, R. L.

1993-01-01

The fraction of the grid cell area covered by rainfall, mu, is an essential parameter in descriptions of land surface hydrology in climate models. A simple procedure is presented for estimating this fraction, based on extensive observations of storm areas and rainfall volumes. Storm area and rainfall volume are often linearly related; this relation can be used to compute the storm area from the volume of rainfall simulated by a climate model. A formula is developed for computing mu, which describes the dependence of the fractional coverage of rainfall on the season of the year, the geographical region, rainfall volume, and the spatial and temporal resolution of the model. The new formula is applied in computing mu over the Amazon region. Significant temporal variability in the fractional coverage of rainfall is demonstrated. The implications of this variability for the modeling of land surface hydrology in climate models are discussed.

Regional rainfall thresholds for landslide occurrence using a centenary database

NASA Astrophysics Data System (ADS)

Vaz, Teresa; Luís Zêzere, José; Pereira, Susana; Cruz Oliveira, Sérgio; Quaresma, Ivânia

2017-04-01

Rainfall is one of the most important triggering factors for landslides occurrence worldwide. The relation between rainfall and landslide occurrence is complex and some approaches have been focus on the rainfall thresholds identification, i.e., rainfall critical values that when exceeded can initiate landslide activity. In line with these approaches, this work proposes and validates rainfall thresholds for the Lisbon region (Portugal), using a centenary landslide database associated with a centenary daily rainfall database. The main objectives of the work are the following: i) to compute antecedent rainfall thresholds using linear and potential regression; ii) to define lower limit and upper limit rainfall thresholds; iii) to estimate the probability of critical rainfall conditions associated with landslide events; and iv) to assess the thresholds performance using receiver operating characteristic (ROC) metrics. In this study we consider the DISASTER database, which lists landslides that caused fatalities, injuries, missing people, evacuated and homeless people occurred in Portugal from 1865 to 2010. The DISASTER database was carried out exploring several Portuguese daily and weekly newspapers. Using the same newspaper sources, the DISASTER database was recently updated to include also the landslides that did not caused any human damage, which were also considered for this study. The daily rainfall data were collected at the Lisboa-Geofísico meteorological station. This station was selected considering the quality and completeness of the rainfall data, with records that started in 1864. The methodology adopted included the computation, for each landslide event, of the cumulative antecedent rainfall for different durations (1 to 90 consecutive days). In a second step, for each combination of rainfall quantity-duration, the return period was estimated using the Gumbel probability distribution. The pair (quantity-duration) with the highest return period was considered as the critical rainfall combination responsible for triggering the landslide event. Only events whose critical rainfall combinations have a return period above 3 years were included. This criterion reduces the likelihood of been included events whose triggering factor was other than rainfall. The rainfall quantity-duration threshold for the Lisbon region was firstly defined using the linear and potential regression. Considering that this threshold allow the existence of false negatives (i.e. events below the threshold) it was also identified the lower limit and upper limit rainfall thresholds. These limits were defined empirically by establishing the quantity-durations combinations bellow which no landslides were recorded (lower limit) and the quantity-durations combinations above which only landslides were recorded without any false positive occurrence (upper limit). The zone between the lower limit and upper limit rainfall thresholds was analysed using a probabilistic approach, defining the uncertainties of each rainfall critical conditions in the triggering of landslides. Finally, the performances of the thresholds obtained in this study were assessed using ROC metrics. This work was supported by the project FORLAND - Hydrogeomorphologic risk in Portugal: driving forces and application for land use planning [grant number PTDC/ATPGEO/1660/2014] funded by the Portuguese Foundation for Science and Technology (FCT), Portugal. Sérgio Cruz Oliveira is a post-doc fellow of the FCT [grant number SFRH/BPD/85827/2012].

Measuring dynamic infiltration rates during rainfall of fluctuating intensity: an approach using affine Horton equations.

NASA Astrophysics Data System (ADS)

Dunkerley, David

2017-04-01

It is important to develop methods for determining infiltrability and infiltration rates under conditions of fluctuating rainfall intensity, since rainfall intensity rarely remains constant. During rain of fluctuating intensity, ponding deepens and dissipates, and the drivers of soil infiltration, including sorptivity, fluctuate in value. This has been explored on dryland soils in the field, using small plots and rainfall simulation, involving repeated changes in intensity as well as short and long hiatuses in rainfall. The field area was the Fowlers Gap Arid Zone Research Station, in western NSW, Australia. The field experiments used multiple 60 minute design rainfall events that all had the same total depth and average rainfall intensity, but which included intensity bursts at various positions within the event. These were based on the character of local rainfall events in the field area. Infiltration was found from plot runoff rates measured every 2 minutes, and rainfall intensities that were adjusted by computer-controlled pumps at 1 second intervals. Data were analysed by fitting a family of affine Horton equations, all having the same final infiltrability (about 6-7 mm/h) but having initial infiltrabilities and exponential decay constants that were permitted to recover during periods of very low intensity rain, or rainfall hiatuses. Results show that the terms in the Horton equation, f0, fc, and Kf, can all be estimated from field data of the kind collected. This is a considerable advance over 'steady-state' rainfall simulation methods, which typically only allow the estimation of the final infiltrability fc. This may rarely be reached owing to the occurrence of short rainfall events, or to changing intensity under natural rainfall, that prohibits the establishment of steady-state infiltration and runoff. Importantly, this method allows a focus on the recovery of infiltrability during periods of reduced rainfall intensity. Recovery of infiltrability is shown to proceed at rates of up to 1 mm/h per minute of hiatus time, or by 20 mm/h during a 20 minute period of low rainfall intensity.

Relationships between Tropical Rainfall Events and Regional Annual Rainfall Anomalies

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

NASA Astrophysics Data System (ADS)

Engida, Agizew N.; Esteves, Michel

2011-03-01

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

Automated reconstruction of rainfall events responsible for shallow landslides

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

Interpolating precipitation and its relation to runoff and non-point source pollution.

PubMed

Chang, Chia-Ling; Lo, Shang-Lien; Yu, Shaw-L

2005-01-01

When rainfall spatially varies, complete rainfall data for each region with different rainfall characteristics are very important. Numerous interpolation methods have been developed for estimating unknown spatial characteristics. However, no interpolation method is suitable for all circumstances. In this study, several methods, including the arithmetic average method, the Thiessen Polygons method, the traditional inverse distance method, and the modified inverse distance method, were used to interpolate precipitation. The modified inverse distance method considers not only horizontal distances but also differences between the elevations of the region with no rainfall records and of its surrounding rainfall stations. The results show that when the spatial variation of rainfall is strong, choosing a suitable interpolation method is very important. If the rainfall is uniform, the precipitation estimated using any interpolation method would be quite close to the actual precipitation. When rainfall is heavy in locations with high elevation, the rainfall changes with the elevation. In this situation, the modified inverse distance method is much more effective than any other method discussed herein for estimating the rainfall input for WinVAST to estimate runoff and non-point source pollution (NPSP). When the spatial variation of rainfall is random, regardless of the interpolation method used to yield rainfall input, the estimation errors of runoff and NPSP are large. Moreover, the relationship between the relative error of the predicted runoff and predicted pollutant loading of SS is high. However, the pollutant concentration is affected by both runoff and pollutant export, so the relationship between the relative error of the predicted runoff and the predicted pollutant concentration of SS may be unstable.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Demographic patterns of a widespread long-lived tree are associated with rainfall and disturbances along rainfall gradients in SE Australia

PubMed Central

Cohn, Janet S; Lunt, Ian D; Bradstock, Ross A; Hua, Quan; McDonald, Simon

2013-01-01

Predicting species distributions with changing climate has often relied on climatic variables, but increasingly there is recognition that disturbance regimes should also be included in distribution models. We examined how changes in rainfall and disturbances along climatic gradients determined demographic patterns in a widespread and long-lived tree species, Callitris glaucophylla in SE Australia. We examined recruitment since 1950 in relation to annual (200–600 mm) and seasonal (summer, uniform, winter) rainfall gradients, edaphic factors (topography), and disturbance regimes (vertebrate grazing [tenure and species], fire). A switch from recruitment success to failure occurred at 405 mm mean annual rainfall, coincident with a change in grazing regime. Recruitment was lowest on farms with rabbits below 405 mm rainfall (mean = 0–0.89 cohorts) and highest on less-disturbed tenures with no rabbits above 405 mm rainfall (mean = 3.25 cohorts). Moderate levels of recruitment occurred where farms had no rabbits or less disturbed tenures had rabbits above and below 405 mm rainfall (mean = 1.71–1.77 cohorts). These results show that low annual rainfall and high levels of introduced grazing has led to aging, contracting populations, while higher annual rainfall with low levels of grazing has led to younger, expanding populations. This study demonstrates how demographic patterns vary with rainfall and spatial variations in disturbances, which are linked in complex ways to climatic gradients. Predicting changes in tree distribution with climate change requires knowledge of how rainfall and key disturbances (tenure, vertebrate grazing) will shift along climatic gradients. PMID:23919160

Estimation of rainfall using remote sensing for Riyadh climate, KSA

NASA Astrophysics Data System (ADS)

AlHassoun, Saleh A.

2013-05-01

Rainfall data constitute an important parameter for studying water resources-related problems. Remote sensing techniques could provide rapid and comprehensive overview of the rainfall distribution in a given area. Thus, the infrared data from the LandSat satellite in conjunction with the Scofield-oliver method were used to monitor and model rainfall in Riyadh area as a resemble of any area in the Kingdom of Saudi Arabia(KSA). Four convective clouds that covered two rain gage stations were analyzed. Good estimation of rainfall was obtained from satellite images. The results showed that the satellite rainfall estimations were well correlated to rain gage measurements. The satellite climate data appear to be useful for monitoring and modeling rainfall at any area where no rain gage is available.

Rainfall statistics changes in Sicily

NASA Astrophysics Data System (ADS)

Arnone, E.; Pumo, D.; Viola, F.; Noto, L. V.; La Loggia, G.

2013-07-01

Changes in rainfall characteristics are one of the most relevant signs of current climate alterations. Many studies have demonstrated an increase in rainfall intensity and a reduction of frequency in several areas of the world, including Mediterranean areas. Rainfall characteristics may be crucial for vegetation patterns formation and evolution in Mediterranean ecosystems, with important implications, for example, in vegetation water stress or coexistence and competition dynamics. At the same time, characteristics of extreme rainfall events are fundamental for the estimation of flood peaks and quantiles that can be used in many hydrological applications, such as design of the most common hydraulic structures, or planning and management of flood-prone areas. In the past, Sicily has been screened for several signals of possible climate change. Annual, seasonal and monthly rainfall data in the entire Sicilian region have been analyzed, showing a global reduction of total annual rainfall. Moreover, annual maximum rainfall series for different durations have been rarely analyzed in order to detect the presence of trends. Results indicated that for short durations, historical series generally exhibit increasing trends, while for longer durations the trends are mainly negative. Starting from these premises, the aim of this study is to investigate and quantify changes in rainfall statistics in Sicily, during the second half of the last century. Time series of about 60 stations over the region have been processed and screened by using the nonparametric Mann-Kendall test. In particular, extreme events have been analyzed using annual maximum rainfall series at 1, 3, 6, 12 and 24 h duration, while daily rainfall properties have been analyzed in terms of frequency and intensity, also characterizing seasonal rainfall features. Results of extreme events analysis confirmed an increasing trend for rainfall of short durations, especially for 1 h rainfall duration. Conversely, precipitation events of long durations have exhibited a decreased trend. Increase in short-duration precipitation has been observed especially in stations located along the coastline; however, no clear and well-defined spatial pattern has been outlined by the results. Outcomes of analysis for daily rainfall properties have showed that heavy-torrential precipitation events tend to be more frequent at regional scale, while light rainfall events exhibited a negative trend at some sites. Values of total annual precipitation events confirmed a significant negative trend, mainly due to the reduction during the winter season.

Using CHIRPS Rainfall Dataset to detect rainfall trends in West Africa

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

The capacity of radar, crowdsourced personal weather stations and commercial microwave links to monitor small scale urban rainfall

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; de Vos, L. W.; Leijnse, H.; Overeem, A.; Raupach, T. H.; Berne, A.

2017-12-01

For the purpose of urban rainfall monitoring high resolution rainfall measurements are desirable. Typically C-band radar can provide rainfall intensities at km grid cells every 5 minutes. Opportunistic sensing with commercial microwave links yields rainfall intensities over link paths within cities. Additionally, recent developments have made it possible to obtain large amounts of urban in situ measurements from weather amateurs in near real-time. With a known high resolution simulated rainfall event the accuracy of these three techniques is evaluated, taking into account their respective existing layouts and sampling methods. Under ideal measurement conditions, the weather station networks proves to be most promising. For accurate estimation with radar, an appropriate choice for Z-R relationship is vital. Though both the microwave links and the weather station networks are quite dense, both techniques will underestimate rainfall if not at least one link path / station captures the high intensity rainfall peak. The accuracy of each technique improves when considering rainfall at larger scales, especially by increasing time intervals, with the steepest improvements found in microwave links.

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

NASA Astrophysics Data System (ADS)

Rochyani, Neny

2017-11-01

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

A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa

NASA Astrophysics Data System (ADS)

Maidment, Ross I.; Grimes, David; Black, Emily; Tarnavsky, Elena; Young, Matthew; Greatrex, Helen; Allan, Richard P.; Stein, Thorwald; Nkonde, Edson; Senkunda, Samuel; Alcántara, Edgar Misael Uribe

2017-05-01

Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets.

Rainfall thresholds as a landslide indicator for engineered slopes on the Irish Rail network

NASA Astrophysics Data System (ADS)

Martinović, Karlo; Gavin, Kenneth; Reale, Cormac; Mangan, Cathal

2018-04-01

Rainfall thresholds express the minimum levels of rainfall that need to be reached or exceeded in order for landslides to occur in a particular area. They are a common tool in expressing the temporal portion of landslide hazard analysis. Numerous rainfall thresholds have been developed for different areas worldwide, however none of these are focused on landslides occurring on the engineered slopes on transport infrastructure networks. This paper uses empirical method to develop the rainfall thresholds for landslides on the Irish Rail network earthworks. For comparison, rainfall thresholds are also developed for natural terrain in Ireland. The results show that particular thresholds involving relatively low rainfall intensities are applicable for Ireland, owing to the specific climate. Furthermore, the comparison shows that rainfall thresholds for engineered slopes are lower than those for landslides occurring on the natural terrain. This has severe implications as it indicates that there is a significant risk involved when using generic weather alerts (developed largely for natural terrain) for infrastructure management, and showcases the need for developing railway and road specific rainfall thresholds for landslides.

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

PubMed

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

2013-01-01

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

Evaluation of different rainfall products over India for the summer monsoon

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mitra, Ashis; Turner, Andrew; Collins, Mathew; AchutoRao, Krishna

2015-04-01

Summer rainfall over India forms an integral part of the Asian monsoon, which plays a key role in the global water cycle and climate system through coupled atmospheric and oceanic processes. Accurate prediction of Indian summer monsoon rainfall and its variability at various spatiotemporal scales are crucial for agriculture, water resources and hydroelectric-power sectors. Reliable rainfall observations are very important for verification of numerical model outputs and model development. However, high spatiotemporal variability of rainfall makes it difficult to measure adequately with ground-based instruments over a large region of various surface types from deserts to oceans. A number of multi-satellite rainfall products are available to users at different spatial and temporal scales. Each rainfall product has some advantages as well as limitations, hence it is essential to find a suitable region-specific data set among these rainfall products for a particular user application, such as water resources, agricultural modelling etc. In this study, we examine seasonal-mean and daily rainfall datasets for monsoon model validation. First, six multi-satellite and gauge-only rainfall products were evaluated over India at seasonal scale for 27 (JJAS 1979-2005) summer monsoon seasons against gridded 0.5-degree IMD gauge-based rainfall. Various skill metrics are computed to assess the potential of these data sets in representation of large-scale monsoon rainfall at all-India and sub-regional scales. Among the gauge-only data sets, APHRODITE and GPCC appear to outperform the others whereas GPCP is better than CMAP in the merged multi-satellite category. However, there are significant differences among these data sets indicating uncertainty in the observed rainfall over this region, with important implications for the evaluation of model simulations. At the daily scale, TRMM TMPA-3B42 is one of the best available products and is widely used for various hydro-meteorological applications. The existing version 6 (V6) products of TRMM underwent major changes and version 7 (V7) products were released in late 2012, and we compare these to the IMD daily gridded data over the 1998-2010 period. We show a clear improvement in V7 over V6 in the South Asian monsoon region using various skill metrics. Over typical monsoon rainfall zones, biases are improved by 5-10% in V7 over higher-rainfall regions. These results will help users to select appropriate rainfall product for their application. With the recent launch of the GPM Core Observatory, the release of a more advanced high-resolution multi-satellite rainfall product is expected soon.

Trends in autumn rain of West China from 1961 to 2014

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

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

2008-04-01

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

Distributional changes in rainfall and river flow in Sarawak, Malaysia

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Global rainfall erosivity assessment based on high-temporal resolution rainfall records.

PubMed

Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Yu, Bofu; Klik, Andreas; Jae Lim, Kyoung; Yang, Jae E; Ni, Jinren; Miao, Chiyuan; Chattopadhyay, Nabansu; Sadeghi, Seyed Hamidreza; Hazbavi, Zeinab; Zabihi, Mohsen; Larionov, Gennady A; Krasnov, Sergey F; Gorobets, Andrey V; Levi, Yoav; Erpul, Gunay; Birkel, Christian; Hoyos, Natalia; Naipal, Victoria; Oliveira, Paulo Tarso S; Bonilla, Carlos A; Meddi, Mohamed; Nel, Werner; Al Dashti, Hassan; Boni, Martino; Diodato, Nazzareno; Van Oost, Kristof; Nearing, Mark; Ballabio, Cristiano

2017-06-23

The exposure of the Earth's surface to the energetic input of rainfall is one of the key factors controlling water erosion. While water erosion is identified as the most serious cause of soil degradation globally, global patterns of rainfall erosivity remain poorly quantified and estimates have large uncertainties. This hampers the implementation of effective soil degradation mitigation and restoration strategies. Quantifying rainfall erosivity is challenging as it requires high temporal resolution(<30 min) and high fidelity rainfall recordings. We present the results of an extensive global data collection effort whereby we estimated rainfall erosivity for 3,625 stations covering 63 countries. This first ever Global Rainfall Erosivity Database was used to develop a global erosivity map at 30 arc-seconds(~1 km) based on a Gaussian Process Regression(GPR). Globally, the mean rainfall erosivity was estimated to be 2,190 MJ mm ha -1 h -1 yr -1 , with the highest values in South America and the Caribbean countries, Central east Africa and South east Asia. The lowest values are mainly found in Canada, the Russian Federation, Northern Europe, Northern Africa and the Middle East. The tropical climate zone has the highest mean rainfall erosivity followed by the temperate whereas the lowest mean was estimated in the cold climate zone.

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

NASA Technical Reports Server (NTRS)

Rodgers, Edward; Pierce, Harold; Adler, Robert

1999-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A dipole pattern of summertime rainfall across the Indian subcontinent and the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Jiang, X.; Ting, M.

2017-12-01

The Tibetan Plateau (TP) has long been regarded as a key driver for the formation and variations of the Indian summer monsoon (ISM). Recent studies, however, indicated that the ISM also exerts a considerable impact on rainfall variations in the TP, suggesting that the ISM and the TP should be considered as an interactive system. From this perspective, we investigate the co-variability of the July-August mean rainfall across the Indian subcontinent (IS) and the TP. We found that the interannual variation of IS and TP rainfall exhibits a dipole pattern in which rainfall in the central and northern IS tends to be out of phase with that in the southeastern TP. This dipole pattern is associated with significant anomalies in rainfall, atmospheric circulation, and water vapor transport over the Asian continent and nearby oceans. Rainfall anomalies and the associated latent heating in the central and northern IS tend to induce changes in regional circulation -that suppress rainfall in the southeastern TP and vice versa. Furthermore, the sea surface temperature anomalies in the tropical southeastern Indian Ocean can trigger the dipole rainfall pattern by suppressing convection over the central IS and the northern Bay of Bengal, which further induces anomalous anticyclonic circulation to the south of TP that favors more rainfall in the southeastern TP by transporting more water vapor to the region. The dipole pattern is also linked to the Silk-Road wave train due to its link to rainfall over the northwestern IS.

Effects of rainfall spatial variability and intermittency on shallow landslide triggering patterns at a catchment scale

NASA Astrophysics Data System (ADS)

von Ruette, J.; Lehmann, P.; Or, D.

2014-10-01

The occurrence of shallow landslides is often associated with intense and prolonged rainfall events, where infiltrating water reduces soil strength and may lead to abrupt mass release. Despite general understanding of the role of rainfall water in slope stability, the prediction of rainfall-induced landslides remains a challenge due to natural heterogeneity that affect hydrologic loading patterns and the largely unobservable internal progressive failures. An often overlooked and potentially important factor is the role of rainfall variability in space and time on landslide triggering that is often obscured by coarse information (e.g., hourly radar data at spatial resolution of a few kilometers). To quantify potential effects of rainfall variability on failure dynamics, spatial patterns, landslide numbers and volumes, we employed a physically based "Catchment-scale Hydromechanical Landslide Triggering" (CHLT) model for a study area where a summer storm in 2002 triggered 51 shallow landslides. In numerical experiments based on the CHLT model, we applied the measured rainfall amount of 53 mm in different artificial spatiotemporal rainfall patterns, resulting in between 30 and 100 landslides and total released soil volumes between 3000 and 60,000 m3 for the various scenarios. Results indicate that low intensity rainfall below soil's infiltration capacity resulted in the largest mechanical perturbation. This study illustrates how small-scale rainfall variability that is often overlooked by present operational rainfall data may play a key role in shaping landslide patterns.

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

NASA Astrophysics Data System (ADS)

Akinsanola, A. A.; Zhou, Wen

2018-05-01

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

A Monte-Carlo Bayesian framework for urban rainfall error modelling

NASA Astrophysics Data System (ADS)

Ochoa Rodriguez, Susana; Wang, Li-Pen; Willems, Patrick; Onof, Christian

2016-04-01

Rainfall estimates of the highest possible accuracy and resolution are required for urban hydrological applications, given the small size and fast response which characterise urban catchments. While significant progress has been made in recent years towards meeting rainfall input requirements for urban hydrology -including increasing use of high spatial resolution radar rainfall estimates in combination with point rain gauge records- rainfall estimates will never be perfect and the true rainfall field is, by definition, unknown [1]. Quantifying the residual errors in rainfall estimates is crucial in order to understand their reliability, as well as the impact that their uncertainty may have in subsequent runoff estimates. The quantification of errors in rainfall estimates has been an active topic of research for decades. However, existing rainfall error models have several shortcomings, including the fact that they are limited to describing errors associated to a single data source (i.e. errors associated to rain gauge measurements or radar QPEs alone) and to a single representative error source (e.g. radar-rain gauge differences, spatial temporal resolution). Moreover, rainfall error models have been mostly developed for and tested at large scales. Studies at urban scales are mostly limited to analyses of propagation of errors in rain gauge records-only through urban drainage models and to tests of model sensitivity to uncertainty arising from unmeasured rainfall variability. Only few radar rainfall error models -originally developed for large scales- have been tested at urban scales [2] and have been shown to fail to well capture small-scale storm dynamics, including storm peaks, which are of utmost important for urban runoff simulations. In this work a Monte-Carlo Bayesian framework for rainfall error modelling at urban scales is introduced, which explicitly accounts for relevant errors (arising from insufficient accuracy and/or resolution) in multiple data sources (in this case radar and rain gauge estimates typically available at present), while at the same time enabling dynamic combination of these data sources (thus not only quantifying uncertainty, but also reducing it). This model generates an ensemble of merged rainfall estimates, which can then be used as input to urban drainage models in order to examine how uncertainties in rainfall estimates propagate to urban runoff estimates. The proposed model is tested using as case study a detailed rainfall and flow dataset, and a carefully verified urban drainage model of a small (~9 km2) pilot catchment in North-East London. The model has shown to well characterise residual errors in rainfall data at urban scales (which remain after the merging), leading to improved runoff estimates. In fact, the majority of measured flow peaks are bounded within the uncertainty area produced by the runoff ensembles generated with the ensemble rainfall inputs. REFERENCES: [1] Ciach, G. J. & Krajewski, W. F. (1999). On the estimation of radar rainfall error variance. Advances in Water Resources, 22 (6), 585-595. [2] Rico-Ramirez, M. A., Liguori, S. & Schellart, A. N. A. (2015). Quantifying radar-rainfall uncertainties in urban drainage flow modelling. Journal of Hydrology, 528, 17-28.

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

NASA Astrophysics Data System (ADS)

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.

Relationships between atmospheric circulation indices and rainfall in Northern Algeria and comparison of observed and RCM-generated rainfall

NASA Astrophysics Data System (ADS)

Taibi, S.; Meddi, M.; Mahé, G.; Assani, A.

2017-01-01

This work aims, as a first step, to analyze rainfall variability in Northern Algeria, in particular extreme events, during the period from 1940 to 2010. Analysis of annual rainfall shows that stations in the northwest record a significant decrease in rainfall since the 1970s. Frequencies of rainy days for each percentile (5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th) and each rainfall interval class (1-5, 5-10, 10-20, 20-50, and ≥50 mm) do not show a significant change in the evolution of daily rainfall. The Tenes station is the only one to show a significant decrease in the frequency of rainy days up to the 75th percentile and for the 10-20-mm interval class. There is no significant change in the temporal evolution of extreme events in the 90th, 95th, and 99th percentiles. The relationships between rainfall variability and general atmospheric circulation indices for interannual and extreme event variability are moderately influenced by the El Niño-Southern Oscillation and Mediterranean Oscillation. Significant correlations are observed between the Southern Oscillation Index and annual rainfall in the northwestern part of the study area, which is likely linked with the decrease in rainfall in this region. Seasonal rainfall in Northern Algeria is affected by the Mediterranean Oscillation and North Atlantic Oscillation in the west. The ENSEMBLES regional climate models (RCMs) are assessed using the bias method to test their ability to reproduce rainfall variability at different time scales. The Centre National de Recherches Météorologiques (CNRM), Czech Hydrometeorological Institute (CHMI), Eidgenössische Technische Hochschule Zürich (ETHZ), and Forschungszentrum Geesthacht (GKSS) models yield the least biased results.

A Deep Neural Network Model for Rainfall Estimation UsingPolarimetric WSR-88DP Radar Observations

NASA Astrophysics Data System (ADS)

Tan, H.; Chandra, C. V.; Chen, H.

2016-12-01

Rainfall estimation based on radar measurements has been an important topic for a few decades. Generally, radar rainfall estimation is conducted through parametric algorisms such as reflectivity-rainfall relation (i.e., Z-R relation). On the other hand, neural networks are developed for ground rainfall estimation based on radar measurements. This nonparametric method, which takes into account of both radar observations and rainfall measurements from ground rain gauges, has been demonstrated successfully for rainfall rate estimation. However, the neural network-based rainfall estimation is limited in practice due to the model complexity and structure, data quality, as well as different rainfall microphysics. Recently, the deep learning approach has been introduced in pattern recognition and machine learning areas. Compared to traditional neural networks, the deep learning based methodologies have larger number of hidden layers and more complex structure for data representation. Through a hierarchical learning process, the high level structured information and knowledge can be extracted automatically from low level features of the data. In this paper, we introduce a novel deep neural network model for rainfall estimation based on ground polarimetric radar measurements .The model is designed to capture the complex abstractions of radar measurements at different levels using multiple layers feature identification and extraction. The abstractions at different levels can be used independently or fused with other data resource such as satellite-based rainfall products and/or topographic data to represent the rain characteristics at certain location. In particular, the WSR-88DP radar and rain gauge data collected in Dallas - Fort Worth Metroplex and Florida are used extensively to train the model, and for demonstration purposes. Quantitative evaluation of the deep neural network based rainfall products will also be presented, which is based on an independent rain gauge network.

Regional frequency analysis of extreme rainfall for the Baltimore Metropolitan region based on stochastic storm transposition

NASA Astrophysics Data System (ADS)

Zhou, Z.; Smith, J. A.; Yang, L.; Baeck, M. L.; Wright, D.; Liu, S.

2017-12-01

Regional frequency analyses of extreme rainfall are critical for development of engineering hydrometeorology procedures. In conventional approaches, the assumptions that `design storms' have specified time profiles and are uniform in space are commonly applied but often not appropriate, especially over regions with heterogeneous environments (due to topography, water-land boundaries and land surface properties). In this study, we present regional frequency analyses of extreme rainfall for Baltimore study region combining storm catalogs of rainfall fields derived from weather radar and stochastic storm transposition (SST, developed by Wright et al., 2013). The study region is Dead Run, a small (14.3 km2) urban watershed, in the Baltimore Metropolitan region. Our analyses build on previous empirical and modeling studies showing pronounced spatial heterogeneities in rainfall due to the complex terrain, including the Chesapeake Bay to the east, mountainous terrain to the west and urbanization in this region. We expand the original SST approach by applying a multiplier field that accounts for spatial heterogeneities in extreme rainfall. We also characterize the spatial heterogeneities of extreme rainfall distribution through analyses of rainfall fields in the storm catalogs. We examine the characteristics of regional extreme rainfall and derive intensity-duration-frequency (IDF) curves using the SST approach for heterogeneous regions. Our results highlight the significant heterogeneity of extreme rainfall in this region. Estimates of IDF show the advantages of SST in capturing the space-time structure of extreme rainfall. We also illustrate application of SST analyses for flood frequency analyses using a distributed hydrological model. Reference: Wright, D. B., J. A. Smith, G. Villarini, and M. L. Baeck (2013), Estimating the frequency of extreme rainfall using weather radar and stochastic storm transposition, J. Hydrol., 488, 150-165.

Fitting monthly Peninsula Malaysian rainfall using Tweedie distribution

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Rainfall intensity effects on removal of fecal indicator bacteria from solid dairy manure applied over grass-covered soil.

PubMed

Blaustein, Ryan A; Hill, Robert L; Micallef, Shirley A; Shelton, Daniel R; Pachepsky, Yakov A

2016-01-01

The rainfall-induced release of pathogens and microbial indicators from land-applied manure and their subsequent removal with runoff and infiltration precedes the impairment of surface and groundwater resources. It has been assumed that rainfall intensity and changes in intensity during rainfall do not affect microbial removal when expressed as a function of rainfall depth. The objective of this work was to test this assumption by measuring the removal of Escherichia coli, enterococci, total coliforms, and chloride ion from dairy manure applied in soil boxes containing fescue, under 3, 6, and 9cmh(-1) of rainfall. Runoff and leachate were collected at increasing time intervals during rainfall, and post-rainfall soil samples were taken at 0, 2, 5, and 10cm depths. Three kinetic-based models were fitted to the data on manure-constituent removal with runoff. Rainfall intensity appeared to have positive effects on rainwater partitioning to runoff, and removal with this effluent type occurred in two stages. While rainfall intensity generally did not impact the parameters of runoff-removal models, it had significant, inverse effects on the numbers of bacteria remaining in soil after rainfall. As rainfall intensity and soil profile depth increased, the numbers of indicator bacteria tended to decrease. The cumulative removal of E. coli from manure exceeded that of enterococci, especially in the form of removal with infiltration. This work may be used to improve the parameterization of models for bacteria removal with runoff and to advance estimations of depths of bacteria removal with infiltration, both of which are critical to risk assessment of microbial fate and transport in the environment. Published by Elsevier B.V.

A paleoclimate rainfall reconstruction in the Murray-Darling Basin (MDB), Australia: 1. Evaluation of different paleoclimate archives, rainfall networks, and reconstruction techniques

NASA Astrophysics Data System (ADS)

Ho, Michelle; Kiem, Anthony S.; Verdon-Kidd, Danielle C.

2015-10-01

From ˜1997 to 2009 the Murray-Darling Basin (MDB), Australia's largest water catchment and reputed "food bowl," experienced a severe drought termed the "Millennium Drought" or "Big Dry" followed by devastating floods in the austral summers of 2010/2011, 2011/2012, and 2012/2013. The magnitude and severity of these extreme events highlight the limitations associated with assessing hydroclimatic risk based on relatively short instrumental records (˜100 years). An option for extending hydroclimatic records is through the use of paleoclimate records. However, there are few in situ proxies of rainfall or streamflow suitable for assessing hydroclimatic risk in Australia and none are available in the MDB. In this paper, available paleoclimate records are reviewed and those of suitable quality for hydroclimatic risk assessments are used to develop preinstrumental information for the MDB. Three different paleoclimate reconstruction techniques are assessed using two instrumental rainfall networks: (1) corresponding to rainfall at locations where rainfall-sensitive Australian paleoclimate archives currently exist and (2) corresponding to rainfall at locations identified as being optimal for explaining MDB rainfall variability. It is shown that the optimized rainfall network results in a more accurate model of MDB rainfall compared to reconstructions based on rainfall at locations where paleoclimate rainfall proxies currently exist. This highlights the importance of first identifying key locations where existing and as yet unrealized paleoclimate records will be most useful in characterizing variability. These results give crucial insight as to where future investment and research into developing paleoclimate proxies for Australia could be most beneficial, with respect to better understanding instrumental, preinstrumental and potential future variability in the MDB.

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

NASA Astrophysics Data System (ADS)

Aronica, G. T.; Candela, A.

2007-12-01

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

Determining the influence of rainfall patterns and carbendazim on the surface activity of the earthworm Lumbricus terrestris.

PubMed

Ellis, Sian R; Hodson, Mark E; Wege, Phil

2010-08-01

Carbendazim is highly toxic to earthworms and is used as a standard control substance when running field-based trials of pesticides, but results using carbendazim are highly variable. In the present study, impacts of timing of rainfall events following carbendazim application on earthworms were investigated. Lumbricus terrestris were maintained in soil columns to which carbendazim and then deionized water (a rainfall substitute) were applied. Carbendazim was applied at 4 kg/ha, the rate recommended in pesticide field trials. Three rainfall regimes were investigated: initial and delayed heavy rainfall 24 h and 6 d after carbendazim application, and frequent rainfall every 48 h. Earthworm mortality and movement of carbendazim through the soil was assessed 14 d after carbendazim application. No detectable movement of carbendazim occurred through the soil in any of the treatments or controls. Mortality in the initial heavy and frequent rainfall was significantly higher (approximately 55%) than in the delayed rainfall treatment (approximately 25%). This was due to reduced bioavailability of carbendazim in the latter treatment due to a prolonged period of sorption of carbendazim to soil particles before rainfall events. The impact of carbendazim application on earthworm surface activity was assessed using video cameras. Carbendazim applications significantly reduced surface activity due to avoidance behavior of the earthworms. Surface activity reductions were least in the delayed rainfall treatment due to the reduced bioavailability of the carbendazim. The nature of rainfall events' impacts on the response of earthworms to carbendazim applications, and details of rainfall events preceding and following applications during field trials should be made at a higher level of resolution than is currently practiced according to standard International Organization for Standardization protocols. Copyright 2010 SETAC

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

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Rainfall-induced soil aggregate breakdown in field experiments at different rainfall intensities and initial soil moisture conditions

NASA Astrophysics Data System (ADS)

Shi, Pu; Thorlacius, Sigurdur; Keller, Thomas; Keller, Martin; Schulin, Rainer

2017-04-01

Soil aggregate breakdown under rainfall impact is an important process in interrill erosion, but is not represented explicitly in water erosion models. Aggregate breakdown not only reduces infiltration through surface sealing during rainfall, but also determines the size distribution of the disintegrated fragments and thus their availability for size-selective sediment transport and re-deposition. An adequate representation of the temporal evolution of fragment mass size distribution (FSD) during rainfall events and the dependence of this dynamics on factors such as rainfall intensity and soil moisture content may help improve mechanistic erosion models. Yet, little is known about the role of those factors in the dynamics of aggregate breakdown under field conditions. In this study, we conducted a series of artificial rainfall experiments on a field silt loam soil to investigate aggregate breakdown dynamics at different rainfall intensity (RI) and initial soil water content (IWC). We found that the evolution of FSD in the course of a rainfall event followed a consistent two-stage pattern in all treatments. The fragment mean weight diameter (MWD) drastically decreased in an approximately exponential way at the beginning of a rainfall event, followed by a further slow linear decrease in the second stage. We proposed an empirical model that describes this temporal pattern of MWD decrease during a rainfall event and accounts for the effects of RI and IWC on the rate parameters. The model was successfully tested using an independent dataset, showing its potential to be used in erosion models for the prediction of aggregate breakdown. The FSD at the end of the experimental rainfall events differed significantly among treatments, indicating that different aggregate breakdown mechanisms responded differently to the variation in initial soil moisture and rainfall intensity. These results provide evidence that aggregate breakdown dynamics needs to be considered in a case-specific manner in modelling sediment mobilization and transport during water erosion events.

Response mechanism of post-earthquake slopes under heavy rainfall

NASA Astrophysics Data System (ADS)

Qiu, Hong-zhi; Kong, Ji-ming; Wang, Ren-chao; Cui, Yun; Huang, Sen-wang

2017-07-01

This paper uses the catastrophic landslide that occurred in Zhongxing Town, Dujiangyan City, as an example to study the formation mechanism of landslides induced by heavy rainfall in the post-Wenchuan earthquake area. The deformation characteristics of a slope under seismic loading were investigated via a shaking table test. The results show that a large number of cracks formed in the slope due to the tensile and shear forces of the vibrations, and most of the cracks had angles of approximately 45° with respect to the horizontal. A series of flume tests were performed to show how the duration and intensity of rainfall influence the responses of the shaken and non-shaken slopes. Wetting fronts were recorded under different rainfall intensities, and the depth of rainfall infiltration was greater in the shaken slope than in the non-shaken slope because the former experienced a greater extreme rainfall intensity under the same early rainfall and rainfall duration conditions. At the beginning of the rainfall infiltration experiment, the pore water pressure in the slope was negative, and settling occurred at the top of the slope. With increasing rainfall, the pore water pressure changed from negative to positive, and cracks were observed on the back surface of the slope and the shear outlet of the landslide on the front of the slope. The shaken slope was more susceptible to crack formation than the non-shaken slope under the same rainfall conditions. A comparison of the responses of the shaken and non-shaken slopes under heavy rainfall revealed that cracks formed by earthquakes provided channels for infiltration. Soil particles in the cracks of slopes were washed away, and the pore water pressure increased rapidly, especially the transient pore water pressure in the slope caused by short-term concentrated rainfall which decreased rock strength and slope stability.

Daily Rainfall Simulation Using Climate Variables and Nonhomogeneous Hidden Markov Model

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Novel SVM-based technique to improve rainfall estimation over the Mediterranean region (north of Algeria) using the multispectral MSG SEVIRI imagery

NASA Astrophysics Data System (ADS)

Sehad, Mounir; Lazri, Mourad; Ameur, Soltane

2017-03-01

In this work, a new rainfall estimation technique based on the high spatial and temporal resolution of the Spinning Enhanced Visible and Infra Red Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) is presented. This work proposes efficient scheme rainfall estimation based on two multiclass support vector machine (SVM) algorithms: SVM_D for daytime and SVM_N for night time rainfall estimations. Both SVM models are trained using relevant rainfall parameters based on optical, microphysical and textural cloud proprieties. The cloud parameters are derived from the Spectral channels of the SEVIRI MSG radiometer. The 3-hourly and daily accumulated rainfall are derived from the 15 min-rainfall estimation given by the SVM classifiers for each MSG observation image pixel. The SVMs were trained with ground meteorological radar precipitation scenes recorded from November 2006 to March 2007 over the north of Algeria located in the Mediterranean region. Further, the SVM_D and SVM_N models were used to estimate 3-hourly and daily rainfall using data set gathered from November 2010 to March 2011 over north Algeria. The results were validated against collocated rainfall observed by rain gauge network. Indeed, the statistical scores given by correlation coefficient, bias, root mean square error and mean absolute error, showed good accuracy of rainfall estimates by the present technique. Moreover, rainfall estimates of our technique were compared with two high accuracy rainfall estimates methods based on MSG SEVIRI imagery namely: random forests (RF) based approach and an artificial neural network (ANN) based technique. The findings of the present technique indicate higher correlation coefficient (3-hourly: 0.78; daily: 0.94), and lower mean absolute error and root mean square error values. The results show that the new technique assign 3-hourly and daily rainfall with good and better accuracy than ANN technique and (RF) model.

Design of a reliable and operational landslide early warning system at regional scale

NASA Astrophysics Data System (ADS)

Calvello, Michele; Piciullo, Luca; Gariano, Stefano Luigi; Melillo, Massimo; Brunetti, Maria Teresa; Peruccacci, Silvia; Guzzetti, Fausto

2017-04-01

Landslide early warning systems at regional scale are used to warn authorities, civil protection personnel and the population about the occurrence of rainfall-induced landslides over wide areas, typically through the prediction and measurement of meteorological variables. A warning model for these systems must include a regional correlation law and a decision algorithm. A regional correlation law can be defined as a functional relationship between rainfall and landslides; it is typically based on thresholds of rainfall indicators (e.g., cumulated rainfall, rainfall duration) related to different exceedance probabilities of landslide occurrence. A decision algorithm can be defined as a set of assumptions and procedures linking rainfall thresholds to warning levels. The design and the employment of an operational and reliable early warning system for rainfall-induced landslides at regional scale depend on the identification of a reliable correlation law as well as on the definition of a suitable decision algorithm. Herein, a five-step process chain addressing both issues and based on rainfall thresholds is proposed; the procedure is tested in a landslide-prone area of the Campania region in southern Italy. To this purpose, a database of 96 shallow landslides triggered by rainfall in the period 2003-2010 and rainfall data gathered from 58 rain gauges are used. First, a set of rainfall thresholds are defined applying a frequentist method to reconstructed rainfall conditions triggering landslides in the test area. In the second step, several thresholds at different exceedance probabilities are evaluated, and different percentile combinations are selected for the activation of three warning levels. Subsequently, within steps three and four, the issuing of warning levels is based on the comparison, over time and for each combination, between the measured rainfall and the pre-defined warning level thresholds. Finally, the optimal percentile combination to be employed in the regional early warning system is selected evaluating the model performance in terms of success and error indicators by means of the "event, duration matrix, performance" (EDuMaP) method.

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

NASA Astrophysics Data System (ADS)

Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe

2017-09-01

The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce warning on a daily basis for the entire region.

A gridded hourly rainfall dataset for the UK applied to a national physically-based modelling system

NASA Astrophysics Data System (ADS)

Lewis, Elizabeth; Blenkinsop, Stephen; Quinn, Niall; Freer, Jim; Coxon, Gemma; Woods, Ross; Bates, Paul; Fowler, Hayley

2016-04-01

An hourly gridded rainfall product has great potential for use in many hydrological applications that require high temporal resolution meteorological data. One important example of this is flood risk management, with flooding in the UK highly dependent on sub-daily rainfall intensities amongst other factors. Knowledge of sub-daily rainfall intensities is therefore critical to designing hydraulic structures or flood defences to appropriate levels of service. Sub-daily rainfall rates are also essential inputs for flood forecasting, allowing for estimates of peak flows and stage for flood warning and response. In addition, an hourly gridded rainfall dataset has significant potential for practical applications such as better representation of extremes and pluvial flash flooding, validation of high resolution climate models and improving the representation of sub-daily rainfall in weather generators. A new 1km gridded hourly rainfall dataset for the UK has been created by disaggregating the daily Gridded Estimates of Areal Rainfall (CEH-GEAR) dataset using comprehensively quality-controlled hourly rain gauge data from over 1300 observation stations across the country. Quality control measures include identification of frequent tips, daily accumulations and dry spells, comparison of daily totals against the CEH-GEAR daily dataset, and nearest neighbour checks. The quality control procedure was validated against historic extreme rainfall events and the UKCP09 5km daily rainfall dataset. General use of the dataset has been demonstrated by testing the sensitivity of a physically-based hydrological modelling system for Great Britain to the distribution and rates of rainfall and potential evapotranspiration. Of the sensitivity tests undertaken, the largest improvements in model performance were seen when an hourly gridded rainfall dataset was combined with potential evapotranspiration disaggregated to hourly intervals, with 61% of catchments showing an increase in NSE between observed and simulated streamflows as a result of more realistic sub-daily meteorological forcing.

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

NASA Astrophysics Data System (ADS)

Lucero, Omar A.; Rozas, Daniel

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

Rainfall interception of three trees in Oakland, California

Treesearch

Qingfu Xiao; E. Gregory McPherson

2011-01-01

A rainfall interception study was conducted in Oakland, California to determine the partitioning of rainfall and the chemical composition of precipitation, throughfall, and stemflow. Rainfall interception measurements were conducted on a gingko (Ginkgo biloba) (13.5 m tall deciduous tree), sweet gum (Liquidambar styraciflua) (8...

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

PubMed Central

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2018-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions. PMID:29657544

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania

PubMed Central

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

2017-01-01

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

Performance of Sorghum Varieties under Variable Rainfall in Central Tanzania.

PubMed

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards.

PubMed

Wright, Daniel B; Mantilla, Ricardo; Peters-Lidard, Christa D

2017-04-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, RainyDay can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, RainyDay can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. RainyDay can be useful for hazard modeling under nonstationary conditions.

A Remote Sensing-Based Tool for Assessing Rainfall-Driven Hazards

NASA Technical Reports Server (NTRS)

Wright, Daniel B.; Mantilla, Ricardo; Peters-Lidard, Christa D.

2017-01-01

RainyDay is a Python-based platform that couples rainfall remote sensing data with Stochastic Storm Transposition (SST) for modeling rainfall-driven hazards such as floods and landslides. SST effectively lengthens the extreme rainfall record through temporal resampling and spatial transposition of observed storms from the surrounding region to create many extreme rainfall scenarios. Intensity-Duration-Frequency (IDF) curves are often used for hazard modeling but require long records to describe the distribution of rainfall depth and duration and do not provide information regarding rainfall space-time structure, limiting their usefulness to small scales. In contrast, Rainy Day can be used for many hazard applications with 1-2 decades of data, and output rainfall scenarios incorporate detailed space-time structure from remote sensing. Thanks to global satellite coverage, Rainy Day can be used in inaccessible areas and developing countries lacking ground measurements, though results are impacted by remote sensing errors. Rainy Day can be useful for hazard modeling under nonstationary conditions.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A Bivariate Mixed Distribution with a Heavy-tailed Component and its Application to Single-site Daily Rainfall Simulation

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

Li, Chao ..; Singh, Vijay P.; Mishra, Ashok K.

2013-02-06

This paper presents an improved brivariate mixed distribution, which is capable of modeling the dependence of daily rainfall from two distinct sources (e.g., rainfall from two stations, two consecutive days, or two instruments such as satellite and rain gauge). The distribution couples an existing framework for building a bivariate mixed distribution, the theory of copulae and a hybrid marginal distribution. Contributions of the improved distribution are twofold. One is the appropriate selection of the bivariate dependence structure from a wider admissible choice (10 candidate copula families). The other is the introduction of a marginal distribution capable of better representing lowmore » to moderate values as well as extremes of daily rainfall. Among several applications of the improved distribution, particularly presented here is its utility for single-site daily rainfall simulation. Rather than simulating rainfall occurrences and amounts separately, the developed generator unifies the two processes by generalizing daily rainfall as a Markov process with autocorrelation described by the improved bivariate mixed distribution. The generator is first tested on a sample station in Texas. Results reveal that the simulated and observed sequences are in good agreement with respect to essential characteristics. Then, extensive simulation experiments are carried out to compare the developed generator with three other alternative models: the conventional two-state Markov chain generator, the transition probability matrix model and the semi-parametric Markov chain model with kernel density estimation for rainfall amounts. Analyses establish that overall the developed generator is capable of reproducing characteristics of historical extreme rainfall events and is apt at extrapolating rare values beyond the upper range of available observed data. Moreover, it automatically captures the persistence of rainfall amounts on consecutive wet days in a relatively natural and easy way. Another interesting observation is that the recognized ‘overdispersion’ problem in daily rainfall simulation ascribes more to the loss of rainfall extremes than the under-representation of first-order persistence. The developed generator appears to be a sound option for daily rainfall simulation, especially in particular hydrologic planning situations when rare rainfall events are of great importance.« less

Feasibility Study on the Satellite Rainfall Data for Prediction of Sediment- Related Disaster by the Japanese Prediction Methodology

NASA Astrophysics Data System (ADS)

Shimizu, Y.; Ishizuka, T.; Osanai, N.; Okazumi, T.

2014-12-01

In this study, the sediment-related disaster prediction method which based ground gauged rainfall-data, currently practiced in Japan was coupled with satellite rainfall data and applied to domestic large-scale sediment-related disasters. The study confirmed the feasibility of this integrated method. In Asia, large-scale sediment-related disasters which can sweep away an entire settlement occur frequently. Leyte Island suffered from a huge landslide in 2004, and Typhoon Molakot in 2009 caused huge landslides in Taiwan. In the event of these sediment-related disasters, immediate responses by central and local governments are crucial in crisis management. In general, there are not enough rainfall gauge stations in developing countries. Therefore national and local governments have little information to determine the risk level of water induced disasters in their service areas. In the Japanese methodology, a criterion is set by combining two indices: the short-term rainfall index and long-term rainfall index. The short-term rainfall index is defined as the 60-minute total rainfall; the long-term rainfall index as the soil-water index, which is an estimation of the retention status of fallen rainfall in soil. In July 2009, a high-density sediment related disaster, or a debris flow, occurred in Hofu City of Yamaguchi Prefecture, in the western region of Japan. This event was calculated by the Japanese standard methodology, and then analyzed for its feasibility. Hourly satellite based rainfall has underestimates compared with ground based rainfall data. Long-term index correlates with each other. Therefore, this study confirmed that it is possible to deliver information on the risk level of sediment-related disasters such as shallow landslides and debris flows. The prediction method tested in this study is expected to assist for timely emergency responses to rainfall-induced natural disasters in sparsely gauged areas. As the Global Precipitation Measurement (GPM) Plan progresses, spatial resolution, time resolution and accuracy of rainfall data should be further improved and will be more effective in practical use.

Influence of Rainfall Product on Hydrological and Sediment Outputs when Calibrating the STREAP Rainfall Generator for the CAESAR-Lisflood Landscape Evolution Model

NASA Astrophysics Data System (ADS)

Skinner, Christopher; Peleg, Nadav; Quinn, Niall

2017-04-01

The use of Landscape Evolution Models often requires a timeseries of rainfall to drive the model. The spatial and temporal resolution of the driving data has an impact on several model outputs, including the shape of the landscape itself. Attempts to compensate for the spatiotemporal smoothing of local rainfall intensities are insufficient and may exacerbate these issues, meaning that to produce the best results the model needs to be run with data of highest spatial and temporal resolutions available. Some rainfall generators are able to produce timeseries with high spatial and temporal resolution. Observed data is used for the calibration of these generators. However, rainfall observations are highly uncertain and vary between different products (e.g. raingauges, weather radar) which may cascade through the Landscape Evolution Model. Here, we used the STREAP rainfall generator to produce high spatial (1km) and temporal (hourly) resolution ensembles of rainfall for a 50-year period, and used these to drive the CAESAR-Lisflood Landscape Evolution Model for a test catchment. Three different calibrations of STREAP were used against different products: gridded raingauge (TBR), weather radar (NIMROD), and a merged of the two. Analysis of the discharge and sediment yields from the model runs showed that the models run by STREAP calibrated by the different products were statistically significantly different, with the raingauge calibration producing 12.4 % more sediment on average over the 50-year period. The merged product produced results which were between the raingauge and radar products. The results demonstrate the importance of considering the selection of rainfall driving data on Landscape Evolution Modelling. Rainfall products are highly uncertain, different instruments will observe rainfall differently, and these uncertainties are clearly shown to cascade through the calibration of the rainfall generator and the Landscape Evolution Model. Merging raingauge and radar products is a common practise operationally, and by using features of both to calibrate the rainfall generator it is likely a more robust rainfall timeseries is produced.

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

DOE PAGES

Yoon, Jin -Ho

2015-12-07

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

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

NASA Technical Reports Server (NTRS)

Choudhury, Bhaskar J.; Digirolamo, Nicolo E.

1994-01-01

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

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

PubMed

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

2007-12-01

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

A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa

PubMed Central

Maidment, Ross I.; Grimes, David; Black, Emily; Tarnavsky, Elena; Young, Matthew; Greatrex, Helen; Allan, Richard P.; Stein, Thorwald; Nkonde, Edson; Senkunda, Samuel; Alcántara, Edgar Misael Uribe

2017-01-01

Rainfall information is essential for many applications in developing countries, and yet, continually updated information at fine temporal and spatial scales is lacking. In Africa, rainfall monitoring is particularly important given the close relationship between climate and livelihoods. To address this information gap, this paper describes two versions (v2.0 and v3.0) of the TAMSAT daily rainfall dataset based on high-resolution thermal-infrared observations, available from 1983 to the present. The datasets are based on the disaggregation of 10-day (v2.0) and 5-day (v3.0) total TAMSAT rainfall estimates to a daily time-step using daily cold cloud duration. This approach provides temporally consistent historic and near-real time daily rainfall information for all of Africa. The estimates have been evaluated using ground-based observations from five countries with contrasting rainfall climates (Mozambique, Niger, Nigeria, Uganda, and Zambia) and compared to other satellite-based rainfall estimates. The results indicate that both versions of the TAMSAT daily estimates reliably detects rainy days, but have less skill in capturing rainfall amount—results that are comparable to the other datasets. PMID:28534868

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Influence of meteorological variables on rainfall partitioning for deciduous and coniferous tree species in urban area

NASA Astrophysics Data System (ADS)

Zabret, Katarina; Rakovec, Jože; Šraj, Mojca

2018-03-01

Rainfall partitioning is an important part of the ecohydrological cycle, influenced by numerous variables. Rainfall partitioning for pine (Pinus nigra Arnold) and birch (Betula pendula Roth.) trees was measured from January 2014 to June 2017 in an urban area of Ljubljana, Slovenia. 180 events from more than three years of observations were analyzed, focusing on 13 meteorological variables, including the number of raindrops, their diameter, and velocity. Regression tree and boosted regression tree analyses were performed to evaluate the influence of the variables on rainfall interception loss, throughfall, and stemflow in different phenoseasons. The amount of rainfall was recognized as the most influential variable, followed by rainfall intensity and the number of raindrops. Higher rainfall amount, intensity, and the number of drops decreased percentage of rainfall interception loss. Rainfall amount and intensity were the most influential on interception loss by birch and pine trees during the leafed and leafless periods, respectively. Lower wind speed was found to increase throughfall, whereas wind direction had no significant influence. Consideration of drop size spectrum properties proved to be important, since the number of drops, drop diameter, and median volume diameter were often recognized as important influential variables.

River catchment rainfall series analysis using additive Holt-Winters method

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

PubMed

Dave, Prashant; Bhushan, Mani; Venkataraman, Chandra

2017-12-11

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

Midweek Intensification of Rain in the U.S.: Does Air Pollution Invigorate Storms?

NASA Technical Reports Server (NTRS)

Bell, T. L.; Rosenfeld, D.; Hahnenberger, M.

2005-01-01

The effect of pollution on rainfall has been observed to depend both on the type of pollution and the precipitating environment. The climatological consequences of pollution for rainfall are uncertain. In some urban areas, pollution varies with the day of the week because of weekly variations in human activity, in effect providing a repeated experiment on the effects of pollution. Weekly variations in temperature, pressure, cloud characteristics, hails and lightning are observed in many areas. Observing a weekly cycle in rainfall statistics has proven to be more difficult, although there is some evidence for it. Here we examine rainfall statistics from the Tropical Rainfall Measuring Mission (TRMM) satellite over the southern U.S. and adjacent waters, and find that there is a distinct, statistically significant weekly cycle in summertime rainfall over the southeast U.S., as well as weekly variations in rainfall over the nearby Atlantic and the Gulf of Mexico. Rainfall over land peaks in the middle of the week, suggesting that summer rainfall on large scales may increase as pollution levels rise. Both rain statistics over land and what appear to be compensating effects over adjacent seas support the suggestion that air pollution invigorates convection and outflow aloft.

Real-time adjusting of rainfall estimates from commercial microwave links

NASA Astrophysics Data System (ADS)

Fencl, Martin; Dohnal, Michal; Bareš, Vojtěch

2017-04-01

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

Rainfall estimates for hydrological models: Comparing rain gauge, radar and microwave link data as input for the Wageningen Lowland Runoff Simulator (WALRUS)

NASA Astrophysics Data System (ADS)

Brauer, Claudia; Overeem, Aart; Uijlenhoet, Remko

2015-04-01

Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of differences in rainfall estimates on discharge simulations in a lowland catchment by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in the Hupsel Brook catchment. We used two automatic rain gauges with hourly resolution, located inside the catchment (the base run) and 30 km northeast. Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. Traditionally, the precipitation research community places emphasis on quantifying spatial errors and uncertainty, but for hydrological applications, temporal errors and uncertainty should be quantified as well. Its memory makes the hydrologic system sensitive to missed or badly timed rainfall events, but also emphasizes the effect of a bias in rainfall estimates. Systematic underestimation of rainfall by the uncorrected operational radar product leads to very dry model states and an increasing underestimation of discharge. Using the rain gauge 30 km northeast of the catchment yields good results for climatological studies, but not for forecasting individual floods. Simulating discharge using the maps derived from microwave link data and the gauge-adjusted radar product yields good results for both events and climatological studies. This indicates that these products can be used in catchments without gauges in or near the catchment. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. Improving rainfall measurements can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Leaf and wood carbon isotope ratios, specific leaf areas and wood growth of Eucalyptus species across a rainfall gradient in Australia.

PubMed

Schulze, Ernst-Detlef; Turner, Neil C; Nicolle, Dean; Schumacher, Jens

2006-04-01

Leaves and samples of recent wood of Eucalyptus species were collected along a rainfall gradient parallel to the coast of Western Australia between Perth in the north and Walpole in the south and along a southwest to northeast transect from Walpole in southwestern Australia, to near Mount Olga in central Australia. The collection included 65 species of Eucalyptus sampled at 73 sites and many of the species were collected at several sites along the rainfall gradient. Specific leaf area (SLA) and isotopic ratio of 13C to 12C (delta 13C) of leaves that grew in 2002, and tree ring growth and delta 13C of individual cell layers of the wood were measured. Rainfall data were obtained from the Australian Bureau of Meteorology for 29 locations that represented one or a few closely located collection sites. Site-averaged data and species-specific values of delta 13C decreased with decreasing annual rainfall between 1200 and 300 mm at a rate of 1.63 per thousand per 1000 mm decrease in rainfall. Responses became variable in the low rainfall region (< 300 mm), with some species showing decreasing delta 13C with rainfall, whereas delta 13C increased or remained constant in other species. The range of delta 13C values in the low rainfall region was as large as the range observed at sites receiving > 300 mm of annual rainfall. Specific leaf area varied between 2 and 6 m2 kg(-1) and tended to increase with decreasing annual rainfall in some species, but not all, whereas delta 13C decreased with SLA. The relationship between delta 13C and SLA was highly species and soil-type specific. Leaf-area-based nitrogen (N) content varied between 2 and almost 6 g m(-2) and decreased with rainfall. Thus, thicker leaves were associated with higher N content and this compensated for the effect of drought on delta 13C. Nitrogen content was also related to soil type and species identity. Based on a linear mixed model, statistical analysis of the whole data set showed that 27% of the variation in delta 13C was associated with changes in SLA, 16% with soil type and only 1% with rainfall. Additionally, 21% was associated with species identity. For a subset of sites with > 300 mm rainfall, 43% of the variation was explained by SLA, 13% by soil type and only 3% by rainfall. The species effect decreased to 9% because there were fewer species in the subset of sites. The small effect of rainfall on delta 13C was further supported by a path analysis that yielded a standardized path coefficient of 0.38 for the effect of rainfall on SLA and -0.50 for the effect of SLA on delta 13C, but an insignificantly low standardized path coefficient of -0.05 for the direct effect of rainfall on delta 13C. Thus, in contrast to our hypothesis that delta 13C decreases with rainfall independent of soil type and species, we detected no statistically significant relationship between rainfall and delta 13C in leaves of trees growing at sites receiving < 300 mm of rainfall annually. Rainfall affected delta 13C indirectly through soil type (a surrogate for water-holding capacity) across the rainfall gradient. Annual tree rings are not clearly visible in evergreen Eucalyptus species, even in the seasonally cool climate of SW Australia. Generally, visible density transitions in the wood are related not to a strict annual cycle but to periods of growth associated mainly with rainfall. The relationship between delta 13C of leaves and the width of these stem increments was not statistically significant. Analysis of stem growth periods showed that delta 13C in wood responded to rainfall events, but carbohydrate storage and reallocation also affected the isotopic signature. Although delta 13C in wood of any one species varied over a range of 2 to 4 per thousand, there was a general relationship between delta 13C of the leaves and the annual range of delta 13C in wood. We conclude that species-specific traits are important in understanding the response of Eucalyptus to rainfall and that the diversity of the genus may reflect its response to the large climatic gradient in Australia and to the large annual and interannual variations in rainfall at any one location.

Cascade rainfall disaggregation application in U.S. Central Plains

USDA-ARS?s Scientific Manuscript database

Hourly rainfall are increasingly used in complex, process-based simulations of the environment. Long records of daily rainfall are common, but long continuous records of hourly rainfall are rare and must be developed. A Multiplicative Random Cascade (MRC) model is proposed to disaggregate observed d...

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

EPA Science Inventory

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

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

DOE PAGES

Yoo, Chulsang; Lee, Jinwook; Ro, Yonghun

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Trends and spatial distribution of annual and seasonal rainfall in Ethiopia

USGS Publications Warehouse

Cheung, W.H.; Senay, G.B.; Singh, A.

2008-01-01

As a country whose economy is heavily dependent on low-productivity rainfed agriculture, rainfall trends are often cited as one of the more important factors in explaining various socio-economic problems such as food insecurity. Therefore, in order to help policymakers and developers make more informed decisions, this study investigated the temporal dynamics of rainfall and its spatial distribution within Ethiopia. Changes in rainfall were examined using data from 134 stations in 13 watersheds between 1960 and 2002. The variability and trends in seasonal and annual rainfall were analysed at the watershed scale with data (1) from all available years, and (2) excluding years that lacked observations from at least 25% of the gauges. Similar analyses were also performed at the gauge, regional, and national levels. By regressing annual watershed rainfall on time, results from the one-sample t-test show no significant changes in rainfall for any of the watersheds examined. However, in our regressions of seasonal rainfall averages against time, we found a significant decline in June to September rainfall (i.e. Kiremt) for the Baro-Akobo, Omo-Ghibe, Rift Valley, and Southern Blue Nile watersheds located in the southwestern and central parts of Ethiopia. While the gauge level analysis showed that certain gauge stations experienced recent changes in rainfall, these trends are not necessarily reflected at the watershed or regional levels.

Sensitivity of Latent Heating Profiles to Environmental Conditions: Implications for TRMM and Climate Research

NASA Technical Reports Server (NTRS)

Shepherd, J. Marshall; Einaudi, Franco (Technical Monitor)

2000-01-01

The Tropical Rainfall Measuring Mission (TRMM) as a part of NASA's Earth System Enterprise is the first mission dedicated to measuring tropical rainfall through microwave and visible sensors, and includes the first spaceborne rain radar. Tropical rainfall comprises two-thirds of global rainfall. It is also the primary distributor of heat through the atmosphere's circulation. It is this circulation that defines Earth's weather and climate. Understanding rainfall and its variability is crucial to understanding and predicting global climate change. Weather and climate models need an accurate assessment of the latent heating released as tropical rainfall occurs. Currently, cloud model-based algorithms are used to derive latent heating based on rainfall structure. Ultimately, these algorithms can be applied to actual data from TRMM. This study investigates key underlying assumptions used in developing the latent heating algorithms. For example, the standard algorithm is highly dependent on a system's rainfall amount and structure. It also depends on an a priori database of model-derived latent heating profiles based on the aforementioned rainfall characteristics. Unanswered questions remain concerning the sensitivity of latent heating profiles to environmental conditions (both thermodynamic and kinematic), regionality, and seasonality. This study investigates and quantifies such sensitivities and seeks to determine the optimal latent heating profile database based on the results. Ultimately, the study seeks to produce an optimized latent heating algorithm based not only on rainfall structure but also hydrometeor profiles.

Requirements for future development of small scale rainfall simulators

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

A stochastical event-based continuous time step rainfall generator based on Poisson rectangular pulse and microcanonical random cascade models

NASA Astrophysics Data System (ADS)

Pohle, Ina; Niebisch, Michael; Zha, Tingting; Schümberg, Sabine; Müller, Hannes; Maurer, Thomas; Hinz, Christoph

2017-04-01

Rainfall variability within a storm is of major importance for fast hydrological processes, e.g. surface runoff, erosion and solute dissipation from surface soils. To investigate and simulate the impacts of within-storm variabilities on these processes, long time series of rainfall with high resolution are required. Yet, observed precipitation records of hourly or higher resolution are in most cases available only for a small number of stations and only for a few years. To obtain long time series of alternating rainfall events and interstorm periods while conserving the statistics of observed rainfall events, the Poisson model can be used. Multiplicative microcanonical random cascades have been widely applied to disaggregate rainfall time series from coarse to fine temporal resolution. We present a new coupling approach of the Poisson rectangular pulse model and the multiplicative microcanonical random cascade model that preserves the characteristics of rainfall events as well as inter-storm periods. In the first step, a Poisson rectangular pulse model is applied to generate discrete rainfall events (duration and mean intensity) and inter-storm periods (duration). The rainfall events are subsequently disaggregated to high-resolution time series (user-specified, e.g. 10 min resolution) by a multiplicative microcanonical random cascade model. One of the challenges of coupling these models is to parameterize the cascade model for the event durations generated by the Poisson model. In fact, the cascade model is best suited to downscale rainfall data with constant time step such as daily precipitation data. Without starting from a fixed time step duration (e.g. daily), the disaggregation of events requires some modifications of the multiplicative microcanonical random cascade model proposed by Olsson (1998): Firstly, the parameterization of the cascade model for events of different durations requires continuous functions for the probabilities of the multiplicative weights, which we implemented through sigmoid functions. Secondly, the branching of the first and last box is constrained to preserve the rainfall event durations generated by the Poisson rectangular pulse model. The event-based continuous time step rainfall generator has been developed and tested using 10 min and hourly rainfall data of four stations in North-Eastern Germany. The model performs well in comparison to observed rainfall in terms of event durations and mean event intensities as well as wet spell and dry spell durations. It is currently being tested using data from other stations across Germany and in different climate zones. Furthermore, the rainfall event generator is being applied in modelling approaches aimed at understanding the impact of rainfall variability on hydrological processes. Reference Olsson, J.: Evaluation of a scaling cascade model for temporal rainfall disaggregation, Hydrology and Earth System Sciences, 2, 19.30

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

The contribution of tropical cyclones to rainfall in Mexico

NASA Astrophysics Data System (ADS)

Agustín Breña-Naranjo, J.; Pedrozo-Acuña, Adrián; Pozos-Estrada, Oscar; Jiménez-López, Salma A.; López-López, Marco R.

Investigating the contribution of tropical cyclones to the terrestrial water cycle can help quantify the benefits and hazards caused by the rainfall generated from this type of hydro-meteorological event. Rainfall induced by tropical cyclones can enhance both flood risk and groundwater recharge, and it is therefore important to characterise its minimum, mean and maximum contributions to a region or country's water balance. This work evaluates the rainfall contribution of tropical depressions, storms and hurricanes across Mexico from 1998 to 2013 using the satellite-derived precipitation dataset TMPA 3B42. Additionally, the sensitivity of rainfall to other datasets was assessed: the national rain gauge observation network, real-time satellite rainfall and a merged product that combines rain gauges with non-calibrated space-borne rainfall measurements. The lower Baja California peninsula had the highest contribution from cyclonic rainfall in relative terms (∼40% of its total annual rainfall), whereas the contributions in the rest of the country showed a low-to-medium dependence on tropical cyclones, with mean values ranging from 0% to 20%. In quantitative terms, southern regions of Mexico can receive more than 2400 mm of cyclonic rainfall during years with significant TC activity. Moreover, (a) the number of tropical cyclones impacting Mexico has been significantly increasing since 1998, but cyclonic contributions in relative and quantitative terms have not been increasing, and (b) wind speed and rainfall intensity during cyclones are not highly correlated. Future work should evaluate the impacts of such contributions on surface and groundwater hydrological processes and connect the knowledge gaps between the magnitude of tropical cyclones, flood hazards, and economic losses.

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

NASA Astrophysics Data System (ADS)

Afzal, Muhammad Hassan Bin

2015-05-01

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

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Monsoon rainfall over India in June and link with northwest tropical pacific - June ISMR and link with northwest tropical pacific

NASA Astrophysics Data System (ADS)

Surendran, Sajani; Gadgil, Sulochana; Rajendran, Kavirajan; Varghese, Stella Jes; Kitoh, Akio

2018-03-01

Recent years have witnessed large interannual variation of all-India rainfall (AIR) in June, with intermittent large deficits and excesses. Variability of June AIR is found to have the strongest link with variation of rainfall over northwest tropical Pacific (NWTP), with AIR deficit (excess) associated with enhancement (suppression) of NWTP rainfall. This association is investigated using high-resolution Meteorological Research Institute model which shows high skill in simulating important features of Asian summer monsoon, its variability and the inverse relationship between NWTP rainfall and AIR. Analysis of the variation of NWTP rainfall shows that it is associated with a change in the latitudinal position of subtropical westerly jet over the region stretching from West of Tibetan Plateau (WTP) to NWTP and the phase of Rossby wave steered in it with centres over NWTP and WTP. In years with large rainfall excess/deficit, the strong link between AIR and NWTP rainfall exists through differences in Rossby wave phase steered in the jet. The positive phase of the WTP-NWTP pattern, with troughs over WTP and west of NWTP, tends to be associated with increased rainfall over NWTP and decreased AIR. This scenario is reversed in the opposite phase. Thus, the teleconnection between NWTP rainfall and AIR is a manifestation of the difference in the phase of Rossby wave between excess and deficit years, with centres over WTP and NWTP. This brings out the importance of prediction of phase of Rossby waves over WTP and NWTP in advance, for prediction of June rainfall over India.

Satellite rainfall monitoring over Africa using multi-spectral MSG data in an artificial neural network approach

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Grimes, David

2010-05-01

Rainfall monitoring over Africa is crucial for a variety of humanitarian and agricultural purposes, and satellites have been used for some time to provide real-time rainfall estimates over the region. Several recent applications of satellite rainfall estimates, such as flash-flood warning systems and crop-yield models, require accurate rainfall totals at daily timescales or below. Multi-spectral Meteosat Second Generation (MSG) data provide information on cloud properties such as optical depth and cloud particle size and phase. These parameters are all relevant to the probability of rainfall occurring from a cloud and the likely intensity of that rainfall, so the use of MSG data should lead to improved satellite rainfall estimates. An artificial neural network (ANN) using multi-spectral inputs from MSG has been trained to provide daily rainfall estimates over Ethiopia, using daily rain-gauge data for calibration. Although ANN methods have previously been applied to the problem of producing rainfall estimates from multi-spectral satellite data, in general precipitation radar data have been used for calibration. The advantage of using rain-gauge data is that gauges are far more widespread over Africa than radar networks, so this method can be easily transferred and if necessary re-calibrated in different climatological regions of the continent. The ANN estimates have been validated against independent Ethiopian gauge data at a variety of time and space scales. The ANN shows an improvement in accuracy at daily timescale when compared to rainfall estimates from the TAMSAT algorithm, which uses only single channel MSG data.

Evaluating rainfall kinetic energy - intensity relationships with observed disdrometric data

NASA Astrophysics Data System (ADS)

Angulo-Martinez, Marta; Begueria, Santiago; Latorre, Borja

2016-04-01

Rainfall kinetic energy is required for determining erosivity, the ability of rainfall to detach soil particles and initiate erosion. Its determination relay on the use of disdrometers, i.e. devices capable of measuring the drop size distribution and velocity of falling raindrops. In the absence of such devices, rainfall kinetic energy is usually estimated with empirical expressions relating rainfall energy and intensity. We evaluated the performance of 14 rainfall energy equations in estimating one-minute rainfall energy and event total energy, in comparison with observed data from 821 rainfall episodes (more than 100 thousand one-minute observations) by means of an optical disdrometer. In addition, two sources of bias when using such relationships were evaluated: i) the influence of using theoretical terminal raindrop fall velocities instead of measured values; and ii) the influence of time aggregation (rainfall intensity data every 5-, 10-, 15-, 30-, and 60-minutes). Empirical relationships did a relatively good job when complete events were considered (R2 > 0.82), but offered poorer results for within-event (one-minute resolution) variation. Also, systematic biases where large for many equations. When raindrop size distribution was known, estimating the terminal fall velocities by empirical laws produced good results even at fine time resolution. The influence of time aggregation was very high in the estimated kinetic energy, although linear scaling may allow empirical correction. This results stress the importance of considering all these effects when rainfall energy needs to be estimated from more standard precipitation records. , and recommends the use of disdrometer data to locally determine rainfall kinetic energy.

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

NASA Astrophysics Data System (ADS)

Richard, Sandra; Walsh, Kevin J. E.

2017-09-01

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

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

PubMed

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

2014-12-01

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

Relating rainfall characteristics to cloud top temperatures at different scales

NASA Astrophysics Data System (ADS)

Klein, Cornelia; Belušić, Danijel; Taylor, Christopher

2017-04-01

Extreme rainfall from mesoscale convective systems (MCS) poses a threat to lives and livelihoods of the West African population through increasingly frequent devastating flooding and loss of crops. However, despite the significant impact of such extreme events, the dominant processes favouring their occurrence are still under debate. In the data-sparse West African region, rainfall radar data from the Tropical Rainfall Measuring Mission (TRMM) gives invaluable information on the distribution and frequency of extreme rainfall. The TRMM 2A25 product provides a 15-year dataset of snapshots of surface rainfall from 2-4 overpasses per day. Whilst this sampling captures the overall rainfall characteristics, it is neither long nor frequent enough to diagnose changes in MCS properties, which may be linked to the trend towards rainfall intensification in the region. On the other hand, Meteosat geostationary satellites provide long-term sub-hourly records of cloud top temperatures, raising the possibility of combining these with the high-quality rainfall data from TRMM. In this study, we relate TRMM 2A25 rainfall to Meteosat Second Generation (MSG) cloud top temperatures, which are available from 2004 at 15 minutes intervals, to get a more detailed picture of the structure of intense rainfall within the life cycle of MCS. We find TRMM rainfall intensities within an MCS to be strongly coupled with MSG cloud top temperatures: the probability for extreme rainfall increases from <10% for minimum temperatures warmer than -40°C to over 70% when temperatures drop below -70°C, confirming the potential in analysing cloud-top temperatures as a proxy for extreme rain. The sheer size of MCS raises the question which scales of sub-cloud structures are more likely to be associated with extreme rain than others. In the end, this information could help to associate scale changes in cloud top temperatures with processes that affect the probability of extreme rain. We use 2D continuous wavelets to decompose cloud top temperatures into power spectra at scales between 15 and 200km. From these, cloud sub-structures are identified as circular areas of respective scale with local power maxima in their centre. These areas are then mapped onto coinciding TRMM rainfall, allowing us to assign rainfall fields to sub-cloud features of different scales. We find a higher probability for extreme rainfall for cloud features above a scale of 30km, with features 100km contributing most to the number of extreme rainfall pixels. Over the average diurnal cycle, the number of smaller cloud features between 15-60km shows an increase between 15 - 1700UTC, gradually developing into larger ones. The maximum of extreme rainfall pixels around 1900UTC coincides with a peak for scales 100km, suggesting a dominant role of these scales for intense rain for the analysed cloud type. Our results demonstrate the suitability of 2D wavelet decomposition for the analysis of sub-cloud structures and their relation to rainfall characteristics, and help us to understand long-term changes in the properties of MCS.

SUBPIXEL-SCALE RAINFALL VARIABILITY AND THE EFFECTS ON SEPARATION OF RADAR AND GAUGE RAINFALL ERRORS

EPA Science Inventory

One of the primary sources of the discrepancies between radar-based rainfall estimates and rain gauge measurements is the point-area difference, i.e., the intrinsic difference in the spatial dimensions of the rainfall fields that the respective data sets are meant to represent. ...

Spatial distribution and temporal trends of rainfall erosivity in mainland China for 1951-2010

Treesearch

Wei Qin; Qiankun Guo; Changqing Zuo; Zhijie Shan; Liang Ma; Ge Sun

2016-01-01

Rainfall erosivity is an important factor for estimating soil erosion rates. Understanding the spatial distributionand temporal trends of rainfall erosivity is especially critical for soil erosion risk assessment and soil conservationplanning in mainland China. However, reports on the spatial distribution and temporal trends of rainfall...

Influence of Latent Heating over the Asian and Western Pacific Monsoon Region on Sahel Summer Rainfall.

PubMed

He, Shan; Yang, Song; Li, Zhenning

2017-08-09

There has been an interdecadal shift towards a less humid state in Sahel summer rainfall since the 1960s. The decreased Sahel summer rainfall was associated with enhanced summer latent heating over the South Asian and western Pacific summer monsoon region and anomalous zonal-vertical cell of the Asian summer monsoon circulation, indicating that the latent heating plays a significant role in the change in Sahel rainfall. The effects of the latent heating over different monsoon domains on the Sahel rainfall are investigated through several model experiments. Results show that the remote monsoon heating mainly affects Sahel rainfall by generating changes in the zonal-vertical atmospheric circulation.

Adequacy of satellite derived rainfall data for stream flow modeling

USGS Publications Warehouse

Artan, G.; Gadain, Hussein; Smith, Jodie; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.

2007-01-01

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

Estimating the Risk of Domestic Water Source Contamination following Precipitation Events

PubMed Central

Eisenhauer, Ian F.; Hoover, Christopher M.; Remais, Justin V.; Monaghan, Andrew; Celada, Marco; Carlton, Elizabeth J.

2016-01-01

Climate change is expected to increase precipitation extremes, threatening water quality. In low resource settings, it is unclear which water sources are most vulnerable to contamination following rainfall events. We evaluated the relationship between rainfall and drinking water quality in southwest Guatemala where heavy rainfall is frequent and access to safe water is limited. We surveyed 59 shallow household wells, measured precipitation, and calculated simple hydrological variables. We compared Escherichia coli concentration at wells where recent rainfall had occurred versus had not occurred, and evaluated variability in the association between rainfall and E. coli concentration under different conditions using interaction models. Rainfall in the past 24 hours was associated with greater E. coli concentrations, with the strongest association between rainfall and fecal contamination at wells where pigs were nearby. Because of the small sample size, these findings should be considered preliminary, but provide a model to evaluate vulnerability to climate change. PMID:27114298

The development rainfall forecasting using kalman filter

NASA Astrophysics Data System (ADS)

Zulfi, Mohammad; Hasan, Moh.; Dwidja Purnomo, Kosala

2018-04-01

Rainfall forecasting is very interesting for agricultural planing. Rainfall information is useful to make decisions about the plan planting certain commodities. In this studies, the rainfall forecasting by ARIMA and Kalman Filter method. Kalman Filter method is used to declare a time series model of which is shown in the form of linear state space to determine the future forecast. This method used a recursive solution to minimize error. The rainfall data in this research clustered by K-means clustering. Implementation of Kalman Filter method is for modelling and forecasting rainfall in each cluster. We used ARIMA (p,d,q) to construct a state space for KalmanFilter model. So, we have four group of the data and one model in each group. In conclusions, Kalman Filter method is better than ARIMA model for rainfall forecasting in each group. It can be showed from error of Kalman Filter method that smaller than error of ARIMA model.

Rainfall interception by tree crown and leaf litter: an interactive process

Treesearch

Xiang Li; Qingfu Xiao; Jianzhi Niu; Salli Dymond; E. Gregory McPherson; Natalie van Doorn; Xinxiao Yu; Baoyuan Xie; Kebin Zhang; Jiao Li

2017-01-01

Rainfall interception research in forest ecosystems usually focuses on interception by either tree crown or leaf litter, although the 2 components interact when rainfall occurs. A process-based study was conducted to jointly measure rainfall interception by crown and litter and the interaction between the 2 interception processes for 4 tree species (...

Rainfall Data Simulation

Treesearch

T.L. Rogerson

1980-01-01

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

Global rainfall erosivity assessment based on high-temporal resolution rainfall records

USDA-ARS?s Scientific Manuscript database

Rainfall erosivity quantifies the climatic effect on water erosion. In the framework of the Universal Soil Loss Equation, rainfall erosivity, also known as the R-factor, is defined as the mean annual sum of event erosivity values. For a new global soil erosion assessment, also in the broad context...

Stochastic Generation of Monthly Rainfall Data

NASA Astrophysics Data System (ADS)

Srikanthan, R.

2009-03-01

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

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

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Characteristics of Heavy Summer Rainfall in Southwestern Taiwan in Relation to Orographic Effects

NASA Technical Reports Server (NTRS)

Chen, Ching-Sen; Chen, Wan-Chin; Tao, Wei-Kuo

2004-01-01

On the windward side of southwestern Taiwan, about a quarter to a half of all rainfall during mid-July through August from 1994 to 2000 came from convective systems embedded in the southwesterly monsoon flow. k this study, the causes of two heavy rainfall events (daily rainfall exceeding 100 mm day over at least three rainfall stations) observed over the slopes and/or lowlands of southwestern Taiwan were examined. Data from European Center for Medium-Range Weather Forecasts /Tropical Ocean- Global Atmosphere (EC/TOGA) analyses, the rainfall stations of the Automatic Rainfall and Meteorological Telemetry System (ARMTS) and the conventional surface stations over Taiwan, and the simulation results from a regional-scale numerical model were used to accomplish the objectives. In one event (393 mm day on 9 August 1999), heavy rainfall was observed over the windward slopes of southern Taiwan in a potentially unstable environment with very humid air around 850 hPa. The extreme accumulation was simulated and attributed to orographic lifting effects. No preexisting convection drifted in from the Taiwan Strait into western Taiwan.

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

Modelling rainfall amounts using mixed-gamma model for Kuantan district

NASA Astrophysics Data System (ADS)

Zakaria, Roslinazairimah; Moslim, Nor Hafizah

2017-05-01

An efficient design of flood mitigation and construction of crop growth models depend upon good understanding of the rainfall process and characteristics. Gamma distribution is usually used to model nonzero rainfall amounts. In this study, the mixed-gamma model is applied to accommodate both zero and nonzero rainfall amounts. The mixed-gamma model presented is for the independent case. The formulae of mean and variance are derived for the sum of two and three independent mixed-gamma variables, respectively. Firstly, the gamma distribution is used to model the nonzero rainfall amounts and the parameters of the distribution (shape and scale) are estimated using the maximum likelihood estimation method. Then, the mixed-gamma model is defined for both zero and nonzero rainfall amounts simultaneously. The formulae of mean and variance for the sum of two and three independent mixed-gamma variables derived are tested using the monthly rainfall amounts from rainfall stations within Kuantan district in Pahang Malaysia. Based on the Kolmogorov-Smirnov goodness of fit test, the results demonstrate that the descriptive statistics of the observed sum of rainfall amounts is not significantly different at 5% significance level from the generated sum of independent mixed-gamma variables. The methodology and formulae demonstrated can be applied to find the sum of more than three independent mixed-gamma variables.

Mineralogical evidence of reduced East Asian summer monsoon rainfall on the Chinese loess plateau during the early Pleistocene interglacials

NASA Astrophysics Data System (ADS)

Meng, Xianqiang; Liu, Lianwen; Wang, Xingchen T.; Balsam, William; Chen, Jun; Ji, Junfeng

2018-03-01

The East Asian summer monsoon (EASM) is an important component of the global climate system. A better understanding of EASM rainfall variability in the past can help constrain climate models and better predict the response of EASM to ongoing global warming. The warm early Pleistocene, a potential analog of future climate, is an important period to study EASM dynamics. However, existing monsoon proxies for reconstruction of EASM rainfall during the early Pleistocene fail to disentangle monsoon rainfall changes from temperature variations, complicating the comparison of these monsoon records with climate models. Here, we present three 2.6 million-year-long EASM rainfall records from the Chinese Loess Plateau (CLP) based on carbonate dissolution, a novel proxy for rainfall intensity. These records show that the interglacial rainfall on the CLP was lower during the early Pleistocene and then gradually increased with global cooling during the middle and late Pleistocene. These results are contrary to previous suggestions that a warmer climate leads to higher monsoon rainfall on tectonic timescales. We propose that the lower interglacial EASM rainfall during the early Pleistocene was caused by reduced sea surface temperature gradients across the equatorial Pacific, providing a testable hypothesis for climate models.

Origins and interrelationship of Intraseasonal rainfall variations around the Maritime Continent during boreal winter

NASA Astrophysics Data System (ADS)

Cao, Xi; Wu, Renguang

2018-04-01

Large intraseasonal rainfall variations are identified over the southern South China Sea (SSCS), tropical southeastern Indian Ocean (SEIO), and east coast of the Philippines (EPHI) in boreal winter. The present study contrasts origins and propagations and investigates interrelations of intraseasonal rainfall variations on the 10-20- and 30-60-day time scales in these regions. Different origins are identified for intraseasonal rainfall anomalies over the SSCS, SEIO, and EPHI on both time scales. On the 10-20-day time scale, strong northerly or northeasterly wind anomalies related to the East Asian winter monsoon (EAWM) play a major role in intraseasonal rainfall variations over the SSCS and EPHI. On the 30-60-day time scale, both the intraseasonal signal from the tropical Indian Ocean and the EAWM-related wind anomalies contribute to intraseasonal rainfall variations over the SSCS, whereas the EAWM-related wind anomalies have a major contribution to the intraseasonal rainfall variations over the EPHI. No relation is detected between the intraseasonal rainfall variations over the SEIO and the EAWM on both the 10-20-day and 30-60-day time scales. The anomalies associated with intraseasonal rainfall variations over the SSCS and EPHI propagate northwestward and northeastward, respectively, on the 10-20- and 30-60-day time scales. The intraseasonal rainfall anomalies display northwestward and northward propagation over the Bay of Bengal, respectively, on the 10-20- and 30-60-day time scales.

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

NASA Astrophysics Data System (ADS)

Hutchinson, P.

1992-05-01

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

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

NASA Astrophysics Data System (ADS)

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 .

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Estimation of debris flow critical rainfall thresholds by a physically-based model

NASA Astrophysics Data System (ADS)

Papa, M. N.; Medina, V.; Ciervo, F.; Bateman, A.

2012-11-01

Real time assessment of debris flow hazard is fundamental for setting up warning systems that can mitigate its risk. A convenient method to assess the possible occurrence of a debris flow is the comparison of measured and forecasted rainfall with rainfall threshold curves (RTC). Empirical derivation of the RTC from the analysis of rainfall characteristics of past events is not possible when the database of observed debris flows is poor or when the environment changes with time. For landslides triggered debris flows, the above limitations may be overcome through the methodology here presented, based on the derivation of RTC from a physically based model. The critical RTC are derived from mathematical and numerical simulations based on the infinite-slope stability model in which land instability is governed by the increase in groundwater pressure due to rainfall. The effect of rainfall infiltration on landside occurrence is modelled trough a reduced form of the Richards equation. The simulations are performed in a virtual basin, representative of the studied basin, taking into account the uncertainties linked with the definition of the characteristics of the soil. A large number of calculations are performed combining different values of the rainfall characteristics (intensity and duration of event rainfall and intensity of antecedent rainfall). For each combination of rainfall characteristics, the percentage of the basin that is unstable is computed. The obtained database is opportunely elaborated to derive RTC curves. The methodology is implemented and tested on a small basin of the Amalfi Coast (South Italy).

A regression-kriging model for estimation of rainfall in the Laohahe basin

NASA Astrophysics Data System (ADS)

Wang, Hong; Ren, Li L.; Liu, Gao H.

2009-10-01

This paper presents a multivariate geostatistical algorithm called regression-kriging (RK) for predicting the spatial distribution of rainfall by incorporating five topographic/geographic factors of latitude, longitude, altitude, slope and aspect. The technique is illustrated using rainfall data collected at 52 rain gauges from the Laohahe basis in northeast China during 1986-2005 . Rainfall data from 44 stations were selected for modeling and the remaining 8 stations were used for model validation. To eliminate multicollinearity, the five explanatory factors were first transformed using factor analysis with three Principal Components (PCs) extracted. The rainfall data were then fitted using step-wise regression and residuals interpolated using SK. The regression coefficients were estimated by generalized least squares (GLS), which takes the spatial heteroskedasticity between rainfall and PCs into account. Finally, the rainfall prediction based on RK was compared with that predicted from ordinary kriging (OK) and ordinary least squares (OLS) multiple regression (MR). For correlated topographic factors are taken into account, RK improves the efficiency of predictions. RK achieved a lower relative root mean square error (RMSE) (44.67%) than MR (49.23%) and OK (73.60%) and a lower bias than MR and OK (23.82 versus 30.89 and 32.15 mm) for annual rainfall. It is much more effective for the wet season than for the dry season. RK is suitable for estimation of rainfall in areas where there are no stations nearby and where topography has a major influence on rainfall.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Applications of Polarimetric Radar to the Hydrometeorology of Urban Floods in St. Louis

NASA Astrophysics Data System (ADS)

Chaney, M. M.; Smith, J. A.; Baeck, M. L.

2017-12-01

Predicting and responding to flash flooding requires accurate spatial and temporal representation of rainfall rates. The polarimetric upgrade of all US radars has led to optimism about more accurate rainfall rate estimation from the NEXRAD network of WSR-88D radars in the US. Previous work has proposed different algorithms to do so, but significant uncertainties remain, especially for extreme short-term rainfall rates that control flash floods in urban settings. We will examine the relationship between radar rainfall estimates and gage rainfall rates for a catalog of 30 storms in St. Louis during the period of polarimetric radar measurements, 2012-2016. The storms are selected to provide a large sample of extreme rainfall measurements at the 15-minute to 3-hour time scale. A network of 100 rain gages and a lack of orographic or coastal effects make St. Louis an interesting location to study these relationships. A better understanding of the relationships between polarimetric radar measurements and gage rainfall rates will aid in refining polarimetric radar rainfall algorithms, in turn helping hydrometeorologists predict flash floods and other hazards associated with severe rainfall. Given the fact that St. Louis contains some of the flashiest watersheds in the United States (Smith and Smith, 2015), it is an especially important urban area in which to have accurate, real-time rainfall data. Smith, Brianne K, and James A Smith. "The Flashiest Watersheds in the Contiguous United States." American Meteorological Society (2015): 2365-2381. Web.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Non-parametric characterization of long-term rainfall time series

NASA Astrophysics Data System (ADS)

Tiwari, Harinarayan; Pandey, Brij Kishor

2018-03-01

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

Comparison between intensity- duration thresholds and cumulative rainfall thresholds for the forecasting of landslide

NASA Astrophysics Data System (ADS)

Lagomarsino, Daniela; Rosi, Ascanio; Rossi, Guglielmo; Segoni, Samuele; Catani, Filippo

2014-05-01

This work makes a quantitative comparison between the results of landslide forecasting obtained using two different rainfall threshold models, one using intensity-duration thresholds and the other based on cumulative rainfall thresholds in an area of northern Tuscany of 116 km2. The first methodology identifies rainfall intensity-duration thresholds by means a software called MaCumBA (Massive CUMulative Brisk Analyzer) that analyzes rain-gauge records, extracts the intensities (I) and durations (D) of the rainstorms associated with the initiation of landslides, plots these values on a diagram, and identifies thresholds that define the lower bounds of the I-D values. A back analysis using data from past events can be used to identify the threshold conditions associated with the least amount of false alarms. The second method (SIGMA) is based on the hypothesis that anomalous or extreme values of rainfall are responsible for landslide triggering: the statistical distribution of the rainfall series is analyzed, and multiples of the standard deviation (σ) are used as thresholds to discriminate between ordinary and extraordinary rainfall events. The name of the model, SIGMA, reflects the central role of the standard deviations in the proposed methodology. The definition of intensity-duration rainfall thresholds requires the combined use of rainfall measurements and an inventory of dated landslides, whereas SIGMA model can be implemented using only rainfall data. These two methodologies were applied in an area of 116 km2 where a database of 1200 landslides was available for the period 2000-2012. The results obtained are compared and discussed. Although several examples of visual comparisons between different intensity-duration rainfall thresholds are reported in the international literature, a quantitative comparison between thresholds obtained in the same area using different techniques and approaches is a relatively undebated research topic.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Do we really use rainfall observations consistent with reality in hydrological modelling?

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Regularized joint inverse estimation of extreme rainfall amounts in ungauged coastal basins of El Salvador

USGS Publications Warehouse

Friedel, M.J.

2008-01-01

A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To test this hypothesis, peak-flow discharge values determined from streamflow recurrence information (10-year, 25-year, and 100-year) collected outside the study basins are used to develop regional (country-wide) regression equations. Peak-flow discharge derived from these equations together with preferred spatial parameter relations as soft prior information are used to constrain the simultaneous calibration of 20 tributary basin models. The nonlinear range of uncertainty in estimated parameter values (1 curve number and 3 recurrent rainfall amounts for each model) is determined using an inverse calibration-constrained Monte Carlo approach. Cumulative probability distributions for rainfall amounts indicate differences among basins for a given return period and an increase in magnitude and range among basins with increasing return interval. Comparison of the estimated median rainfall amounts for all return periods were reasonable but larger (3.2-26%) than rainfall estimates computed using the frequency-duration (traditional) approach and individual rain gauge data. The observed 25-year recurrence rainfall amount at La Hachadura in the Paz River basin during Hurricane Mitch (1998) is similar in value to, but outside and slightly less than, the estimated rainfall confidence limits. The similarity in joint inverse and traditionally computed rainfall events, however, suggests that the rainfall observation may likely be due to under-catch and not model bias. ?? Springer Science+Business Media B.V. 2007.

Observed Recent Trends in Tropical Cyclone Rainfall Over Major Ocean Basins

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

Ongoma, Victor; Chen, Haishan; Gao, Chujie

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

USGS Publications Warehouse

Kinner, David A.; Moody, John A.

2008-01-01

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

The spatial return level of aggregated hourly extreme rainfall in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Shaffie, Mardhiyyah; Eli, Annazirin; Wan Zin, Wan Zawiah; Jemain, Abdul Aziz

2015-07-01

This paper is intended to ascertain the spatial pattern of extreme rainfall distribution in Peninsular Malaysia at several short time intervals, i.e., on hourly basis. Motivation of this research is due to historical records of extreme rainfall in Peninsular Malaysia, whereby many hydrological disasters at this region occur within a short time period. The hourly periods considered are 1, 2, 3, 6, 12, and 24 h. Many previous hydrological studies dealt with daily rainfall data; thus, this study enables comparison to be made on the estimated performances between daily and hourly rainfall data analyses so as to identify the impact of extreme rainfall at a shorter time scale. Return levels based on the time aggregate considered are also computed. Parameter estimation using L-moment method for four probability distributions, namely, the generalized extreme value (GEV), generalized logistic (GLO), generalized Pareto (GPA), and Pearson type III (PE3) distributions were conducted. Aided with the L-moment diagram test and mean square error (MSE) test, GLO was found to be the most appropriate distribution to represent the extreme rainfall data. At most time intervals (10, 50, and 100 years), the spatial patterns revealed that the rainfall distribution across the peninsula differ for 1- and 24-h extreme rainfalls. The outcomes of this study would provide additional information regarding patterns of extreme rainfall in Malaysia which may not be detected when considering only a higher time scale such as daily; thus, appropriate measures for shorter time scales of extreme rainfall can be planned. The implementation of such measures would be beneficial to the authorities to reduce the impact of any disastrous natural event.

[Output characteristics of rainfall runoff phosphorus pollution from a typical small watershed in Yimeng mountainous area].

PubMed

Yu, Xing-xiu; Li, Zhen-wei; Liu, Qian-jin; Jing, Guang-hua

2012-08-01

Relationships between phosphorus pollutant concentrations and precipitation-runoff were analyzed by monitoring pollutant losses at outlets of the Menglianggu watershed in 2010. A typical small watershed was selected to examine the runoff and quality parameters such as total phosphorus (TP), particle phosphorus (PP), dissolve phosphorus (DP) and dissolve inorganic phosphorus (DIP) in rainfall-runoff of 10 rainfall events. Precipitation was above 2 mm for all the 10 rainfall events. The results showed that the peak of phosphorus concentrations occurred before the peak of water flows, whereas change processes of the phosphorus fluxes were consistent with that of the water flows and the phosphorus flux also have a strong linear relationship with the water flows. The minimums of the phosphorus concentrations in every 10 natural rainfall events have small differences with each other, but the maximum and EMCs of the phosphorus concentrations have significant differences with each rainfall event. This was mainly influenced by the precipitation, maximum rainfall intensity and mean rainfall intensity (EMCs) and was less influenced by rainfall duration. DP and TP were mainly composed of DIP and PP, respectively. There were no significant correlations between DIP/DP dynamic changes and rainfall characteristics, whereas significant correlations between PP/TP dynamic changes and maximum rainfall intensity were detected. The production of DIP, DP, AND TP were mainly influenced by the direct runoff (DR) and base flow (BF). The EMCs of DIP, DP, TP and the variations of DIP/DP were all found to have significant polynomial relationships with DR/TR., but the dynamic changes of PP/ TP and the EMCS of PP were less influenced by the DR/TR.

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

PubMed

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

2013-01-01

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

Merging of rain gauge and radar data for urban hydrological modelling

NASA Astrophysics Data System (ADS)

Berndt, Christian; Haberlandt, Uwe

2015-04-01

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

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

NASA Astrophysics Data System (ADS)

Roghani, Rabbaneh; Soltani, Saeid; Bashari, Hossein

2016-04-01

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

Rainfall erosivity and sediment load over the Poyang Lake Basin under variable climate and human activities since the 1960s

NASA Astrophysics Data System (ADS)

Gu, Chaojun; Mu, Xingmin; Gao, Peng; Zhao, Guangju; Sun, Wenyi; Yu, Qiang

2018-03-01

Accelerated soil erosion exerts adverse effects on water and soil resources. Rainfall erosivity reflects soil erosion potential driven by rainfall, which is essential for soil erosive risk assessment. This study investigated the spatiotemporal variation of rainfall erosivity and its impacts on sediment load over the largest freshwater lake basin of China (the Poyang Lake Basin, abbreviate to PYLB). The spatiotemporal variations of rainfall erosivity from 1961 to 2014 based on 57 meteorological stations were detected using the Mann-Kendall test, linear regression, and kriging interpolation method. The sequential t test analysis of regime shift (STARS) was employed to identify the abrupt changes of sediment load, and the modified double mass curve was used to assess the impacts of rainfall erosivity variability on sediment load. It was found that there was significant increase (P < 0.05) in rainfall erosivity in winter due to the significant increase in January over the last 54 years, whereas no trend in year and other seasons. Annual sediment load into the Poyang Lake (PYL) decreased significantly (P < 0.01) between 1961 and 2014, and the change-points were identified in both 1985 and 2003. It was found that take annual rainfall erosivity as the explanatory variables of the double mass curves is more reasonable than annual rainfall and erosive rainfall. The estimation via the modified double mass curve demonstrated that compared with the period before change-point (1961-1984), the changes of rainfall erosivity increased 8.0 and 2.1% of sediment load during 1985-2002 and 2003-2014, respectively. Human activities decreased 50.2 and 69.7% of sediment load during the last two periods, which indicated effects of human activities on sediment load change was much larger than that of rainfall erosivity variability in the PYLB.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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 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.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

PubMed

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

2015-09-01

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

Vegetation-rainfall feedbacks across the Sahel: a combined observational and modeling study

NASA Astrophysics Data System (ADS)

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

2016-12-01

The Sahel rainfall is characterized by large interannual variability. Past modeling studies have concluded that the Sahel rainfall variability is primarily driven by oceanic forcings and amplified by land-atmosphere interactions. However, the relative importance of oceanic versus terrestrial drivers has never been assessed from observations. The current understanding of vegetation's impacts on climate, i.e. positive vegetation-rainfall feedback through the albedo, moisture, and momentum mechanisms, comes from untested models. Neither the positive vegetation-rainfall feedback, nor the underlying mechanisms, has been fully resolved in observations. The current study fills the knowledge gap about the observed vegetation-rainfall feedbacks, through the application of the multivariate statistical method Generalized Equilibrium Feedback Assessment (GEFA) to observational data. According to GEFA, the observed oceanic impacts dominate over terrestrial impacts on Sahel rainfall, except in the post-monsoon period. Positive leaf area index (LAI) anomalies favor an extended, wetter monsoon across the Sahel, largely due to moisture recycling. The albedo mechanism is not responsible for this positive vegetation feedback on the seasonal-interannual time scale, which is too short for a grass-desert transition. A low-level stabilization and subsidence is observed in response to increased LAI - potentially responsible for a negative vegetation-rainfall feedback. However, the positive moisture feedback overwhelms the negative momentum feedback, resulting in an observed positive vegetation-rainfall feedback. We further applied GEFA to a fully-coupled Community Earth System Model (CESM) control run, as an example of evaluating climate models against the GEFA-based observational benchmark. In contrast to the observed positive vegetation-rainfall feedbacks, CESM simulates a negative vegetation-rainfall feedback across Sahel, peaking in the pre-monsoon season. The simulated negative feedback is largely due to the low-level stabilization caused by increased LAI. Positive moisture feedback is present in the CESM simulation, but an order weaker than the observed and weaker than the negative momentum feedback, thereby leading to the simulated negative vegetation-rainfall feedbacks.

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

NASA Astrophysics Data System (ADS)

Barman, S.; Bhattacharjya, R. K.

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Climate-change driven increase in high intensity rainfall events: Analysis of development in the last decades and towards an extrapolation of future progression

NASA Astrophysics Data System (ADS)

Müller, Eva; Pfister, Angela; Gerd, Büger; Maik, Heistermann; Bronstert, Axel

2015-04-01

Hydrological extreme events can be triggered by rainfall on different spatiotemporal scales: river floods are typically caused by event durations of between hours and days, while urban flash floods as well as soil erosion or contaminant transport rather result from storms events of very short duration (minutes). Still, the analysis of climate change impacts on rainfall-induced extreme events is usually carried out using daily precipitation data at best. Trend analyses of extreme rainfall at sub-daily or even sub-hourly time scales are rare. In this contribution two lines of research are combined: first, we analyse sub-hourly rainfall data for several decades in three European regions.Second, we investigate the scaling behaviour of heavy short-term precipitation with temperature, i.e. the dependence of high intensity rainfall on the atmospheric temperature at that particular time and location. The trend analysis of high-resolution rainfall data shows for the first time that the frequency of short and intensive storm events in the temperate lowland regions in Germany has increased by up to 0.5 events per year over the last decades. I.e. this trend suggests that the occurrence of these types of storms have multiplied over only a few decades. Parallel to the changes in the rainfall regime, increases in the annual and seasonal average temperature and changes in the occurrence of circulation patterns responsible for the generation of high-intensity storms have been found. The analysis of temporally highly resolved rainfall records from three European regions further indicates that extreme precipitation events are more intense with warmer temperatures during the rainfall event. These observations follow partly the Clausius-Clapeyron relation. Based on this relation one may derive a general rule of maximum rainfall intensity associated to the event temperature, roughly following the Clausius-Clapeyron (CC) relation. This rule might be used for scenarios of future maximum rainfall intensities under a warming climate.

Climate downscaling over South America for 1971-2000: application in SMAP rainfall-runoff model for Grande River Basin

NASA Astrophysics Data System (ADS)

da Silva, Felipe das Neves Roque; Alves, José Luis Drummond; Cataldi, Marcio

2018-03-01

This paper aims to validate inflow simulations concerning the present-day climate at Água Vermelha Hydroelectric Plant (AVHP—located on the Grande River Basin) based on the Soil Moisture Accounting Procedure (SMAP) hydrological model. In order to provide rainfall data to the SMAP model, the RegCM regional climate model was also used working with boundary conditions from the MIROC model. Initially, present-day climate simulation performed by RegCM model was analyzed. It was found that, in terms of rainfall, the model was able to simulate the main patterns observed over South America. A bias correction technique was also used and it was essential to reduce mistakes related to rainfall simulation. Comparison between rainfall simulations from RegCM and MIROC showed improvements when the dynamical downscaling was performed. Then, SMAP, a rainfall-runoff hydrological model, was used to simulate inflows at Água Vermelha Hydroelectric Plant. After calibration with observed rainfall, SMAP simulations were evaluated in two different periods from the one used in calibration. During calibration, SMAP captures the inflow variability observed at AVHP. During validation periods, the hydrological model obtained better results and statistics with observed rainfall. However, in spite of some discrepancies, the use of simulated rainfall without bias correction captured the interannual flow variability. However, the use of bias removal in the simulated rainfall performed by RegCM brought significant improvements to the simulation of natural inflows performed by SMAP. Not only the curve of simulated inflow became more similar to the observed inflow, but also the statistics improved their values. Improvements were also noticed in the inflow simulation when the rainfall was provided by the regional climate model compared to the global model. In general, results obtained so far prove that there was an added value in rainfall when regional climate model was compared to global climate model and that data from regional models must be bias-corrected so as to improve their results.

Models for estimating daily rainfall erosivity in China

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

The Effects of More Extreme Rainfall Patterns on Infiltration and Nutrient Losses in Agricultural Soils

NASA Astrophysics Data System (ADS)

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

2015-12-01

In the coming century, the proportion of total rainfall that falls in heavy storm events is expected to increase in many areas, especially in the US Midwest, a major agricultural region. These changes in rainfall patterns may have consequences for hydrologic flow and nutrient losses, especially in agricultural soils, with potentially negative consequences for receiving ground- and surface waters. We used a tracer experiment to examine how more extreme rainfall patterns may affect the movement of water and solutes through an agricultural soil profile in the upper Midwest, and to what extent tillage may moderate these effects. Two rainfall patterns were created with 5m x 5m rainout shelters at the Kellogg Biological Station LTER site in replicated plots with either conventional tillage or no-till management. Control rainfall treatments received water 3x per week, and extreme rainfall treatments received the same total amount of water but once every two weeks, to simulate less frequent but larger storms. In April 2015, potassium bromide (KBr) was added as a conservative tracer of water flow to all plots, and Br- concentrations in soil water at 1.2m depth were measured weekly from April through July. Soil water Br- concentrations increased and peaked more quickly under the extreme rainfall treatment, suggesting increased infiltration and solute transfer to depth compared to soils exposed to control rainfall patterns. Soil water Br- also increased and peaked more quickly in no-till than in conventional tillage treatments, indicating differences in flow paths between management systems. Soil moisture measured every 15 minutes at 10, 40, and 100cm depths corroborates tracer experiment results: rainfall events simulated in extreme rainfall treatments led to large increases in deep soil moisture, while the smaller rainfall events simulated under control conditions did not. Deep soil moisture in no-till treatments also increased sooner after water application as compared to in conventional soils. Our results suggest that exposure to more extreme rainfall patterns will likely increase infiltration depth and nutrient losses in agricultural soils. In particular, soils under no-till management, which leads to development of preferential flow paths, may be particularly vulnerable to vertical nutrient losses.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Validation Of TRMM For Hazard Assessment In The Remote Context Of Tropical Africa

NASA Astrophysics Data System (ADS)

Monsieurs, E.; Kirschbaum, D.; Tan, J.; Jacobs, L.; Kervyn, M.; Demoulin, A.; Dewitte, O.

2017-12-01

Accurate rainfall data is fundamental for understanding and mitigating the disastrous effects of many rainfall-triggered hazards, especially when one considers the challenges arising from climate change and rainfall variability. In tropical Africa in particular, the sparse operational rainfall gauging network hampers the ability to understand these hazards. Satellite rainfall estimates (SRE) can therefore be of great value. Yet, rigorous validation is required to identify the uncertainties when using SRE for hazard applications. We evaluated the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 Research Derived Daily Product from 1998 to 2017, at 0.25° x 0.25° spatial and 24 h temporal resolution. The validation was done over the western branch of the East African Rift, with the perspective of regional landslide hazard assessment in mind. Even though we collected an unprecedented dataset of 47 gauges with a minimum temporal resolution of 24 h, the sparse and heterogeneous temporal coverage in a region with high rainfall variability poses challenges for validation. In addition, the discrepancy between local-scale gauge data and spatially averaged ( 775 km²) TMPA data in the context of local convective storms and orographic rainfall is a crucial source of uncertainty. We adopted a flexible framework for SRE validation that fosters explorative research in a remote context. Results show that TMPA performs reasonably well during the rainy seasons for rainfall intensities <20 mm/day. TMPA systematically underestimates rainfall, but most problematic is the decreasing probability of detection of high intensity rainfalls. We suggest that landslide hazard might be efficiently assessed if we take account of the systematic biases in TMPA data and determine rainfall thresholds modulated by controls on, and uncertainties of, TMPA revealed in this study. Moreover, it is found relevant in mapping regional-scale rainfall-triggered hazards that are in any case poorly covered by the sparse available gauges. We anticipate validation of TMPA's successor (Integrated Multi-satellitE Retrievals for Global Precipitation Measurement; 10 km × 10 km, half-hourly) using the proposed framework, as soon as this product will be available in early 2018 for the 1998-present period.

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

NASA Astrophysics Data System (ADS)

Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

2017-04-01

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this research. Hopefully, all results developed from this research can be used as a warning system for Predicting Large Scale Landslides in the southern Taiwan. Keywords：Heavy Rainfall, Large Scale, landslides, Critical Rainfall Value

Evaluating the use of different precipitation datasets in simulating a flood event

NASA Astrophysics Data System (ADS)

Akyurek, Z.; Ozkaya, A.

2016-12-01

Floods caused by convective storms in mountainous regions are sensitive to the temporal and spatial variability of rainfall. Space-time estimates of rainfall from weather radar, satellites and numerical weather prediction models can be a remedy to represent pattern of the rainfall with some inaccuracy. However, there is a strong need for evaluation of the performance and limitations of these estimates in hydrology. This study aims to provide a comparison of gauge, radar, satellite (Hydro-Estimator (HE)) and numerical weather prediciton model (Weather Research and Forecasting (WRF)) precipitation datasets during an extreme flood event (22.11.2014) lasting 40 hours in Samsun-Turkey. For this study, hourly rainfall data from 13 ground observation stations were used in the analyses. This event having a peak discharge of 541 m3/sec created flooding at the downstream of Terme Basin. Comparisons were performed in two parts. First the analysis were performed in areal and point based manner. Secondly, a semi-distributed hydrological model was used to assess the accuracy of the rainfall datasets to simulate river flows for the flood event. Kalman Filtering was used in the bias correction of radar rainfall data compared to gauge measurements. Radar, gauge, corrected radar, HE and WRF rainfall data were used as model inputs. Generally, the HE product underestimates the cumulative rainfall amounts in all stations, radar data underestimates the results in cumulative sense but keeps the consistency in the results. On the other hand, almost all stations in WRF mean statistics computations have better results compared to the HE product but worse than the radar dataset. Results in point comparisons indicated that, trend of the rainfall is captured by the radar rainfall estimation well but radar underestimates the maximum values. According to cumulative gauge value, radar underestimated the cumulative rainfall amount by % 32. Contrary to other datasets, the bias of WRF is positive due to the overestimation of rainfall forecasts. It was seen that radar-based flow predictions demonstrated good potential for successful hydrological modeling. Moreover, flow predictions obtained from bias corrected radar rainfall values produced an increase in the peak flows compared to the ones obtained from radar data itself.

Assessing the Change in Rainfall Characteristics and Trends for the Southern African ITCZ Region

NASA Astrophysics Data System (ADS)

Baumberg, Verena; Weber, Torsten; Helmschrot, Jörg

2015-04-01

Southern Africa is strongly influenced by the movement and intensity of the Intertropical Convergence Zone (ITCZ) thus determining the climate in this region with distinct seasonal and inter-annual rainfall dynamics. The amount and variability of rainfall affect the various ecosystems by controlling the hydrological system, regulating water availability and determining agricultural practices. Changes in rainfall characteristics potentially caused by climate change are of uppermost relevance for both ecosystem functioning and human well-being in this region and, thus, need to be investigated. To analyse the rainfall variability governed by the ITCZ in southern Africa, observational daily rainfall datasets with a high spatial resolution of 0.25° x 0.25° (about 28 km x 28 km) from satellite-based Tropical Rainfall Measuring Mission (TRMM) and Global Land Data Assimilation System (GLDAS) are used. These datasets extend from 1998 to 2008 and 1948 to 2010, respectively, and allow for the assessment of rainfall characteristics over different spatial and temporal scales. Furthermore, a comparison of TRMM and GLDAS and, where available, with observed data will be made to determine the differences of both datasets. In order to quantify the intra- and inner-annual variability of rainfall, the amount of total rainfall, duration of rainy seasons and number of dry spells along with further indices are calculated from the observational datasets. Over the southern African ITCZ region, the rainfall characteristics change moving from wetter north to the drier south, but also from west to east, i.e. the coast to the interior. To address expected spatial and temporal variabilities, the assessment of changes in the rainfall parameters will be carried out for different transects in zonal and meridional directions over the region affected by the ITCZ. Revealing trends over more than 60 years, the results will help to identify and understand potential impacts of climate change on rainfall characteristics for the southern African ITCZ region. The findings of this study will feed into various ecosystem assessment and biodiversity change studies in Angola and Zambia.

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

NASA Astrophysics Data System (ADS)

Nduwayezu, Emmanuel; Kanevski, Mikhail; Jaboyedoff, Michel

2013-04-01

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

Meteorological Trigger Conditions for Different Geomorphic Processes in Steep Mountain Channels in the Austrian Alps

NASA Astrophysics Data System (ADS)

Kaitna, R.; Braun, M.

2016-12-01

Steep mountain channels episodically can experience very different geomorphic processes, ranging from flash floods, intensive bedload transport, debris floods, and debris flows. Rainfall-related trigger conditions and geomorphic disposition for each of these processes to occur, as well as conditions leading to one process and not to the other, are not well understood. In this contribution, we analyze triggering rainfalls for all documented events in the Eastern (Austrian) Alps on a daily and sub-daily basis. The analysis with daily rainfall data covers more than 6640 events between 1901 and 2014 and the analysis based on sub-daily (10 min interval) rainfall data includes around 950 events between 1992 and 2014. Of the four investigated event types, we find that debris flows are typically associated with the least cumulative rainfall, while intensive bedload transport as well as torrential floods occur when there is a substantial amount of cumulative rainfall. Debris floods are occurring on average with cumulative rainfall in a range between the aforementioned processes. Comparison of historical data shows, that about 90% of events are triggered with a combination of extreme rainfall and temperature. Bayesian analysis reveals that a high degree of geomorphic events is associated with very short rainfall durations that cannot be resolved with daily rainfall data. A comparison of both datasets shows that subdaily data gives more accurate results. Additionally, we find a high degree of regional differences, e.g. between regions north and south of the Alpine chain or high or low Alpine regions. There is indication that especially debris flows need less total rainfall amount when occurring in regions with a high relief energy than in less steep environments. The limitation of our analysis is mainly due to the distance between the locations of event triggering and rainfall measurement and the definition of rainfall events for the Bayesian analysis. In a next step, we will connect our results with the analyses of the hydrological as well as geomorphological disposition in selected study regions and with projections of changing climate conditions.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

PubMed Central

2011-01-01

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

Topographic relationships for design rainfalls over Australia

NASA Astrophysics Data System (ADS)

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

2016-02-01

Design rainfall statistics are the primary inputs used to assess flood risk across river catchments. These statistics normally take the form of Intensity-Duration-Frequency (IDF) curves that are derived from extreme value probability distributions fitted to observed daily, and sub-daily, rainfall data. The design rainfall relationships are often required for catchments where there are limited rainfall records, particularly catchments in remote areas with high topographic relief and hence some form of interpolation is required to provide estimates in these areas. This paper assesses the topographic dependence of rainfall extremes by using elevation-dependent thin plate smoothing splines to interpolate the mean annual maximum rainfall, for periods from one to seven days, across Australia. The analyses confirm the important impact of topography in explaining the spatial patterns of these extreme rainfall statistics. Continent-wide residual and cross validation statistics are used to demonstrate the 100-fold impact of elevation in relation to horizontal coordinates in explaining the spatial patterns, consistent with previous rainfall scaling studies and observational evidence. The impact of the complexity of the fitted spline surfaces, as defined by the number of knots, and the impact of applying variance stabilising transformations to the data, were also assessed. It was found that a relatively large number of 3570 knots, suitably chosen from 8619 gauge locations, was required to minimise the summary error statistics. Square root and log data transformations were found to deliver marginally superior continent-wide cross validation statistics, in comparison to applying no data transformation, but detailed assessments of residuals in complex high rainfall regions with high topographic relief showed that no data transformation gave superior performance in these regions. These results are consistent with the understanding that in areas with modest topographic relief, as 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.

Reduced-complexity multi-site rainfall generation: one million years over night using the model TripleM

NASA Astrophysics Data System (ADS)

Breinl, Korbinian; Di Baldassarre, Giuliano; Girons Lopez, Marc

2017-04-01

We assess uncertainties of multi-site rainfall generation across spatial scales and different climatic conditions. Many research subjects in earth sciences such as floods, droughts or water balance simulations require the generation of long rainfall time series. In large study areas the simulation at multiple sites becomes indispensable to account for the spatial rainfall variability, but becomes more complex compared to a single site due to the intermittent nature of rainfall. Weather generators can be used for extrapolating rainfall time series, and various models have been presented in the literature. Even though the large majority of multi-site rainfall generators is based on similar methods, such as resampling techniques or Markovian processes, they often become too complex. We think that this complexity has been a limit for the application of such tools. Furthermore, the majority of multi-site rainfall generators found in the literature are either not publicly available or intended for being applied at small geographical scales, often only in temperate climates. Here we present a revised, and now publicly available, version of a multi-site rainfall generation code first applied in 2014 in Austria and France, which we call TripleM (Multisite Markov Model). We test this fast and robust code with daily rainfall observations from the United States, in a subtropical, tropical and temperate climate, using rain gauge networks with a maximum site distance above 1,000km, thereby generating one million years of synthetic time series. The modelling of these one million years takes one night on a recent desktop computer. In this research, we first start the simulations with a small station network of three sites and progressively increase the number of sites and the spatial extent, and analyze the changing uncertainties for multiple statistical metrics such as dry and wet spells, rainfall autocorrelation, lagged cross correlations and the inter-annual rainfall variability. Our study contributes to the scientific community of earth sciences and the ongoing debate on extreme precipitation in a changing climate by making a stable, and very easily applicable, multi-site rainfall generation code available to the research community and providing a better understanding of the performance of multi-site rainfall generation depending on spatial scales and climatic conditions.

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

First flush characteristics of rainfall runoff from a paddy field in the Taihu Lake watershed, China.

PubMed

Li, Songmin; Wang, Xiaoling; Qiao, Bin; Li, Jiansheng; Tu, Jiamin

2017-03-01

Nonpoint storm runoff remains a major threat to surface water quality in China. As a paddy matures, numerous fertilizers are needed, especially in the rainy seasons; the concentration of nitrogen and phosphorus in rainfall runoff from farmland is much higher than at other times, and this poses a great threat to water bodies and is the main reason for water eutrophication, especially in high concentration drainages. To date, most studies regarding the characteristics of pollutants in rainfall runoff have mainly been concentrated on urban runoff and watershed runoff; therefore, it is particularly important to investigate the characteristics of nitrogen and phosphorus loss in rainfall runoff from paddy fields. To study the characteristics of nitrogen and phosphorus loss and whether the first flush effect exists, continuous monitoring of the rainfall runoff process of six rainfall events was conducted in 2013, of which four rainfall events during storm, high, middle, and low intensity rainfalls were analyzed, and runoff and quality parameters, such as suspended solids (SS), total nitrogen (TN), ammonium nitrogen (NH 4 + -N), nitrate nitrogen (NO 3 - -N), total phosphorus (TP), and phosphate (PO 4 3- -P), were analyzed to determine the relationship between runoff and water quality. The paddy field is located north of Wuxi Lake Basin along the Hejia River upstream in Zhoutie town, Yixing city. An analysis of the load distribution during rainfall runoff was conducted. Event mean concentration (EMC) was used to evaluate the pollution situation of the paddy field's rainfall runoff. A curve of the dimensionless normalized cumulative load (L) vs. normalized cumulative flow (F) (L-F curve), the probability of the mass first flush (MFFn), and the pollutants carried by the initial 25% of runoff (FF 25 ) were used to analyze the first flush effect of the paddy field runoff, and different contaminants show different results: the concentration of nitrogen and phosphorus fluctuate and follow a similar trend as runoff changes, NO 3 - -N concentration is lower in the early part of runoff and higher in the later, and TP mainly occurs in the particle state in storm runoff and mainly in the dissolved state when the rainfall intensity is smaller. Nitrogen and phosphorus losses from paddy fields are closely related to the average rainfall intensity and the max rainfall intensity, and the runoff loss of nitrogen and phosphorus is more severe when the rainfall intensity is large. Based on an analysis of multiple methodologies, TN and NH 4 + -N show a certain degree of a first flush effect, whereas the first flush effect of TP is not obvious. The first flush effect of SS is obvious in larger intensity rainfall and shows a slight secondary flush effect in smaller rainfall events.

Monsoon Rainfall and Landslides in Nepal

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Seasonal variation and climate change impact in Rainfall Erosivity across Europe

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

USDA-ARS?s Scientific Manuscript database

Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

Coupled modes of rainfall over China and the pacific sea surface temperature in boreal summertime

NASA Astrophysics Data System (ADS)

Li, Chun; Ma, Hao

2011-09-01

In addition, the possible atmospheric teleconnections of the coupled rainfall and SST modes were discussed. For the ENSO-NC mode, anomalous low-pressure and high-pressure over the Asian continent induces moisture divergence over North China and reduces summer rainfall there. For the WTP-YRV mode, East Asia-Pacific teleconnection induces moisture convergence over the Yangtze River valley and enhances the summer rainfall there. The TPMM SST and the summer rainfall anomalies over the YRVL are linked by a circumglobal, wave-train-like, atmospheric teleconnection.

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

Yoon, Jin -Ho

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Estimation of Rainfall Rates from Passive Microwave Remote Sensing.

NASA Astrophysics Data System (ADS)

Sharma, Awdhesh Kumar

Rainfall rates have been estimated using the passive microwave and visible/infrared remote sensing techniques. Data of September 14, 1978 from the Scanning Multichannel Microwave Radiometer (SMMR) on board SEA SAT-A and the Visible and Infrared Spin Scan Radiometer (VISSR) on board GOES-W (Geostationary Operational Environmental Satellite - West) was obtained and analyzed for rainfall rate retrieval. Microwave brightness temperatures (MBT) are simulated, using the microwave radiative transfer model (MRTM) and atmospheric scattering models. These MBT were computed as a function of rates of rainfall from precipitating clouds which are in a combined phase of ice and water. Microwave extinction due to ice and liquid water are calculated using Mie-theory and Gamma drop size distributions. Microwave absorption due to oxygen and water vapor are based on the schemes given by Rosenkranz, and Barret and Chung. The scattering phase matrix involved in the MRTM is found using Eddington's two stream approximation. The surface effects due to winds and foam are included through the ocean surface emissivity model. Rainfall rates are then inverted from MBT using the optimization technique "Leaps and Bounds" and multiple linear regression leading to a relationship between the rainfall rates and MBT. This relationship has been used to infer the oceanic rainfall rates from SMMR data. The VISSR data has been inverted for the rainfall rates using Griffith's scheme. This scheme provides an independent means of estimating rainfall rates for cross checking SMMR estimates. The inferred rainfall rates from both techniques have been plotted on a world map for comparison. A reasonably good correlation has been obtained between the two estimates.

An improved rainfall disaggregation technique for GCMs

NASA Astrophysics Data System (ADS)

Onof, C.; Mackay, N. G.; Oh, L.; Wheater, H. S.

1998-08-01

Meteorological models represent rainfall as a mean value for a grid square so that when the latter is large, a disaggregation scheme is required to represent the spatial variability of rainfall. In general circulation models (GCMs) this is based on an assumption of exponentiality of rainfall intensities and a fixed value of areal rainfall coverage, dependent on rainfall type. This paper examines these two assumptions on the basis of U.K. and U.S. radar data. Firstly, the coverage of an area is strongly dependent on its size, and this dependence exhibits a scaling law over a range of sizes. Secondly, the coverage is, of course, dependent on the resolution at which it is measured, although this dependence is weak at high resolutions. Thirdly, the time series of rainfall coverages has a long-tailed autocorrelation function which is comparable to that of the mean areal rainfalls. It is therefore possible to reproduce much of the temporal dependence of coverages by using a regression of the log of the mean rainfall on the log of the coverage. The exponential assumption is satisfactory in many cases but not able to reproduce some of the long-tailed dependence of some intensity distributions. Gamma and lognormal distributions provide a better fit in these cases, but they have their shortcomings and require a second parameter. An improved disaggregation scheme for GCMs is proposed which incorporates the previous findings to allow the coverage to be obtained for any area and any mean rainfall intensity. The parameters required are given and some of their seasonal behavior is analyzed.

Why continuous simulation? The role of antecedent moisture in design flood estimation

NASA Astrophysics Data System (ADS)

Pathiraja, S.; Westra, S.; Sharma, A.

2012-06-01

Continuous simulation for design flood estimation is increasingly becoming a viable alternative to traditional event-based methods. The advantage of continuous simulation approaches is that the catchment moisture state prior to the flood-producing rainfall event is implicitly incorporated within the modeling framework, provided the model has been calibrated and validated to produce reasonable simulations. This contrasts with event-based models in which both information about the expected sequence of rainfall and evaporation preceding the flood-producing rainfall event, as well as catchment storage and infiltration properties, are commonly pooled together into a single set of "loss" parameters which require adjustment through the process of calibration. To identify the importance of accounting for antecedent moisture in flood modeling, this paper uses a continuous rainfall-runoff model calibrated to 45 catchments in the Murray-Darling Basin in Australia. Flood peaks derived using the historical daily rainfall record are compared with those derived using resampled daily rainfall, for which the sequencing of wet and dry days preceding the heavy rainfall event is removed. The analysis shows that there is a consistent underestimation of the design flood events when antecedent moisture is not properly simulated, which can be as much as 30% when only 1 or 2 days of antecedent rainfall are considered, compared to 5% when this is extended to 60 days of prior rainfall. These results show that, in general, it is necessary to consider both short-term memory in rainfall associated with synoptic scale dependence, as well as longer-term memory at seasonal or longer time scale variability in order to obtain accurate design flood estimates.

Short-term versus long-term rainfall time series in the assessment of potable water savings by using rainwater in houses.

PubMed

Ghisi, Enedir; Cardoso, Karla Albino; Rupp, Ricardo Forgiarini

2012-06-15

The main objective of this article is to assess the possibility of using short-term instead of long-term rainfall time series to evaluate the potential for potable water savings by using rainwater in houses. The analysis was performed considering rainfall data from 1960 to 1995 for the city of Santa Bárbara do Oeste, located in the state of São Paulo, southeastern Brazil. The influence of the rainfall time series, roof area, potable water demand and percentage rainwater demand on the potential for potable water savings was evaluated. The potential for potable water savings was estimated using computer simulations considering a set of long-term rainfall time series and different sets of short-term rainfall time series. The ideal rainwater tank capacity was also assessed for some cases. It was observed that the higher the percentage rainwater demand and the shorter the rainfall time series, the larger the difference between the potential for potable water savings and the greater the variation in the ideal rainwater tank size. The sets of short-term rainfall time series considered adequate for different scenarios ranged from 1 to 13 years depending on the roof area, percentage rainwater demand and potable water demand. The main finding of the research is that sets of short-term rainfall time series can be used to assess the potential for potable water savings by using rainwater, as the results obtained are similar to those obtained from the long-term rainfall time series. Copyright © 2012 Elsevier Ltd. All rights reserved.

A protocol for conducting rainfall simulation to study soil runoff.

PubMed

Kibet, Leonard C; Saporito, Louis S; Allen, Arthur L; May, Eric B; Kleinman, Peter J A; Hashem, Fawzy M; Bryant, Ray B

2014-04-03

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff.

A Protocol for Conducting Rainfall Simulation to Study Soil Runoff

PubMed Central

Kibet, Leonard C.; Saporito, Louis S.; Allen, Arthur L.; May, Eric B.; Kleinman, Peter J. A.; Hashem, Fawzy M.; Bryant, Ray B.

2014-01-01

Rainfall is a driving force for the transport of environmental contaminants from agricultural soils to surficial water bodies via surface runoff. The objective of this study was to characterize the effects of antecedent soil moisture content on the fate and transport of surface applied commercial urea, a common form of nitrogen (N) fertilizer, following a rainfall event that occurs within 24 hr after fertilizer application. Although urea is assumed to be readily hydrolyzed to ammonium and therefore not often available for transport, recent studies suggest that urea can be transported from agricultural soils to coastal waters where it is implicated in harmful algal blooms. A rainfall simulator was used to apply a consistent rate of uniform rainfall across packed soil boxes that had been prewetted to different soil moisture contents. By controlling rainfall and soil physical characteristics, the effects of antecedent soil moisture on urea loss were isolated. Wetter soils exhibited shorter time from rainfall initiation to runoff initiation, greater total volume of runoff, higher urea concentrations in runoff, and greater mass loadings of urea in runoff. These results also demonstrate the importance of controlling for antecedent soil moisture content in studies designed to isolate other variables, such as soil physical or chemical characteristics, slope, soil cover, management, or rainfall characteristics. Because rainfall simulators are designed to deliver raindrops of similar size and velocity as natural rainfall, studies conducted under a standardized protocol can yield valuable data that, in turn, can be used to develop models for predicting the fate and transport of pollutants in runoff. PMID:24748061

Simulation of extreme rainfall and projection of future changes using the GLIMCLIM model

NASA Astrophysics Data System (ADS)

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

2017-10-01

In this study, the performance of the Generalized LInear Modelling of daily CLImate sequence (GLIMCLIM) statistical downscaling model was assessed to simulate extreme rainfall indices and annual maximum daily rainfall (AMDR) when downscaled daily rainfall from National Centers for Environmental Prediction (NCEP) reanalysis and Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCM) (four GCMs and two scenarios) output datasets and then their changes were estimated for the future period 2041-2060. The model was able to reproduce the monthly variations in the extreme rainfall indices reasonably well when forced by the NCEP reanalysis datasets. Frequency Adapted Quantile Mapping (FAQM) was used to remove bias in the simulated daily rainfall when forced by CMIP5 GCMs, which reduced the discrepancy between observed and simulated extreme rainfall indices. Although the observed AMDR were within the 2.5th and 97.5th percentiles of the simulated AMDR, the model consistently under-predicted the inter-annual variability of AMDR. A non-stationary model was developed using the generalized linear model for local, shape and scale to estimate the AMDR with an annual exceedance probability of 0.01. The study shows that in general, AMDR is likely to decrease in the future. The Onkaparinga catchment will also experience drier conditions due to an increase in consecutive dry days coinciding with decreases in heavy (>long term 90th percentile) rainfall days, empirical 90th quantile of rainfall and maximum 5-day consecutive total rainfall for the future period (2041-2060) compared to the base period (1961-2000).

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

NASA Astrophysics Data System (ADS)

Wei, C.; Cheng, K. S.

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

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

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Modeling landslide recurrence in Seattle, Washington, USA

USGS Publications Warehouse

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

2008-01-01

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

How certain is desiccation in west African Sahel rainfall (1930-1990)?

NASA Astrophysics Data System (ADS)

Chappell, Adrian; Agnew, Clive T.

2008-04-01

Hypotheses for the late 1960s to 1990 period of desiccation (secular decrease in rainfall) in the west African Sahel (WAS) are typically tested by comparing empirical evidence or model predictions against "observations" of Sahelian rainfall. The outcomes of those comparisons can have considerable influence on the understanding of regional and global environmental systems. Inverse-distance squared area-weighted (IDW) estimates of WAS rainfall observations are commonly aggregated over space to provide temporal patterns without uncertainty. Spatial uncertainty of WAS rainfall was determined using the median approximation sequential indicator simulation. Every year (1930-1990) 300 equally probable realizations of annual summer rainfall were produced to honor station observations, match percentiles of the observed cumulative distributions and indicator variograms and perform adequately during cross validation. More than 49% of the IDW mean annual rainfall fell outside the 5th and 95th percentiles for annual rainfall realization means. The IDW means represented an extreme realization. Uncertainty in desiccation was determined by repeatedly (100,000) sampling the annual distribution of rainfall realization means and by applying Mann-Kendall nonparametric slope detection and significance testing. All of the negative gradients for the entire period were statistically significant. None of the negative gradients for the expected desiccation period were statistically significant. The results support the presence of a long-term decline in annual rainfall but demonstrate that short-term desiccation (1965-1990) cannot be detected. Estimates of uncertainty for precipitation and other climate variables in this or other regions, or across the globe, are essential for the rigorous detection of spatial patterns and time series trends.

Mechanisms for Diurnal Variability of Global Tropical Rainfall Observed from TRMM

NASA Technical Reports Server (NTRS)

Yang, Song; Smith, Eric A.

2004-01-01

The behavior and various controls of diurnal variability in tropical-subtropical rainfall are investigated using Tropical Rainfall Measuring Mission (TRMM) precipitation measurements retrieved from: (1) TRMM Microwave Imager (TMI), (2) Precipitation Radar (PR), and (3) TMI/PR Combined, standard level 2 algorithms for the 1998 annual cycle. Results show that the diurnal variability characteristics of precipitation are consistent for all three algorithms, providing assurance that TRMM retrievals are providing consistent estimates of rainfall variability. As anticipated, most ocean areas exhibit more rainfall at night, while over most land areas rainfall peaks during daytime ,however, various important exceptions are found. The dominant feature of the oceanic diurnal cycle is a rainfall maximum in late-evening/early-morning (LE-EM) hours, while over land the dominant maximum occurs in the mid- to late-afternoon (MLA). In conjunction with these maxima are pronounced seasonal variations of the diurnal amplitudes. Amplitude analysis shows that the diurnal pattern and its seasonal evolution are closely related to the rainfall accumulation pattern and its seasonal evolution. In addition, the horizontal distribution of diurnal variability indicates that for oceanic rainfall there is a secondary MLA maximum, co-existing with the LE-EM maximum, at latitudes dominated by large scale convergence and deep convection. Analogously, there is a preponderance for an LE-EM maximum over land, co-existing with the stronger MLA maximum, although it is not evident that this secondary continental feature is closely associated with the large scale circulation. The ocean results clearly indicate that rainfall diurnal variability associated with large scale convection is an integral part of the atmospheric general circulation.

Rainfall prediction with backpropagation method

NASA Astrophysics Data System (ADS)

Wahyuni, E. G.; Fauzan, L. M. F.; Abriyani, F.; Muchlis, N. F.; Ulfa, M.

2018-03-01

Rainfall is an important factor in many fields, such as aviation and agriculture. Although it has been assisted by technology but the accuracy can not reach 100% and there is still the possibility of error. Though current rainfall prediction information is needed in various fields, such as agriculture and aviation fields. In the field of agriculture, to obtain abundant and quality yields, farmers are very dependent on weather conditions, especially rainfall. Rainfall is one of the factors that affect the safety of aircraft. To overcome the problems above, then it’s required a system that can accurately predict rainfall. In predicting rainfall, artificial neural network modeling is applied in this research. The method used in modeling this artificial neural network is backpropagation method. Backpropagation methods can result in better performance in repetitive exercises. This means that the weight of the ANN interconnection can approach the weight it should be. Another advantage of this method is the ability in the learning process adaptively and multilayer owned on this method there is a process of weight changes so as to minimize error (fault tolerance). Therefore, this method can guarantee good system resilience and consistently work well. The network is designed using 4 input variables, namely air temperature, air humidity, wind speed, and sunshine duration and 3 output variables ie low rainfall, medium rainfall, and high rainfall. Based on the research that has been done, the network can be used properly, as evidenced by the results of the prediction of the system precipitation is the same as the results of manual calculations.

The Role of Rainfall Patterns in Seasonal Malaria Transmission

NASA Astrophysics Data System (ADS)

Bomblies, A.

2010-12-01

Seasonal total precipitation is well known to affect malaria transmission because Anopheles mosquitoes depend on standing water for breeding habitat. However, the within-season temporal pattern of the rainfall influences persistence of standing water and thus rainfall patterns also affect mosquito population dynamics. In this talk, I show that intraseasonal rainfall pattern describes 40% of the variance in simulated mosquito abundance in a Niger Sahel village where malaria is endemic but highly seasonal, demonstrating the necessity for detailed distributed hydrology modeling to explain the variance from this important effect. I apply a field validated, high spatial- and temporal-resolution hydrology model coupled with an entomology model. Using synthetic rainfall time series generated using a stationary first-order Markov Chain model, I hold all variables except hourly rainfall constant, thus isolating the contribution of rainfall pattern to variance in mosquito abundance. I further show the utility of hydrology modeling to assess precipitation effects by analyzing collected water. Time-integrated surface area of pools explains 70% of the variance in mosquito abundance, and time-integrated surface area of pools persisting longer than seven days explains 82% of the variance, showing an improved predictive ability when pool persistence is explicitly modeled at high spatio-temporal resolution. I extend this analysis to investigate the impacts of this effect on malaria vector mosquito populations under climate shift scenarios, holding all climate variables except precipitation constant. In these scenarios, rainfall mean and variance change with climatic change, and the modeling approach evaluates the impact of non-stationarity in rainfall and the associated rainfall patterns on expected mosquito activity.

Evaluating Satellite-based Rainfall Estimates for Basin-scale Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Yilmaz, K. K.; Hogue, T. S.; Hsu, K.; Gupta, H. V.; Mahani, S. E.; Sorooshian, S.

2003-12-01

The reliability of any hydrologic simulation and basin outflow prediction effort depends primarily on the rainfall estimates. The problem of estimating rainfall becomes more obvious in basins with scarce or no rain gauges. We present an evaluation of satellite-based rainfall estimates for basin-scale hydrologic modeling with particular interest in ungauged basins. The initial phase of this study focuses on comparison of mean areal rainfall estimates from ground-based rain gauge network, NEXRAD radar Stage-III, and satellite-based PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) and their influence on hydrologic model simulations over several basins in the U.S. Six-hourly accumulations of the above competing mean areal rainfall estimates are used as input to the Sacramento Soil Moisture Accounting Model. Preliminary experiments for the Leaf River Basin in Mississippi, for the period of March 2000 - June 2002, reveals that seasonality plays an important role in the comparison. There is an overestimation during the summer and underestimation during the winter in satellite-based rainfall with respect to the competing rainfall estimates. The consequence of this result on the hydrologic model is that simulated discharge underestimates the major observed peak discharges during early spring for the basin under study. Future research will entail developing correction procedures, which depend on different factors such as seasonality, geographic location and basin size, for satellite-based rainfall estimates over basins with dense rain gauge network and/or radar coverage. Extension of these correction procedures to satellite-based rainfall estimates over ungauged basins with similar characteristics has the potential for reducing the input uncertainty in ungauged basin modeling efforts.

The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

NASA Technical Reports Server (NTRS)

Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

2013-01-01

The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

Landslides, floods and sinkholes in a karst environment: the 1-6 September 2014 Gargano event, southern Italy

NASA Astrophysics Data System (ADS)

Martinotti, Maria Elena; Pisano, Luca; Marchesini, Ivan; Rossi, Mauro; Peruccacci, Silvia; Brunetti, Maria Teresa; Melillo, Massimo; Amoruso, Giuseppe; Loiacono, Pierluigi; Vennari, Carmela; Vessia, Giovanna; Trabace, Maria; Parise, Mario; Guzzetti, Fausto

2017-03-01

In karst environments, heavy rainfall is known to cause multiple geohydrological hazards, including inundations, flash floods, landslides and sinkholes. We studied a period of intense rainfall from 1 to 6 September 2014 in the Gargano Promontory, a karst area in Puglia, southern Italy. In the period, a sequence of torrential rainfall events caused severe damage and claimed two fatalities. The amount and accuracy of the geographical and temporal information varied for the different hazards. The temporal information was most accurate for the inundation caused by a major river, less accurate for flash floods caused by minor torrents and even less accurate for landslides. For sinkholes, only generic information on the period of occurrence of the failures was available. Our analysis revealed that in the promontory, rainfall-driven hazards occurred in response to extreme meteorological conditions and that the karst landscape responded to the torrential rainfall with a threshold behaviour. We exploited the rainfall and the landslide information to design the new ensemble-non-exceedance probability (E-NEP) algorithm for the quantitative evaluation of the possible occurrence of rainfall-induced landslides and of related geohydrological hazards. The ensemble of the metrics produced by the E-NEP algorithm provided better diagnostics than the single metrics often used for landslide forecasting, including rainfall duration, cumulated rainfall and rainfall intensity. We expect that the E-NEP algorithm will be useful for landslide early warning in karst areas and in other similar environments. We acknowledge that further tests are needed to evaluate the algorithm in different meteorological, geological and physiographical settings.

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

USGS Publications Warehouse

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

2009-01-01

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

Circulation system configuration characteristics of four rainfall patterns in summer over the East China

NASA Astrophysics Data System (ADS)

Zhao, Junhu; Yang, Liu; Feng, Guolin

2018-02-01

In this study, the simultaneous atmospheric circulation system configuration characteristics of the four rainfall patterns (FRP) over the East China during the period 1951-2015 are analyzed in order to investigate their formation mechanisms. The results confirm that the FRP possess obvious differences in the upper-level, middle-level, and lower-level troposphere. In northern China rainfall pattern (NCP) years, the East Asian subtropical westerly jet stream (EAJS) shows a northward trend, with a higher intensity than normal; the blocking high (BH) in the mid-high latitudes is inactive; and the western Pacific subtropical high (WPSH) tends to be stronger, with a location to the north of its normal position. The East Asian summer monsoon (EASM) is stronger, which promotes vapor transport to northern China, and this leads to increased rainfall. In intermediate rainfall pattern (IRP) years, the EAJS position is close to that in normal years; the BH is inactive; the WPSH tends to be weaker, with a location to the east of its normal position; and the EASM is stronger, which is conducive to increased rainfall over the Huaihe River Basin. In Yangtze River rainfall pattern (YRP) years, the circulations are found to be almost opposite in their features to those in NCP years. In South China rainfall pattern (SCP) years, the circulations are found to be almost opposite in their features to those in IRP years. This leads to increased rainfall over South China. Therefore, the different circulation system configuration characteristics lead to the different rainfall patterns.

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

NASA Astrophysics Data System (ADS)

Notaro, Michael

2018-01-01

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

Southern Hemisphere rainfall variability over the past 200 years

NASA Astrophysics Data System (ADS)

Gergis, Joëlle; Henley, Benjamin J.

2017-04-01

This study presents an analysis of three palaeoclimate rainfall reconstructions from the Southern Hemisphere regions of south-eastern Australia (SEA), southern South Africa (SAF) and southern South America (SSA). We provide a first comparison of rainfall variations in these three regions over the past two centuries, with a focus on identifying synchronous wet and dry periods. Despite the uncertainties associated with the spatial and temporal limitations of the rainfall reconstructions, we find evidence of dynamically-forced climate influences. An investigation of the twentieth century relationship between regional rainfall and the large-scale climate circulation features of the Pacific, Indian and Southern Ocean regions revealed that Indo-Pacific variations of the El Niño-Southern Oscillation (ENSO) and the Indian Ocean dipole dominate rainfall variability in SEA and SAF, while the higher latitude Southern Annular Mode (SAM) exerts a greater influence in SSA. An assessment of the stability of the regional rainfall-climate circulation modes over the past two centuries revealed a number of non-stationarities, the most notable of which occurs during the early nineteenth century around 1820. This corresponds to a time when the influence of ENSO on SEA, SAF and SSA rainfall weakens and there is a strengthening of the influence of SAM. We conclude by advocating the use of long-term palaeoclimate data to estimate decadal rainfall variability for future water resource management.

Relation Between the Rainfall and Soil Moisture During Different Phases of Indian Monsoon

NASA Astrophysics Data System (ADS)

Varikoden, Hamza; Revadekar, J. V.

2018-03-01

Soil moisture is a key parameter in the prediction of southwest monsoon rainfall, hydrological modelling, and many other environmental studies. The studies on relationship between the soil moisture and rainfall in the Indian subcontinent are very limited; hence, the present study focuses the association between rainfall and soil moisture during different monsoon seasons. The soil moisture data used for this study are the ESA (European Space Agency) merged product derived from four passive and two active microwave sensors spanning over the period 1979-2013. The rainfall data used are India Meteorological Department gridded daily data. Both of these data sets are having a spatial resolution of 0.25° latitude-longitude grid. The study revealed that the soil moisture is higher during the southwest monsoon period similar to rainfall and during the pre-monsoon period, the soil moisture is lower. The annual cycle of both the soil moisture and rainfall has the similitude of monomodal variation with a peak during the month of August. The interannual variability of soil moisture and rainfall shows that they are linearly related with each other, even though they are not matched exactly for individual years. The study of extremes also exhibits the surplus amount of soil moisture during wet monsoon years and also the regions of surplus soil moisture are well coherent with the areas of high rainfall.

Prediction of spatially explicit rainfall intensity–duration thresholds for post-fire debris-flow generation in the western United States

USGS Publications Warehouse

Staley, Dennis M.; Negri, Jacquelyn; Kean, Jason W.; Laber, Jayme L.; Tillery, Anne C.; Youberg, Ann M.

2017-01-01

Early warning of post-fire debris-flow occurrence during intense rainfall has traditionally relied upon a library of regionally specific empirical rainfall intensity–duration thresholds. Development of this library and the calculation of rainfall intensity-duration thresholds often require several years of monitoring local rainfall and hydrologic response to rainstorms, a time-consuming approach where results are often only applicable to the specific region where data were collected. Here, we present a new, fully predictive approach that utilizes rainfall, hydrologic response, and readily available geospatial data to predict rainfall intensity–duration thresholds for debris-flow generation in recently burned locations in the western United States. Unlike the traditional approach to defining regional thresholds from historical data, the proposed methodology permits the direct calculation of rainfall intensity–duration thresholds for areas where no such data exist. The thresholds calculated by this method are demonstrated to provide predictions that are of similar accuracy, and in some cases outperform, previously published regional intensity–duration thresholds. The method also provides improved predictions of debris-flow likelihood, which can be incorporated into existing approaches for post-fire debris-flow hazard assessment. Our results also provide guidance for the operational expansion of post-fire debris-flow early warning systems in areas where empirically defined regional rainfall intensity–duration thresholds do not currently exist.

Post-fire, rainfall intensity-peak discharge relations for three mountainous watersheds in the Western USA

USGS Publications Warehouse

Moody, J.A.; Martin, D.A.

2001-01-01

Wildfire alters the hydrologic response of watersheds, including the peak discharges resulting from subsequent rainfall. Improving predictions of the magnitude of flooding that follows wildfire is needed because of the increase in human population at risk in the wildland-urban interface. Because this wildland-urban interface is typically in mountainous terrain, we investigated rainfall-runoff relations by measuring the maximum 30 min rainfall intensity and the unit-area peak discharge (peak discharge divided by the area burned) in three mountainous watersheds (17-26.8 km2) after a wildfire. We found rainfall-runoff relations that relate the unit-area peak discharges to the maximum 30 min rainfall intensities by a power law. These rainfall-runoff relations appear to have a threshold value for the maximum 30 min rainfall intensity (around 10 mm h-1) such that, above this threshold, the magnitude of the flood peaks increases more rapidly with increases in intensity. This rainfall intensity could be used to set threshold limits in rain gauges that are part of an early-warning flood system after wildfire. The maximum unit-area peak discharges from these three burned watersheds ranged from 3.2 to 50 m3 s-1 km-2. These values could provide initial estimates of the upper limits of runoff that can be used to predict floods after wildfires in mountainous terrain. Published in 2001 by John Wiley and Sons, Ltd.

The Spatial Scaling of Global Rainfall Extremes

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

NASA Astrophysics Data System (ADS)

Staley, Dennis M.; Negri, Jacquelyn A.; Kean, Jason W.; Laber, Jayme L.; Tillery, Anne C.; Youberg, Ann M.

2017-02-01

Early warning of post-fire debris-flow occurrence during intense rainfall has traditionally relied upon a library of regionally specific empirical rainfall intensity-duration thresholds. Development of this library and the calculation of rainfall intensity-duration thresholds often require several years of monitoring local rainfall and hydrologic response to rainstorms, a time-consuming approach where results are often only applicable to the specific region where data were collected. Here, we present a new, fully predictive approach that utilizes rainfall, hydrologic response, and readily available geospatial data to predict rainfall intensity-duration thresholds for debris-flow generation in recently burned locations in the western United States. Unlike the traditional approach to defining regional thresholds from historical data, the proposed methodology permits the direct calculation of rainfall intensity-duration thresholds for areas where no such data exist. The thresholds calculated by this method are demonstrated to provide predictions that are of similar accuracy, and in some cases outperform, previously published regional intensity-duration thresholds. The method also provides improved predictions of debris-flow likelihood, which can be incorporated into existing approaches for post-fire debris-flow hazard assessment. Our results also provide guidance for the operational expansion of post-fire debris-flow early warning systems in areas where empirically defined regional rainfall intensity-duration thresholds do not currently exist.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

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

NASA Astrophysics Data System (ADS)

Shepherd, J.

2002-05-01

A recent paper by Shepherd et al. (in press at Journal of Applied Meteorology) used rainfall data from the Precipitation Radar on NASA's Tropical Rainfall Measuring Mission's (TRMM) satellite to identify warm season rainfall anomalies downwind of major urban areas. Data (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. A convective-mesoscale model with extensive land-surface processes is currently being employed to (a) determine if an urban heat island (UHI) thermal perturbation can induce a dynamic response to affect rainfall processes and (b) quantify the impact of the following three factors on the evolution of rainfall: (1) urban surface roughness, (2) magnitude of the UHI temperature anomaly, and (3) physical size of the UHI temperature anomaly. The sensitivity experiments are achieved by inserting a slab of land with urban properties (e.g. roughness length, albedo, thermal character) within a rural surface environment and varying the appropriate lower boundary condition parameters. The study will discuss the feasibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. The talk also introduces very preliminary results from the modeling component of the study.

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

PubMed

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

2013-02-01

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

On the asymmetric distribution of shear-relative typhoon rainfall

NASA Astrophysics Data System (ADS)

Gao, Si; Zhai, Shunan; Li, Tim; Chen, Zhifan

2018-02-01

The Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation, the National Centers for Environmental Prediction (NCEP) Final analysis and the Regional Specialized Meteorological Center (RSMC) Tokyo best-track data during 2000-2015 are used to compare spatial rainfall distribution associated with Northwest Pacific tropical cyclones (TCs) with different vertical wind shear directions and investigate possible mechanisms. Results show that the maximum TC rainfall are all located in the downshear left quadrant regardless of shear direction, and TCs with easterly shear have greater magnitudes of rainfall than those with westerly shear, consistent with previous studies. Rainfall amount of a TC is related to its relative position and proximity from the western Pacific subtropical high (WPSH) and the intensity of water vapor transport, and low-level jet is favorable for water vapor transport. The maximum of vertically integrated moisture flux convergence (MFC) are located on the downshear side regardless of shear direction, and the contribution of wind convergence to the total MFC is far larger than that of moisture advection. The cyclonic displacement of the maximum rainfall relative to the maximum MFC is possibly due to advection of hydrometeors by low- and middle-level cyclonic circulation of TCs. The relationship between TC rainfall and the WPSH through water vapor transport and vertical wind shear implies that TC rainfall may be highly predictable given the high predictability of the WPSH.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Estimating impact of rainfall change on hydrological processes in Jianfengling rainforest watershed, China using BASINS-HSPF-CAT modeling system

Treesearch

Zhang Zhou; Ying Ouyang; Yide Li; Zhijun Qiu; Matt Moran

2017-01-01

Climate change over the past several decades has resulted in shifting rainfall pattern and modifying rain-fall intensity, which has exacerbated hydrological processes and added the uncertainty and instability tothese processes. This study ascertained impacts of potential future rainfall change on hydrological pro-cesses at the Jianfengling (JFL) tropical mountain...

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

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

USGS Publications Warehouse

Wilson, Raymond C.

1997-01-01

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

Effect of rainfall seasonality on carbon storage in tropical dry ecosystems

NASA Astrophysics Data System (ADS)

Rohr, Tyler; Manzoni, Stefano; Feng, Xue; Menezes, Rômulo S. C.; Porporato, Amilcare

2013-07-01

seasonally dry conditions are typical of large areas of the tropics, their biogeochemical responses to seasonal rainfall and soil carbon (C) sequestration potential are not well characterized. Seasonal moisture availability positively affects both productivity and soil respiration, resulting in a delicate balance between C deposition as litterfall and C loss through heterotrophic respiration. To understand how rainfall seasonality (i.e., duration of the wet season and rainfall distribution) affects this balance and to provide estimates of long-term C sequestration, we develop a minimal model linking the seasonal behavior of the ensemble soil moisture, plant productivity, related C inputs through litterfall, and soil C dynamics. A drought-deciduous caatinga ecosystem in northeastern Brazil is used as a case study to parameterize the model. When extended to different patterns of rainfall seasonality, the results indicate that for fixed annual rainfall, both plant productivity and soil C sequestration potential are largely, and nonlinearly, dependent on wet season duration. Moreover, total annual rainfall is a critical driver of this relationship, leading at times to distinct optima in both production and C storage. These theoretical predictions are discussed in the context of parameter uncertainties and possible changes in rainfall regimes in tropical dry ecosystems.

HOW STRONG IS THE RELATIONSHIP BETWEEN RAINFALL VARIABILITY AND CAATINGA PRODUCTIVITY? A CASE STUDY UNDER A CHANGING CLIMATE.

PubMed

Salimon, Cleber; Anderson, Liana

2017-05-22

Despite the knowledge of the influence of rainfall on vegetation dynamics in semiarid tropical Brazil, few studies address and explore quantitatively the various aspects of this relationship. Moreover, Northeast Brazil is expected to have its rainfall reduced by as much as 60% until the end of the 21st Century, under scenario AII of the IPCC Report 2010. We sampled and analyzed satellite-derived monthly rainfall and a vegetation index data for 40 sites with natural vegetation cover in Paraíba State, Brazil from 2001 to 2012. In addition, the anomalies for both variables were calculated. Rainfall variation explained as much as 50% of plant productivity, using the vegetation index as a proxy, and rainfall anomaly explained 80% of the vegetation productivity anomaly. In an extreme dry year (2012), with 65% less rainfall than average for the period 2001-2012, the vegetation index decreased by 25%. If such decrease persists in a long term trend in rainfall reduction, this could lead to a disruption in this ecosystem functioning and the dominant vegetation could become even more xeric or desert-like, bringing serious environmental, social and economical impacts.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

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

2012-09-01

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

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

PubMed

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

2017-05-01

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

Predicting of soil erosion with regarding to rainfall erosivity and soil erodibility

NASA Astrophysics Data System (ADS)

Suif, Zuliziana; Razak, Mohd Amirun Anis Ab; Ahmad, Nordila

2018-02-01

The soil along the hill and slope are wearing away due to erosion and it can take place due to occurrence of weak and heavy rainfall. The aim of this study is to predict the soil erosion degree in Universiti Pertahanan Nasional Malaysia (UPNM) area focused on two major factor which is soil erodibility and rainfall erosivity. Soil erodibility is the possibilities of soil to detach and carried away during rainfall and runoff. The "ROM" scale was used in this study to determine the degree of soil erodibility, namely low, moderate, high, and very high. As for rainfall erosivity, the erosive power caused by rainfall that cause soil loss. A daily rainfall data collected from January to April was analyzed by using ROSE index classification to identify the potential risk of soil erosion. The result shows that the soil erodibilty are moderate at MTD`s hill, high at behind of block Lestari and Landslide MTD hill, and critical at behind the mess cadet. While, the highest rainfall erosivity was recorded in March and April. Overall, this study would benefit the organization greatly in saving cost in landslide protection as relevant authorities can take early measures repairing the most affected area of soil erosion.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Extreme Monsoon Rainfall Signatures Preserved in the Invasive Terrestrial Gastropod Lissachatina fulica

NASA Astrophysics Data System (ADS)

Ghosh, Prosenjit; Rangarajan, Ravi; Thirumalai, Kaustubh; Naggs, Fred

2017-11-01

Indian summer monsoon (ISM) rainfall lasts for a period of 4 months with large variations recorded in terms of rainfall intensity during its period between June and September. Proxy reconstructions of past ISM rainfall variability are required due to the paucity of long instrumental records. However, reconstructing subseasonal rainfall is extremely difficult using conventional hydroclimate proxies due to inadequate sample resolution. Here, we demonstrate the utility of the stable oxygen isotope composition of gastropod shells in reconstructing past rainfall on subseasonal timescales. We present a comparative isotopic study on present day rainwater and stable isotope ratios of precipitate found in the incremental growth bands of giant African land snail Lissachatina fulica (Bowdich) from modern day (2009) and in the historical past (1918). Isotopic signatures present in the growth bands allowed for the identification of ISM rainfall variability in terms of its active and dry spells in the modern as well as past gastropod record. Our results demonstrate the utility of gastropod growth band stable isotope ratios in semiquantitative reconstructions of seasonal rainfall patterns. High resolution climate records extracted from gastropod growth band stable isotopes (museum and archived specimens) can expand the scope for understanding past subseasonal-to-seasonal climate variability.

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

NASA Technical Reports Server (NTRS)

Negri, Andrew J.

2005-01-01

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

Recharge characteristics of an unconfined aquifer from the rainfall-water table relationship

NASA Astrophysics Data System (ADS)

Viswanathan, M. N.

1984-02-01

The determination of recharge levels of unconfined aquifers, recharged entirely by rainfall, is done by developing a model for the aquifer that estimates the water-table levels from the history of rainfall observations and past water-table levels. In the present analysis, the model parameters that influence the recharge were not only assumed to be time dependent but also to have varying dependence rates for various parameters. Such a model is solved by the use of a recursive least-squares method. The variable-rate parameter variation is incorporated using a random walk model. From the field tests conducted at Tomago Sandbeds, Newcastle, Australia, it was observed that the assumption of variable rates of time dependency of recharge parameters produced better estimates of water-table levels compared to that with constant-recharge parameters. It was observed that considerable recharge due to rainfall occurred on the very same day of rainfall. The increase in water-table level was insignificant for subsequent days of rainfall. The level of recharge very much depends upon the intensity and history of rainfall. Isolated rainfalls, even of the order of 25 mm day -1, had no significant effect on the water-table levels.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Variability of rainfall over small areas

NASA Technical Reports Server (NTRS)

Runnels, R. C.

1983-01-01

A preliminary investigation was made to determine estimates of the number of raingauges needed in order to measure the variability of rainfall in time and space over small areas (approximately 40 sq miles). The literature on rainfall variability was examined and the types of empirical relationships used to relate rainfall variations to meteorological and catchment-area characteristics were considered. Relations between the coefficient of variation and areal-mean rainfall and area have been used by several investigators. These parameters seemed reasonable ones to use in any future study of rainfall variations. From a knowledge of an appropriate coefficient of variation (determined by the above-mentioned relations) the number rain gauges needed for the precise determination of areal-mean rainfall may be calculated by statistical estimation theory. The number gauges needed to measure the coefficient of variation over a 40 sq miles area, with varying degrees of error, was found to range from 264 (10% error, mean precipitation = 0.1 in) to about 2 (100% error, mean precipitation = 0.1 in).

Assessment on spatiotemporal relationship between rainfall and cloud top temperature from new generation weather satellite imagery

NASA Astrophysics Data System (ADS)

Wei, Chiang; Yeh, Hui-Chung; Chen, Yen-Chang

2017-04-01

This study addressed the relationship between rainfall and cloud top temperature (CCT) from new generation satellite Himawari-8 imagery at different spatiotemporal scale. This satellite provides higher band, more bits for data format, spatial and temporal resolution compared with previous GMS series. The multi-infrared channels with 10-minute and 1-2 km resolution make it possible for rainfall estimating/forecasting in small/medium watershed. The preliminary result investigated at Chenyulan watershed (443.6 square kilometer) of Central Taiwan in 2016 Typhoon Megi shows the regression coefficient fitted by negative exponential equation of largest rainfall vs. CCT (B8 band) at pixel scale increases as time scales enlarges and reach 0.462 for 120-minute accumulative rainfall; the value (CTT of B15 band) decreases from 0.635 for 10-minute to 0.423 for 120-minute accumulative rainfall at basin-wide scale. More rainfall events for different regime are yet to evaluate to get solid results.

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

PubMed

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

Schewe, Jacob; Levermann, Anders

2017-07-01

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

On the Numerical Study of Heavy Rainfall in Taiwan

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Ching-Sen; Chen, Yi-Leng; Jou, Ben Jong-Dao; Lin, Pay-Liam; Starr, David OC. (Technical Monitor)

2001-01-01

Heavy rainfall events are frequently observed over the western side of the CMR (central mountain range), which runs through Taiwan in a north-south orientation, in a southwesterly flow regime and over the northeastern side of the CMR in a northeasterly flow regime. Previous studies have revealed the mechanisms by which the heavy rainfall events are formed. Some of them have examined characteristics of the heavy rainfall via numerical simulations. In this paper, some of the previous numerical studies on heavy rainfall events around Taiwan during the Mei-Yu season (May and June), summer (non-typhoon cases) and autumn will be reviewed. Associated mechanisms proposed from observational studies will be reviewed first, and then characteristics of numerically simulated heavy rainfall events will be presented. The formation mechanisms of heavy rainfall from simulated results and from observational analysis are then compared and discussed. Based on these previous modeling studies, we will also discuss what are the major observations and modeling processes which will be needed for understanding the heavy precipitation in the future.

The effects of simulated rainfall on immature population dynamics of Aedes albopictus and female oviposition

NASA Astrophysics Data System (ADS)

Dieng, Hamady; Rahman, G. M. Saifur; Abu Hassan, A.; Che Salmah, M. R.; Satho, Tomomitsu; Miake, Fumio; Boots, Michael; Sazaly, Abubakar

2012-01-01

Larvae of Aedes albopictus Skuse typically inhabit natural and artificial containers. Since these larval habitats are replenished by rainfall, Ae. albopictus may experience increased loss of immature stages in areas with high levels of rainfall. In this study, we investigated the effects of rainfall and container water level on population density, and oviposition activity of Ae. albopictus. In field and laboratory experiments, we found that rainfall resulted in the flushing of breeding habitats. Excess rain negatively impacted larval and pupal retention, especially in small habitats. When filled with water to overflowing, container habitats were significantly repellent to ovipositing females. Taken together, these data suggest that rainfall triggers population loss of Ae. albopictus and related species through a direct detrimental effect (flushing out) and an indirect effect (ovipositional repellency).

Spectral analysis of temporal non-stationary rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Chang, Ching-Min; Yeh, Hund-Der

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

NASA Astrophysics Data System (ADS)

Staley, Dennis; Negri, Jacquelyn; Kean, Jason

2016-04-01

Population expansion into fire-prone steeplands has resulted in an increase in post-fire debris-flow risk in the western United States. Logistic regression methods for determining debris-flow likelihood and the calculation of empirical rainfall intensity-duration thresholds for debris-flow initiation represent two common approaches for characterizing hazard and reducing risk. Logistic regression models are currently being used to rapidly assess debris-flow hazard in response to design storms of known intensities (e.g. a 10-year recurrence interval rainstorm). Empirical rainfall intensity-duration thresholds comprise a major component of the United States Geological Survey (USGS) and the National Weather Service (NWS) debris-flow early warning system at a regional scale in southern California. However, these two modeling approaches remain independent, with each approach having limitations that do not allow for synergistic local-scale (e.g. drainage-basin scale) characterization of debris-flow hazard during intense rainfall. The current logistic regression equations consider rainfall a unique independent variable, which prevents the direct calculation of the relation between rainfall intensity and debris-flow likelihood. Regional (e.g. mountain range or physiographic province scale) rainfall intensity-duration thresholds fail to provide insight into the basin-scale variability of post-fire debris-flow hazard and require an extensive database of historical debris-flow occurrence and rainfall characteristics. Here, we present a new approach that combines traditional logistic regression and intensity-duration threshold methodologies. This method allows for local characterization of both the likelihood that a debris-flow will occur at a given rainfall intensity, the direct calculation of the rainfall rates that will result in a given likelihood, and the ability to calculate spatially explicit rainfall intensity-duration thresholds for debris-flow generation in recently burned areas. Our approach synthesizes the two methods by incorporating measured rainfall intensity into each model variable (based on measures of topographic steepness, burn severity and surface properties) within the logistic regression equation. This approach provides a more realistic representation of the relation between rainfall intensity and debris-flow likelihood, as likelihood values asymptotically approach zero when rainfall intensity approaches 0 mm/h, and increase with more intense rainfall. Model performance was evaluated by comparing predictions to several existing regional thresholds. The model, based upon training data collected in southern California, USA, has proven to accurately predict rainfall intensity-duration thresholds for other areas in the western United States not included in the original training dataset. In addition, the improved logistic regression model shows promise for emergency planning purposes and real-time, site-specific early warning. With further validation, this model may permit the prediction of spatially-explicit intensity-duration thresholds for debris-flow generation in areas where empirically derived regional thresholds do not exist. This improvement would permit the expansion of the early-warning system into other regions susceptible to post-fire debris flow.

Radio Wave Propagation over Salem

NASA Astrophysics Data System (ADS)

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

2007-07-01

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

Evaluation of Surface Runoff Generation Processes Using a Rainfall Simulator: A Small Scale Laboratory Experiment

NASA Astrophysics Data System (ADS)

Danáčová, Michaela; Valent, Peter; Výleta, Roman

2017-12-01

Nowadays, rainfall simulators are being used by many researchers in field or laboratory experiments. The main objective of most of these experiments is to better understand the underlying runoff generation processes, and to use the results in the process of calibration and validation of hydrological models. Many research groups have assembled their own rainfall simulators, which comply with their understanding of rainfall processes, and the requirements of their experiments. Most often, the existing rainfall simulators differ mainly in the size of the irrigated area, and the way they generate rain drops. They can be characterized by the accuracy, with which they produce a rainfall of a given intensity, the size of the irrigated area, and the rain drop generating mechanism. Rainfall simulation experiments can provide valuable information about the genesis of surface runoff, infiltration of water into soil and rainfall erodibility. Apart from the impact of physical properties of soil, its moisture and compaction on the generation of surface runoff and the amount of eroded particles, some studies also investigate the impact of vegetation cover of the whole area of interest. In this study, the rainfall simulator was used to simulate the impact of the slope gradient of the irrigated area on the amount of generated runoff and sediment yield. In order to eliminate the impact of external factors and to improve the reproducibility of the initial conditions, the experiments were conducted in laboratory conditions. The laboratory experiments were carried out using a commercial rainfall simulator, which was connected to an external peristaltic pump. The pump maintained a constant and adjustable inflow of water, which enabled to overcome the maximum volume of simulated precipitation of 2.3 l, given by the construction of the rainfall simulator, while maintaining constant characteristics of the simulated precipitation. In this study a 12-minute rainfall with a constant intensity of 5 mm/min was used to irrigate a corrupted soil sample. The experiment was undertaken for several different slopes, under the condition of no vegetation cover. The results of the rainfall simulation experiment complied with the expectations of a strong relationship between the slope gradient, and the amount of surface runoff generated. The experiments with higher slope gradients were characterised by larger volumes of surface runoff generated, and by shorter times after which it occurred. The experiments with rainfall simulators in both laboratory and field conditions play an important role in better understanding of runoff generation processes. The results of such small scale experiments could be used to estimate some of the parameters of complex hydrological models, which are used to model rainfall-runoff and erosion processes at catchment scale.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

DOE PAGES

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

2018-05-07

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

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Characterizing rainfall of hot arid region by using time-series modeling and sustainability approaches: a case study from Gujarat, India

NASA Astrophysics Data System (ADS)

Machiwal, Deepesh; Kumar, Sanjay; Dayal, Devi

2016-05-01

This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time-series modeling techniques and sustainability approach. Five characteristics, i.e., normality, stationarity, homogeneity, presence/absence of trend, and persistence of 34-year (1980-2013) period annual rainfall time series of ten stations were identified/detected by applying multiple parametric and non-parametric statistical tests. Furthermore, the study involves novelty of proposing sustainability concept for evaluating rainfall time series and demonstrated the concept, for the first time, by identifying the most sustainable rainfall series following reliability ( R y), resilience ( R e), and vulnerability ( V y) approach. Box-whisker plots, normal probability plots, and histograms indicated that the annual rainfall of Mandvi and Dayapar stations is relatively more positively skewed and non-normal compared with that of other stations, which is due to the presence of severe outlier and extreme. Results of Shapiro-Wilk test and Lilliefors test revealed that annual rainfall series of all stations significantly deviated from normal distribution. Two parametric t tests and the non-parametric Mann-Whitney test indicated significant non-stationarity in annual rainfall of Rapar station, where the rainfall was also found to be non-homogeneous based on the results of four parametric homogeneity tests. Four trend tests indicated significantly increasing rainfall trends at Rapar and Gandhidham stations. The autocorrelation analysis suggested the presence of persistence of statistically significant nature in rainfall series of Bhachau (3-year time lag), Mundra (1- and 9-year time lag), Nakhatrana (9-year time lag), and Rapar (3- and 4-year time lag). Results of sustainability approach indicated that annual rainfall of Mundra and Naliya stations ( R y = 0.50 and 0.44; R e = 0.47 and 0.47; V y = 0.49 and 0.46, respectively) are the most sustainable and dependable compared with that of other stations. The highest values of sustainability index at Mundra (0.120) and Naliya (0.112) stations confirmed the earlier findings of R y- R e- V y approach. In general, annual rainfall of the study area is less reliable, less resilient, and moderately vulnerable, which emphasizes the need of developing suitable strategies for managing water resources of the area on sustainable basis. Finally, it is recommended that multiple statistical tests (at least two) should be used in time-series modeling for making reliable decisions. Moreover, methodology and findings of the sustainability concept in rainfall time series can easily be adopted in other arid regions of the world.

Spatiotemporal variability of rainfall extremes in monsoonal climates - examples from the South American Monsoon and the Indian Monsoon Systems (Invited)

NASA Astrophysics Data System (ADS)

Bookhagen, B.; Boers, N.; Marwan, N.; Malik, N.; Kurths, J.

2013-12-01

Monsoonal rainfall is the crucial component for more than half of the world's population. Runoff associated with monsoon systems provide water resources for agriculture, hydropower, drinking-water generation, recreation, and social well-being and are thus a fundamental part of human society. However, monsoon systems are highly stochastic and show large variability on various timescales. Here, we use various rainfall datasets to characterize spatiotemporal rainfall patterns using traditional as well as new approaches emphasizing nonlinear spatial correlations from a complex networks perspective. Our analyses focus on the South American (SAMS) and Indian (ISM) Monsoon Systems on the basis of Tropical Rainfall Measurement Mission (TRMM) using precipitation radar and passive-microwave products with horizontal spatial resolutions of ~5x5 km^2 (products 2A25, 2B31) and 25x25 km^2 (3B42) and interpolated rainfall-gauge data for the ISM (APHRODITE, 25x25 km^2). The eastern slopes of the Andes of South America and the southern front of the Himalaya are characterized by significant orographic barriers that intersect with the moisture-bearing, monsoonal wind systems. We demonstrate that topography exerts a first-order control on peak rainfall amounts on annual timescales in both mountain belts. Flooding in the downstream regions is dominantly caused by heavy rainfall storms that propagate deep into the mountain range and reach regions that are arid and without vegetation cover promoting rapid runoff. These storms exert a significantly different spatial distribution than average-rainfall conditions and assessing their recurrence intervals and prediction is key in understanding flooding for these regions. An analysis of extreme-value distributions of our high-spatial resolution data reveal that semi-arid areas are characterized by low-frequency/high-magnitude events (i.e., are characterized by a ';heavy tail' distribution), whereas regions with high mean annual rainfall have a less skewed distribution. In a second step, an analysis of the spatial characteristics of extreme rainfall synchronicity by means of complex networks reveals patterns of the propagation of extreme rainfall events. These patterns differ substantially from those obtained from the mean annual rainfall distribution. In addition, we have developed a scheme to predict rainfall extreme events in the eastern Central Andes based on event synchronization and spatial patterns of complex networks. The presented methods and result will allow to critically evaluate data and models in space and time.

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

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

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

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

Influence of high resolution rainfall data on the hydrological response of urban flat catchments

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-claire; van de Giesen, Nick

2016-04-01

In the last decades, cities have become more and more urbanized and population density in urban areas is increased. At the same time, due to the climate changes, rainfall events present higher intensity and shorter duration than in the past. The increase of imperviousness degree, due to urbanization, combined with short and intense rainfall events, determinates a fast hydrological response of the urban catchment and in some cases it can lead to flooding. Urban runoff processes are sensitive to rainfall spatial and temporal variability and, for this reason, high resolution rainfall data are required as input for the hydrological model. A better knowledge of the hydrological response of system can help to prevent damages caused by flooding. This study aims to evaluate the sensitivity of urban hydrological response to spatial and temporal rainfall variability in urban areas, focusing especially on understanding the hydrological behaviour in lowland areas. In flat systems, during intense rainfall events, the flow in the sewer network can be pressurized and it can change direction, depending on the setting of pumping stations and CSOs (combined sewer overflow). In many cases these systems are also looped and it means that the water can follow different paths, depending on the pipe filling process. For these reasons, hydrological response of flat and looped catchments is particularly complex and it can be difficult characterize and predict it. A new dual polarimetric X-band weather radar, able to measure rainfall with temporal resolution of 1 min and spatial resolution of 100mX100m, was recently installed in the city of Rotterdam (NL). With this instrument, high resolution rainfall data were measured and used, in this work, as input for the hydrodynamic model. High detailed, semi-distributed hydrodynamic models of some districts of Rotterdam were used to investigate the hydrological response of flat catchments to high resolution rainfall data. In particular, the hydrological response of some subcatchments of the district of Kralingen was studied. Rainfall data were combined with level and discharge measurements at the pumping station that connects the sewer system with the waste water treatment plane. Using this data it was possible to study the water balance and to have a better idea of the amount of water that leave the system during a specific rainfall events. Results show that the hydrological response of flat and looped catchments is sensitive to spatial and temporal rainfall variability and it can be strongly influenced by rainfall event characteristics, such as intensity, velocity and intermittency of the storm.

The canopy interception-landslide initiation conundrum: insight from a tropical secondary forest in northern Thailand

NASA Astrophysics Data System (ADS)

Sidle, Roy C.; Ziegler, Alan D.

2017-01-01

The interception and smoothing effect of forest canopies on pulses of incident rainfall and its delivery to the soil has been suggested as a factor in moderating peak pore water pressure in soil mantles, thus reducing the risk of shallow landslides. Here we provide 3 years of rainfall and throughfall data in a tropical secondary dipterocarp forest characterized by few large trees in northern Thailand, along with selected soil moisture dynamics, to address this issue. Throughfall was an estimated 88 % of rainfall, varying from 86 to 90 % in individual years. Data from 167 events demonstrate that canopy interception was only weakly associated (via a nonlinear relationship) with total event rainfall, but not significantly correlated with duration, mean intensity, or antecedent 2-day precipitation (API2). Mean interception during small events (≤ 35 mm) was 17 % (n = 135 events) compared with only 7 % for large events (> 35 mm; n = 32). Examining small temporal intervals within the largest and highest intensity events that would potentially trigger landslides revealed complex patterns of interception. The tropical forest canopy had little smoothing effect on incident rainfall during the largest events. During events with high peak intensities, high wind speeds, and/or moderate-to-high pre-event wetting, measured throughfall was occasionally higher than rainfall during large event peaks, demonstrating limited buffering. However, in events with little wetting and low-to-moderate wind speed, early event rainfall peaks were buffered by the canopy. As rainfall continued during most large events, there was little difference between rainfall and throughfall depths. A comparison of both rainfall and throughfall depths to conservative mean intensity-duration thresholds for landslide initiation revealed that throughfall exceeded the threshold in 75 % of the events in which rainfall exceeded the threshold for both wet and dry conditions. Throughfall intensity for the 11 largest events (rainfall = 65-116 mm) plotted near or above the intensity-duration threshold for landslide initiation during wet conditions; 5 of the events were near or above the threshold for dry conditions. Soil moisture responses during large events were heavily and progressively buffered at depths of 1 to 2 m, indicating that the timescale of any short-term smoothing of peak rainfall inputs (i.e., ≤ 1 h) has little influence on peak pore water pressure at depths where landslides would initiate in this area. Given these findings, we conclude that canopy interception would have little effect on mitigating shallow landslide initiation during the types of monsoon rainfall conditions in this and similar tropical secondary forest sites.

Regionalization of monthly rainfall erosivity patternsin Switzerland

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Persistent after-effects of heavy rain on concentrations of ice nuclei and rainfall suggest a biological cause

NASA Astrophysics Data System (ADS)

Bigg, E. K.; Soubeyrand, S.; Morris, C. E.

2015-03-01

Rainfall is one of the most important aspects of climate, but the extent to which atmospheric ice nuclei (IN) influence its formation, quantity, frequency, and location is not clear. Microorganisms and other biological particles are released following rainfall and have been shown to serve as efficient IN, in turn impacting cloud and precipitation formation. Here we investigated potential long-term effects of IN on rainfall frequency and quantity. Differences in IN concentrations and rainfall after and before days of large rainfall accumulation (i.e., key days) were calculated for measurements made over the past century in southeastern and southwestern Australia. Cumulative differences in IN concentrations and daily rainfall quantity and frequency as a function of days from a key day demonstrated statistically significant increasing logarithmic trends (R2 > 0.97). Based on observations that cumulative effects of rainfall persisted for about 20 days, we calculated cumulative differences for the entire sequence of key days at each site to create a historical record of how the differences changed with time. Comparison of pre-1960 and post-1960 sequences most commonly showed smaller rainfall totals in the post-1960 sequences, particularly in regions downwind from coal-fired power stations. This led us to explore the hypothesis that the increased leaf surface populations of IN-active bacteria due to rain led to a sustained but slowly diminishing increase in atmospheric concentrations of IN that could potentially initiate or augment rainfall. This hypothesis is supported by previous research showing that leaf surface populations of the ice-nucleating bacterium Pseudomonas syringae increased by orders of magnitude after heavy rain and that microorganisms become airborne during and after rain in a forest ecosystem. At the sites studied in this work, aerosols that could have initiated rain from sources unrelated to previous rainfall events (such as power stations) would automatically have reduced the influences on rainfall of those whose concentrations were related to previous rain, thereby leading to inhibition of feedback. The analytical methods described here provide means to map and delimit regions where rainfall feedback mediated by microorganisms is suspected to occur or has occurred historically, thereby providing rational means to establish experimental set-ups for verification.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

Urban rainfall monitoring with crowdsourced automatic weather stations in Amsterdam

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Bivariate Rainfall and Runoff Analysis Using Shannon Entropy Theory

NASA Astrophysics Data System (ADS)

Rahimi, A.; Zhang, L.

2012-12-01

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

Hydro-mechanical mechanism and thresholds of rainfall-induced unsaturated landslides

NASA Astrophysics Data System (ADS)

Yang, Zongji; Lei, Xiaoqin; Huang, Dong; Qiao, Jianping

2017-04-01

The devastating Ms 8 Wenchuan earthquake in 2008 created the greatest number of co-seismic mountain hazards ever recorded in China. However, the dynamics of rainfall induced mass remobilization and transport deposits after giant earthquake are not fully understood. Moreover, rainfall intensity and duration (I-D) methods are the predominant early warning indicators of rainfall-induced landslides in post-earthquake region, which are a convenient and straight-forward way to predict the hazards. However, the rainfall-based criteria and thresholds are generally empirical and based on statistical analysis,consequently, they ignore the failure mechanisms of the landslides. This study examines the mechanism and hydro-mechanical behavior and thresholds of these unsaturated deposits under the influence of rainfall. To accomplish this, in situ experiments were performed in an instrumented landslide deposit, The field experimental tests were conducted on a natural co-seismic fractured slope to 1) simulate rainfall-induced shallow failures in the depression channels of a debris flow catchment in an earthquake-affected region, 2)explore the mechanisms and transient processes associated with hydro-mechanical parameter variations in response to the infiltration of rainfall, and 3) identify the hydrologic parameter thresholds and critical criteria of gravitational erosion in areas prone to mass remobilization as a source of debris flows. These experiments provided instrumental evidence and directly proved that post-earthquake rainfall-induced mass remobilization occurred under unsaturated conditions in response to transient rainfall infiltration, and revealed the presence of transient processes and the dominance of preferential flow paths during rainfall infiltration. A hydro-mechanical method was adopted for the transient hydrologic process modelling and unsaturated slope stability analysis. and the slope failures during the experimental test were reproduced by the model, indicating that the decrease in matrix suction and increase in moisture content in response to rainfall infiltration contributed greatly to post-earthquake shallow mass movement. Thus, a threshold model for the initiation of mass remobilization is proposed based on correlations between slope stability and volumetric water content and matrix suction As a complement to rainfall-based early warning strategies, the water content and suction threshold models based on the water infiltration induced slope failure mechanism. the proposed method are expected to improve the accuracy of prediction and early warnings of post-earthquake mountain hazards

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

PubMed

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

2015-12-01

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

A probabilistic approach of the Flash Flood Early Warning System (FF-EWS) in Catalonia based on radar ensemble generation

NASA Astrophysics Data System (ADS)

Velasco, David; Sempere-Torres, Daniel; Corral, Carles; Llort, Xavier; Velasco, Enrique

2010-05-01

Early Warning Systems (EWS) are commonly identified as the most efficient tools in order to improve the preparedness and risk management against heavy rains and Flash Floods (FF) with the objective of reducing economical losses and human casualties. In particular, flash floods affecting torrential Mediterranean catchments are a key element to be incorporated within operational EWSs. The characteristic high spatial and temporal variability of the storms requires high-resolution data and methods to monitor/forecast the evolution of rainfall and its hydrological impact in small and medium torrential basins. A first version of an operational FF-EWS has been implemented in Catalonia (NE Spain) under the name of EHIMI system (Integrated Tool for Hydrometeorological Forecasting) with the support of the Catalan Water Agency (ACA) and the Meteorological Service of Catalonia (SMC). Flash flood warnings are issued based on radar-rainfall estimates. Rainfall estimation is performed on radar observations with high spatial and temporal resolution (1km2 and 10 minutes) in order to adapt the warning scale to the 1-km grid of the EWS. The method is based on comparing observed accumulated rainfall against rainfall thresholds provided by the regional Intensity-Duration-Frequency (IDF) curves. The so-called "aggregated rainfall warning" at every river cell is obtained as the spatially averaged rainfall over its associated upstream draining area. Regarding the time aggregation of rainfall, the critical duration is thought to be an accumulation period similar to the concentration time of each cachtment. The warning is issued once the forecasted rainfall accumulation exceeds the rainfall thresholds mentioned above, which are associated to certain probability of occurrence. Finally, the hazard warning is provided and shown to the decision-maker in terms of exceeded return periods at every river cell covering the whole area of Catalonia. The objective of the present work includes the probabilistic component to the FF-EWS. As a first step, we have incorporated the uncertainty in rainfall estimates and forecasts based on an ensemble of equiprobable rainfall scenarios. The presented study has focused on a number of rainfall events and the performance of the FF-EWS evaluated in terms of its ability to produce probabilistic hazard warnings for decision-making support.

Tropical Rainfall Measuring Mission

NASA Technical Reports Server (NTRS)

1999-01-01

Tropical rainfall affects the lives and economics of a majority of the Earth's population. Tropical rain systems, such as hurricanes, typhoons, and monsoons, are crucial to sustaining the livelihoods of those living in the tropics. Excess rainfall can cause floods and great property and crop damage, whereas too little rainfall can cause drought and crop failure. The latent heat release during the process of precipitation is a major source of energy that drives the atmospheric circulation. This latent heat can intensify weather systems, affecting weather thousands of kilometers away, thus making tropical rainfall an important indicator of atmospheric circulation and short-term climate change. Tropical forests and the underlying soils are major sources of many of the atmosphere's trace constituents. Together, the forests and the atmosphere act as a water-energy regulating system. Most of the rainfall is returned to the atmosphere through evaporation and transpiration, and the atmospheric trace constituents take part in the recycling process. Hence, the hydrological cycle provides a direct link between tropical rainfall and the global cycles of carbon, nitrogen, and sulfur, all important trace materials for the Earth's system. Because rainfall is such an important component in the interactions between the ocean, atmosphere, land, and the biosphere, accurate measurements of rainfall are crucial to understanding the workings of the Earth-atmosphere system. The large spatial and temporal variability of rainfall systems, however, poses a major challenge to estimating global rainfall. So far, there has been a lack of rain gauge networks, especially over the oceans, which points to satellite measurement as the only means by which global observation of rainfall can be made. The Tropical Rainfall Measuring Mission (TRMM), jointly sponsored by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan, provides visible, infrared, and microwave observations of tropical and subtropical rain systems.The satellite observations are complemented by ground radar and rain gauge measurements to validate satellite rain estimation techniques. Goddard Space Flight Center's involvement includes the observatory, four instruments, integration and testing of the observatory, data processing and distribution, and satellite operations. TRMM has a design lifetime of three years. Data generated from TRMM and archived at the GDAAC are useful not only for hydrologists, atmospheric scientists, and climatologists, but also for the health community studying infectious diseases, the ocean research community, and the agricultural community.

Impact of rainfall on the moisture content of large woody fuels

Treesearch

Helen H. Mohr; Thomas A. Waldrop

2013-01-01

This unreplicated case study evaluates the impact of rainfall on large woody fuels over time. We know that one rainfall event may decrease the Keetch-Byram Drought Index, but this study shows no real increase in fuel moisture in 1,000- hour fuels after just one rainfall. Several rain events over time are required for the moisture content of large woody fuels to...

Chemical and biological relationships relevant to the effect of acid rainfall on the soil-plant system

Treesearch

Marvin Nyborg

1976-01-01

This paper deals with problems of measuring acidity in rainfall and the interpretation of these measurements in terms of effects on the soil-plant system. Theoretical relationships of the carbon-dioxide-bicarbonate equalibria and its effect on rainfall acidity measurements are given. The relationship of a cation-anion balance model of acidity in rainfall to plant...

Evaluation of rainfall structure on hydrograph simulation: Comparison of radar and interpolated methods, a study case in a tropical catchment

NASA Astrophysics Data System (ADS)

Velasquez, N.; Ochoa, A.; Castillo, S.; Hoyos Ortiz, C. D.

2017-12-01

The skill of river discharge simulation using hydrological models strongly depends on the quality and spatio-temporal representativeness of precipitation during storm events. All precipitation measurement strategies have their own strengths and weaknesses that translate into discharge simulation uncertainties. Distributed hydrological models are based on evolving rainfall fields in the same time scale as the hydrological simulation. In general, rainfall measurements from a dense and well maintained rain gauge network provide a very good estimation of the total volume for each rainfall event, however, the spatial structure relies on interpolation strategies introducing considerable uncertainty in the simulation process. On the other hand, rainfall retrievals from radar reflectivity achieve a better spatial structure representation but with higher uncertainty in the surface precipitation intensity and volume depending on the vertical rainfall characteristics and radar scan strategy. To assess the impact of both rainfall measurement methodologies on hydrological simulations, and in particular the effects of the rainfall spatio-temporal variability, a numerical modeling experiment is proposed including the use of a novel QPE (Quantitative Precipitation Estimation) method based on disdrometer data in order to estimate surface rainfall from radar reflectivity. The experiment is based on the simulation of 84 storms, the hydrological simulations are carried out using radar QPE and two different interpolation methods (IDW and TIN), and the assessment of simulated peak flow. Results show significant rainfall differences between radar QPE and the interpolated fields, evidencing a poor representation of storms in the interpolated fields, which tend to miss the precise location of the intense precipitation cores, and to artificially generate rainfall in some areas of the catchment. Regarding streamflow modelling, the potential improvement achieved by using radar QPE depends on the density of the rain gauge network and its distribution relative to the precipitation events. The results for the 84 storms show a better model skill using radar QPE than the interpolated fields. Results using interpolated fields are highly affected by the dominant rainfall type and the basin scale.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

The Angola Low: relationship with southern African rainfall and ENSO

NASA Astrophysics Data System (ADS)

Crétat, Julien; Pohl, Benjamin; Dieppois, Bastien; Berthou, Ségolène; Pergaud, Julien

2018-05-01

The main states of the Angola Low (AL) are identified using clustering analysis applied to daily anomalous patterns of 700-hPa wind vorticity over Angola and adjacent countries from November to March for the 1980/81-2014/15 period. At the daily timescale, we examine the extent to which the main states of the AL modulate daily rainfall over southern Africa. At the interannual timescale, we assess both the relationship between the occurrence of these AL states and El Niño southern oscillation (ENSO) and the role of the AL in explaining ENSO's failure in driving southern African rainfall at times. Three reanalyses are considered to account for uncertainties induced by the scarcity of data available for assimilation over southern Africa. Three preferential states of the Angola Low are identified: AL state close to its seasonal climatology with slight zonal displacements, anomalously weak AL state and anomalously strong AL state with meridional displacements. These different states all significantly modulate daily southern African rainfall. Near-climatological AL state promotes wet rainfall anomalies over eastern subtropical southern Africa and dry rainfall anomalies over its western part. A slight westward shift in the near-climatological position of the AL leads to reversed zonal gradient in rainfall. The remaining regimes significantly modulate the meridional gradient in southern African rainfall. Anomalously weak and anomalously northward AL states promote wet rainfall anomalies over tropical southern Africa and dry rainfall anomalies over subtropical southern Africa. The reverse prevails for anomalously southward AL. At the interannual timescale, ENSO significantly modulates the seasonal occurrence of most AL states in the three reanalyses. Anomalously weak and southward AL states are more strongly correlated with regional rainfall than ENSO in all reanalyses, suggesting that accounting for AL variability may improve seasonal forecasts. Case study analysis of the major 1982/83 and 1997/98 El Niño events suggests that the weak rainfall anomalies and strong seasonal AL in 1997/98 may result from counteracting effects between ENSO and Indian Ocean coupled modes of variability.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Effects of variable regolith depth, hydraulic properties, and rainfall on debris-flow initiation during the September 2013 northern Colorado Front Range rainstorm

NASA Astrophysics Data System (ADS)

Baum, R. L.; Coe, J. A.; Kean, J. W.; Jones, E. S.; Godt, J.

2015-12-01

Heavy rainfall during 9 - 13 September 2013 induced about 1100 debris flows in the foothills and mountains of the northern Colorado Front Range. Weathered bedrock was partially exposed in the basal surfaces of many of the shallow source areas at depths ranging from 0.2 to 5 m. Typical values of saturated hydraulic conductivity of soils and regolith units mapped in the source areas range from about 10-4 - 10-6 m/s, with a median value of 2.8 x 10-5 m/s based on number of source areas in each map unit. Rainfall intensities varied spatially and temporally, from 0 to 2.5 x 10-5 m/s (90 mm/hour), with two periods of relatively heavy rainfall on September 12 - 13. The distribution of debris flows appears to correlate with total storm rainfall, and reported times of greatest landslide activity coincide with times of heaviest rainfall. Process-based models of rainfall infiltration and slope stability (TRIGRS) representing the observed ranges of regolith depth, hydraulic conductivity, and rainfall intensity, provide additional insights about the timing and distribution of debris flows from this storm. For example, small debris flows from shallower source areas (<2 m) occurred late on September 11 and in the early morning of September 12, whereas large debris flows from deeper (3 - 5 m) source areas in the western part of the affected area occurred late on September 12. Timing of these flows can be understood in terms of the time required for pore pressure rise depending on regolith depth and rainfall intensity. The variable hydraulic properties combined with variable regolith depth and slope angles account for much of the observed range in timing in areas of similar rainfall intensity and duration. Modeling indicates that the greatest and most rapid pore pressure rise likely occurred in areas of highest rainfall intensity and amount. This is consistent with the largest numbers of debris flows occurring on steep canyon walls in areas of high total storm rainfall.

Evaluation of the Potential of NASA Multi-satellite Precipitation Analysis in Global Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.

2007-01-01

Landslides are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage every year. In the U.S. alone landslides occur in every state, causing an estimated $2 billion in damage and 25- 50 deaths each year. Annual average loss of life from landslide hazards in Japan is 170. The situation is much worse in developing countries and remote mountainous regions due to lack of financial resources and inadequate disaster management ability. Recently, a landslide buried an entire village on the Philippines Island of Leyte on Feb 17,2006, with at least 1800 reported deaths and only 3 houses left standing of the original 300. Intense storms with high-intensity , long-duration rainfall have great potential to trigger rapidly moving landslides, resulting in casualties and property damage across the world. In recent years, through the availability of remotely sensed datasets, it has become possible to conduct global-scale landslide hazard assessment. This paper evaluates the potential of the real-time NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA) system to advance our understanding of and predictive ability for rainfall-triggered landslides. Early results show that the landslide occurrences are closely associated with the spatial patterns and temporal distribution of rainfall characteristics. Particularly, the number of landslide occurrences and the relative importance of rainfall in triggering landslides rely on the influence of rainfall attributes [e.g. rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms). TMPA precipitation data are available in both real-time and post-real-time versions, which are useful to assess the location and timing of rainfall-triggered landslide hazards by monitoring landslide-prone areas while receiving heavy rainfall. For the purpose of identifying rainfall-triggered landslides, an empirical global rainfall intensity-duration threshold is developed by examining a number of landslide occurrences and their corresponding TMPA precipitation characteristics across the world. These early results , in combination with TRMM real-time precipitation estimation system, may form a starting point for developing an operational early warning system for rainfall-triggered landslides around the globe.

Assessing the importance of rainfall uncertainty on hydrological models with different spatial and temporal scale

NASA Astrophysics Data System (ADS)

Nossent, Jiri; Pereira, Fernando; Bauwens, Willy

2015-04-01

Precipitation is one of the key inputs for hydrological models. As long as the values of the hydrological model parameters are fixed, a variation of the rainfall input is expected to induce a change in the model output. Given the increased awareness of uncertainty on rainfall records, it becomes more important to understand the impact of this input - output dynamic. Yet, modellers often still have the intention to mimic the observed flow, whatever the deviation of the employed records from the actual rainfall might be, by recklessly adapting the model parameter values. But is it actually possible to vary the model parameter values in such a way that a certain (observed) model output can be generated based on inaccurate rainfall inputs? Thus, how important is the rainfall uncertainty for the model output with respect to the model parameter importance? To address this question, we apply the Sobol' sensitivity analysis method to assess and compare the importance of the rainfall uncertainty and the model parameters on the output of the hydrological model. In order to be able to treat the regular model parameters and input uncertainty in the same way, and to allow a comparison of their influence, a possible approach is to represent the rainfall uncertainty by a parameter. To tackle the latter issue, we apply so called rainfall multipliers on hydrological independent storm events, as a probabilistic parameter representation of the possible rainfall variation. As available rainfall records are very often point measurements at a discrete time step (hourly, daily, monthly,…), they contain uncertainty due to a latent lack of spatial and temporal variability. The influence of the latter variability can also be different for hydrological models with different spatial and temporal scale. Therefore, we perform the sensitivity analyses on a semi-distributed model (SWAT) and a lumped model (NAM). The assessment and comparison of the importance of the rainfall uncertainty and the model parameters is achieved by considering different scenarios for the included parameters and the state of the models.

Transpiration Response and Growth in Pearl Millet Parental Lines and Hybrids Bred for Contrasting Rainfall Environments

PubMed Central

Medina, Susan; Gupta, S. K.; Vadez, Vincent

2017-01-01

Under conditions of high vapor pressure deficit (VPD) and soil drying, restricting transpiration is an important avenue to gain efficiency in water use. The question we raise in this article is whether breeding for agro-ecological environments that differ for the rainfall have selected for traits that control plant water use. These are measured in pearl millet materials bred for zones varying in rainfall (8 combinations of parent and F1-hybrids, 18 F1-hybrids and then 40 F1-hybrids). In all cases, we found an agro-ecological variation in the slope of the transpiration response to increasing VPD, and parental line variation in the transpiration response to soil drying within hybrids/parent combinations. The hybrids adapted to lower rainfall had higher transpiration response curves than those from the highest rainfall zones, but showed no variation in how transpiration responded to soil drying. The genotypes bred for lower rainfall zones showed lower leaf area, dry matter, thicker leaves, root development, and exudation, than the ones bred for high rainfall zone when grown in the low VPD environment of the greenhouse, but there was no difference in their root length neither on the root/shoot index in these genotypes. By contrast, when grown under high VPD conditions outdoors, the lower rainfall hybrids had the highest leaf, tiller, and biomass development. Finally, under soil drying the genotypes from the lower rainfall accumulated less biomass than the ones from higher rainfall zone, and so did the parental lines compared to the hybrids. These differences in the transpiration response and growth clearly showed that breeding for different agro-ecological zones also bred for different genotype strategies in relation to traits related to plant water use. Highlights: • Variation in transpiration response reflected breeding for agro-ecological zones • Different growth strategies depended on the environmental conditions • Different ideotypes reflected rainfall levels in specific agro-ecological zones PMID:29163578

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

PubMed

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

2018-03-01

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

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

NASA Technical Reports Server (NTRS)

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

2002-01-01

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

Contribution of raindrop impact to the change of soil physical properties and water erosion under semi-arid rainfalls.

PubMed

Vaezi, Ali Reza; Ahmadi, Morvarid; Cerdà, Artemi

2017-04-01

Soil erosion by water is a three-phase process that consists of detachment of soil particles from the soil mass, transportation of detached particles either by raindrop impact or surface water flow, and sedimentation. Detachment by raindrops is a key component of the soil erosion process. However, little information is available on the role of raindrop impact on soil losses in the semi-arid regions where vegetation cover is often poor and does not protect the soil from rainfall. The objective of this study is to determine the contribution of raindrop impact to changes in soil physical properties and soil losses in a semiarid weakly-aggregated agricultural soil. Soil losses were measured under simulated rainfalls of 10, 20, 30, 40, 50, 60 and 70mmh -1 , and under two conditions: i) with raindrop impact; and, ii) without raindrop impact. Three replications at each rainfall intensity and condition resulted in a total of 42 microplots of 1m×1.4m installed on a 10% slope according to a randomized complete block design. The contribution of raindrop impact to soil loss was computed using the difference between soil loss with raindrop impact and without raindrop impact at each rainfall intensity. Soil physical properties (aggregate size, bulk density and infiltration rate) were strongly damaged by raindrop impact as rainfall intensity increased. Soil loss was significantly affected by rainfall intensity under both soil surface conditions. The contribution of raindrop impact to soil loss decreased steadily with increasing rainfall intensity. At the lower rainfall intensities (20-30mmh -1 ), raindrop impact was the dominant factor controlling soil loss from the plots (68%) while at the higher rainfall intensities (40-70mmh -1 ) soil loss was mostly affected by increasing runoff discharge. At higher rainfall intensities the sheet flow protected the soil from raindrop impact. Copyright © 2017 Elsevier B.V. All rights reserved.

Extreme climatic events drive mammal irruptions: regression analysis of 100-year trends in desert rainfall and temperature

PubMed Central

Greenville, Aaron C; Wardle, Glenda M; Dickman, Chris R

2012-01-01

Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra-annual rainfall had become more variable over time. Using long-term live-trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires. PMID:23170202

The cross wavelet and wavelet coherence analysis of spatio-temporal rainfall-groundwater system in Pingtung plain, Taiwan

NASA Astrophysics Data System (ADS)

Lin, Yuan-Chien; Yu, Hwa-Lung

2013-04-01

The increasing frequency and intensity of extreme rainfall events has been observed recently in Taiwan. Particularly, Typhoon Morakot, Typhoon Fanapi, and Typhoon Megi consecutively brought record-breaking intensity and magnitude of rainfalls to different locations of Taiwan in these two years. However, records show the extreme rainfall events did not elevate the amount of annual rainfall accordingly. Conversely, the increasing frequency of droughts has also been occurring in Taiwan. The challenges have been confronted by governmental agencies and scientific communities to come up with effective adaptation strategies for natural disaster reduction and sustainable environment establishment. Groundwater has long been a reliable water source for a variety of domestic, agricultural, and industrial uses because of its stable quantity and quality. In Taiwan, groundwater accounts for the largest proportion of all water resources for about 40%. This study plans to identify and quantify the nonlinear relationship between precipitation and groundwater recharge, find the non-stationary time-frequency relations between the variations of rainfall and groundwater levels to understand the phase difference of time series. Groundwater level data and over-50-years hourly rainfall records obtained from 20 weather stations in Pingtung Plain, Taiwan has been collected. Extract the space-time pattern by EOF method, which is a decomposition of a signal or data set in terms of orthogonal basis functions determined from the data for both time series and spatial patterns, to identify the important spatial pattern of groundwater recharge and using cross wavelet and wavelet coherence method to identify the relationship between rainfall and groundwater levels. Results show that EOF method can specify the spatial-temporal patterns which represents certain geological characteristics and other mechanisms of groundwater, and the wavelet coherence method can identify general correlation between rainfall and groundwater signal at low frequency and high frequency relationship at some certain extreme rainfall events. Keywords: extreme rainfall, groundwater, EOF, wavelet coherence

Tropical Cyclones Feed More Heavy Rain in a Warmer Climate

NASA Technical Reports Server (NTRS)

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

2007-01-01

The possible linkage of tropical cyclones (TC) to global warming is a hotly debated scientific topic, with immense societal impacts. Most of the debate has been focused on the issue of uncertainty in the use of non-research quality data for long-term trend analyses, especially with regard to TC intensity provided by TC forecasting centers. On the other hand, it is well known that TCs are associated with heavy rain during the processes of genesis and intensification, and that there are growing evidences that rainfall characteristics (not total rainfall) are most likely to be affected by global warming. Yet, satellite rainfall data have not been exploited in any recent studies of linkage between tropical cyclones (TC) and global warming. This is mostly due to the large uncertainties associated with detection of long-term trend in satellite rainfall estimates over the ocean. This problem, as we demonstrate in this paper, can be alleviated by examining rainfall distribution, rather than rainfall total. This paper is the first to use research-quality, satellite-derived rainfall from TRMM and GPCP over the tropical oceans to estimate shift in rainfall distribution during the TC season, and its relationships with TCs, and sea surface temperature (SST) in the two major ocean basins, the northern Atlantic and the northern Pacific for 1979-2005. From the rainfall distribution, we derive the TC contributions to rainfall in various extreme rainfall categories as a function to time. Our results show a definitive trend indicating that TCs are contributing increasingly to heavier rain events, i.e., intense TC's are more frequent in the last 27 years. The TC contribution to top 5% heavy rain has nearly doubled in the last two decades in the North Atlantic, and has increased by about 10% in the North Pacific. The different rate of increase in TC contribution to heavy rain may be related to the different rates of different rate of expansion of the warm pool (SST >2S0 C) area in the two oceans.

Does the GPM mission resolve the systematic error dependence with climatology and topography - a statistical and hydrologic evaluation over India?

NASA Astrophysics Data System (ADS)

Beria, H.; Nanda, T., Sr.; Bisht, D. S.; Chatterjee, C.

2016-12-01

Increasing hydrologic extremes in a changing climate with lack of quality rainfall forcings have inspired the development of a number of satellite and reanalysis based precipitation products in the past decade. Tropical Rainfall Measuring Mission (TRMM) has emerged as the front runner in this race, providing high quality precipitation forcings in the tropical part of the world. However, TRMM is known to suffer from its poor sensitivity to low rainfall intensities due to limited resolving power of its sensors, and is also not known to accurately resolve topography in its rainfall estimates. The Global Precipitation Mission (GPM), a follow-up mission of TRMM, promises enhanced spatio-temporal resolution along with upgrades in sensors and rainfall estimation techniques. In this study, the rainfall estimates of Integrated Multi-satellitE Retrievals for GPM (IMERG), was compared with those of TRMM for the major basins in India for the year 2014. IMERG depicted higher skill (in terms of correlation) for the majority of basins at all rainfall intensities, with a drastic improvement in low rainfall estimates (smaller biases in 75 out of 86 basins). IMERG was found to improve the topographic resolution, with lower error in high elevation basins. IMERG could better resolve the sharp topographic gradient in the Western Ghat region of India. However, IMERG suffered from poor skill in the semi-arid basins of Rajasthan, at all rainfall intensities. Rainfall-runoff exercise over Mahanadi River basin (a flood prone basin on the Eastern coast of India) using Variable Infiltration Capacity Model (VIC) showed better simulations with TRMM, mainly due to the overestimation of low rainfall events by IMERG. Also, the calibration scheme could be put to fault as the period of availability of IMERG is rather small, and more in-depth hydrologic analysis could only be carried out with sufficiently longer time series. Overall, the fine spatial and temporal resolution along with improved accuracy, promises new horizons in hydrologic forecasting under data scarcity.

Effect of rain gauge density over the accuracy of rainfall: a case study over Bangalore, India.

PubMed

Mishra, Anoop Kumar

2013-12-01

Rainfall is an extremely variable parameter in both space and time. Rain gauge density is very crucial in order to quantify the rainfall amount over a region. The level of rainfall accuracy is highly dependent on density and distribution of rain gauge stations over a region. Indian Space Research Organisation (ISRO) have installed a number of Automatic Weather Station (AWS) rain gauges over Indian region to study rainfall. In this paper, the effect of rain gauge density over daily accumulated rainfall is analyzed using ISRO AWS gauge observations. A region of 50 km × 50 km box over southern part of Indian region (Bangalore) with good density of rain gauges is identified for this purpose. Rain gauge numbers are varied from 1-8 in 50 km box to study the variation in the daily accumulated rainfall. Rainfall rates from the neighbouring stations are also compared in this study. Change in the rainfall as a function of gauge spacing is studied. Use of gauge calibrated satellite observations to fill the gauge station value is also studied. It is found that correlation coefficients (CC) decrease from 82% to 21% as gauge spacing increases from 5 km to 40 km while root mean square error (RMSE) increases from 8.29 mm to 51.27 mm with increase in gauge spacing from 5 km to 40 km. Considering 8 rain gauges as a standard representative of rainfall over the region, absolute error increases from 15% to 64% as gauge numbers are decreased from 7 to 1. Small errors are reported while considering 4 to 7 rain gauges to represent 50 km area. However, reduction to 3 or less rain gauges resulted in significant error. It is also observed that use of gauge calibrated satellite observations significantly improved the rainfall estimation over the region with very few rain gauge observations.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Transpiration Response and Growth in Pearl Millet Parental Lines and Hybrids Bred for Contrasting Rainfall Environments.

PubMed

Medina, Susan; Gupta, S K; Vadez, Vincent

2017-01-01

Under conditions of high vapor pressure deficit (VPD) and soil drying, restricting transpiration is an important avenue to gain efficiency in water use. The question we raise in this article is whether breeding for agro-ecological environments that differ for the rainfall have selected for traits that control plant water use. These are measured in pearl millet materials bred for zones varying in rainfall (8 combinations of parent and F 1 -hybrids, 18 F 1 -hybrids and then 40 F 1 -hybrids). In all cases, we found an agro-ecological variation in the slope of the transpiration response to increasing VPD, and parental line variation in the transpiration response to soil drying within hybrids/parent combinations. The hybrids adapted to lower rainfall had higher transpiration response curves than those from the highest rainfall zones, but showed no variation in how transpiration responded to soil drying. The genotypes bred for lower rainfall zones showed lower leaf area, dry matter, thicker leaves, root development, and exudation, than the ones bred for high rainfall zone when grown in the low VPD environment of the greenhouse, but there was no difference in their root length neither on the root/shoot index in these genotypes. By contrast, when grown under high VPD conditions outdoors, the lower rainfall hybrids had the highest leaf, tiller, and biomass development. Finally, under soil drying the genotypes from the lower rainfall accumulated less biomass than the ones from higher rainfall zone, and so did the parental lines compared to the hybrids. These differences in the transpiration response and growth clearly showed that breeding for different agro-ecological zones also bred for different genotype strategies in relation to traits related to plant water use. Highlights : • Variation in transpiration response reflected breeding for agro-ecological zones • Different growth strategies depended on the environmental conditions • Different ideotypes reflected rainfall levels in specific agro-ecological zones.

Rainfall and hydrological stability alter the impact of top predators on food web structure and function.

PubMed

Marino, Nicholas A C; Srivastava, Diane S; MacDonald, A Andrew M; Leal, Juliana S; Campos, Alice B A; Farjalla, Vinicius F

2017-02-01

Climate change will alter the distribution of rainfall, with potential consequences for the hydrological dynamics of aquatic habitats. Hydrological stability can be an important determinant of diversity in temporary aquatic habitats, affecting species persistence and the importance of predation on community dynamics. As such, prey are not only affected by drought-induced mortality but also the risk of predation [a non-consumptive effect (NCE)] and actual consumption by predators [a consumptive effect (CE)]. Climate-induced changes in rainfall may directly, or via altered hydrological stability, affect predator-prey interactions and their cascading effects on the food web, but this has rarely been explored, especially in natural food webs. To address this question, we performed a field experiment using tank bromeliads and their aquatic food web, composed of predatory damselfly larvae, macroinvertebrate prey and bacteria. We manipulated the presence and consumption ability of damselfly larvae under three rainfall scenarios (ambient, few large rainfall events and several small rainfall events), recorded the hydrological dynamics within bromeliads and examined the effects on macroinvertebrate colonization, nutrient cycling and bacterial biomass and turnover. Despite our large perturbations of rainfall, rainfall scenario had no effect on the hydrological dynamics of bromeliads. As a result, macroinvertebrate colonization and nutrient cycling depended on the hydrological stability of bromeliads, with no direct effect of rainfall or predation. In contrast, rainfall scenario determined the direction of the indirect effects of predators on bacteria, driven by both predator CEs and NCEs. These results suggest that rainfall and the hydrological stability of bromeliads had indirect effects on the food web through changes in the CEs and NCEs of predators. We suggest that future studies should consider the importance of the variability in hydrological dynamics among habitats as well as the biological mechanisms underlying the ecological responses to climate change. © 2016 John Wiley & Sons Ltd.

Multisite rainfall downscaling and disaggregation in a tropical urban area

NASA Astrophysics Data System (ADS)

Lu, Y.; Qin, X. S.

2014-02-01

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

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

PubMed

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

2018-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Integrating real-time subsurface hydrologic monitoring with empirical rainfall thresholds to improve landslide early warning

USGS Publications Warehouse

Mirus, Benjamin B.; Becker, Rachel E.; Baum, Rex L.; Smith, Joel B.

2018-01-01

Early warning for rainfall-induced shallow landsliding can help reduce fatalities and economic losses. Although these commonly occurring landslides are typically triggered by subsurface hydrological processes, most early warning criteria rely exclusively on empirical rainfall thresholds and other indirect proxies for subsurface wetness. We explore the utility of explicitly accounting for antecedent wetness by integrating real-time subsurface hydrologic measurements into landslide early warning criteria. Our efforts build on previous progress with rainfall thresholds, monitoring, and numerical modeling along the landslide-prone railway corridor between Everett and Seattle, Washington, USA. We propose a modification to a previously established recent versus antecedent (RA) cumulative rainfall thresholds by replacing the antecedent 15-day rainfall component with an average saturation observed over the same timeframe. We calculate this antecedent saturation with real-time telemetered measurements from five volumetric water content probes installed in the shallow subsurface within a steep vegetated hillslope. Our hybrid rainfall versus saturation (RS) threshold still relies on the same recent 3-day rainfall component as the existing RA thresholds, to facilitate ready integration with quantitative precipitation forecasts. During the 2015–2017 monitoring period, this RS hybrid approach has an increase of true positives and a decrease of false positives and false negatives relative to the previous RA rainfall-only thresholds. We also demonstrate that alternative hybrid threshold formats could be even more accurate, which suggests that further development and testing during future landslide seasons is needed. The positive results confirm that accounting for antecedent wetness conditions with direct subsurface hydrologic measurements can improve thresholds for alert systems and early warning of rainfall-induced shallow landsliding.

Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

NASA Astrophysics Data System (ADS)

Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

2015-04-01

Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

Estimation of groundwater recharge via percolation outputs from a rainfall/runoff model for the Verlorenvlei estuarine system, west coast, South Africa

NASA Astrophysics Data System (ADS)

Watson, Andrew; Miller, Jodie; Fleischer, Melanie; de Clercq, Willem

2018-03-01

Wetlands are conservation priorities worldwide, due to their high biodiversity and productivity, but are under threat from agricultural and climate change stresses. To improve the water management practices and resource allocation in these complex systems, a modelling approach has been developed to estimate potential recharge for data poor catchments using rainfall data and basic assumptions regarding soil and aquifer properties. The Verlorenvlei estuarine lake (RAMSAR #525) on the west coast of South Africa is a data poor catchment where rainfall records have been supplemented with farmer's rainfall records. The catchment has multiple competing users. To determine the ecological reserve for the wetlands, the spatial and temporal distribution of recharge had to be well constrained using the J2000 rainfall/runoff model. The majority of rainfall occurs in the mountains (±650 mm/yr) and considerably less in the valley (±280 mm/yr). Percolation was modelled as ∼3.6% of rainfall in the driest parts of the catchment, ∼10% of rainfall in the moderately wet parts of the catchment and ∼8.4% but up to 28.9% of rainfall in the wettest parts of the catchment. The model results are representative of rainfall and water level measurements in the catchment, and compare well with water table fluctuation technique, although estimates are dissimilar to previous estimates within the catchment. This is most likely due to the daily timestep nature of the model, in comparison to other yearly average methods. These results go some way in understanding the fact that although most semi-arid catchments have very low yearly recharge estimates, they are still capable of sustaining high biodiversity levels. This demonstrates the importance of incorporating shorter term recharge event modeling for improving recharge estimates.

A Prototype Visualization of Real-time River Drainage Network Response to Rainfall

NASA Astrophysics Data System (ADS)

Demir, I.; Krajewski, W. F.

2011-12-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to and visualization of flood inundation maps, real-time flood conditions, flood forecasts both short-term and seasonal, and other flood-related data for communities in Iowa. The key element of the system's architecture is the notion of community. Locations of the communities, those near streams and rivers, define basin boundaries. The IFIS streams rainfall data from NEXRAD radar, and provides three interfaces including animation for rainfall intensity, daily rainfall totals and rainfall accumulations for past 14 days for Iowa. A real-time interactive visualization interface is developed using past rainfall intensity data. The interface creates community-based rainfall products on-demand using watershed boundaries of each community as a mask. Each individual rainfall pixel is tracked in the interface along the drainage network, and the ones drains to same pixel location are accumulated. The interface loads recent rainfall data in five minute intervals that are combined with current values. Latest web technologies are utilized for the development of the interface including HTML 5 Canvas, and JavaScript. The performance of the interface is optimized to run smoothly on modern web browsers. The interface controls allow users to change internal parameters of the system, and operation conditions of the animation. The interface will help communities understand the effects of rainfall on water transport in stream and river networks and make better-informed decisions regarding the threat of floods. This presentation provides an overview of a unique visualization interface and discusses future plans for real-time dynamic presentations of streamflow forecasting.

A Web-based Data Intensive Visualization of Real-time River Drainage Network Response to Rainfall

NASA Astrophysics Data System (ADS)

Demir, I.; Krajewski, W. F.

2012-04-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to and visualization of flood inundation maps, real-time flood conditions, flood forecasts both short-term and seasonal, and other flood-related data for communities in Iowa. The key element of the system's architecture is the notion of community. Locations of the communities, those near streams and rivers, define basin boundaries. The IFIS streams rainfall data from NEXRAD radar, and provides three interfaces including animation for rainfall intensity, daily rainfall totals and rainfall accumulations for past 14 days for Iowa. A real-time interactive visualization interface is developed using past rainfall intensity data. The interface creates community-based rainfall products on-demand using watershed boundaries of each community as a mask. Each individual rainfall pixel is tracked in the interface along the drainage network, and the ones drains to same pixel location are accumulated. The interface loads recent rainfall data in five minute intervals that are combined with current values. Latest web technologies are utilized for the development of the interface including HTML 5 Canvas, and JavaScript. The performance of the interface is optimized to run smoothly on modern web browsers. The interface controls allow users to change internal parameters of the system, and operation conditions of the animation. The interface will help communities understand the effects of rainfall on water transport in stream and river networks and make better-informed decisions regarding the threat of floods. This presentation provides an overview of a unique visualization interface and discusses future plans for real-time dynamic presentations of streamflow forecasting.

Use of a large-scale rainfall simulator reveals novel insights into stemflow generation

NASA Astrophysics Data System (ADS)

Levia, D. F., Jr.; Iida, S. I.; Nanko, K.; Sun, X.; Shinohara, Y.; Sakai, N.

2017-12-01

Detailed knowledge of stemflow generation and its effects on both hydrological and biogoechemical cycling is important to achieve a holistic understanding of forest ecosystems. Field studies and a smaller set of experiments performed under laboratory conditions have increased our process-based knowledge of stemflow production. Building upon these earlier works, a large-scale rainfall simulator was employed to deepen our understanding of stemflow generation processes. The use of the large-scale rainfall simulator provides a unique opportunity to examine a range of rainfall intensities under constant conditions that are difficult under natural conditions due to the variable nature of rainfall intensities in the field. Stemflow generation and production was examined for three species- Cryptomeria japonica D. Don (Japanese cedar), Chamaecyparis obtusa (Siebold & Zucc.) Endl. (Japanese cypress), Zelkova serrata Thunb. (Japanese zelkova)- under both leafed and leafless conditions at several different rainfall intensities (15, 20, 30, 40, 50, and 100 mm h-1) using a large-scale rainfall simulator in National Research Institute for Earth Science and Disaster Resilience (Tsukuba, Japan). Stemflow production and rates and funneling ratios were examined in relation to both rainfall intensity and canopy structure. Preliminary results indicate a dynamic and complex response of the funneling ratios of individual trees to different rainfall intensities among the species examined. This is partly the result of different canopy structures, hydrophobicity of vegetative surfaces, and differential wet-up processes across species and rainfall intensities. This presentation delves into these differences and attempts to distill them into generalizable patterns, which can advance our theories of stemflow generation processes and ultimately permit better stewardship of forest resources. ________________ Funding note: This research was supported by JSPS Invitation Fellowship for Research in Japan (Grant Award No.: S16088) and JSPS KAKENHI (Grant Award No.: JP15H05626).

Changing On Diurnal Cycle Of Rainfall In Northern Coastal Of West Java

NASA Astrophysics Data System (ADS)

Yulihastin, E.; Hadi, T. W.; Ningsih, N. S.

2017-12-01

The floods event in the north of Java was largely due to persistent of rainfall that occurred in the morning which indicated of deviation of diurnal pattern of rainfall. The shift of the phase of diurnal rainfall cycle using TRMM satellite hourly data of 3B41RT on the rainy period of 2000-2016 exhibits over land from Late Afternoon-Early Midnight (LA-EM) to morning. The peak of the cycle changes from diurnal to semidiurnal with a peak occurring in LA-EM and morning. Location of rainfall which usually occurs in the oceans shifted into near coastal area. The classification of diurnal rainfall cycles based on composite analysis shows four types: Normal (N) Type (45.6%) with one peak rainfall occurring in the afternoon until night, Diurnal (D) Type (26%) with one peak and phase opposite to normal type, Semidiurnal (SD) Type (6.5 %) with two peaks and the main peak occurring in the afternoon until night, Third Diurnal (TD) Type (21.7%) with three peaks and the main peak occurs in the morning. The classification was confirmed using the objective method of Empirical Mode Decomposition (EMD) and obtained three IMFs representing three diurnal cycle modes of Type TD (67.8%) with the main rain peak taking place in the afternoon, Type D with rain peak occurring in the early hours (18.9%), and SD type (9.9%) with the first peak occurred in the afternoon. For D Type, the results also prove that the diurnal cycle with significant deviations in amplitude occurred in February 2002, 2004, 2008, 2014, wich is the maximum rainfall occurs in the EM. It also seems that in those years, rainfall intensity is concentrated on the northern coast of West Java while in the Java Sea rainfall was minimum.

Small scale rainfall simulators: Challenges for a future use in soil erosion research

NASA Astrophysics Data System (ADS)

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

2013-04-01

Rainfall simulation on micro-plot scale is a method used worldwide to assess the generation of overland flow, soil erosion, infiltration and interrelated processes such as soil sealing, crusting, splash and redistribution of solids and solutes. The produced data are of great significance not only for the analysis of the simulated processes, but also as a source of input-data for soil erosion modelling. The reliability of the data is therefore of paramount importance, and quality management of rainfall simulation procedure a general responsibility of the rainfall simulation community. This was an accepted outcome at the "International Rainfall Simulator Workshop 2011" at Trier University. The challenges of the present and near future use of small scale rainfall simulations concern the comparability of results and scales, the quality of the data for soil erosion modelling, and further technical developments to overcome physical limitations and constraints. Regarding the high number of research questions, different fields of application, and due to the great technical creativity of researchers, a large number of different types of rainfall simulators is available. But each of the devices produces a different rainfall, leading to different kinetic energy values influencing soil surface and erosion processes. Plot sizes are also variable, as well as the experimental simulation procedures. As a consequence, differing runoff and erosion results are produced. The presentation summarises the three important aspects of rainfall simulations, following a processual order: 1. Input-factor "rain" and its calibration 2. Surface-factor "plot" and its documentation 3. Output-factors "runoff" and "sediment concentration" Finally, general considerations about the limitations and challenges for further developments and applications of rainfall simulation data are presented.

The impact of inter-annual rainfall variability on African savannas changes with mean rainfall.

PubMed

Synodinos, Alexis D; Tietjen, Britta; Lohmann, Dirk; Jeltsch, Florian

2018-01-21

Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520-780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580-780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during 'dry' extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Remote sensing-based characterization of rainfall during atmospheric rivers over the central United States

NASA Astrophysics Data System (ADS)

Nayak, Munir A.; Villarini, Gabriele

2018-01-01

Atmospheric rivers (ARs) play a central role in the hydrology and hydroclimatology of the central United States. More than 25% of the annual rainfall is associated with ARs over much of this region, with many large flood events tied to their occurrence. Despite the relevance of these storms for flood hydrology and water budget, the characteristics of rainfall associated with ARs over the central United has not been investigated thus far. This study fills this major scientific gap by describing the rainfall during ARs over the central United States using five remote sensing-based precipitation products over a 12-year study period. The products we consider are: Stage IV, Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA, both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); the CPC MORPHing Technique (CMORPH). As part of the study, we evaluate these products against a rain gauge-based dataset using both graphical- and metrics-based diagnostics. Based on our analyses, Stage IV is found to better reproduce the reference data. Hence, we use it for the characterization of rainfall in ARs. Most of the AR-rainfall is located in a narrow region within ∼150 km on both sides of the AR major axis. In this region, rainfall has a pronounced positive relationship with the magnitude of the water vapor transport. Moreover, we have also identified a consistent increase in rainfall intensity with duration (or persistence) of AR conditions. However, there is not a strong indication of diurnal variability in AR rainfall. These results can be directly used in developing flood protection strategies during ARs. Further, weather prediction agencies can benefit from the results of this study to achieve higher skill of resolving precipitation processes in their models.

Destabilization of a Clay-Rich Slope by Rainfall : Monitoring of Precursons on an Hectometric Sliding Surface

NASA Astrophysics Data System (ADS)

Doan, M. L.; Bièvre, G.; Jongmans, D.; Helmstetter, A.; Radiguet, M.

2016-12-01

The Avignonet landslide is an active clay landslide near Grenoble, France, and therefore one of the monitored site of OMIV observatory. Previous geophysical investigation, including borehole drilling and surface geophysics proved that the landslide deformation is accommodated by several localized shear zones. The shallowest shear zone is about 5 m deep and extends over 100 m. Several sensors monitor the landslide. They record several precursors prior to a major disturbance of the landslide in autumn 2012, that affects all sensors in the landslide for several months. After major rainfalls, the two piezometers located near the 5 m deep interface got larger impulsional response to rainfall. The moderate rainfalls of Oct 26th caused the hydraulic head both reached a plateau before experiencing a sudden change, triggered by the small rainfall of Oct 31st. It's not the bigger rainfall that induced the disturbance. It was not the first rainfall neither.Other sensors suggest that the destabilization of the landslide was progressive. Spontaneous potential sensors regularly spaced within the 100 m wide sensors begin to separate after Oct 28th, suggesting a landslide wide precursor. Repeated microseismic events, of high frequency, suggesting a local origin, are more frequent. Their occurrence peaks after the small rainfall of Oct 29th and again on Oct 31st, before the rainfall that triggered the disturbance. They stop at the same time as sudden change in piezometric data. Despite the lack of displacement sensor, it is assumed that the 5 m deep shear zone slipped on Oct 31st, since it affects the piezometer sampling this interface. The data shows a progressive path towards destabilization. Especially, triggering of the landslide disturbances is associated to the cumulative effect of seismic activity and rainfall, even minor. This suggests a hydromechanical process.

Calibration and validation of rainfall thresholds for shallow landslide forecasting in Sicily, southern Italy

NASA Astrophysics Data System (ADS)

Gariano, S. L.; Brunetti, M. T.; Iovine, G.; Melillo, M.; Peruccacci, S.; Terranova, O.; Vennari, C.; Guzzetti, F.

2015-01-01

Empirical rainfall thresholds are tools to forecast the possible occurrence of rainfall-induced shallow landslides. Accurate prediction of landslide occurrence requires reliable thresholds, which need to be properly validated before their use in operational warning systems. We exploited a catalogue of 200 rainfall conditions that have resulted in at least 223 shallow landslides in Sicily, southern Italy, in the 11-year period 2002-2011, to determine regional event duration-cumulated event rainfall (ED) thresholds for shallow landslide occurrence. We computed ED thresholds for different exceedance probability levels and determined the uncertainty associated to the thresholds using a consolidated bootstrap nonparametric technique. We further determined subregional thresholds, and we studied the role of lithology and seasonal periods in the initiation of shallow landslides in Sicily. Next, we validated the regional rainfall thresholds using 29 rainfall conditions that have resulted in 42 shallow landslides in Sicily in 2012. We based the validation on contingency tables, skill scores, and a receiver operating characteristic (ROC) analysis for thresholds at different exceedance probability levels, from 1% to 50%. Validation of rainfall thresholds is hampered by lack of information on landslide occurrence. Therefore, we considered the effects of variations in the contingencies and the skill scores caused by lack of information. Based on the results obtained, we propose a general methodology for the objective identification of a threshold that provides an optimal balance between maximization of correct predictions and minimization of incorrect predictions, including missed and false alarms. We expect that the methodology will increase the reliability of rainfall thresholds, fostering the operational use of validated rainfall thresholds in operational early warning system for regional shallow landslide forecasting.

SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds. The two-CN system approach

NASA Astrophysics Data System (ADS)

Soulis, K. X.; Valiantzas, J. D.

2011-10-01

The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN values can be estimated by being selected from tables. However, it is more accurate to estimate the CN value from measured rainfall-runoff data (assumed available) in a watershed. Previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. They suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the novel hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of the inevitable presence of soil-cover complex spatial variability along watersheds is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CN-rainfall variation by reducing the CN spatial variability into two classes. The behavior of the CN-rainfall function produced by the proposed two-CN system concept is approached theoretically, it is analyzed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous original method based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.

Determining hydroclimatic extreme events over the south-central Andes

NASA Astrophysics Data System (ADS)

RamezaniZiarani, Maryam; Bookhagen, Bodo; Schmidt, Torsten; Wickert, Jens; de la Torre, Alejandro; Volkholz, Jan

2017-04-01

The south-central Andes in NW Argentina are characterized by a strong rainfall asymmetry. In the east-west direction exists one of the steepest rainfall gradients on Earth, resulting from the large topographic differences in this region. In addition, in the north-south direction the rainfall intensity varies as the climatic regime shifts from the tropical central Andes to the subtropical south-central Andes. In this study, we investigate hydroclimatic extreme events over the south-central Andes using ERA-Interim reanalysis data of the ECMWF (European Centre for Medium-Range Weather Forecasts), the high resolution regional climate model (COSMO-CLM) data and TRMM (Tropical Rainfall Measuring Mission) data. We divide the area in three different study regions based on elevation: The high-elevation Altiplano-Puna plateau, an intermediate area characterized by intramontane basins, and the foreland area. We analyze the correlations between climatic variables, such as specific humidity, zonal wind component, meridional wind component and extreme rainfall events in all three domains. The results show that there is a high positive temporal correlation between extreme rainfall events (90th and 99th percentile rainfall) and extreme specific humidity events (90th and 99th percentile specific humidity). In addition, the temporal variations analysis represents a trend of increasing specific humidity with time during time period (1994-2013) over the Altiplano-Puna plateau which is in agreement with rainfall trend. Regarding zonal winds, our results indicate that 99th percentile rainfall events over the Altiplano-Puna plateau coincide temporally with strong easterly winds from intermountain and foreland regions in the east. In addition, the results regarding the meridional wind component represent strong northerly winds in the foreland region coincide temporally with 99th percentile rainfall over the Altiplano-Puna plateau.

Assessing the Regional Frequency, Intensity, and Spatial Extent of Tropical Cyclone Rainfall

NASA Astrophysics Data System (ADS)

Bosma, C.; Wright, D.; Nguyen, P.

2017-12-01

While the strength of a hurricane is generally classified based on its wind speed, the unprecedented rainfall-driven flooding experienced in southeastern Texas during Hurricane Harvey clearly highlights the need for better understanding of the hazards associated with extreme rainfall from hurricanes and other tropical systems. In this study, we seek to develop a framework for describing the joint probabilistic and spatio-temporal properties of extreme rainfall from hurricanes and other tropical systems. Furthermore, we argue that commonly-used terminology - such as the "500-year storm" - fail to convey the true properties of tropical cyclone rainfall occurrences in the United States. To quantify the magnitude and spatial extent of these storms, a database consisting of hundreds of unique rainfall volumetric shapes (or "voxels") was created. Each voxel is a four-dimensional object, created by connecting, in both space and time, gridded rainfall observations from the daily, gauge-based NOAA CPC-Unified precipitation dataset. Individual voxels were then associated with concurrent tropical cyclone tracks from NOAA's HURDAT-2 archive, to create distinct representations of the rainfall associated with every Atlantic tropical system making landfall over (or passing near) the United States since 1948. Using these voxels, a series of threshold-excess extreme value models were created to estimate the recurrence intervals of extreme tropical cyclone rainfall, both nationally and locally, for single and multi-day timescales. This voxel database also allows for the "indexing" of past events, placing recent extremes - such as the 50+ inches of rain observed during Hurricane Harvey - into a national context and emphasizing how rainfall totals that are rare at the point scale may be more frequent from a regional perspective.

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

PubMed

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

2007-08-01

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

Global intensification in observed short-duration rainfall extremes

NASA Astrophysics Data System (ADS)

Fowler, H. J.; Lewis, E.; Guerreiro, S.; Blenkinsop, S.; Barbero, R.; Westra, S.; Lenderink, G.; Li, X.

2017-12-01

Extreme rainfall events are expected to intensify with a warming climate and this is currently driving extensive research. While daily rainfall extremes are widely thought to have increased globally in recent decades, changes in rainfall extremes on shorter timescales, often associated with flash flooding, have not been documented at global scale due to surface observational limitations and the lack of a global sub-daily rainfall database. The access to and use of such data remains a challenge. For the first time, we have synthesized across multiple data sources providing gauge-based sub-daily rainfall observations across the globe over the last 6 decades. This forms part of the INTENSE project (part of the World Climate Research Programme (WCRP)'s Grand Challenge on 'Understanding and Predicting Weather and Climate Extremes' and the Global Water and Energy Exchanges (GEWEX) Hydroclimate Project cross-cut on sub-daily rainfall). A set of global hydroclimatic indices have been produced based upon stakeholder recommendations including indices that describe maximum rainfall totals and timing, the intensity, duration and frequency of storms, frequency of storms above specific thresholds and information about the diurnal cycle. This will provide a unique global data resource on sub-daily precipitation whose derived indices will be freely available to the wider scientific community. Because of the physical connection between global warming and the moisture budget, we also sought to infer long-term changes in sub-daily rainfall extremes contingent on global mean temperature. Whereas the potential influence of global warming is uncertain at regional scales, where natural variability dominates, aggregating surface stations across parts of the world may increase the global warming-induced signal. Changes in terms of annual maximum rainfall across various resolutions ranging from 1-h to 24-h are presented and discussed.

Program control on the Tropical Rainfall Measuring Mission

NASA Technical Reports Server (NTRS)

Pennington, Dorothy J.; Majerowicw, Walter

1994-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Incident rainfall in Rome and its relation to biodeterioration of buildings

NASA Astrophysics Data System (ADS)

Caneva, G.; Gori, E.; Danin, A.

Intensity and distribution of incident rainfall in Rome, and degree of lithobiont cover of building walls, were estimated, and their correlation was discussed. Rainfall and wind data over 10 years for the Rome Meteorological Observatory of Torre Calandrelli (UCEA) were used to calculate the actual hydrocontribution received over walls at various exposures. The biological colonization by lithobionts was evaluated on a sample of 14 buildings in various places of the city, using a phytosociological scale for quantifying their total cover. During all seasons the rainfall shows a significant peak in the south and the southeast exposures, where the highest cover of lithobionts is found. These results show the role of incident rainfall in the climatic conditions of Rome as the main driving factor for the growth of lithobionts on walls where rainfall is their principal source of water.

Is the interspecific variation of body size of land snails correlated with rainfall in Israel and Palestine?

NASA Astrophysics Data System (ADS)

Hausdorf, Bernhard

2006-11-01

The hypothesis that body size of land snail species increases with aridity in Israel and Palestine because large snails lose relatively less water due to their lower surface to volume ratio has been investigated. Data on rainfall amplitudes of 84 land snail species in Israel and Palestine and on their body sizes were used to test for interspecific correlations between body size and rainfall. Four methods, means of body sizes in rainfall categories, the midpoint method, the across-species method, and a phylogenetically controlled analysis (CAIC) showed that there is no significant correlation between body size of land snail species and their rainfall amplitude in Israel and Palestine. The lack of an interspecific correlation between body size and rainfall amplitude may be the result of conflicting selective forces on body size.

Tree ring reconstructed rainfall over the southern Amazon Basin

NASA Astrophysics Data System (ADS)

Lopez, Lidio; Stahle, David; Villalba, Ricardo; Torbenson, Max; Feng, Song; Cook, Edward

2017-07-01

Moisture sensitive tree ring chronologies of Centrolobium microchaete have been developed from seasonally dry forests in the southern Amazon Basin and used to reconstruct wet season rainfall totals from 1799 to 2012, adding over 150 years of rainfall estimates to the short instrumental record for the region. The reconstruction is correlated with the same atmospheric variables that influence the instrumental measurements of wet season rainfall. Anticyclonic circulation over midlatitude South America promotes equatorward surges of cold and relatively dry extratropical air that converge with warm moist air to form deep convection and heavy rainfall over this sector of the southern Amazon Basin. Interesting droughts and pluvials are reconstructed during the preinstrumental nineteenth and early twentieth centuries, but the tree ring reconstruction suggests that the strong multidecadal variability in instrumental and reconstructed wet season rainfall after 1950 may have been unmatched since 1799.

Characterizing multiscale variability of zero intermittency in spatial rainfall

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1994-01-01

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

Indian Monsoon Depression: Climatology and Variability

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

Yoon, Jin-Ho; Huang, Wan-Ru

The monsoon climate is traditionally characterized by large seasonal rainfall and reversal of wind direction (e.g., Krishnamurti 1979). Most importantly this rainfall is the major source of fresh water to various human activities such as agriculture. The Indian subcontinent resides at the core of the Southeast Asian summer monsoon system, with the monsoon trough extended from northern India across Indochina to the Western Tropical Pacific (WTP). Large fraction of annual rainfall occurs during the summer monsoon season, i.e., June - August with two distinct maxima. One is located over the Bay of Bengal with rainfall extending northwestward into eastern andmore » central India, and the other along the west coast of India where the lower level moist wind meets the Western Ghat Mountains (Saha and Bavardeckar 1976). The rest of the Indian subcontinent receives relatively less rainfall. Various weather systems such as tropical cyclones and weak disturbances contribute to monsoon rainfall (Ramage 1971). Among these systems, the most efficient rain-producing system is known as the Indian monsoon depression (hereafter MD). This MD is critical for monsoon rainfall because: (i) it occurs about six times during each summer monsoon season, (ii) it propagates deeply into the continent and produces large amounts of rainfall along its track, and (iii) about half of the monsoon rainfall is contributed to by the MDs (e.g., Krishnamurti 1979). Therefore, understanding various properties of the MD is a key towards comprehending the veracity of the Indian summer monsoon and especially its hydrological process.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A study of 2014 record drought in India with CFSv2 model: role of water vapor transport

NASA Astrophysics Data System (ADS)

Ramakrishna, S. S. V. S.; Brahmananda Rao, V.; Srinivasa Rao, B. R.; Hari Prasad, D.; Nanaji Rao, N.; Panda, Roshmitha

2017-07-01

The Indian summer monsoon season of 2014 was erratic and ended up with a seasonal rainfall deficit of 12 % and a record drought in June. In this study we analyze the moisture transport characteristics for the monsoon season of 2014 using both NCEP FNL reanalysis (FNL) and CFSv2 (CFS) model data. In FNL, in June 2014 there was a large area of divergence of moisture flux. In other months also there was lesser flux. This probably is the cause of 2014 drought. The CFS model overestimated the drought and it reproduces poorly the observed rainfall over central India (65E-95E; 5N-35N). The correlation coefficient (CC) between the IMD observed rainfall and CFS model rainfall is only 0.1 while the CC between rainfall and moisture flux convergence in CFS model is only 0.20 and with FNL data -0.78. This clearly shows that the CFS model has serious difficulty in reproducing the moisture flux convergence and rainfall. We found that the rainfall variations are strongly related to the moisture convergence or divergence. The hypothesis of Krishnamurti et al. (J Atmos Sci 67:3423-3441, 2010) namely the intrusion of west African desert air and the associated low convective available potential energy inhibiting convection and rainfall shows some promise to explain dry spells in Indian summer monsoon. However, the rainfall or lack of it is mainly explained by convergence or divergence of moisture flux.

Short-term effects of rainfall on CO2 fluxes above rangelands dominated by Artemisia, Bromus tectorum, and Agropyron

NASA Astrophysics Data System (ADS)

Ivans, S.; Saliendra, N. Z.; Johnson, D. A.

2003-04-01

The short-term effects of rainfall on carbon dioxide (CO_2) fluxes have not been well documented in rangelands of the Intermountain Region of the western USA. We used the Bowen ratio-energy balance technique to continuously measure CO_2 fluxes above three rangeland sites in Idaho and Utah dominated by: 1) Artemisia (sagebrush) near Malta, Idaho; 2) Bromus tectorum (cheatgrass) near Malta, Idaho; and 3) Agropyron (crested wheatgrass) in Rush Valley, Utah. We examined CO_2 fluxes immediately before and after rainfall during periods of 10--19 July 2001 (Summer), 8--17 October 2001 (Autumn), and 16--30 May 2002 (Spring). On sunny days before rainfall during Spring, all three sites were sinks for CO_2. After rainfall in Spring, all three sites became sources of CO_2 for about two days and after that became CO_2 sinks again. During Summer and Autumn when water was limiting, sites were small sources of CO_2 and became larger sources for one day after rainfall. In all three seasons, daytime CO_2 fluxes decreased and nighttime CO_2 fluxes increased after rainfall, suggesting that rainfall stimulated belowground respiration at all three sites. Results from this study indicated that CO_2 fluxes above rangeland sites in the Intermountain West changed markedly after rainfall, especially during Spring when fluxes were highest. KEY WORDS: Bowen ratio-energy balance, Intermountain West, rangelands, sagebrush, cheatgrass, crested wheatgrass

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Spatial dependence of extreme rainfall

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2008-05-01

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

Effects of episodic rainfall on a subterranean estuary

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data

NASA Astrophysics Data System (ADS)

Leonarduzzi, Elena; Molnar, Peter; McArdell, Brian W.

2017-08-01

A high-resolution gridded daily precipitation data set was combined with a landslide inventory containing over 2000 events in the period 1972-2012 to analyze rainfall thresholds which lead to landsliding in Switzerland. We colocated triggering rainfall to landslides, developed distributions of triggering and nontriggering rainfall event properties, and determined rainfall thresholds and intensity-duration ID curves and validated their performance. The best predictive performance was obtained by the intensity-duration ID threshold curve, followed by peak daily intensity Imax and mean event intensity Imean. Event duration by itself had very low predictive power. A single country-wide threshold of Imax = 28 mm/d was extended into space by regionalization based on surface erodibility and local climate (mean daily precipitation). It was found that wetter local climate and lower erodibility led to significantly higher rainfall thresholds required to trigger landslides. However, we showed that the improvement in model performance due to regionalization was marginal and much lower than what can be achieved by having a high-quality landslide database. Reference cases in which the landslide locations and timing were randomized and the landslide sample size was reduced showed the sensitivity of the Imax rainfall threshold model. Jack-knife and cross-validation experiments demonstrated that the model was robust. The results reported here highlight the potential of using rainfall ID threshold curves and rainfall threshold values for predicting the occurrence of landslides on a country or regional scale with possible applications in landslide warning systems, even with daily data.

Impact of Synoptic-Scale Factors on Rainfall Forecast in Different Stages of a Persistent Heavy Rainfall Event in South China

NASA Astrophysics Data System (ADS)

Zhang, Murong; Meng, Zhiyong

2018-04-01

This study investigates the stage-dependent rainfall forecast skills and the associated synoptic-scale features in a persistent heavy rainfall event in south China, Guangdong Province, during 29-31 March 2014, using operational global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts. This persistent rainfall was divided into two stages with a better precipitation forecast skill in Stage 2 (S2) than Stage 1 (S1) although S2 had a longer lead time. Using ensemble-based sensitivity analysis, key synoptic-scale factors that affected the rainfall were diagnosed by correlating the accumulated precipitation of each stage to atmospheric state variables in the middle of respective stage. The precipitation in both stages was found to be significantly correlated with midlevel trough, low-level vortex, and particularly the low-level jet on the southeast flank of the vortex and its associated moisture transport. The rainfall forecast skill was mainly determined by the forecast accuracy in the location of the low-level jet, which was possibly related to the different juxtapositions between the direction of the movement of the low-level vortex and the orientation of the low-level jet. The uncertainty in rainfall forecast in S1 was mainly from the location uncertainty of the low-level jet, while the uncertainty in rainfall forecast in S2 was mainly from the width uncertainty of the low-level jet with the relatively accurate location of the low-level jet.

Rainfall Chemistry and Potential Beneficial/Detrimental Impact to Indigenous Vegetation.

DTIC Science & Technology

1983-08-23

AD-A138 471 RAINFALL CHEMISTRY AND POTENTIAL BENEFIC IAL/DETRIMENTAL 1/ S NABARRR RFRA BEWNEIMPACT TO INDIGEN .. (U) VIRGINIA POLYTECHN C INST AND...ReportRainfall Chemistry and Potential Beneficial/21/ 2/ZA0,Detrimental Impact to Indigenous Vegetation .. PERFORMING Ono. REPORT NUMMER A4JTHOR(sJ 6...pollution sensitivity of coniferous species which grow near RAAP. $1 RAINFALL CHEMISTRY AND POTENTIAL BENEFICIAL/DETRIMENTAL IMPACT TO INDIGENOUS

Rain-fed fig yield as affected by rainfall distribution

NASA Astrophysics Data System (ADS)

Bagheri, Ensieh; Sepaskhah, Ali Reza

2014-08-01

Variable annual rainfall and its uneven distribution are the major uncontrolled inputs in rain-fed fig production and possibly the main cause of yield fluctuation in Istahban region of Fars Province, I.R. of Iran. This introduces a considerable risk in rain-fed fig production. The objective of this study was to find relationships between seasonal rainfall distribution and rain-fed fig production in Istahban region to determine the critical rainfall periods for rain-fed fig production and supplementary irrigation water application. Further, economic analysis for rain-fed fig production was considered in this region to control the risk of production. It is concluded that the monthly, seasonal and annual rainfall indices are able to show the effects of rainfall and its distribution on the rain-fed fig yield. Fig yield with frequent occurrence of 80 % is 374 kg ha-1. The internal rates of return for interest rate of 4, 8 and 12 % are 21, 58 and 146 %, respectively, that are economically feasible. It is concluded that the rainfall in spring especially in April and in December has negatively affected fig yield due to its interference with the life cycle of Blastophaga bees for pollination. Further, it is concluded that when the rainfall is limited, supplementary irrigation can be scheduled in March.

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

NASA Technical Reports Server (NTRS)

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

1999-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

A New Look at Rainfall Fluctuations and Scaling Properties of Spatial Rainfall Using Orthogonal Wavelets.

NASA Astrophysics Data System (ADS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1993-02-01

It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.

2002-01-01

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

Summer Leeside Rainfall Maxima over the Island of Hawaii

NASA Astrophysics Data System (ADS)

Huang, Y. F.; Chen, Y. L.

2016-12-01

The Kona area on the leeside in the island of Hawaii has distinctive summer rainfall maxima. The primary physical processes for the summer rainfall maxima in Kona are analyzed by comparing it with the winter rainfall. The annual and diurnal cycles there are investigated by employing the Fifth-generation Pennsylvania State University-NCAR Mesoscale Model coupled with the advanced land surface model from June 2004 and February 2010. During the summer, the nocturnal rainfall maximum adjacent to the Kona coast is larger than in winter because of the stronger, moister westerly reversed flow and offshore flow in summer. Comparisons between winter trade-wind days and winter mean show that the leeside Kona rainfall offshore in winter mainly occurs under trade-wind conditions. Moreover, the model results also attest to the impact of moisture content on the Kona leeside rainfall offshore. Comparisons between winter and summer trade-wind days indicate that upslope flows on the Kona slopes are stronger and the moisture content from the westerly reversed flow is higher in summer than in winter. The rainfall maximum on the lower Kona slopes is more pronounced in summer than in winter as a result of enhanced orographic lifting due to stronger upslope flow in the afternoon hours and the moister westerly reversed flow offshore, which merges with the upslope flow inland.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Statistical downscaling modeling with quantile regression using lasso to estimate extreme rainfall

NASA Astrophysics Data System (ADS)

Santri, Dewi; Wigena, Aji Hamim; Djuraidah, Anik

2016-02-01

Rainfall is one of the climatic elements with high diversity and has many negative impacts especially extreme rainfall. Therefore, there are several methods that required to minimize the damage that may occur. So far, Global circulation models (GCM) are the best method to forecast global climate changes include extreme rainfall. Statistical downscaling (SD) is a technique to develop the relationship between GCM output as a global-scale independent variables and rainfall as a local- scale response variable. Using GCM method will have many difficulties when assessed against observations because GCM has high dimension and multicollinearity between the variables. The common method that used to handle this problem is principal components analysis (PCA) and partial least squares regression. The new method that can be used is lasso. Lasso has advantages in simultaneuosly controlling the variance of the fitted coefficients and performing automatic variable selection. Quantile regression is a method that can be used to detect extreme rainfall in dry and wet extreme. Objective of this study is modeling SD using quantile regression with lasso to predict extreme rainfall in Indramayu. The results showed that the estimation of extreme rainfall (extreme wet in January, February and December) in Indramayu could be predicted properly by the model at quantile 90th.

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

PubMed

Komen, Kibii

2017-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Determining the precipitable water vapor thresholds under different rainfall strengths in Taiwan

NASA Astrophysics Data System (ADS)

Yeh, Ta-Kang; Shih, Hsuan-Chang; Wang, Chuan-Sheng; Choy, Suelynn; Chen, Chieh-Hung; Hong, Jing-Shan

2018-02-01

Precipitable Water Vapor (PWV) plays an important role for weather forecasting. It is helpful in evaluating the changes of the weather system via observing the distribution of water vapor. The ability of calculating PWV from Global Positioning System (GPS) signals is useful to understand the special weather phenomenon. In this study, 95 ground-based GPS and rainfall stations in Taiwan were utilized from 2006 to 2012 to analyze the relationship between PWV and rainfall. The PWV data were classified into four classes (no, light, moderate and heavy rainfall), and the vertical gradients of the PWV were obtained and the variations of the PWV were analyzed. The results indicated that as the GPS elevation increased every 100 m, the PWV values decreased by 9.5 mm, 11.0 mm, 12.2 mm and 12.3 mm during the no, light, moderate and heavy rainfall conditions, respectively. After applying correction using the vertical gradients mentioned above, the average PWV thresholds were 41.8 mm, 52.9 mm, 62.5 mm and 64.4 mm under the no, light, moderate and heavy rainfall conditions, respectively. This study offers another type of empirical threshold to assist the rainfall prediction and can be used to distinguish the rainfall features between different areas in Taiwan.

The local and global climate forcings induced inhomogeneity of Indian rainfall.

PubMed

Nair, P J; Chakraborty, A; Varikoden, H; Francis, P A; Kuttippurath, J

2018-04-16

India is home for more than a billion people and its economy is largely based on agrarian society. Therefore, rainfall received not only decides its livelihood, but also influences its water security and economy. This situation warrants continuous surveillance and analysis of Indian rainfall. These kinds of studies would also help forecasters to better tune their models for accurate weather prediction. Here, we introduce a new method for estimating variability and trends in rainfall over different climate regions of India. The method based on multiple linear regression helps to assess contributions of different remote and local climate forcings to seasonal and regional inhomogeneity in rainfall. We show that the Indian Summer Monsoon Rainfall (ISMR) variability is governed by Eastern and Central Pacific El Niño Southern Oscillation, equatorial zonal winds, Atlantic zonal mode and surface temperatures of the Arabian Sea and Bay of Bengal, and the North East Monsoon Rainfall variability is controlled by the sea surface temperature of the North Atlantic and extratropial oceans. Also, our analyses reveal significant positive trends (0.43 mm/day/dec) in the North West for ISMR in the 1979-2017 period. This study cautions against the significant changes in Indian rainfall in a perspective of global climate change.

A new look at rainfall fluctuations and scaling properties of spatial rainfall using orthogonal wavelets

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1993-01-01

It has been observed that the finite-dimensional distribution functions of rainfall cannot obey simple scaling laws due to rainfall intermittency (mixed distribution with an atom at zero) and the probability of rainfall being an increasing function of area. Although rainfall fluctuations do not suffer these limitations, it is interesting to note that very few attempts have been made to study them in terms of their self-similarity characteristics. This is due to the lack of unambiguous definition of fluctuations in multidimensions. This paper shows that wavelet transforms offer a convenient and consistent method for the decomposition of inhomogeneous and anisotropic rainfall fields in two dimensions and that the components of this decomposition can be looked at as fluctuations of the rainfall field. It is also shown that under some mild assumptions, the component fields can be treated as homogeneous and thus are amenable to second-order analysis, which can provide useful insight into the nature of the process. The fact that wavelet transforms are a space-scale method also provides a convenient tool to study scaling characteristics of the process. Orthogonal wavelets are used, and these properties are investigated for a squall-line storm to study the presence of self-similarity.

Evaluation of high resolution global satellite precipitation products using daily raingauge data over the Upper Blue Nile Basin

NASA Astrophysics Data System (ADS)

Sahlu, Dejene; Moges, Semu; Anagnostou, Emmanouil; Nikolopoulos, Efthymios; Hailu, Dereje; Mei, Yiwen

2017-04-01

Water resources assessment, planning and management in Africa is often constrained by the lack of reliable spatio-temporal rainfall data. Satellite products are steadily growing and offering useful alternative datasets of rainfall globally. The aim of this paper is to examine the error characteristics of the main available global satellite precipitation products with the view of improving the reliability of wet season (June to September) and small rainy season rainfall datasets over the Upper Blue Nile Basin. The study utilized six satellite derived precipitation datasets at 0.25-deg spatial grid size and daily temporal resolution:1) the near real-time (3B42_RT) and gauge adjusted (3B42_V7) products of Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), 2) gauge adjusted and unadjusted Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) products and 3) the gauge adjusted and un-adjusted product of the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center Morphing technique (CMORPH) over the period of 2000 to 2013.The error analysis utilized statistical techniques using bias ratio (Bias), correlation coefficient (CC) and root-mean-square-error (RMSE). Mean relative error (MRE), CC and RMSE metrics are further examined for six categories of 10th, 25th, 50th, 75th, 90thand 95th percentile rainfall thresholds. The skill of the satellite estimates is evaluated using categorical error metrics of missed rainfall volume fraction (MRV), falsely detected rainfall volume fraction (FRV), probability of detection (POD) and False Alarm Ratio (FAR). Results showed that six satellite based rainfall products underestimated wet season (June to September) gauge precipitation, with the exception of non-adjusted PERSIANN that overestimated the initial part of the rainy season (March to May). During the wet season, adjusted CMORPH has relatively better bias ratio (89 %) followed by 3B42_V7 (88%), adjusted-PERSIANN (81%), and non-adjusted products have relatively lower bias ratio. The results from CC statistic range from 0.34 to 0.43 for the wet season with adjusted products having slightly higher values. The initial rainy season has relatively higher CC than the wet season. Results from the categorical error metrics showed that CMORPH products have higher POD (91%), which are better in avoiding detecting false rainfall events in the wet season. For the initial rainy season PERSIANN (<50%), TMPA and CMORPH products are nearly equivalent (63-67%). On the other hand, FAR is below 0.1% for all products while in the wet season is higher (10-25%). In terms of rainfall volume of missed and false detected rainfall, CMORPH exhibited lower MRV ( 4.5%) than the TMPA and PERSIANN products (11-19%.) in the wet season. MRV for the initial rainy season was 20% for TMPA and CMORPH products and above 30% for PERSIANN products. All products are nearly equivalent in the wet season in terms of FRV (< 0.2%). The magnitude of MRE increases with gauge rainfall threshold categories with 3B42-V7 and adjusted CMORPH having lower magnitude, showing that underestimation of rainfall increases with increasing rainfall magnitude. CC also decreases with gauge rainfall threshold categories with CMORPH products having slightly higher values. Overall, all satellite products underestimated (overestimated) lower (higher) quantiles quantiles. We have observed that among the six satellite rainfall products the adjusted CMORPH has relatively better potential to improve wet season rainfall estimate and 3B42-V7 that initial rainy season in the Upper Blue Nile Basin.

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

PubMed

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

2016-02-01

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

Rainfall-ground movement modelling for natural gas pipelines through landslide terrain

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

O`Neil, G.D.; Simmonds, G.R.; Grivas, D.A.

1996-12-31

Perhaps the greatest challenge to geotechnical engineers is to maintain the integrity of pipelines at river crossings where landslide terrain dominates the approach slopes. The current design process at NOVA Gas Transmission Ltd. (NGTL) has developed to the point where this impact can be reasonably estimated using in-house models of pipeline-soil interaction. To date, there has been no method to estimate ground movements within unexplored slopes at the outset of the design process. To address this problem, rainfall and slope instrumentation data have been processed to derive rainfall-ground movement relationships. Early results indicate that the ground movements exhibit two components:more » a steady, small rate of movement independent of the rainfall, and, increased rates over short periods of time following heavy amounts of rainfall. Evidence exists of a definite threshold value of rainfall which has to be exceeded before any incremental movement is induced. Additional evidence indicates a one-month lag between rainfall and ground movement. While these models are in the preliminary stage, results indicate a potential to estimate ground movements for both initial design and planned maintenance actions.« less

Global Warming Induced Changes in Rainfall Characteristics in IPCC AR5 Models

NASA Technical Reports Server (NTRS)

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

2012-01-01

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