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).

How temporal patterns in rainfall determine the geomorphology and carbon fluxes of tropical peatlands.

PubMed

Cobb, Alexander R; Hoyt, Alison M; Gandois, Laure; Eri, Jangarun; Dommain, René; Abu Salim, Kamariah; Kai, Fuu Ming; Haji Su'ut, Nur Salihah; Harvey, Charles F

2017-06-27

Tropical peatlands now emit hundreds of megatons of carbon dioxide per year because of human disruption of the feedbacks that link peat accumulation and groundwater hydrology. However, no quantitative theory has existed for how patterns of carbon storage and release accompanying growth and subsidence of tropical peatlands are affected by climate and disturbance. Using comprehensive data from a pristine peatland in Brunei Darussalam, we show how rainfall and groundwater flow determine a shape parameter (the Laplacian of the peat surface elevation) that specifies, under a given rainfall regime, the ultimate, stable morphology, and hence carbon storage, of a tropical peatland within a network of rivers or canals. We find that peatlands reach their ultimate shape first at the edges of peat domes where they are bounded by rivers, so that the rate of carbon uptake accompanying their growth is proportional to the area of the still-growing dome interior. We use this model to study how tropical peatland carbon storage and fluxes are controlled by changes in climate, sea level, and drainage networks. We find that fluctuations in net precipitation on timescales from hours to years can reduce long-term peat accumulation. Our mathematical and numerical models can be used to predict long-term effects of changes in temporal rainfall patterns and drainage networks on tropical peatland geomorphology and carbon storage.

How temporal patterns in rainfall determine the geomorphology and carbon fluxes of tropical peatlands

PubMed Central

Hoyt, Alison M.; Gandois, Laure; Eri, Jangarun; Dommain, René; Abu Salim, Kamariah; Kai, Fuu Ming; Haji Su’ut, Nur Salihah; Harvey, Charles F.

2017-01-01

Tropical peatlands now emit hundreds of megatons of carbon dioxide per year because of human disruption of the feedbacks that link peat accumulation and groundwater hydrology. However, no quantitative theory has existed for how patterns of carbon storage and release accompanying growth and subsidence of tropical peatlands are affected by climate and disturbance. Using comprehensive data from a pristine peatland in Brunei Darussalam, we show how rainfall and groundwater flow determine a shape parameter (the Laplacian of the peat surface elevation) that specifies, under a given rainfall regime, the ultimate, stable morphology, and hence carbon storage, of a tropical peatland within a network of rivers or canals. We find that peatlands reach their ultimate shape first at the edges of peat domes where they are bounded by rivers, so that the rate of carbon uptake accompanying their growth is proportional to the area of the still-growing dome interior. We use this model to study how tropical peatland carbon storage and fluxes are controlled by changes in climate, sea level, and drainage networks. We find that fluctuations in net precipitation on timescales from hours to years can reduce long-term peat accumulation. Our mathematical and numerical models can be used to predict long-term effects of changes in temporal rainfall patterns and drainage networks on tropical peatland geomorphology and carbon storage. PMID:28607068

Interdecadal change of the controlling mechanisms for East Asian early summer rainfall variation around the mid-1990s

NASA Astrophysics Data System (ADS)

Yim, So-Young; Wang, Bin; Kwon, MinHo

2014-03-01

East Asian (EA) summer monsoon shows considerable differences in the mean state and principal modes of interannual variation between early summer (May-June, MJ) and late summer (July-August, JA). The present study focuses on the early summer (MJ) precipitation variability. We find that the interannual variation of the MJ precipitation and the processes controlling the variation have been changed abruptly around the mid-1990s. The rainfall anomaly represented by the leading empirical orthogonal function has changed from a dipole-like pattern in pre-95 epoch (1979-1994) to a tripole-like pattern in post-95 epoch (1995-2010); the prevailing period of the corresponding principal component has also changed from 3-5 to 2-3 years. These changes are concurrent with the changes of the corresponding El Nino-Southern Oscillation (ENSO) evolutions. During the pre-95 epoch, the MJ EA rainfall anomaly is coupled to a slow decay of canonical ENSO events signified by an eastern Pacific warming, which induces a dipole rainfall feature over EA. On the other hand, during the post-95 epoch the anomalous MJ EA rainfall is significantly linked to a rapid decay of a central Pacific warming and a distinct tripolar sea surface temperature (SST) in North Atlantic. The central Pacific warming-induced Philippine Sea anticyclone induces an increased rainfall in southern China and decreased rainfall in central eastern China. The North Atlantic Oscillation-related tripolar North Atlantic SST anomaly induces a wave train that is responsible for the increase northern EA rainfall. Those two impacts form the tripole-like rainfall pattern over EA. Understanding such changes is important for improving seasonal to decadal predictions and long-term climate change in EA.

Short-term climate change and the extinction of the snail Rhachistia aldabrae (Gastropoda: Pulmonata).

PubMed

Gerlach, Justin

2007-10-22

The only known population of the Aldabra banded snail Rhachistia aldabrae declined through the late twentieth century, leading to its extinction in the late 1990s. This occurred within a stable habitat and its extinction is attributable to decreasing rainfall on Aldabra atoll, associated with regional changes in rainfall patterns in the late twentieth and early twenty-first century. It is proposed that the extinction of this species is a direct result of decreasing rainfall leading to increased mortality of juvenile snails.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

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

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

The long-term variability of Changma in the East Asian summer monsoon system: A review and revisit

NASA Astrophysics Data System (ADS)

Lee, June-Yi; Kwon, MinHo; Yun, Kyung-Sook; Min, Seung-Ki; Park, In-Hong; Ham, Yoo-Geun; Jin, Emilia Kyung; Kim, Joo-Hong; Seo, Kyong-Hwan; Kim, WonMoo; Yim, So-Young; Yoon, Jin-Ho

2017-05-01

Changma, which is a vital part of East Asian summer monsoon (EASM) system, plays a critical role in modulating water and energy cycles in Korea. Better understanding of its long-term variability and change is therefore a matter of scientific and societal importance. It has been indicated that characteristics of Changma have undergone significant interdecadal changes in association with the mid-1970s global-scale climate shift and the mid-1990s EASM shift. This paper reviews and revisits the characteristics on the long-term changes of Changma focusing on the underlying mechanisms for the changes. The four important features are manifested mainly during the last few decades: 1) mean and extreme rainfalls during Changma period from June to September have been increased with the amplification of diurnal cycle of rainfall, 2) the dry spell between the first and second rainy periods has become shorter, 3) the rainfall amount as well as the number of rainy days during August have significantly increased, probably due to the increase in typhoon landfalls, and 4) the relationship between the Changma rainfall and Western Pacific Subtropical High on interannual time scale has been enhanced. The typhoon contribution to the increase in heavy rainfall is attributable to enhanced interaction between typhoons and midlatitude baroclinic environment. It is noted that the change in the relationship between Changma and the tropical sea surface temperature (SST) over the Indian, Pacific, and Atlantic Oceans is a key factor in the long-term changes of Changma and EASM. Possible sources for the recent mid-1990s change include 1) the tropical dipole-like SST pattern between the central Pacific and Indo-Pacific region (the global warming hiatus pattern), 2) the recent intensification of tropical SST gradients among the Indian Ocean, the western Pacific, and the eastern Pacific, and 3) the tropical Atlantic SST warming.

Discovering temporal patterns in water quality time series, focusing on floods with the LDA method

NASA Astrophysics Data System (ADS)

Hélène Aubert, Alice; Tavenard, Romain; Emonet, Rémi; Malinowski, Simon; Guyet, Thomas; Quiniou, René; Odobez, Jean-Marc; Gascuel-Odoux, Chantal

2013-04-01

Studying floods has been a major issue in hydrological research for years. It is often done in terms of water quantity but it is also of interest in terms of water quality. Stream chemistry is a mix of solutes. They originate from various sources in the catchment, reach the stream by various flow pathways and are transformed by biogeochemical reactions at different locations. Therefore, we hypothesized that reaction of the stream chemistry to a rainfall event is not unique but varies according to the season (1), and the global meteorological conditions of the year (2). Identifying a typology of temporal chemical patterns of reaction to a rainfall event is a way to better understand catchment processes at the flood time scale. To answer this issue, we applied a probabilistic model (Latent Dirichlet Allocation or LDA (3)) mining recurrent sequential patterns to a dataset of floods. The dataset is 12 years long and daily recorded. It gathers a broad range of parameters from which we selected rainfall, discharge, water table depth, temperature as well as nitrate, dissolved organic carbon, sulphate and chloride concentrations. It comes from a long-term hydrological observatory (AgrHys, western France) located at Kervidy-Naizin. A set of 472 floods was automatically extracted (4). From each flood, a document has been generated that is made of a set of "hydrological words". Each hydrological word corresponds to a measurement: it is a triplet made of the considered variable, the time at which the measurement is made (relative to the beginning of the flood), and its magnitude (that can be low, medium or high). The documents are used as input data to the LDA algorithm. LDA relies on spotting co-occurrences (as an alternative to the more traditional study of correlation) between words that appear within the flood documents. It has two nice properties that are its ability to easily deal with missing data and its additive property that allows a document to be seen as a mixture of several flood patterns. The output of LDA is a set of patterns that can easily be represented in graphics. These patterns correspond to typical reactions to rainfall events. The patterns themselves are carefully studied, as well as their repartition along the year and along the 12 years of the dataset. The novelties are fourfold. First, as a methodological point of view, we learn that hydrological data can be analyzed with this LDA model giving a typology of a multivariate chemical signature of floods. Second, we outline that chemistry parameters are sufficient to obtain meaningful patterns. There is no need to include hydro-meteorological parameters to define the patterns. However, hydro-meteorological parameters are useful to understand the processes leading to these patterns. Third, our hypothesis of seasonal specific reaction to rainfall is verified, moreover detailed; so is our hypothesis of different reactions to rainfall for years with different hydro-meteorological conditions. Fourth, this method allows the consideration of overlapping floods that are usually not studied. We would recommend the use of such model to study chemical reactions of stream after rainfall events, or more broadly after any hydrological events. The typology that has been provided by this method is a kind of bar code of water chemistry during floods. It could be well suited to compare different geographical locations by using the same patterns and analysing the resulting different pattern distributions. (1) Aubert, A.H. et al., 2012. The chemical signature of a livestock farming catchment: synthesis from a high-frequency multi-element long term monitoring. HESSD, 9(8): 9715 - 9741. (2) Aubert, A.H., Gascuel-Odoux, C., Merot, P., 2013. Annual hysteresis of water quality: A method to analyse the effect of intra- and inter-annual climatic conditions. Journal of Hydrology, 478(0): 29-39. (3) Blei, D. M.; Ng, A. Y.; Jordan, M. I., 2003. Latent Dirichlet allocation. Journal of Machine Learning Research, 3(4-5): 993-1022. (4) de Lavenne, A., Cudennec, C., Streamflow velocity estimation in GIUH-type approach: what can neighbouring basins tell us? Poster Presentation - EGU General Assembly, 22-27 April 2012, Vienna, Austria.

Simulation of precipitation by weather pattern and frontal analysis

NASA Astrophysics Data System (ADS)

Wilby, Robert

1995-12-01

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

Climate change and the impact of increased rainfall variability on sediment transport and catchment scale water quality

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Willgoose, G. R.; Cohen, S.

2009-12-01

Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.

Responses of the sustainable yield of groundwater to annual rainfall and pumping patterns in the Baotou Plain, North China

NASA Astrophysics Data System (ADS)

Liao, Z.; LONG, Y., Sr.; Wei, Y.; Guo, Z.

2017-12-01

Serious water deficits and deteriorating environmental quality are threatening the sustainable socio-economic development and the protection of the ecology and the environment in North China, especially in Baotou City. There is a common misconception that groundwater extraction can be sustainable if the pumping rate does not exceed the total natural recharge in a groundwater basin. The truth is that the natural recharge is mainly affected by the rainfall and that groundwater withdrawal determines the sustainable yield of the aquifer flow system. The concept of the sustainable yield is defined as the allowance pumping patterns and rates that avoid adverse impacts on the groundwater system. The sustainable yield introduced in this paper is a useful baseline for groundwater management under all rainfall conditions and given pumping scenarios. A dynamic alternative to the groundwater sustainable yield for a given pumping pattern and rate should consider the responses of the recharge, discharge, and evapotranspiration to the groundwater level fluctuation and to different natural rainfall conditions. In this study, methods for determining the sustainable yield through time series data of groundwater recharge, discharge, extraction, and precipitation in an aquifer are introduced. A numerical simulation tool was used to assess and quantify the dynamic changes in groundwater recharge and discharge under excessive pumping patterns and rates and to estimate the sustainable yield of groundwater flow based on natural rainfall conditions and specific groundwater development scenarios during the period of 2007 to 2014. The results of this study indicate that the multi-year sustainable yield only accounts for about one-half of the average annual recharge. The future sustainable yield for the current pumping scenarios affected by rainfall conditions are evaluated quantitatively to obtain long-term groundwater development strategies. The simulation results show that sufficient rainfall supports excessive pumping patterns, causing a slow and disproportionate groundwater storage recovery and water level rise. In addition, the decrease in the recharge and the increase in the discharge were found to have a notable effect on the dynamic annual sustainable yield, especially in a drought year.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

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.

Rain Check Application: Mobile tool to monitor rainfall in remote parts of Haiti

NASA Astrophysics Data System (ADS)

Huang, X.; Baird, J.; Chiu, M. T.; Morelli, R.; de Lanerolle, T. R.; Gourley, J. R.

2011-12-01

Rainfall observations performed uniformly and continuously over a period of time are valuable inputs in developing climate models and predicting events such as floods and droughts. Rain-Check is a mobile application developed in Google App Inventor Platform, for android based smart phones, to allow field researchers to monitor various rain gauges distributed though out remote regions of Haiti and send daily readings via SMS messages for further analysis and long term trending. Rainfall rate and quantity interact with many other factors to influence erosion, vegetative cover, groundwater recharge, stream water chemistry and runoff into streams impacting agriculture and livestock. Rainfall observation from various sites is especially significant in Haiti with over 80% of the country is mountainous terrain. Data sets from global models and limited number of ground stations do not capture the fine-scale rainfall patterns necessary to describe local climate. Placement and reading of rain gauges are critical to accurate measurement of rainfall.

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.

A two-parameter design storm for Mediterranean convective rainfall

NASA Astrophysics Data System (ADS)

García-Bartual, Rafael; Andrés-Doménech, Ignacio

2017-05-01

The following research explores the feasibility of building effective design storms for extreme hydrological regimes, such as the one which characterizes the rainfall regime of the east and south-east of the Iberian Peninsula, without employing intensity-duration-frequency (IDF) curves as a starting point. Nowadays, after decades of functioning hydrological automatic networks, there is an abundance of high-resolution rainfall data with a reasonable statistic representation, which enable the direct research of temporal patterns and inner structures of rainfall events at a given geographic location, with the aim of establishing a statistical synthesis directly based on those observed patterns. The authors propose a temporal design storm defined in analytical terms, through a two-parameter gamma-type function. The two parameters are directly estimated from 73 independent storms identified from rainfall records of high temporal resolution in Valencia (Spain). All the relevant analytical properties derived from that function are developed in order to use this storm in real applications. In particular, in order to assign a probability to the design storm (return period), an auxiliary variable combining maximum intensity and total cumulated rainfall is introduced. As a result, for a given return period, a set of three storms with different duration, depth and peak intensity are defined. The consistency of the results is verified by means of comparison with the classic method of alternating blocks based on an IDF curve, for the above mentioned study case.

Long Term Precipitation Pattern Identification and Derivation of Non Linear Precipitation Trend in a Catchment using Singular Spectrum Analysis

NASA Astrophysics Data System (ADS)

Unnikrishnan, Poornima; Jothiprakash, Vinayakam

2017-04-01

Precipitation is the major component in the hydrologic cycle. Awareness of not only the total amount of rainfall pertaining to a catchment, but also the pattern of its spatial and temporal distribution are equally important in the management of water resources systems in an efficient way. Trend is the long term direction of a time series; it determines the overall pattern of a time series. Singular Spectrum Analysis (SSA) is a time series analysis technique that decomposes the time series into small components (eigen triples). This property of the method of SSA has been utilized to extract the trend component of the rainfall time series. In order to derive trend from the rainfall time series, we need to select components corresponding to trend from the eigen triples. For this purpose, periodogram analysis of the eigen triples have been proposed to be coupled with SSA, in the present study. In the study, seasonal data of England and Wales Precipitation (EWP) for a time period of 1766-2013 have been analyzed and non linear trend have been derived out of the precipitation data. In order to compare the performance of SSA in deriving trend component, Mann Kendall (MK) test is also used to detect trends in EWP seasonal series and the results have been compared. The result showed that the MK test could detect the presence of positive or negative trend for a significance level, whereas the proposed methodology of SSA could extract the non-linear trend present in the rainfall series along with its shape. We will discuss further the comparison of both the methodologies along with the results in the presentation.

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.

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.

Influence of net freshwater supply on salinity in Florida Bay

USGS Publications Warehouse

Nuttle, William K.; Fourqurean, James W.; Cosby, Bernard J.; Zieman, Joseph C.; Robblee, Michael B.

2000-01-01

An annual water budget for Florida Bay, the large, seasonally hypersaline estuary in the Everglades National Park, was constructed using physically based models and long‐term (31 years) data on salinity, hydrology, and climate. Effects of seasonal and interannual variations of the net freshwater supply (runoff plus rainfall minus evaporation) on salinity variation within the bay were also examined. Particular attention was paid to the effects of runoff, which are the focus of ambitious plans to restore and conserve the Florida Bay ecosystem. From 1965 to 1995 the annual runoff from the Everglades into the bay was less than one tenth of the annual direct rainfall onto the bay, while estimated annual evaporation slightly exceeded annual rainfall. The average net freshwater supply to the bay over a year was thus approximately zero, and interannual variations in salinity appeared to be affected primarily by interannual fluctuations in rainfall. At the annual scale, runoff apparently had little effect on the bay as a whole during this period. On a seasonal basis, variations in rainfall, evaporation, and runoff were not in phase, and the net freshwater supply to the bay varied between positive and negative values, contributing to a strong seasonal pattern in salinity, especially in regions of the bay relatively isolated from exchanges with the Gulf of Mexico and Atlantic Ocean. Changes in runoff could have a greater effect on salinity in the bay if the seasonal patterns of rainfall and evaporation and the timing of the runoff are considered. One model was also used to simulate spatial and temporal patterns of salinity responses expected to result from changes in net freshwater supply. Simulations in which runoff was increased by a factor of 2 (but with no change in spatial pattern) indicated that increased runoff will lower salinity values in eastern Florida Bay, increase the variability of salinity in the South Region, but have little effect on salinity in the Central and West Regions.

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.

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.

Aerosol and Urban Land Use Effect on Rainfall Around Cities in Indo-Gangetic Basin From Observations and Cloud Resolving Model Simulations

NASA Astrophysics Data System (ADS)

Sarangi, Chandan; Tripathi, S. N.; Qian, Yun; Kumar, Shailendra; Ruby Leung, L.

2018-04-01

Coupling of urban land use land cover (LULC) and aerosol loading on rainfall around cities in the Gangetic Basin (GB) is examined here. Long-term observations illustrate more rainfall at urban core and climatological downwind regions compared to the upwind regions of Kanpur, a metropolitan area located in central GB. In addition, analysis of a 15 day cloud resolving simulation using the Weather Research and Forecasting model also illustrated similar rainfall pattern around other major cities in the GB. Interestingly, the enhancement of downwind rainfall was greater than that over urban regions, and it was positively associated with both the urban area of the city and ambient aerosol loading during the propagating storm. Further, to gain a process-level understanding, a typical storm that propagated northwestward across Kanpur was simulated using Weather Research and Forecasting under three different scenarios. Case 1 has realistic LULC representation of Kanpur, while the grids representing the Kanpur urban region were replaced by cropland LULC pattern in Case 2. Comparison illustrated that urban heat island effect caused convergence of winds and moisture in the lower troposphere, which enhances convection over urban region and induced more rainfall over the urban core compared to upwind regions. Case 3 is similar to Case 1 but lower aerosol concentration (by a factor of 100) over the storm region. Analysis shows that aerosol-induced microphysical changes delay the initiation of warm rain (over the upwind region) but enhance ice phase particle formation in latter stages (over the urban and downwind regions) resulting in increase in downwind 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.

Forecasting of monsoon heavy rains: challenges in NWP

NASA Astrophysics Data System (ADS)

Sharma, Kuldeep; Ashrit, Raghavendra; Iyengar, Gopal; Bhatla, R.; Rajagopal, E. N.

2016-05-01

Last decade has seen a tremendous improvement in the forecasting skill of numerical weather prediction (NWP) models. This is attributed to increased sophistication in NWP models, which resolve complex physical processes, advanced data assimilation, increased grid resolution and satellite observations. However, prediction of heavy rains is still a challenge since the models exhibit large error in amounts as well as spatial and temporal distribution. Two state-of-art NWP models have been investigated over the Indian monsoon region to assess their ability in predicting the heavy rainfall events. The unified model operational at National Center for Medium Range Weather Forecasting (NCUM) and the unified model operational at the Australian Bureau of Meteorology (Australian Community Climate and Earth-System Simulator -- Global (ACCESS-G)) are used in this study. The recent (JJAS 2015) Indian monsoon season witnessed 6 depressions and 2 cyclonic storms which resulted in heavy rains and flooding. The CRA method of verification allows the decomposition of forecast errors in terms of error in the rainfall volume, pattern and location. The case by case study using CRA technique shows that contribution to the rainfall errors come from pattern and displacement is large while contribution due to error in predicted rainfall volume is least.

Regional patterns of the change in annual-mean tropical rainfall under global warming

NASA Astrophysics Data System (ADS)

Huang, P.

2013-12-01

Projection of the change in tropical rainfall under global warming is a major challenge with great societal implications. The current study analyzes the 18 models from the Coupled Models Intercomparison Project, and investigates the regional pattern of annual-mean rainfall change under global warming. With surface warming, the climatological ascending pumps up increased surface moisture and leads rainfall increase over the tropical convergence zone (wet-get-wetter effect), while the pattern of sea surface temperature (SST) increase induces ascending flow and then increasing rainfall over the equatorial Pacific and the northern Indian Ocean where the local oceanic warming exceeds the tropical mean temperature increase (warmer-get-wetter effect). The background surface moisture and SST also can modify warmer-get-wetter effect: the former can influence the moisture change and contribute to the distribution of moist instability change, while the latter can suppress the role of instability change over the equatorial eastern Pacific due to the threshold effect of convection-SST relationship. The wet-get-wetter and modified warmer-get-wetter effects form a hook-like pattern of rainfall change over the tropical Pacific and an elliptic pattern over the northern Indian Ocean. The annual-mean rainfall pattern can be partly projected based on current rainfall climatology, while it also has great uncertainties due to the uncertain change in SST pattern.

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.

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.

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.

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.

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.

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.

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.

Heat and Freshwater Budgets in the Eastern Pacific Warm Pool

NASA Astrophysics Data System (ADS)

Wijesekera, H. W.; Rudnick, D.; Paulson, C. A.; Pierce, S.

2002-12-01

Heat and freshwater budgets of the upper ocean in the Eastern Equatorial Pacific warm pool at 10N, 95W are investigated for the 20-day R/V New Horizon survey made as a part of the EPIC-2001 program. We collected underway hydrographic data from a SeaBird CTD mounted on an undulating platform, SeaSoar, and horizontal velocity data from the ship mounted ADCP, along a butterfly pattern centered near 10N, 95W. The time of completion of a single butterfly pattern (146x146 km) at a speed of 8 knots was approximately 36 hours, which is about half an inertial period at 10N. The butterfly survey lasted from September 14 to October 03, 2001. During the 20-day period, temperature and salinity in the upper 20 m dropped by 1.5C and 0.5 psu, respectively, and most of these changes took place over two days of heavy rainfall between September 23 and 24. The near surface became strongly stratified during these rain events. The rainfall signature weakened and mixed down to the top of the pycnocline (~30-m depth) within a few days after the rainfall. The change in fresh water content of the upper 30 m which occurred during the 2-day period of heavy rainfall is equivalent to about 0.12 m of rainfall, which is significantly less than the rainfall observed on the New Horizon. The difference may be due to spatial inhomogeneity in the rainfall and to the neglect of advection. Estimates of advection are presented using ADCP velocities and SeaSoar hydrography. Heat and fresh water budgets are presented by combining surface fluxes, and advection and storage terms.

Spatial and temporal variation of rainfall trends of Sri Lanka

NASA Astrophysics Data System (ADS)

Wickramagamage, P.

2016-08-01

This study was based on daily rainfall data of 48 stations distributed over the entire island covering a 30-year period from 1981 to 2010. Data analysis was done to identify the spatial pattern of rainfall trends. The methods employed in data analysis are linear regression and interpolation by Universal Kriging and Radial Basis function. The slope of linear regression curves of 48 stations was used in interpolation. The regression coefficients show spatially and seasonally variable positive and negative trends of annual and seasonal rainfall. About half of the mean annual pentad series show negative trends, while the rest shows positive trends. By contrast, the rainfall trends of the Southwest Monsoon (SWM) season are predominantly negative throughout the country. The first phase of the Northeast Monsoon (NEM1) displays downward trends everywhere, with the exception of the Southeastern coastal area. The strongest negative trends were found in the Northeast and in the Central Highlands. The second phase (NEM2) is mostly positive, except in the Northeast. The Inter-Monsoon (IM) periods have predominantly upward trends almost everywhere, but still the trends in some parts of the Highlands and Northeast are negative. The long-term data at Watawala Nuwara Eliya and Sandringham show a consistent decline in the rainfall over the last 100 years, particularly during the SWM. There seems to be a faster decline in the rainfall in the last 3 decades. These trends are consistent with the observations in India. It is generally accepted that there has been changes in the circulation pattern. Weakening of the SWM circulation parameters caused by global warming appears to be the main causes of recent changes. Effect of the Asian Brown Cloud may also play a role in these changes.

The northward shift of Meiyu rain belt and its possible association with rainfall intensity changes and the Pacific-Japan pattern

NASA Astrophysics Data System (ADS)

Gao, Qingjiu; Sun, Yuting; You, Qinglong

2016-12-01

The meridional location change of Meiyu rain belt and its relationship with the rainfall intensity and circulation background changes for the period 1958-2009 are examined using daily rainfall datasets from 756 stations in China, the 6-h ERA-Interim reanalyses, CRU monthly temperature and daily outgoing long-wave radiation (OLR) data from the US National Oceanic and Atmospheric Administration (NOAA). The results indicate that the Meiyu rain belt experienced a northward shift in the late 1990s in response to global warming. Moreover, the intensity of interannual and day-to-day variability of rainfall within Meiyu period has been increasing in the warming climate. The amplification of the variability within Meiyu period over the northern Yangtze-Huai River Valley (YHRV) is much larger than that of the southern YHRV. The large difference in the trends of variance within the Meiyu period between these two regions induces a spatial varying for different rainfall categories in terms of intensity. More significant positive trends in heavy and extreme heavy rainfall occur over northern YHRV compared with southern YHRV, which is a crucial indicator of changes in the rain band, despite the observation of an increase in heavy and very heavy rain events and a decrease in weak events throughout the entire YHRV. A composite of the atmospheric circulation indicates that intense northward horizontal transport and the convergence of water vapor fluxes are the immediate causes of the rain band shift. Besides, through forcing a northward extended convection over the tropics, the Pacific-Japan (P-J) pattern induces a northward expansion of western Pacific Subtropical High, leading to intensified convergence and enhanced rainfall over Northern YHRV.

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.

Development and integration of sub-hourly rainfall-runoff modeling capability within a watershed model

USDA-ARS?s Scientific Manuscript database

Increasing urbanization changes runoff patterns to be flashy and instantaneous with decreased base flow. A model with the ability to simulate sub-daily rainfall–runoff processes and continuous simulation capability is required to realistically capture the long-term flow and water quality trends in w...

Role of moisture transport for Central American precipitation

NASA Astrophysics Data System (ADS)

María Durán-Quesada, Ana; Gimeno, Luis; Amador, Jorge

2017-02-01

A climatology of moisture sources linked with Central American precipitation was computed based upon Lagrangian trajectories for the analysis period 1980-2013. The response of the annual cycle of precipitation in terms of moisture supply from the sources was analysed. Regional precipitation patterns are mostly driven by moisture transport from the Caribbean Sea (CS). Moisture supply from the eastern tropical Pacific (ETPac) and northern South America (NSA) exhibits a strong seasonal pattern but weaker compared to CS. The regional distribution of rainfall is largely influenced by a local signal associated with surface fluxes during the first part of the rainy season, whereas large-scale dynamics forces rainfall during the second part of the rainy season. The Caribbean Low Level Jet (CLLJ) and the Chocó Jet (CJ) are the main conveyors of regional moisture, being key to define the seasonality of large-scale forced rainfall. Therefore, interannual variability of rainfall is highly dependent of the regional LLJs to the atmospheric variability modes. The El Niño-Southern Oscillation (ENSO) was found to be the dominant mode affecting moisture supply for Central American precipitation via the modulation of regional phenomena. Evaporative sources show opposite anomaly patterns during warm and cold ENSO phases, as a result of the strengthening and weakening, respectively, of the CLLJ during the summer months. Trends in both moisture supply and precipitation over the last three decades were computed, results suggest that precipitation trends are not homogeneous for Central America. Trends in moisture supply from the sources identified show a marked north-south seesaw, with an increasing supply from the CS Sea to northern Central America. Long-term trends in moisture supply are larger for the transition months (March and October). This might have important implications given that any changes in the conditions seen during the transition to the rainy season may induce stronger precipitation trends.

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

Nishiyama, Koji; Iseri, Yoshihiko; Jinno, Kenji

2009-11-01

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

Impact of rainfall pattern on interrill erosion process

USDA-ARS?s Scientific Manuscript database

The impact of rainfall pattern on the interrill erosion process is not fully understood despite its importance. Systematic rainfall simulation experiments involving different rain intensities, stages, intensity sequences, and surface cover conditions were conducted to investigate the impacts of rain...

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.

Long term leaf phenology and leaf exchange strategies of a cerrado savanna community

NASA Astrophysics Data System (ADS)

de Camargo, Maria Gabriela G.; Costa Alberton, Bruna; de Carvalho, Gustavo H.; Magalhães, Paula A. N. R.; Morellato, Leonor Patrícia C.

2017-04-01

Leaf development and senescence cycles are linked to a range of ecosystem processes, affecting seasonal patterns of atmosphere-ecosystem carbon and energy exchanges, resource availability and nutrient cycling. The degree of deciduousness of tropical trees and communities depend on ecosystems characteristics such as amount of biomass, species diversity and the strength and length of the dry season. Besides defining the growing season, deciduousness can also be an indicator of species response to climate changes in the tropics, mainly because severity of dry season can intensify leaf loss. Based on seven-years of phenological observations (2005 to 2011) we describe the long-term patterns of leafing phenology of a Brazilian cerrado savanna, aiming to (i) identify leaf exchange strategies of species, quantifying the degree of deciduousness, and verify whether these strategies vary among years depending on the length and strength of the dry seasons; (ii) define the growing seasons along the years and the main drivers of leaf flushing in the cerrado. We analyzed leafing patterns of 107 species and classified 69 species as deciduous (11 species), semi-deciduous (29) and evergreen (29). Leaf exchange was markedly seasonal, as expected for seasonal tropical savannas. Leaf fall predominated in the dry season, peaking in July, and leaf flushing in the transition between dry to wet seasons, peaking in September. Leafing patterns were similar among years with the growing season starting at the end of dry season, in September, for most species. However, leaf exchange strategies varied among years for most species (65%), except for evergreen strategy, mainly constant over years. Leafing patterns of cerrado species were strongly constrained by rainfall. The length of the dry season and rainfall intensity were likely affecting the individuals' leaf exchange strategies and suggesting a differential resilience of species to changes of rainfall regime, predicted on future global change scenarios.

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.

Plant calendar pattern based on rainfall forecast and the probability of its success in Deli Serdang regency of Indonesia

NASA Astrophysics Data System (ADS)

Darnius, O.; Sitorus, S.

2018-03-01

The objective of this study was to determine the pattern of plant calendar of three types of crops; namely, palawija, rice, andbanana, based on rainfall in Deli Serdang Regency. In the first stage, we forecasted rainfall by using time series analysis, and obtained appropriate model of ARIMA (1,0,0) (1,1,1)12. Based on the forecast result, we designed a plant calendar pattern for the three types of plant. Furthermore, the probability of success in the plant types following the plant calendar pattern was calculated by using the Markov process by discretizing the continuous rainfall data into three categories; namely, Below Normal (BN), Normal (N), and Above Normal (AN) to form the probability transition matrix. Finally, the combination of rainfall forecasting models and the Markov process were used to determine the pattern of cropping calendars and the probability of success in the three crops. This research used rainfall data of Deli Serdang Regency taken from the office of BMKG (Meteorologist Climatology and Geophysics Agency), Sampali Medan, Indonesia.

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.

Combined effects of short-term rainfall patterns and soil texture on nitrogen cycling -- A Modeling Analysis

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

Gu, C.; Riley, W.J.

2009-11-01

Precipitation variability and magnitude are expected to change in many parts of the world over the 21st century. We examined the potential effects of intra-annual rainfall patterns on soil nitrogen (N) transport and transformation in the unsaturated soil zone using a deterministic dynamic modeling approach. The model (TOUGHREACT-N), which has been tested and applied in several experimental and observational systems, mechanistically accounts for microbial activity, soil-moisture dynamics that respond to precipitation variability, and gaseous and aqueous tracer transport in the soil. Here, we further tested and calibrated the model against data from a precipitation variability experiment in a tropical systemmore » in Costa Rica. The model was then used to simulate responses of soil moisture, microbial dynamics, nitrogen (N) aqueous and gaseous species, N leaching, and N trace-gas emissions to changes in rainfall patterns; the effect of soil texture was also examined. The temporal variability of nitrate leaching and NO, N{sub 2}, and N{sub 2}O effluxes were significantly influenced by rainfall dynamics. Soil texture combined with rainfall dynamics altered soil moisture dynamics, and consequently regulated soil N responses to precipitation changes. The clay loam soil more effectively buffered water stress during relatively long intervals between precipitation events, particularly after a large rainfall event. Subsequent soil N aqueous and gaseous losses showed either increases or decreases in response to increasing precipitation variability due to complex soil moisture dynamics. For a high rainfall scenario, high precipitation variability resulted in as high as 2.4-, 2.4-, 1.2-, and 13-fold increases in NH{sub 3}, NO, N{sub 2}O and NO{sub 3}{sup -} fluxes, respectively, in clay loam soil. In sandy loam soil, however, NO and N{sub 2}O fluxes decreased by 15% and 28%, respectively, in response to high precipitation variability. Our results demonstrate that soil N cycling responses to increasing precipitation variability depends on precipitation amount and soil texture, and that accurate prediction of future N cycling and gas effluxes requires models with relatively sophisticated representation of the relevant processes.« less

Droughts, rainfall and rural water supply in northern Nigeria

NASA Astrophysics Data System (ADS)

Tarhule, Aondover Augustine

Knowledge concerning various aspects of drought and water scarcity is required to predict, and to articulate strategies to minimize the effects of future events. This thesis investigated different aspects of droughts and rainfall variability at several time scales and described the dynamics of water supply and use in a rural village in northeastern Nigeria. The parallel existence of measured climatic records and information on famine/folklore events is utilized to calibrate the historical information against the measured data. It is shown that famines or historical droughts occurred when the cumulative deficit of rainfall fell below 1.3 times the standard deviation of the long-term mean rainfall. The study demonstrated that famine chronologies are adequate proxy for drought events, providing a means for the reconstruction of the drought/climatic history of the region. Analysis of recent changes in annual rainfall characteristics show that the series of annual rainfall and number of rain days experienced a discontinuity during the 1960's, caused largely by the decrease in the frequency of moderate to high intensity rain events. The periods prior to and after the change point are homogenous and provide an objective basis for the estimation of changes in rainfall characteristics, drought parameters and for demarcating the region into sub-zones. Rainfall variability was unaffected by the abrupt change. Furthermore, the variability is independently distributed and adequately described by the normal distribution. This allows estimates of the probability of various magnitudes or thresholds of variability. The effects of droughts and rainfall variability are most strongly felt in rural areas. Analysis of the patterns of water supply and use in a typical rural village revealed that the hydrologic system is driven by the local rainfall. Perturbations in the rains propagate through the system with short lag time between the various components. Where fadama aquifers occur, they offer a major supplement of water for six to seven months during the dry season. Under traditional systems, the pattern of water withdrawal from the fadama aquifers is designed to accommodate the diverse interests of different groups and to minimize the potential for conflict. The results contribute to our understanding of drought and water scarcity and are useful in various practical applications.

Experimental drought induces short-term changes in soil functionality and microbial community structure after fire in a Mediterranean shrubland

NASA Astrophysics Data System (ADS)

Hinojosa, M. B.; Parra, A.; Laudicina, V. A.; Moreno, J. M.

2014-10-01

Fire is a major ecosystem driver, causing significant changes in soil nutrients and microbial community structure and functionality. Post-fire soil dynamics can vary depending on rainfall patterns, although variations in response to drought are poorly known. This is particularly important in areas with poor soils and limited rainfall, like arid and semiarid ones. Furthermore, climate change projections in many such areas anticipate reduced precipitation and longer drought, together with an increase in fire severity. The effects of experimental drought and fire were studied on soils in a Mediterranean Cistus-Erica shrubland in Central Spain. A replicated (n = 4) field experiment was carried out in which four levels of rainfall pattern were implemented by means of a rain-out shelters and irrigation system. The treatments were: environmental control (natural rainfall), historical control (long-term average rainfall, 2 months drought), moderate drought (25% reduction of historical control, 5 months drought) and severe drought (45% reduction, 7 months drought). After one growing season, the plots were burned with high fire intensity, except a set of unburned plots that served as control. Soils were collected seasonally during one year and variables related to soil nutrient availability and microbial community structure and functionality were studied. Burned soils increased nutrient availability (P, N, K) with respect to unburned ones, but drought reduced such an increase in P, while it further increased N and K. Such changes in available soil nutrients were short-lived. Drought caused a further decrease of enzyme activities, carbon mineralization rate and microbial biomass. Fire decreased the relative abundance of fungi and actinomycetes. However, fire and drought caused a further reduction in fungi, with bacteria becoming relatively more abundant. Arguably, increasing drought and fires due to climate change will likely shift soil recovery after fire.

Mixed memory, (non) Hurst effect, and maximum entropy of rainfall in the tropical Andes

NASA Astrophysics Data System (ADS)

Poveda, Germán

2011-02-01

Diverse linear and nonlinear statistical parameters of rainfall under aggregation in time and the kind of temporal memory are investigated. Data sets from the Andes of Colombia at different resolutions (15 min and 1-h), and record lengths (21 months and 8-40 years) are used. A mixture of two timescales is found in the autocorrelation and autoinformation functions, with short-term memory holding for time lags less than 15-30 min, and long-term memory onwards. Consistently, rainfall variance exhibits different temporal scaling regimes separated at 15-30 min and 24 h. Tests for the Hurst effect evidence the frailty of the R/ S approach in discerning the kind of memory in high resolution rainfall, whereas rigorous statistical tests for short-memory processes do reject the existence of the Hurst effect. Rainfall information entropy grows as a power law of aggregation time, S( T) ˜ Tβ with < β> = 0.51, up to a timescale, TMaxEnt (70-202 h), at which entropy saturates, with β = 0 onwards. Maximum entropy is reached through a dynamic Generalized Pareto distribution, consistently with the maximum information-entropy principle for heavy-tailed random variables, and with its asymptotically infinitely divisible property. The dynamics towards the limit distribution is quantified. Tsallis q-entropies also exhibit power laws with T, such that Sq( T) ˜ Tβ( q) , with β( q) ⩽ 0 for q ⩽ 0, and β( q) ≃ 0.5 for q ⩾ 1. No clear patterns are found in the geographic distribution within and among the statistical parameters studied, confirming the strong variability of tropical Andean rainfall.

Rainfall-enhanced blooming in typhoon wakes

PubMed Central

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

2016-01-01

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

Rainfall-enhanced blooming in typhoon wakes.

PubMed

Lin, Y-C; Oey, L-Y

2016-08-22

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

Rainfall-enhanced blooming in typhoon wakes

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

Rainfall-enhanced blooming in typhoon wakes

NASA Astrophysics Data System (ADS)

Lin, Y.; Oey, L. Y.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

Sombroek, W

2001-11-01

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

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

NASA Astrophysics Data System (ADS)

Chooi Tan, Kok

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

Meher, J. K.; Das, L.

2017-12-01

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

Application of the empirical orthogonal function to study the rainfall pattern in Daerah Istimewa Yogyakarta province

NASA Astrophysics Data System (ADS)

Adi-Kusumo, Fajar; Gunardi, Utami, Herni; Nurjani, Emilya; Sopaheluwakan, Ardhasena; Aluicius, Irwan Endrayanto; Christiawan, Titus

2016-02-01

We consider the Empirical Orthogonal Function (EOF) to study the rainfall pattern in Daerah Istimewa Yogyakarta (DIY) Province, Indonesia. The EOF is one of the important methods to study the dominant pattern of the data using dimension reduction technique. EOF makes possible to reduce the huge dimension of observed data into a smaller one without losing its significant information in order to figures the whole data. The methods is also known as Principal Components Analysis (PCA) which is conducted to find the pattern of the data. DIY Province is one of the province in Indonesia which has special characteristics related to the rainfall pattern. This province has an active volcano, karst, highlands, and also some lower area including beach. This province is bounded by the Indonesian ocean which is one of the important factor to provide the rainfall. We use at least ten years rainfall monthly data of all stations in this area and study the rainfall characteristics based on the four regencies of the province. EOF analysis is conducted to analyze data in order to decide the station groups which have similar characters.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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.

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.

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

USGS Publications Warehouse

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

2015-01-01

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

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.

Future changes in rainfall associated with ENSO, IOD and changes in the mean state over Eastern Africa

NASA Astrophysics Data System (ADS)

Endris, Hussen Seid; Lennard, Christopher; Hewitson, Bruce; Dosio, Alessandro; Nikulin, Grigory; Artan, Guleid A.

2018-05-01

This study examines the projected changes in the characteristics of the El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) in terms of mean state, intensity and frequency, and associated rainfall anomalies over eastern Africa. Two regional climate models driven by the same four global climate models (GCMs) and the corresponding GCM simulations are used to investigate projected changes in teleconnection patterns and East African rainfall. The period 1976-2005 is taken as the reference for present climate and the far-future climate (2070-2099) under Representative Concentration Pathway 8.5 (RCP8.5) is analyzed for projected change. Analyses of projections based on GCMs indicate an El Niño-like (positive IOD-like) warming pattern over the tropical Pacific (Indian) Ocean. However, large uncertainties remain in the projected future changes in ENSO/IOD frequency and intensity with some GCMs show increase of ENSO/IOD frequency and intensity, and others a decrease or no/small change. Projected changes in mean rainfall over eastern Africa based on the GCM and RCM data indicate a decrease in rainfall over most parts of the region during JJAS and MAM seasons, and an increase in rainfall over equatorial and southern part of the region during OND, with the greatest changes in equatorial region. During ENSO and IOD years, important changes in the strength of the teleconnections are found. During JJAS, when ENSO is an important driver of rainfall variability over the region, both GCM and RCM projections show an enhanced La Niña-related rainfall anomaly compared to the present period. Although the long rains (MAM) have little association with ENSO in the reference period, both GCMs and RCMs project stronger ENSO teleconnections in the future. On the other hand, during the short rains (OND), a dipole future change in rainfall teleconnection associated with ENSO and IOD is found, with a stronger ENSO/IOD related rainfall anomaly over the eastern part of the domain, but a weaker ENSO/IOD signal over the southern part of the region. This signal is consistent and robust in all global and regional model simulations. The projected increase in OND rainfall over the eastern horn of Africa might be linked with the mean changes in SST over Indian and Pacific Ocean basins and the associated Walker circulations.

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.

The influence of atmospheric circulation types on regional patterns of precipitation in Marmara (NW Turkey)

NASA Astrophysics Data System (ADS)

Baltacı, H.; Kındap, T.; Ünal, A.; Karaca, M.

2017-02-01

In this study, regional patterns of precipitation in Marmara are described for the first time by means of Ward's hierarchical cluster analysis. Daily values of winter precipitation data based on 19 meteorological stations were used for the period from 1960 to 2012. Five clusters of coherent zones were determined, namely Black Sea-Marmara, Black Sea, Marmara, Thrace, and Aegean sub-regions. To investigate the prevailing atmospheric circulation types (CTs) that cause precipitation occurrence and intensity in these five different rainfall sub-basins, objective Lamb weather type (LWT) methodology was applied to National Centers of Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis of daily mean sea level pressure (MSLP) data. Precipitation occurrence suggested that wet CTs (i.e. N, NE, NW, and C) offer a high chance of precipitation in all sub-regions. For the eastern (western) part of the region, the high probability of rainfall occurrence is shown under the influence of E (SE, S, SW) atmospheric CTs. In terms of precipitation intensity, N and C CTs had the highest positive gradients in all the sub-basins of the Marmara. In addition, although Marmara and Black Sea sub-regions have the highest daily rainfall potential during NE types, high daily rainfall totals are recorded in all sub-regions except the Black Sea during NW types.

The Effects Of Urban Landscape Patterns On Rainfall-Runoff Processes At Small Scale

NASA Astrophysics Data System (ADS)

Chen, L.

2016-12-01

Many studies have indicated that urban landscape change may alter rainfall-runoff processes. However, how urban landscape pattern affect this process is little addressed. In this study, the hydrological effects of landscape pattern on rainfall-runoff processes at small-scale was explored. Twelve residential blocks with independent drainage systems in Beijing were selected as case study areas. Impervious metrics of these blocks, i.e., total impervious area (TIA) and directly connected impervious area (DCIA), were identified. A drainage index describing catchment general drainage load and the overland flow distance, Ad, was estimated and used as one of the landscape spatial metrics. Three scenarios were designed to test the potential influence of impervious surface pattern on runoff processes. Runoff variables including total and peak runoff depth (Qt and Qp) were simulated under different rainfall conditions by Storm Water Management Model (SWMM). The relationship between landscape patterns and runoff variables were analyzed, and further among the three scenarios. The results demonstrated that, in small urban blocks, spatial patterns have inherent influences on rainfall-runoff processes. Specifically, (1) Imperviousness acts as effective indicators in predicting both Qt and Qp. As rainfall intensity increases, the major affecting factor changes from DCIA to TIA for both Qt and Qp; (2) Increasing the size of drainage area dominated by each drainage inlet will benefit the block peak flow mitigation; (3) Different spatial concentrations of impervious surfaces have inherent influences on Qp, when impervious surfaces located away from the outlet can reduce the peak flow discharge. These findings may provide insights into the role of urban landscape patterns in driving rainfall-runoff responses in urbanization, which is essential for urban planning and stormwater management.

Seasonal and spatial variability of rainfall redistribution under Scots pine and Downy oak forests in Mediterranean conditions

NASA Astrophysics Data System (ADS)

Garcia-Estringana, Pablo; Latron, Jérôme; Molina, Antonio J.; Llorens, Pilar

2013-04-01

The large degree of temporal and spatial variability of throughfall input patterns may lead to significant changes in the volume of water that reach the soil in each location, and beyond in the hydrological response of forested hillslopes. To explore the role of vegetation in the temporal and spatial redistribution of rainfall in Mediterranean climatic conditions two contrasted stands were monitored. One is a Downy oak forest (Quercus pubescens) and the other is a Scots pine forest (Pinus sylvestris), both are located in the Vallcebre research catchments (NE Spain, 42° 12'N, 1° 49'E). These plots are representative of Mediterranean mountain areas with spontaneous afforestation by Scots pine as a consequence of the abandonment of agricultural terraces, formerly covered by Downy oaks. The monitoring design of each plot consists of a set of 20 automatic rain recorders and 40 automatic soil moisture probes located below the canopy. 100 hemispheric photographs of the canopy were used to place the instruments at representative locations (in terms of canopy cover) within the plot. Bulk rainfall, stemflow and meteorological conditions above the forest cover are also automatically recorded. Canopy cover as well as biometric characteristics of the plots are also regularly measured. This work presents the first results describing the variability of throughfall beneath each forest stand and compares the persistence of temporal patterns among stands, and for the oaks stand among the leafed and the leafless period. Furthermore, canopy structure, rainfall characteristics and meteorological conditions of rainfall events are evaluated as main drivers of throughfall redistribution.

Variations in Global Precipitation: Climate-scale to Floods

NASA Technical Reports Server (NTRS)

Adler, Robert

2006-01-01

Variations in global precipitation from climate-scale to small scale are examined using satellite-based analyses of the Global Precipitation Climatology Project (GPCP) and information from the Tropical Rainfall Measuring Mission (TRMM). Global and large regional rainfall variations and possible long-term changes are examined using the 27- year (1979-2005) monthly dataset from the GPCP. In addition to global patterns associated with phenomena such as ENSO, the data set is explored for evidence of longterm change. Although the global change of precipitation in the data set is near zero, the data set does indicate a small upward trend in the Tropics (25S-25N), especially over ocean. Techniques are derived to isolate and eliminate variations due to ENS0 and major volcanic eruptions and the significance of the trend is examined. The status of TRMM estimates is examined in terms of evaluating and improving the long-term global data set. To look at rainfall variations on a much smaller scale TRMM data is used in combination with observations from other satellites to produce a 3-hr resolution, eight-year data set for examination of weather events and for practical applications such as detecting floods. Characteristics of the data set are presented and examples of recent flood events are examined.

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

PubMed

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

2017-12-01

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

Climate influence on dengue epidemics in Puerto Rico.

PubMed

Jury, Mark R

2008-10-01

The variability of the insect-borne disease dengue in Puerto Rico was studied in relation to climatic variables in the period 1979-2005. Annual and monthly reported dengue cases were compared with precipitation and temperature data. Results show that the incidence of dengue in Puerto Rico was relatively constant over time despite global warming, possibly due to the offsetting effects of declining rainfall, improving health care and little change in population. Seasonal fluctuations of dengue were driven by rainfall increases from May to November. Year-to-year variability in dengue cases was positively related to temperature, but only weakly associated with local rainfall and an index of El Nino Southern Oscillation (ENSO). Climatic conditions were mapped with respect to dengue cases and patterns in high and low years were compared. During epidemics, a low pressure system east of Florida draws warm humid air over the northwestern Caribbean. Long-term trends in past observed and future projected rainfall and temperatures were studied. Rainfall has declined slowly, but temperatures in the Caribbean are rising with the influence of global warming. Thus, dengue may increase in the future, and it will be necessary to anticipate dengue epidemics using climate forecasts, to reduce adverse health impacts.

Interactive effects of seasonal drought and elevated atmospheric carbon dioxide concentration on prokaryotic rhizosphere communities.

PubMed

Drigo, Barbara; Nielsen, Uffe N; Jeffries, Thomas C; Curlevski, Nathalie J A; Singh, Brajesh K; Duursma, Remko A; Anderson, Ian C

2017-08-01

Global change models indicate that rainfall patterns are likely to shift towards more extreme events concurrent with increasing atmospheric carbon dioxide concentration ([CO 2 ]). Both changes in [CO 2 ] and rainfall regime are known to impact above- and belowground communities, but the interactive effects of these global change drivers have not been well explored, particularly belowground. In this experimental study, we examined the effects of elevated [CO 2 ] (ambient + 240 ppm; [eCO 2 ]) and changes in rainfall patterns (seasonal drought) on soil microbial communities associated with forest ecosystems. Our results show that bacterial and archaeal communities are highly resistant to seasonal drought under ambient [CO 2 ]. However, substantial taxa specific responses to seasonal drought were observed at [eCO 2 ], suggesting that [eCO 2 ] compromise the resistance of microbial communities to extreme events. Within the microbial community we were able to identify three types of taxa specific responses to drought: tolerance, resilience and sensitivity that contributed to this pattern. All taxa were tolerant to seasonal drought at [aCO 2 ], whereas resilience and sensitivity to seasonal drought were much greater in [eCO 2 ]. These results provide strong evidence that [eCO 2 ] moderates soil microbial community responses to drought in forests, with potential implications for their long-term persistence and ecosystem functioning. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

Summer Rains and Dry Seasons in the Upper Blue Nile Basin: The Predictability of Half a Century of Past and Future Spatiotemporal Patterns

PubMed Central

Mellander, Per-Erik; Gebrehiwot, Solomon G.; Gärdenäs, Annemieke I.; Bewket, Woldeamlak; Bishop, Kevin

2013-01-01

During the last 100 years the Ethiopian upper Blue Nile Basin (BNB) has undergone major changes in land use, and is now potentially facing changes in climate. Rainfall over BNB supplies over two-thirds of the water to the Nile and supports a large local population living mainly on subsistence agriculture. Regional food security is sensitive to both the amount and timing of rain and is already an important political challenge that will be further complicated if scenarios of climate change are realized. In this study a simple spatial model of the timing and duration of summer rains (Kiremt) and dry season (Bega), and annual rain over the upper BNB was established from observed data between 1952 and 2004. The model was used to explore potential impacts of climate change on these rains, using a down-scaled ECHAM5/MP1-OM scenario between 2050 and 2100. Over the observed period the amount, onset and duration of Kiremt rains and rain-free Bega days have exhibited a consistent spatial pattern. The spatially averaged annual rainfall was 1490 mm of which 93% was Kiremt rain. The average Kiremt rain and number of rainy days was higher in the southwest (322 days) and decreased towards the north (136 days). Under the 2050–2100 scenario, the annual mean rainfall is predicted to increase by 6% and maintain the same spatial pattern as in the past. A larger change in annual rainfall is expected in the southwest (ca. +130 mm) with a gradually smaller change towards the north (ca. +70 mm). Results highlight the need to account for the characteristic spatiotemporal zonation when planning water management and climate adaptation within the upper BNB. The presented simple spatial resolved models of the presence of Kiremt and annual total rainfall could be used as a baseline for such long-term planning. PMID:23869219

El Niño, Rainfall, and the Shifting Geography of Cholera in Africa

NASA Astrophysics Data System (ADS)

Moore, S.; Azman, A. S.; Zaitchik, B. F.; McKay, H.; Lessler, J.

2017-12-01

The El Niño Southern Oscillation (ENSO) and other climate patterns can have profound impacts on the occurrence of infectious diseases. Because of the key role of water supplies in cholera transmission, a relationship between El Niño events and cholera incidence is highly plausible, and previous research has shown a link between El Niño patterns and cholera in Bangladesh. However, there is little systematic evidence for this link in Africa where many cholera cases and deaths are reported. To understand how ENSO affects the geographic distribution of cholera incidence in Africa, we used a hierarchical Bayesian approach to integrate over 17,000 annual observations of cholera incidence from 2000-2014 in over 3,000 unique locations of varying spatial extent, ranging from entire countries to neighborhoods. The resulting maps reflect modeled cholera incidence at a fine spatial resolution using reported counts of cholera cases, key explanatory variables, and a spatially-dependent covariance term. We then examined the potential mechanistic association between ENSO-related changes in cholera incidence and several environmental variables including rainfall. El Niño profoundly changed the annual geographic distribution of cholera in Africa from 2000-2014, shifting the burden to continental East Africa, where almost 50,000 additional cases occur during El Niño years. Cholera incidence during El Niño years was higher in regions of East Africa with increased rainfall, but incidence was also higher in some areas with decreased rainfall suggesting a complex relationship between rainfall and cholera incidence. Here we show clear evidence for a shift in the distribution of cholera incidence throughout Africa in El Niño and non-El Niño years, likely mediated by El Niño's impact on local climatic factors. Knowledge of this relationship between cholera and climate patterns coupled with El Niño forecasting could be used to notify countries in Africa when they are likely to see a major shift in their cholera risk.

Comparisons of Rain Estimates from Ground Radar and Satellite Over Mountainous Regions

NASA Technical Reports Server (NTRS)

Lin, Xin; Kidd, Chris; Tao, Jing; Barros, Ana

2016-01-01

A high-resolution rainfall product merging surface radar and an enhanced gauge network is used as a reference to examine two operational surface radar rainfall products over mountain areas. The two operational rainfall products include radar-only and conventional-gauge-corrected radar rainfall products. Statistics of rain occurrence and rain amount including their geographical, seasonal, and diurnal variations are examined using 3-year data. It is found that the three surface radar rainfall products in general agree well with one another over mountainous regions in terms of horizontal mean distributions of rain occurrence and rain amount. Frequency of rain occurrence and fraction of rain amount also indicate similar distribution patterns as a function of rain intensity. The diurnal signals of precipitation over mountain ridges are well captured and joint distributions of coincident raining samples indicate reasonable correlations during both summer and winter. Factors including undetected low-level precipitation, limited availability of gauges for correcting the Z-R relationship over the mountains, and radar beam blocking by mountains are clearly noticed in the two conventional radar rainfall products. Both radar-only and conventional-gauge-corrected radar rainfall products underestimate the rain occurrence and fraction of rain amount at intermediate and heavy rain intensities. Comparison of PR and TMI against a surface radar-only rainfall product indicates that the PR performs equally well with the high-resolution radar-only rainfall product over complex terrains at intermediate and heavy rain intensities during the summer and winter. TMI, on the other hand, requires improvement to retrieve wintertime precipitation over mountain areas.

[Effects of slope gradient on slope runoff and sediment yield under different single rainfall conditions].

PubMed

He, Ji-Jun; Cai, Qiang-Guo; Liu, Song-Bo

2012-05-01

Based on the field observation data of runoff and sediment yield produced by single rainfall events in runoff plots, this paper analyzed the variation patterns of runoff and sediment yield on the slopes with different gradients under different single rainfall conditions. The differences in the rainfall conditions had little effects on the variation patterns of slope runoff with the gradient. Under the conditions of six different rainfall events in the study area, the variation patterns of slope runoff with the gradient were basically the same, i. e., the runoff increased with increasing gradient, but the increment of the runoff decreased slightly with increasing gradient, which was mainly determined by the infiltration flux of atmospheric precipitation. Rainfall condition played an important role on the slope sediment yield. Generally, there existed a critical slope gradient for slope erosion, but the critical gradient was not a fixed value, which varied with rainfall condition. The critical slope gradient for slope erosion increased with increasing slope gradient. When the critical slope gradient was greater, the variation of slope sediment yield with slope gradient always became larger.

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.

A single scaling parameter as a first approximation to describe the rainfall pattern of a place: application on Catalonia

NASA Astrophysics Data System (ADS)

Casas-Castillo, M. Carmen; Llabrés-Brustenga, Alba; Rius, Anna; Rodríguez-Solà, Raúl; Navarro, Xavier

2018-02-01

As well as in other natural processes, it has been frequently observed that the phenomenon arising from the rainfall generation process presents fractal self-similarity of statistical type, and thus, rainfall series generally show scaling properties. Based on this fact, there is a methodology, simple scaling, which is used quite broadly to find or reproduce the intensity-duration-frequency curves of a place. In the present work, the relationship of the simple scaling parameter with the characteristic rainfall pattern of the area of study has been investigated. The calculation of this scaling parameter has been performed from 147 daily rainfall selected series covering the temporal period between 1883 and 2016 over the Catalonian territory (Spain) and its nearby surroundings, and a discussion about the relationship between the scaling parameter spatial distribution and rainfall pattern, as well as about trends of this scaling parameter over the past decades possibly due to climate change, has been presented.

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

Effect of precipitation pattern on leaching of preservative from treated wood and implications for accelerated testing

Treesearch

Stan Lebow

2014-01-01

There is a need to develop improved accelerated test methods for evaluating the leaching of wood preservatives from treated wood exposed to precipitation. In this study the effects of rate of rainfall and length of intervals between rainfall events on leaching was evaluated by exposing specimens to varying patterns of simulated rainfall under controlled laboratory...

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

PubMed

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

2013-08-01

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

Power-law scaling in daily rainfall patterns and consequences in urban stream discharges

NASA Astrophysics Data System (ADS)

Park, Jeryang; Krueger, Elisabeth H.; Kim, Dongkyun; Rao, Suresh C.

2016-04-01

Poissonian rainfall has been frequently used for modelling stream discharge in a catchment at the daily scale. Generally, it is assumed that the daily rainfall depth is described by memoryless exponential distribution which is transformed to stream discharge, resulting in an analytical pdf for discharge [Gamma distribution]. While it is true that catchment hydrological filtering processes (censored by constant rate ET losses, and first-order recession) increases "memory", reflected in 1/f noise in discharge time series. Here, we show that for urban watersheds in South Korea: (1) the observation of daily rainfall depths follow power-law pdfs, and spectral slopes range between 0.2 ~ 0.4; and (2) the stream discharge pdfs have power-law tails. These observation results suggest that multiple hydro-climatic factors (e.g., non-stationarity of rainfall patterns) and hydrologic filtering (increasing impervious area; more complex urban drainage networks) influence the catchment hydrologic responses. We test the role of such factors using a parsimonious model, using different types of daily rainfall patterns (e.g., power-law distributed rainfall depth with Poisson distribution in its frequency) and urban settings to reproduce patterns similar to those observed in empirical records. Our results indicate that fractality in temporally up-scaled rainfall, and the consequences of large extreme events are preserved as high discharge events in urbanizing catchments. Implications of these results to modeling urban hydrologic responses and impacts on receiving waters are discussed.

Analysis of rainfall over northern Peru during El Nino: A PCDS application

NASA Technical Reports Server (NTRS)

Goldberg, R.; Tisnado, G.

1986-01-01

In an examination of GOES satellite data during the 1982 through 1983 El Nino period, the appearance of lee wave cloud patterns was revealed. A correlation was hypothesized relating an anomalous easterly flow across the Andes with the appearance of these wave patterns and with the subsequent onset of intense rainfall. The cloud patterns are belived to be associated with the El Nino period and could be viewed as precursors to significant changes in weather patterns. The ultimate goal of the researchers will be the ability to predict occurrences of rainstorms associated with the appearance of lee waves and related cloud patterns as harbingers of destruction caused by flooding, huaycos, and other catastrophic consequences of heavy and abnormal rainfall. Rainfall data from about 70 stations in northern Peru from 1980 through 1984 were formatted to be utilized within the Pilot Climate Data System (PCDS). This time period includes the 1982 through 1983 El Nino period. As an example of the approach, a well-pronounced lee wave pattern was shown from a GOES satellite image of April 4, 1983. The ground truth data were then displayed via the PCDS to graphically demonstrate the increase in intensity and areal distribution of rainfall in the northern Peruvian area in the next 4 to 5 days.

A Stand-Alone Demography and Landscape Structure Module for Earth System Models: Integration with Inventory Data from Temperate and Boreal Forests

NASA Astrophysics Data System (ADS)

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

2014-12-01

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.

Spatial Organization In Europe of Decadal and Interdecadal Fluctuations In Annual Rainfall

NASA Astrophysics Data System (ADS)

Lucero, O. A.; Rodriguez, N. C.

In this research the spatial patterns of decadal and bidecadal fluctuations in annual rainfall in Europe are identified. Filtering of time series of anomaly of annual rainfall is carried out using the Morlet wavelet technique. Reconstruction is achieved by sum- ming the contributions from bands of wavelet timescales; the decadal band and the bidecadal band are composed of contributions from the band of (10- to 17-year] and (17- to 27- year] timescales respectively. Results indicate that 1) the spatial organi- zation of decadal and bidecadal components of annual rainfall are standing wave-like organized patterns. Three standing decadal fluctuations zonally aligned formed the spatial pattern from 1900 until 1931; thereafter the pattern changed into a NW-SE orientation. The decadal band shows an average 12-year period. 2) The spatial orga- nization of bidecadal component was composed of three standing fluctuations since 1903 to 1986. After 1987 two standing bidecadal fluctuations were located on Europe. The orientation of bidecadal fluctuations changed during the period under study. Until 1913 the spatial pattern of the bidecadal component was zonally aligned. Since 1913 until 1986 the three bidecadal fluctuations composing the spatial pattern were aligned SW U NE; starting 1987 the spatial pattern is composed of two standing fluctuations zonally aligned. The bidecadal spatial pattern shows an average period of 20- to 22- year length. 3) At decadal and bidecadal timescales, the first principal component of the spatial field of anomaly of annual rainfall and the NAO index are connected. The upper positive third (lower negative third) of values of first principal component are indicative of extensive area with positive (negative) anomaly of annual rainfall. 4) At decadal timescale the relative phase between the first PC and the NAO index changes through the period under study; these changes define three regimes: 1) Dur- ing the regime covering the period 1900 (start of period under study) to about 1945, at the time of peak values of decadal NAO-index it takes place a transition between extremes (a neutral state) of the decadal rainfall spatial pattern (first PC takes small absolute values). Besides, for positive (negative) peak value of NAO index the spatial pattern of annual rainfall is evolving toward an area of predominantly positive (nega- tive) anomaly. 2) The second regime starts about 1946 and reaches up to early 1980s. At the time of negative (positive) peak of decadal NAO there is a prevailing spatial pattern of positive (negative) anomaly of decadal rainfall. 3) The third regime starts 1 about late 1970s and reaches to the end of the period under study (in 1996). There is a change of relative phase within this period in late 1980s. In this regime a spatial pattern of prevailing positive or negative anomaly of decadal rainfall takes place dur- ing values of decadal NAO close to zero. 5) At bidecadal timescale the relative phase between the first PC and the NAO index remains almost constant through the period under study. The first PC of the transformed bidecadal component of annual rainfall anomaly attains its positive (negative) peak about three years before the bidecadal component of NAO reaches its negative (positive) peak. 2

Increase in flood risk resulting from climate change in a developed urban watershed - the role of storm temporal patterns

NASA Astrophysics Data System (ADS)

Hettiarachchi, Suresh; Wasko, Conrad; Sharma, Ashish

2018-03-01

The effects of climate change are causing more frequent extreme rainfall events and an increased risk of flooding in developed areas. Quantifying this increased risk is of critical importance for the protection of life and property as well as for infrastructure planning and design. The updated National Oceanic and Atmospheric Administration (NOAA) Atlas 14 intensity-duration-frequency (IDF) relationships and temporal patterns are widely used in hydrologic and hydraulic modeling for design and planning in the United States. Current literature shows that rising temperatures as a result of climate change will result in an intensification of rainfall. These impacts are not explicitly included in the NOAA temporal patterns, which can have consequences on the design and planning of adaptation and flood mitigation measures. In addition there is a lack of detailed hydraulic modeling when assessing climate change impacts on flooding. The study presented in this paper uses a comprehensive hydrologic and hydraulic model of a fully developed urban/suburban catchment to explore two primary questions related to climate change impacts on flood risk. (1) How do climate change effects on storm temporal patterns and rainfall volumes impact flooding in a developed complex watershed? (2) Is the storm temporal pattern as critical as the total volume of rainfall when evaluating urban flood risk? We use the NOAA Atlas 14 temporal patterns, along with the expected increase in temperature for the RCP8.5 scenario for 2081-2100, to project temporal patterns and rainfall volumes to reflect future climatic change. The model results show that different rainfall patterns cause variability in flood depths during a storm event. The changes in the projected temporal patterns alone increase the risk of flood magnitude up to 35 %, with the cumulative impacts of temperature rise on temporal patterns and the storm volume increasing flood risk from 10 to 170 %. The results also show that regional storage facilities are sensitive to rainfall patterns that are loaded in the latter part of the storm duration, while extremely intense short-duration storms will cause flooding at all locations. This study shows that changes in temporal patterns will have a significant impact on urban/suburban flooding and need to be carefully considered and adjusted to account for climate change when used for the design and planning of future storm water systems.

Variable rainfall intensity and tillage effects on runoff, sediment, and carbon losses from a loamy sand under simulated rainfall.

PubMed

Truman, C C; Strickland, T C; Potter, T L; Franklin, D H; Bosch, D D; Bednarz, C W

2007-01-01

The low-carbon, intensively cropped Coastal Plain soils of Georgia are susceptible to runoff, soil loss, and drought. Reduced tillage systems offer the best management tool for sustained row crop production. Understanding runoff, sediment, and chemical losses from conventional and reduced tillage systems is expected to improve if the effect of a variable rainfall intensity storm was quantified. Our objective was to quantify and compare effects of a constant (Ic) intensity pattern and a more realistic, observed, variable (Iv) rainfall intensity pattern on runoff (R), sediment (E), and carbon losses (C) from a Tifton loamy sand cropped to conventional-till (CT) and strip-till (ST) cotton (Gossypium hirsutum L.). Four treatments were evaluated: CT-Ic, CT-Iv, ST-Ic, and ST-Iv, each replicated three times. Field plots (n=12), each 2 by 3 m, were established on each treatment. Each 6-m2 field plot received simulated rainfall at a constant (57 mm h(-1)) or variable rainfall intensity pattern for 70 min (12-run ave.=1402 mL; CV=3%). The Iv pattern represented the most frequent occurring intensity pattern for spring storms in the region. Compared with CT, ST decreased R by 2.5-fold, E by 3.5-fold, and C by 7-fold. Maximum runoff values for Iv events were 1.6-fold higher than those for Ic events and occurred 38 min earlier. Values for Etot and Ctot for Iv events were 19-36% and 1.5-fold higher than corresponding values for Ic events. Values for Emax and Cmax for Iv events were 3-fold and 4-fold higher than corresponding values for Ic events. Carbon enrichment ratios (CER) were or=1.0 for CT plots (except for first 20 min). Maximum CER for CT-Ic, CT-Iv, ST-Ic, and ST-Iv were 2.0, 2.2, 1.0, and 1.2, respectively. Transport of sediment, carbon, and agrichemicals would be better understood if variable rainfall intensity patterns derived from natural rainfall were used in rainfall simulations to evaluate their fate and transport from CT and ST systems.

Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

NASA Astrophysics Data System (ADS)

Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye; Lillo-Saavedra, Mario; Lagos, Octavio

2017-04-01

Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and for the case of the two long-term products the applicability for agricultural drought were evaluated when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in situ rainfall measurements across Chile were initially compared to the satellite data. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite products, and nine statistics were used to evaluate their performance to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze these datasets to better understand their similarities and differences in characterizing rainfall patterns across Chile. Monthly analysis showed that all satellite products highly overestimated rainfall in the arid North zone. However, there were no major difference between all three products from North to South-Central zones. Though, in the South zone, PERSIANN-CDR shows the lowest fit with high underestimation, while CHIRPS 2.0 and TMPA 3B43 v7 had better agreement with in situ measurements. The accuracy of satellite products were highly dependent on the amount of monthly rainfall with the best results found during winter seasons and in zones (Central to South) with higher amounts of precipitation. PERSIANN-CDR and CHIRPS 2.0 were used to derive SPI at time-scale of 1, 3 and 6 months, both satellite products presented similar results when it was compared in situ against satellite SPI's. Because of its higher spatial resolution that allows better characterizing of spatial variation in precipitation pattern, the CHIRPS 2.0 was used to mapping the SPI-3 over Chile. The results of this study show that in order to use the CHIRPS 2.0 and PERSIANN-CDR datasets in Chile to monitor spatial patterns in the rainfall and drought intensity conditions, these products should be calibrated to adjust for the overestimation/underestimation of rainfall geographically specially in the North zone and seasonally during the summer and spring months in the other zones.

Time scales of biogeochemical and organismal responses to individual precipitation events

NASA Astrophysics Data System (ADS)

von Fischer, J. C.; Angert, A. L.; Augustine, D. J.; Brown, C.; Dijkstra, F. A.; Derner, J. D.; Hufbauer, R. A.; Fierer, N.; Milchunas, D. G.; Moore, J. C.; Steltzer, H.; Wallenstein, M. D.

2010-12-01

In temperate grasslands, spatial and intra-annual variability in the activity of plants and microbes are structured by patterns in the precipitation regime. While the effects of total annual precipitation have been well-explored, the ecological dynamics associated with individual precipitation events have not. Rainfall events induce a short-term pulse of soil respiration that may or may not be followed by stimulation of plant photosynthetic activity and growth. Because the underlying heterotrophic and autotrophic responses are interactive, respond over unique timescales and are sensitive to precipitation magnitude, it remains difficult to predict the hydrologic effects on net CO2 exchange. To develop a better mechanistic understanding of these processes, we conducted a synthetic, multi-investigator experiment to characterize the ecosystem responses to rainfall events of different sizes. Our work was conducted on the Shortgrass Steppe (SGS) LTER site over 7 days in June 2009, using 1cm and 2cm rainfall events, with controls and each treatment replicated 5 times in 2m x 2m plots. Our observations revealed both expected responses of plant activity and soil respiration, and surprising patterns in microbial enzyme activity and soil fauna population densities. Coupled with observed dynamics in 15N partitioning and kinetics, our findings provide empirical timescales for the complex ecological interactions that underlie the ecosystem responses to rainfall events. These results can be used to inform a new generation of ecosystem simulation models to more explicitly consider the time lags and interactions of different functional groups.

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.

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

NASA Astrophysics Data System (ADS)

Matsumoto, Kengo; Kato, Kuranoshin; Otani, Kazuo

2017-04-01

In East Asia the significant subtropical frontal zone called the Meiyu (in China) / Baiu (in Japan) appears in early summer (just before the midsummer) and the huge rainfall is brought due to the frequent appearance of the "heavy rainfall days" (referred to as HRDs hereafter) mainly in that western part. On the other hand, large-scale fields around the front in eastern Japan is rather different from that in western Japan but the total precipitation in the eastern Japan is still considerable compared to that in the other midlatitude regions. Thus, it is also interesting to examine how the rainfall characteristics and large-scale atmospheric fields on HRDs (with more than 50 mm/day) in the eastern Japan in the mature stage of the Baiu season (16 June 15 July), together with those in midsummer (1 31 August). Based on such scientific background, further analyses were performed in this study mainly with the daily and the hourly precipitation data and the NCEP/NCAR re-analysis date from 1971 to 2010, succeeding to our previous results (e.g., EGU2015). As reported at EGU2014 and 2015, about half of HRDs at Tokyo (eastern Japan) were related to the typhoon even in the Baiu season. Interestingly, half of HRDs were characterized by the large contribution of moderate rain less than 10 mm/h. While, the precipitation on HRDs at Tokyo in midsummer was mainly brought by the intense rainfall with more than 10 mm/h, in association with the typhoons. In the present study, we examined the composite meridional structure of the rainfall area along 140E. In the pattern only associated with a typhoons in the Baiu season (Pattern A), the heavy rainfall area (more than 50 mm/day) with large contribution of the intense rain (stronger than 10 mm/h) showed rather wide meridional extension. The area was characterized by the duration of the intermittent enhancement of the rainfall. In the pattern associated with a typhoon and a front (Pattern B), while the contribution ratio of the rainfall more than 10mm/h was large in the southern half of the heavy rainfall area, moderate rain with less than 10 mm/h contributed greatly to the total rainfall in the northern half. In Patter B, that heavy rainfall area was located just in the area with strong low-level warm advection around the Baiu front to the east of the typhoon. The warm advection near the heavy rainfall area was also found in Pattern A, the heavy rainfall occurred just on the southwest of the large advection. It is noted that, although the very warm humid air can intrude northward by the strong S-ly wind to the east of the typhoon in both Pattern A and B, the low-level baroclinicity around the eastern Japan was stronger in Pattern B. In midsummer, the similar situations to while the "Pattern B"-like situation was not seen. This might be greatly reflected by the seasonal change in the southern boundary of the Okhotsk air mass from the Baiu to midsummer and we will also examine that in the future.

Indian Ocean dipole and rainfall drive a Moran effect in East Africa malaria transmission.

PubMed

Chaves, Luis Fernando; Satake, Akiko; Hashizume, Masahiro; Minakawa, Noboru

2012-06-15

Patterns of concerted fluctuation in populations-synchrony-can reveal impacts of climatic variability on disease dynamics. We examined whether malaria transmission has been synchronous in an area with a common rainfall regime and sensitive to the Indian Ocean Dipole (IOD), a global climatic phenomenon affecting weather patterns in East Africa. We studied malaria synchrony in 5 15-year long (1984-1999) monthly time series that encompass an altitudinal gradient, approximately 1000 m to 2000 m, along Lake Victoria basin. We quantified the association patterns between rainfall and malaria time series at different altitudes and across the altitudinal gradient encompassed by the study locations. We found a positive seasonal association of rainfall with malaria, which decreased with altitude. By contrast, IOD and interannual rainfall impacts on interannual disease cycles increased with altitude. Our analysis revealed a nondecaying synchrony of similar magnitude in both malaria and rainfall, as expected under a Moran effect, supporting a role for climatic variability on malaria epidemic frequency, which might reflect rainfall-mediated changes in mosquito abundance. Synchronous malaria epidemics call for the integration of knowledge on the forcing of malaria transmission by environmental variability to develop robust malaria control and elimination programs.

Hydrometeorological and statistical analyses of heavy rainfall in Midwestern USA

NASA Astrophysics Data System (ADS)

Thorndahl, S.; Smith, J. A.; Krajewski, W. F.

2012-04-01

During the last two decades the mid-western states of the United States of America has been largely afflicted by heavy flood producing rainfall. Several of these storms seem to have similar hydrometeorological properties in terms of pattern, track, evolution, life cycle, clustering, etc. which raise the question if it is possible to derive general characteristics of the space-time structures of these heavy storms. This is important in order to understand hydrometeorological features, e.g. how storms evolve and with what frequency we can expect extreme storms to occur. In the literature, most studies of extreme rainfall are based on point measurements (rain gauges). However, with high resolution and quality radar observation periods exceeding more than two decades, it is possible to do long-term spatio-temporal statistical analyses of extremes. This makes it possible to link return periods to distributed rainfall estimates and to study precipitation structures which cause floods. However, doing these statistical frequency analyses of rainfall based on radar observations introduces some different challenges, converting radar reflectivity observations to "true" rainfall, which are not problematic doing traditional analyses on rain gauge data. It is for example difficult to distinguish reflectivity from high intensity rain from reflectivity from other hydrometeors such as hail, especially using single polarization radars which are used in this study. Furthermore, reflectivity from bright band (melting layer) should be discarded and anomalous propagation should be corrected in order to produce valid statistics of extreme radar rainfall. Other challenges include combining observations from several radars to one mosaic, bias correction against rain gauges, range correction, ZR-relationships, etc. The present study analyzes radar rainfall observations from 1996 to 2011 based the American NEXRAD network of radars over an area covering parts of Iowa, Wisconsin, Illinois, and Lake Michigan. The radar observations are processed using Hydro-NEXRAD algorithms in order to produce rainfall estimates with a spatial resolution of 1 km and a temporal resolution of 15 min. The rainfall estimates are bias-corrected on a daily basis using a network of rain gauges. Besides a thorough evaluation of the different challenges in investigating heavy rain as described above the study includes suggestions for frequency analysis methods as well as studies of hydrometeorological features of single events.

Water Budget for the Island of Kauai, Hawaii

USGS Publications Warehouse

Shade, Patricia J.

1995-01-01

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

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Hong, Yang; Huffman, George J.

2006-01-01

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

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.

Pluviometric characterization of the Coca river basin by using a stochastic rainfall model

NASA Astrophysics Data System (ADS)

González-Zeas, Dunia; Chávez-Jiménez, Adriadna; Coello-Rubio, Xavier; Correa, Ángel; Martínez-Codina, Ángela

2014-05-01

An adequate design of the hydraulic infrastructures, as well as, the prediction and simulation of a river basin require historical records with a greater temporal and spatial resolution. However, the lack of an extensive network of precipitation data, the short time scale data and the incomplete information provided by the available rainfall stations limit the analysis and design of complex hydraulic engineering systems. As a consequence, it is necessary to develop new quantitative tools in order to face this obstacle imposed by ungauged or poorly gauged basins. In this context, the use of a spatial-temporal rainfall model allows to simulate the historical behavior of the precipitation and at the same time, to obtain long-term synthetic series that preserve the extremal behavior. This paper provides a characterization of the precipitation in the Coca river basin located in Ecuador by using RainSim V3, a robust and well tested stochastic rainfall model based on a spatial-temporal Neyman-Scott rectangular pulses process. A preliminary consistency analysis of the historical rainfall data available has been done in order to identify climatic regions with similar precipitation behavior patterns. Mean and maximum yearly and monthly fields of precipitation of high resolution spaced grids have been obtained through the use of interpolation techniques. According to the climatological similarity, long time series of daily temporal resolution of precipitation have been generated in order to evaluate the model skill in capturing the structure of daily observed precipitation. The results show a good performance of the model in reproducing very well the gross statistics, including the extreme values of rainfall at daily scale. The spatial pattern represented by the observed and simulated precipitation fields highlights the existence of two important regions characterized by different pluviometric comportment, with lower precipitation in the upper part of the basin and higher precipitation in the lower part of the basin.

Statistical characterization of spatial patterns of rainfall cells in extratropical cyclones

NASA Astrophysics Data System (ADS)

Bacchi, Baldassare; Ranzi, Roberto; Borga, Marco

1996-11-01

The assumption of a particular type of distribution of rainfall cells in space is needed for the formulation of several space-time rainfall models. In this study, weather radar-derived rain rate maps are employed to evaluate different types of spatial organization of rainfall cells in storms through the use of distance functions and second-moment measures. In particular the spatial point patterns of the local maxima of rainfall intensity are compared to a completely spatially random (CSR) point process by applying an objective distance measure. For all the analyzed radar maps the CSR assumption is rejected, indicating that at the resolution of the observation considered, rainfall cells are clustered. Therefore a theoretical framework for evaluating and fitting alternative models to the CSR is needed. This paper shows how the "reduced second-moment measure" of the point pattern can be employed to estimate the parameters of a Neyman-Scott model and to evaluate the degree of adequacy to the experimental data. Some limitations of this theoretical framework, and also its effectiveness, in comparison to the use of scaling functions, are discussed.

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.

Influences of the MJO on the space-time organization of tropical convection

NASA Astrophysics Data System (ADS)

Dias, Juliana; Sakaeda, Naoko; Kiladis, George N.; Kikuchi, Kazuyoshi

2017-08-01

The fact that the Madden-Julian Oscillation (MJO) is characterized by large-scale patterns of enhanced tropical rainfall has been widely recognized for decades. However, the precise nature of any two-way feedback between the MJO and the properties of smaller-scale organization that makes up its convective envelope is not well understood. Satellite estimates of brightness temperature are used here as a proxy for tropical rainfall, and a variety of diagnostics are applied to determine the degree to which tropical convection is affected either locally or globally by the MJO. To address the multiscale nature of tropical convective organization, the approach ranges from space-time spectral analysis to an object-tracking algorithm. In addition to the intensity and distribution of global tropical rainfall, the relationship between the MJO and other tropical processes such as convectively coupled equatorial waves, mesoscale convective systems, and the diurnal cycle of tropical convection is also analyzed. The main findings of this paper are that, aside from the well-known increase in rainfall activity across scales within the MJO convective envelope, the MJO does not favor any particular scale or type of organization, and there is no clear signature of the MJO in terms of the globally integrated distribution of brightness temperature or rainfall.

Influence of large-scale climate modes on dynamical complexity patterns of Indian Summer Monsoon rainfall

NASA Astrophysics Data System (ADS)

Papadimitriou, Constantinos; Donner, Reik V.; Stolbova, Veronika; Balasis, Georgios; Kurths, Jürgen

2015-04-01

Indian Summer monsoon is one of the most anticipated and important weather events with vast environmental, economical and social effects. Predictability of the Indian Summer Monsoon strength is crucial question for life and prosperity of the Indian population. In this study, we are attempting to uncover the relationship between the spatial complexity of Indian Summer Monsoon rainfall patterns, and the monsoon strength, in an effort to qualitatively determine how spatial organization of the rainfall patterns differs between strong and weak instances of the Indian Summer Monsoon. Here, we use observational satellite data from 1998 to 2012 from the Tropical Rainfall Measuring Mission (TRMM 3B42V7) and reanalysis gridded daily rainfall data for a time period of 57 years (1951-2007) (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE). In order to capture different aspects of the system's dynamics, first, we convert rainfall time series to binary symbolic sequences, exploring various thresholding criteria. Second, we apply the Shannon entropy formulation (in a block-entropy sense) using different measures of normalization of the resulting entropy values. Finally, we examine the effect of various large-scale climate modes such as El-Niño-Southern Oscillation, North Atlantic Oscillation, and Indian Ocean Dipole, on the emerging complexity patterns, and discuss the possibility for the utilization of such pattern maps in the forecasting of the spatial variability and strength of the Indian Summer Monsoon.

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 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.

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.

Site-specific climate analysis elucidates revegetation challenges for post-mining landscapes in eastern Australia

NASA Astrophysics Data System (ADS)

Audet, P.; Arnold, S.; Lechner, A. M.; Baumgartl, T.

2013-10-01

In eastern Australia, the availability of water is critical for the successful rehabilitation of post-mining landscapes and climatic characteristics of this diverse geographical region are closely defined by factors such as erratic rainfall and periods of drought and flooding. Despite this, specific metrics of climate patterning are seldom incorporated into the initial design of current post-mining land rehabilitation strategies. Our study proposes that a few common rainfall parameters can be combined and rated using arbitrary rainfall thresholds to characterise bioregional climate sensitivity relevant to the rehabilitation these landscapes. This approach included assessments of annual rainfall depth, average recurrence interval of prolonged low intensity rainfall, average recurrence intervals of short or prolonged high intensity events, median period without rain (or water-deficit) and standard deviation for this period in order to address climatic factors such as total water availability, seasonality and intensity - which were selected as potential proxies of both short- and long-term biological sensitivity to climate within the context of post-disturbance ecological development and recovery. Following our survey of available climate data, we derived site "climate sensitivity" indexes and compared the performance of 9 ongoing mine sites: Weipa, Mt. Isa and Cloncurry, Eromanga, Kidston, the Bowen Basin (Curragh), Tarong, North Stradbroke Island, and the Newnes Plateau. The sites were then ranked from most-to-least sensitive and compared with natural bioregional patterns of vegetation density using mean NDVI. It was determined that regular rainfall and relatively short periods of water-deficit were key characteristics of sites having less sensitivity to climate - as found among the relatively more temperate inland mining locations. Whereas, high rainfall variability, frequently occurring high intensity events, and (or) prolonged seasonal drought were primary indicators of sites having greater sensitivity to climate - as found among the semi-arid central-inland sites. Overall, the manner in which these climatic factors are identified and ultimately addressed by land managers and rehabilitation practitioners could be a key determinant of achievable success at given locations at the planning stages of rehabilitation design.

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.

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

NASA Astrophysics Data System (ADS)

Chooi Tan, Kok

2018-04-01

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

Models for short term malaria prediction in Sri Lanka

PubMed Central

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

2008-01-01

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

How predictable is the anomaly pattern of the Indian summer rainfall?

NASA Astrophysics Data System (ADS)

Li, Juan; Wang, Bin

2016-05-01

Century-long efforts have been devoted to seasonal forecast of Indian summer monsoon rainfall (ISMR). Most studies of seasonal forecast so far have focused on predicting the total amount of summer rainfall averaged over the entire India (i.e., all Indian rainfall index-AIRI). However, it is practically more useful to forecast anomalous seasonal rainfall distribution (anomaly pattern) across India. The unknown science question is to what extent the anomalous rainfall pattern is predictable. This study attempted to address this question. Assessment of the 46-year (1960-2005) hindcast made by the five state-of-the-art ENSEMBLE coupled dynamic models' multi-model ensemble (MME) prediction reveals that the temporal correlation coefficient (TCC) skill for prediction of AIRI is 0.43, while the area averaged TCC skill for prediction of anomalous rainfall pattern is only 0.16. The present study aims to estimate the predictability of ISMR on regional scales by using Predictable Mode Analysis method and to develop a set of physics-based empirical (P-E) models for prediction of ISMR anomaly pattern. We show that the first three observed empirical orthogonal function (EOF) patterns of the ISMR have their distinct dynamical origins rooted in an eastern Pacific-type La Nina, a central Pacific-type La Nina, and a cooling center near dateline, respectively. These equatorial Pacific sea surface temperature anomalies, while located in different longitudes, can all set up a specific teleconnection pattern that affects Indian monsoon and results in different rainfall EOF patterns. Furthermore, the dynamical models' skill for predicting ISMR distribution primarily comes primarily from these three modes. Therefore, these modes can be regarded as potentially predictable modes. If these modes are perfectly predicted, about 51 % of the total observed variability is potentially predictable. Based on understanding the lead-lag relationships between the lower boundary anomalies and the predictable modes, a set of P-E models is established to predict the principal component of each predictable mode, so that the ISMR anomaly pattern can be predicted by using the sum of the predictable modes. Three validation schemes are used to assess the performance of the P-E models' hindcast and independent forecast. The validated TCC skills of the P-E model here are more than doubled that of dynamical models' MME hindcast, suggesting a large room for improvement of the current dynamical prediction. The methodology proposed here can be applied to a wide range of climate prediction and predictability studies. The limitation and future improvement are also discussed.

Spatio-temporal analysis of sub-hourly rainfall over Mumbai, India: Is statistical forecasting futile?

NASA Astrophysics Data System (ADS)

Singh, Jitendra; Sekharan, Sheeba; Karmakar, Subhankar; Ghosh, Subimal; Zope, P. E.; Eldho, T. I.

2017-04-01

Mumbai, the commercial and financial capital of India, experiences incessant annual rain episodes, mainly attributable to erratic rainfall pattern during monsoons and urban heat-island effect due to escalating urbanization, leading to increasing vulnerability to frequent flooding. After the infamous episode of 2005 Mumbai torrential rains when only two rain gauging stations existed, the governing civic body, the Municipal Corporation of Greater Mumbai (MCGM) came forward with an initiative to install 26 automatic weather stations (AWS) in June 2006 (MCGM 2007), which later increased to 60 AWS. A comprehensive statistical analysis to understand the spatio-temporal pattern of rainfall over Mumbai or any other coastal city in India has never been attempted earlier. In the current study, a thorough analysis of available rainfall data for 2006-2014 from these stations was performed; the 2013-2014 sub-hourly data from 26 AWS was found useful for further analyses due to their consistency and continuity. Correlogram cloud indicated no pattern of significant correlation when we considered the closest to the farthest gauging station from the base station; this impression was also supported by the semivariogram plots. Gini index values, a statistical measure of temporal non-uniformity, were found above 0.8 in visible majority showing an increasing trend in most gauging stations; this sufficiently led us to conclude that inconsistency in daily rainfall was gradually increasing with progress in monsoon. Interestingly, night rainfall was lesser compared to daytime rainfall. The pattern-less high spatio-temporal variation observed in Mumbai rainfall data signifies the futility of independently applying advanced statistical techniques, and thus calls for simultaneous inclusion of physics-centred models such as different meso-scale numerical weather prediction systems, particularly the Weather Research and Forecasting (WRF) model.

Application of Clustering Algorithms to Observed and Simulated Daily Precipitation over the Tropical and Southern Pacific Ocean

NASA Astrophysics Data System (ADS)

Pike, M.; Lintner, B. R.

2017-12-01

We apply two data organization methods, self-organizing maps (SOMs) and k-means clustering with linear unidimensional scaling (k-means+LUS), to identify and organize the spatial patterns inherent in daily austral summer (December-January-February or DJF) rainfall over the tropical and southern Pacific Ocean basins from Tropical Rainfall Measuring Mission (TRMM) satellite observations. For either a 2x2 SOM or k = 4 clustering of all available DJFs from 1998-2013, we find an El Niño/Southern Oscillation (ENSO) signature, with pairs of maps reflecting either El Niño or La Niña phase conditions. Within each of the ENSO-phase pairs, one map favors Intertropical Convergence Zone (ITCZ)-active conditions, in which precipitation is more intense over the ITCZ region compared to the South Pacific Convergence Zone (SPCZ) region, while the remaining one is SPCZ-active. The SPCZ-active maps show a spatial translation of the principal SPCZ diagonal consistent with the impacts of El Niño/Southern Oscillation (ENSO) or analogous low-frequency modes of variability on the SPCZ as shown in prior studies. Because of the dominant impact of ENSO, we further apply these methods separately on subsets of rainfall data for each ENSO phase. While the overall position of the SPCZ is sensitive to the phase of ENSO, within each phase, more- or less-steeply sloped SPCZ diagonals may occur. Thus, while the mean position of the SPCZ is largely controlled by ENSO phase, the distinct orientations of the SPCZ within the same ENSO phase point to higher-frequency modulation of SPCZ slope. To investigate the nature of these further, we construct composites of pressure-level winds and specific humidity from the Climate Forecast System Reanalysis (CFSR) associated with the rainfall patterns. For either SOM or kmeans-based composites, we find large-scale dynamics and moisture signatures that are consistent with the rainfall patterns and which we interpret in terms of previously described mechanisms of SPCZ variability. By progressively increasing the number of clusters, patterns reminiscent of Rossby wave propagation begin to emerge. To further investigate the connection to propagation, we examine upper air vorticity composites in relationship to the periodic enhancements of SPCZ precipitation which appear to be independent of ENSO.

Identification of deficiencies in seasonal rainfall simulated by CMIP5 climate models

NASA Astrophysics Data System (ADS)

Dunning, Caroline M.; Allan, Richard P.; Black, Emily

2017-11-01

An objective technique for analysing seasonality, in terms of regime, progression and timing of the wet seasons, is applied in the evaluation of CMIP5 simulations across continental Africa. Atmosphere-only and coupled integrations capture the gross observed patterns of seasonal progression and give mean onset/cessation dates within 18 days of the observational dates for 11 of the 13 regions considered. Accurate representation of seasonality over central-southern Africa and West Africa (excluding the southern coastline) adds credence for future projected changes in seasonality here. However, coupled simulations exhibit timing biases over the Horn of Africa, with the long rains 20 days late on average. Although both sets of simulations detect biannual rainfall seasonal cycles for East and Central Africa, coupled simulations fail to capture the biannual regime over the southern West African coastline. This is linked with errors in the Gulf of Guinea sea surface temperature (SST) and deficient representation of the SST/rainfall relationship.

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.

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.

Observations of cloud and rainfall enhancement over irrigated agriculture in an arid environment

NASA Astrophysics Data System (ADS)

Garcia-Carreras, Luis; Marsham, John H.; Spracklen, Dominick V.

2017-04-01

The impact of irrigated agriculture on clouds and rainfall remains uncertain, particularly in less studied arid regions. Irrigated crops account for 20% of global cropland area, and non-renewable groundwater accounts for 20% of global irrigation water demand. Quantifying the feedbacks between agriculture and the atmosphere are therefore not only necessary to better understand the climate impacts of land-use change, but are also crucial for predicting long-term water use in water-scarce regions. Here we use high spatial-resolution satellite data to show the impact of irrigated crops in the arid environment of northern Saudi Arabia on cloud cover and rainfall patterns. Land surface temperatures over the crops are 5-10 K lower than their surroundings, linked to evapotranspiration rates of up to 20 mm/ month. Daytime cloud cover is up to 30% higher over the cropland compared to its immediate surroundings, and this enhancement is highly correlated with the seasonal variability in leaf area index. The cloud enhancement is associated with a much more rapid cloud cloud development during the morning. Afternoon rainfall is 85% higher over, and just downwind, of the cropland during the growing season, although rainfall remains very low in absolute terms. The feedback sign we find is the opposite to what has been observed in tropical and semiarid regions, where temperature gradients promote convergence and clouds on the warmer side of land-surface type discontinuities. This suggests that different processes are responsible for the land-atmosphere feedback in very dry environments, where lack of moisture may be a stronger constraint. Increased cloud and rainfall, and associated increases in diffuse radiation and reductions in temperature, can affect vegetation growth thus producing an internal feedback. These effects will therefore need to be taken into account to properly assess the impact of climate change on crop productivity and water use, as well as how global land-use change affects climate.

Fluvial signatures of modern and paleo orographic rainfall gradients

NASA Astrophysics Data System (ADS)

Schildgen, Taylor; Strecker, Manfred

2016-04-01

The morphology of river profiles is intimately linked to both climate and tectonic forcing. While much interest recently has focused on how river profiles can be inverted to derive uplift histories, here we show how in regions of strong orographic rainfall gradients, rivers may primarily record spatial patterns of precipitation. As a case study, we examine the eastern margin of the Andean plateau in NW Argentina, where the outward (eastward) growth of a broken foreland has led to a eastward shift in the main orographic rainfall gradient over the last several million years. Rivers influenced by the modern rainfall gradient are characterized by normalized river steepness values in tributary valleys that closely track spatial variations in rainfall, with higher steepness values in drier areas and lower steepness values in wetter areas. The same river steepness pattern has been predicted in landscape evolution models that apply a spatial gradient in rainfall to a region of uniform erosivity and uplift rate (e.g., Han et al., 2015). Also, chi plots from river networks on individual ranges affected by the modern orographic rainfall reveal patterns consistent with assymmetric precipitation across the range: the largest channels on the windward slopes are characterized by capture, while the longest channels on the leeward slopes are dominated by beheadings. Because basins on the windward side both lengthen and widen, tributary channels in the lengthening basins are characterized by capture, while tributary channels from neighboring basins on the windward side are dominated by beheadings. These patterns from the rivers influenced by the modern orographic rainfall gradient provide a guide for identifying river morphometric signatures of paleo orographic rainfall gradients. Mountain ranges to the west of the modern orographic rainfall have been interpreted to mark the location of orographic rainfall in the past, but these ranges are now in spatially near-uniform semi-arid to arid precipitation regimes. Indeed, despite uniform lithology and uplift history, we see patterns in river steepness values and in chi plots that are consistest a rainfall gradient on the (former) windward side of the range and asymmetric precipitation across the range. We suggest that morphological aspects of the river networks in such regions are dominated by their history of changing climate. These morphologic signatures appear to persist for millions of years in NW Argentina, most likely because the transition from a wetter to a drier climate has prevented a rapid readjustment to new forcing conditions. Reference: Han, J., Gasparini, N.M., and Johnson, J.P., 2015, Measuring the imprint of orographic rainfall gradients on the morphology of steady-state numerical fluvial landscapes. Earth Surf. Process. Landforms, 40(10), 1334-1350.

Sunspots, El Niño, and the levels of Lake Victoria, East Africa

NASA Astrophysics Data System (ADS)

Stager, J. Curt; Ruzmaikin, Alexander; Conway, Declan; Verburg, Piet; Mason, Peter J.

2007-08-01

An association of high sunspot numbers with rises in the level of Lake Victoria, East Africa, has been the focus of many investigations and vigorous debate during the last century. In this paper, we show that peaks in the ~11-year sunspot cycle were accompanied by Victoria level maxima throughout the 20th century, due to the occurrence of positive rainfall anomalies ~1 year before solar maxima. Similar patterns also occurred in at least five other East African lakes, which indicates that these sunspot-rainfall relationships were broadly regional in scale. Although irradiance fluctuations associated with the sunspot cycle are weak, their effects on tropical rainfall could be amplified through interactions with sea surface temperatures and atmospheric circulation systems, including ENSO. If this Sun-rainfall relationship persists in the future, then sunspot cycles can be used for long-term prediction of precipitation anomalies and associated outbreaks of insect-borne disease in much of East Africa. In that case, unusually wet rainy seasons and Rift Valley Fever epidemics should occur a year or so before the next solar maximum, which is expected to occur in 2011-2012 AD.

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.

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.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.

PubMed

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

PubMed Central

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203

Tropospheric biennial oscillation and south Asian summer monsoon rainfall in a coupled model

NASA Astrophysics Data System (ADS)

Konda, Gopinadh; Chowdary, J. S.; Srinivas, G.; Gnanaseelan, C.; Parekh, Anant; Attada, Raju; Rama Krishna, S. S. V. S.

2018-06-01

In this study Tropospheric Biennial Oscillation (TBO) and south Asian summer monsoon rainfall are examined in the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFSv2) hindcast. High correlation between the observations and model TBO index suggests that the model is able to capture most of the TBO years. Spatial patterns of rainfall anomalies associated with positive TBO over the south Asian region are better represented in the model as in the observations. However, the model predicted rainfall anomaly patterns associated with negative TBO years are improper and magnitudes are underestimated compared to the observations. It is noted that positive (negative) TBO is associated with La Niña (El Niño) like Sea surface temperature (SST) anomalies in the model. This leads to the fact that model TBO is El Niño-Southern Oscillation (ENSO) driven, while in the observations Indian Ocean Dipole (IOD) also plays a role in the negative TBO phase. Detailed analysis suggests that the negative TBO rainfall anomaly pattern in the model is highly influenced by improper teleconnections allied to IOD. Unlike in the observations, rainfall anomalies over the south Asian region are anti-correlated with IOD index in CFSv2. Further, summer monsoon rainfall over south Asian region is highly correlated with IOD western pole than eastern pole in CFSv2 in contrast to the observations. Altogether, the present study highlights the importance of improving Indian Ocean SST teleconnections to south Asian summer rainfall in the model by enhancing the predictability of TBO. This in turn would improve monsoon rainfall prediction skill of the model.

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.

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.

Population dynamics of two species of dragon lizards in arid Australia: the effects of rainfall.

PubMed

Dickman, Christopher R; Letnic, Mike; Mahon, Paul S

1999-05-01

The population dynamics of two species of agamid (dragon) lizards were studied in the Simpson Desert, central Australia, over a period of 7 years, and modelled in relation to rainfall. Both species have annual life cycles, with adults predominating during the breeding season in spring and summer and juveniles predominating in other seasons. Within years, juvenile abundance in both species in autumn and winter was related most strongly to rainfall in the preceding summer and autumn. This pattern suggests that rainfall enhances survival, growth and possibly clutch size and hatching success. Between years, however, rainfall drove successional change in the dominant plant species in the study area, spinifex Triodia basedowii, causing in turn a shift in the relative abundance of the two species. Thus, the central netted dragon Ctenophorus nuchalis was most numerous in 1990 when vegetation cover was <10%, but declined dramatically in abundance after heavy rainfall at the end of that year. In contrast, the military dragon C. isolepis achieved greatest abundance following heavy rains in the summers of 1990 and 1994, when spinifex cover increased to >20%, and remained numerically dominant for much of the study. We suggest that drought-wet cycles periodically reverse the dominance of the two species of Ctenophorus, and perhaps of other lizard species also, thus enhancing local species diversity over time. Further long-term studies are needed to document the population dynamics of other species, and to identify the factors that influence them.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

A Multiplicative Cascade Model for High-Resolution Space-Time Downscaling of Rainfall

NASA Astrophysics Data System (ADS)

Raut, Bhupendra A.; Seed, Alan W.; Reeder, Michael J.; Jakob, Christian

2018-02-01

Distributions of rainfall with the time and space resolutions of minutes and kilometers, respectively, are often needed to drive the hydrological models used in a range of engineering, environmental, and urban design applications. The work described here is the first step in constructing a model capable of downscaling rainfall to scales of minutes and kilometers from time and space resolutions of several hours and a hundred kilometers. A multiplicative random cascade model known as the Short-Term Ensemble Prediction System is run with parameters from the radar observations at Melbourne (Australia). The orographic effects are added through multiplicative correction factor after the model is run. In the first set of model calculations, 112 significant rain events over Melbourne are simulated 100 times. Because of the stochastic nature of the cascade model, the simulations represent 100 possible realizations of the same rain event. The cascade model produces realistic spatial and temporal patterns of rainfall at 6 min and 1 km resolution (the resolution of the radar data), the statistical properties of which are in close agreement with observation. In the second set of calculations, the cascade model is run continuously for all days from January 2008 to August 2015 and the rainfall accumulations are compared at 12 locations in the greater Melbourne area. The statistical properties of the observations lie with envelope of the 100 ensemble members. The model successfully reproduces the frequency distribution of the 6 min rainfall intensities, storm durations, interarrival times, and autocorrelation function.

Eddy-induced salinity pattern in the North Pacific

NASA Astrophysics Data System (ADS)

Abe, H.; Ebuchi, N.; Ueno, H.; Ishiyama, H.; Matsumura, Y.

2017-12-01

This research examines spatio-temporal behavior of sea surface salinity (SSS) after intense rainfall events using observed data from Aquarius. Aquarius SSS in the North Pacific reveals one notable event in which SSS is locally freshened by intense rainfall. Although SSS pattern shortly after the rainfall reflects atmospheric pattern, its final form reflects ocean dynamic structure; an anticyclonic eddy. Since this anticyclonic eddy was located at SSS front created by precipitation, this eddy stirs the water in a clockwise direction. This eddy stirring was visible for several months. It is expected horizontal transport by mesoscale eddies would play significant role in determining upper ocean salinity structure.

Widespread decline of Congo rainforest greenness in the past decade.

PubMed

Zhou, Liming; Tian, Yuhong; Myneni, Ranga B; Ciais, Philippe; Saatchi, Sassan; Liu, Yi Y; Piao, Shilong; Chen, Haishan; Vermote, Eric F; Song, Conghe; Hwang, Taehee

2014-05-01

Tropical forests are global epicentres of biodiversity and important modulators of climate change, and are mainly constrained by rainfall patterns. The severe short-term droughts that occurred recently in Amazonia have drawn attention to the vulnerability of tropical forests to climatic disturbances. The central African rainforests, the second-largest on Earth, have experienced a long-term drying trend whose impacts on vegetation dynamics remain mostly unknown because in situ observations are very limited. The Congolese forest, with its drier conditions and higher percentage of semi-evergreen trees, may be more tolerant to short-term rainfall reduction than are wetter tropical forests, but for a long-term drought there may be critical thresholds of water availability below which higher-biomass, closed-canopy forests transition to more open, lower-biomass forests. Here we present observational evidence for a widespread decline in forest greenness over the past decade based on analyses of satellite data (optical, thermal, microwave and gravity) from several independent sensors over the Congo basin. This decline in vegetation greenness, particularly in the northern Congolese forest, is generally consistent with decreases in rainfall, terrestrial water storage, water content in aboveground woody and leaf biomass, and the canopy backscatter anomaly caused by changes in structure and moisture in upper forest layers. It is also consistent with increases in photosynthetically active radiation and land surface temperature. These multiple lines of evidence indicate that this large-scale vegetation browning, or loss of photosynthetic capacity, may be partially attributable to the long-term drying trend. Our results suggest that a continued gradual decline of photosynthetic capacity and moisture content driven by the persistent drying trend could alter the composition and structure of the Congolese forest to favour the spread of drought-tolerant species.

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.

The Complexities of Urban Flood Response: Hydrologic Analyses for the Charlotte, North Carolina Metropolitan Region

NASA Astrophysics Data System (ADS)

Zhou, Z.; Smith, J. A.; Yang, L.; Baeck, M. L.; Liu, S.; Ten Veldhuis, M. C.

2016-12-01

The objective of this study is to develop a broad characterization of land surface and hydrometeorological controls of urban flood frequency. We focus on a collection of "small" urban watersheds (with drainage area ranging from 7 to 200 km2) in Charlotte metropolitan region, North Carolina. These watersheds are contrasted by a variety of land surface properties, such as size, shape, land use/land cover type, impervious coverage pattern, stormwater infrastructure, etc. We carried out empirical analyses based on long-term (15 years), high-resolution (1 15 minutes) instantaneous USGS stream gaging observations as well as bias-corrected, high-resolution (1 km2, 15 min) radar rainfall fields developed through the Hydro-NEXRAD system. Extreme floods in Charlotte urban watersheds are primarily induced by a mixture of flood agents including warm season thunderstorms and tropical cyclones, which ultimately contributed to the upper-tail properties of flood frequency. Flood response in urban watersheds is dominantly dictated by space-time characteristics of rainfall, with relatively significant correlation between runoff and rainfall over more developed watersheds. The roles of antecedent soil moisture and stormwater management infrastructure in flood response are also contrasted across the urban watersheds. The largest variability of flood response, in terms of flood peak and timing, exists in the watershed at a scale of 100 km2. The scale-dependent hydrological response is closely related to the pattern and evolution of urban development across watersheds. Our analyses show the complexities of urban flood response in Charlotte metropolitan region. There are no simple metrics that could perfectly explain the contrasts in flood response across urban watersheds. Future research is directed towards sophisticated modeling studies for a predictive understanding of flood frequency in urban watersheds.

Modeling the risk of phosphorus runoff following single and split phosphorus fertilizer applications in two contrasting catchments.

PubMed

Burkitt, Lucy L; Dougherty, Warwick J; Corkrey, Ross; Broad, Shane T

2011-01-01

The potential loss of P in runoff is a function of the combined effects of fertilizer-soil interactions and climatic characteristics. In this study, we applied a Bayesian approach to experimental data to model the annualized long-term risk of P runoff following single and split P fertilizer applications using two example catchments with contrasting rainfall/runoff patterns. Split P fertilizer strategies are commonly used in intensive pasture production in Australia and our results showed that three applications of 13.3 kg P ha(-1) resulted in a greater risk of P runoff compared with a single application of 40 kg P ha(-1) when long-term surface runoff data were incorporated into a Bayesian P risk model. Splitting P fertilizer applications increased the likelihood of a coincidence of fertilizer application and runoff occurring. We found that the overall risk of P runoff is also increased in catchments where the rainfall/runoff pattern is less predictable, compared with catchments where rainfall/runoff is winter dominant. The findings of our study also question the effectiveness of current recommendations to avoid applying fertilizer if runoff is likely to occur in the next few days, as we found that total P concentrations at the half-life were still very high (18.2 and 8.2 mg P L(-1)) following single and split P treatments, respectively. Data from the current study also highlight that omitting P fertilizer on soils that already have adequate soil test P concentrations is an effective method of reducing P loss in surface runoff. If P fertilizer must be applied, we recommend less frequent applications and only during periods of the year when the risk of surface P runoff is low.

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

NASA Astrophysics Data System (ADS)

Watterson, I. G.

2018-05-01

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

Effects of the Pacific Decadal Oscillation and global warming on drought in the US Southwest

NASA Astrophysics Data System (ADS)

Grossmann, I.

2012-12-01

Droughts are among the most expensive weather related disasters in the US. In the semi-arid regions of the US Southwest, where average annual rainfall is already very low, multiyear droughts can have large economic, societal and ecological impacts. The US Southwest relies on annual precipitation maxima during winter and the North American Monsoon (NAM), both of which undergo considerable interannual variability associated with large-scale climate patterns, in particular ENSO, the Pacific Decadal Oscillation (PDO) and the Atlantic Multidecadal Oscillation (AMO). The region is also part of the subtropical belt projected to become more arid in a warming climate. These impacts have not been combined and compared with projections of long-term variations due to natural climate patterns. This study addresses this need by deriving future projections of rainfall departures for Arizona and New Mexico with the PDO and AMO and combining these with projected global warming impacts. Depending on the precipitation dataset used, the impacts for the ongoing negative PDO phase are projected to be between 1-1.6 times as large as the multi-model means projection of precipitation minus evaporation during 2020-2040 in the IPCC A1B Scenario. The projected precipitation impacts of a combined negative PDO and positive AMO phase are between 1-2 times as large as the A1B Scenario projection. The study also advances earlier work by addressing problems in detecting the effect of the PDO on precipitation. Given the different mechanisms with which the PDO affects precipitation during winter and the NAM season, precipitation impacts are here investigated on a monthly scale. The impacts of the PDO also vary with other climate patterns. This can be partly addressed by investigating precipitation departures in dependence on other patterns. It is further found that the long-term effect of the PDO can be more clearly separated from short-term variability by considering return periods of multi-year drought measures rather than return periods of simple drought measures.

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...

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

PubMed

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

The association of weather and mortality in Bangladesh from 1983–2009

PubMed Central

Alam, Nurul; Begum, Dilruba; Streatfield, Peter Kim

2012-01-01

Introduction The association of weather and mortality have not been widely studied in subtropical monsoon regions, particularly in Bangladesh. This study aims to assess the association of weather and mortality (measured with temperature and rainfall), adjusting for time trend and seasonal patterns in Abhoynagar, Bangladesh. Material and methods A sample vital registration system (SVRS) was set up in 1982 to facilitate operational research in family planning and maternal and child health. SVRS provided data on death counts and population from 1983–2009. The Bangladesh Meteorological Department provided data on daily temperature and rainfall for the same period. Time series Poisson regression with cubic spline functions was used, allowing for over-dispersion, including lagged weather parameters, and adjusting for time trends and seasonal patterns. Analysis was carried out using R statistical software. Results Both weekly mean temperature and rainfall showed strong seasonal patterns. After adjusting for seasonal pattern and time trend, weekly mean temperatures (lag 0) below the 25th percentile and between the 25th and 75th percentiles were associated with increased mortality risk, particularly in females and adults aged 20–59 years by 2.3–2.4% for every 1°C decrease. Temperature above the 75th percentile did not increase the risk. Every 1 mm increase in rainfall up to 14 mm of weekly average rainfall over lag 0–4 weeks was associated with decreased mortality risks. Rainfall above 14 mm was associated with increased mortality risk. Conclusion The relationships between temperature, rainfall and mortality reveal the importance of understanding the current factors contributing to adaptation and acclimatization, and how these can be enhanced to reduce negative impacts from weather. PMID:23195512

Numerical Study on Interdecadal Modulations of ENSO-related Spring Rainfall over South China by the Pacific Decadal Oscillation

NASA Astrophysics Data System (ADS)

MAO, J.; WU, X.

2017-12-01

The spatio-temporal variations of eastern China spring rainfall are identified via empirical orthogonal function (EOF) analysis of rain-gauge (gridded) precipitation datasets for the period 1958-2013 (1920-2013). The interannual variations of the first two leading EOF modes are linked with the El Niño-Southern Oscillation (ENSO), with this linkage being modulated by the Pacific Decadal Oscillation (PDO). The EOF1 mode, characterized by predominant rainfall anomalies from the Yangtze River to North China (YNC), is more likely associated with out-of-phase PDO-ENSO events [i.e., El Niño during cold PDO (EN_CPDO) and La Niña during warm PDO (LN_WPDO)]. The sea surface temperature anomaly (SSTA) distributions of EN_CPDO (LN_WPDO) events induce a significant anomalous anticyclone (cyclone) over the western North Pacific stretching northwards to the Korean Peninsula and southern Japan, resulting in anomalous southwesterlies (northeasterlies) prevailing over eastern China and above-normal (below-normal) rainfall over YNC. In contrast, EOF2 exhibits a dipole pattern with predominantly positive rainfall anomalies over southern China along with negative anomalies over YNC, which is more likely connected to in-phase PDO-ENSO events [i.e., El Niño during warm PDO (EN_WPDO) and La Niña during cold PDO (LN_CPDO)]. EN_WPDO (LN_CPDO) events force a southwest-northeast oriented dipole-like circulation pattern leading to significant anomalous southwesterlies (northeasterlies) and above-normal (below-normal) rainfall over southern China. Numerical experiments with the CAM5 model forced by the SSTA patterns of EN_WPDO and EN_CPDO events reproduce reasonably well the corresponding anomalous atmospheric circulation patterns and spring rainfall modes over eastern China, validating the related mechanisms.

Hydroclimatology of the 2008 Midwest floods

NASA Astrophysics Data System (ADS)

Budikova, D.; Coleman, J. S. M.; Strope, S. A.; Austin, A.

2010-12-01

The late spring/early summer flooding that occurred in the American Midwest between May and June 2008 resulted from a combination of large-scale atmospheric circulation patterns that supported a steady influx of moisture into the area. A low pressure system centered over the central-western United States steered a strong jet and associated storms along its eastern edge from the west to southwest and an anomalously strong Great Plains Low Level Jet brought continuous warm and moist air into the area from the Gulf of Mexico into the area. We examine and quantify here the impact these circulation patterns had on the hydroclimatology of the Midwest highlighting the magnitude, frequency, geographic distribution, and temporal evolution of precipitation that ultimately magnified the flooding. Historical precipitation records were used to assess the regional rainfall characteristics at various geographic and time scales. Five distinct hydroclimatic characteristics contributed to the definition of the 2008 flood including persistent high surface soil moisture conditions prior to flooding exasperated by anomalously high rainfall, extreme rainfall totals covering extensive areas, increased frequency of shorter-term, smaller-magnitude events, persistent multiday heavy precipitation events, and extreme flood-producing rain storms. The major flooding lasted for approximately 24 days and most greatly impacted the state of Iowa, southern Wisconsin, and central Indiana. Its occurrence during the May-June period makes the event especially unusual for this region.

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

PubMed

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

2017-12-01

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

Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

PubMed Central

Anyamba, Assaf; Linthicum, Kenneth J.; Small, Jennifer L.; Collins, Kathrine M.; Tucker, Compton J.; Pak, Edwin W.; Britch, Seth C.; Eastman, James Ronald; Pinzon, Jorge E.; Russell, Kevin L.

2012-01-01

Background Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya. Methods and Findings We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004–2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3–4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall. Conclusions/Significance Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies. PMID:22292093

Climate teleconnections and recent patterns of human and animal disease outbreaks.

PubMed

Anyamba, Assaf; Linthicum, Kenneth J; Small, Jennifer L; Collins, Kathrine M; Tucker, Compton J; Pak, Edwin W; Britch, Seth C; Eastman, James Ronald; Pinzon, Jorge E; Russell, Kevin L

2012-01-01

Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya. We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004-2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3-4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall. Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Performance of CMORPH, TMPA, and PERSIANN rainfall datasets over plain, mountainous, and glacial regions of Pakistan

NASA Astrophysics Data System (ADS)

Hussain, Yawar; Satgé, Frédéric; Hussain, Muhammad Babar; Martinez-Carvajal, Hernan; Bonnet, Marie-Paule; Cárdenas-Soto, Martin; Roig, Henrique Llacer; Akhter, Gulraiz

2018-02-01

The present study aims at the assessment of six satellite rainfall estimates (SREs) in Pakistan. For each assessed products, both real-time (RT) and post adjusted (Adj) versions are considered to highlight their potential benefits in the rainfall estimation at annual, monthly, and daily temporal scales. Three geomorphological climatic zones, i.e., plain, mountainous, and glacial are taken under considerations for the determination of relative potentials of these SREs over Pakistan at global and regional scales. All SREs, in general, have well captured the annual north-south rainfall decreasing patterns and rainfall amounts over the typical arid regions of the country. Regarding the zonal approach, the performance of all SREs has remained good over mountainous region comparative to arid regions. This poor performance in accurate rainfall estimation of all the six SREs over arid regions has made their use questionable in these regions. Over glacier region, all SREs have highly overestimated the rainfall. One possible cause of this overestimation may be due to the low surface temperature and radiation absorption over snow and ice cover, resulting in their misidentification with rainy clouds as daily false alarm ratio has increased from mountainous to glacial regions. Among RT products, CMORPH-RT is the most biased product. The Bias was almost removed on CMORPH-Adj thanks to the gauge adjustment. On a general way, all Adj versions outperformed their respective RT versions at all considered temporal scales and have confirmed the positive effects of gauge adjustment. CMORPH-Adj and TMPA-Adj have shown the best agreement with in situ data in terms of Bias, RMSE, and CC over the entire study area.

Quasi-continuous stochastic simulation framework for flood modelling

NASA Astrophysics Data System (ADS)

Moustakis, Yiannis; Kossieris, Panagiotis; Tsoukalas, Ioannis; Efstratiadis, Andreas

2017-04-01

Typically, flood modelling in the context of everyday engineering practices is addressed through event-based deterministic tools, e.g., the well-known SCS-CN method. A major shortcoming of such approaches is the ignorance of uncertainty, which is associated with the variability of soil moisture conditions and the variability of rainfall during the storm event.In event-based modeling, the sole expression of uncertainty is the return period of the design storm, which is assumed to represent the acceptable risk of all output quantities (flood volume, peak discharge, etc.). On the other hand, the varying antecedent soil moisture conditions across the basin are represented by means of scenarios (e.g., the three AMC types by SCS),while the temporal distribution of rainfall is represented through standard deterministic patterns (e.g., the alternative blocks method). In order to address these major inconsistencies,simultaneously preserving the simplicity and parsimony of the SCS-CN method, we have developed a quasi-continuous stochastic simulation approach, comprising the following steps: (1) generation of synthetic daily rainfall time series; (2) update of potential maximum soil moisture retention, on the basis of accumulated five-day rainfall; (3) estimation of daily runoff through the SCS-CN formula, using as inputs the daily rainfall and the updated value of soil moisture retention;(4) selection of extreme events and application of the standard SCS-CN procedure for each specific event, on the basis of synthetic rainfall.This scheme requires the use of two stochastic modelling components, namely the CastaliaR model, for the generation of synthetic daily data, and the HyetosMinute model, for the disaggregation of daily rainfall to finer temporal scales. Outcomes of this approach are a large number of synthetic flood events, allowing for expressing the design variables in statistical terms and thus properly evaluating the flood risk.

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

NASA Astrophysics Data System (ADS)

Akhter, Javed; Das, Lalu; Deb, Argha

2017-09-01

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

Watershed soil Cd loss after long-term agricultural practice and biochar amendment under four rainfall levels.

PubMed

Ouyang, Wei; Huang, Weijia; Hao, Xin; Tysklind, Mats; Haglund, Peter; Hao, Fanghua

2017-10-01

Some heavy metals in farmland soil can be transported into the waterbody, affecting the water quality and sediment at the watershed outlet, which can be used to determine the historical loss pattern. Cd is a typical heavy metal leached from farmland that is related to phosphate fertilizers and carries serious environmental risk. The spatial-vertical pattern of Cd in soil and the vertical trend of Cd in the river sediment core were analyzed, which showed the migration and accumulation of Cd in the watershed. To prevent watershed Cd loss, biochar was employed, and leaching experiments were conducted to investigate the Cd loss from soil depending on the initial concentration. Four rainfall intensities, 1.25 mm/h, 2.50 mm/h, 5.00 mm/h, and 10.00 mm/h, were used to simulate typical rainfall scenarios for the study area. Biochar was prepared from corn straw after pretreatment with ammonium dihydrogen phosphate (ADP) and pyrolysis at 400 °C under anoxic conditions. To identify the effects of biochar amendment on Cd migration, the biochar was mixed with soil for 90 days at concentrations of 0%, 0.5%, 1.0%, 3.0%, and 5.0% soil by weight. The results showed that the Cd leaching load increased as the initial load and rainfall intensity increased and that eluviation caused surface Cd to diffuse to the deep soils. The biochar application caused more of the heavy metals to be immobilized in the amended soil rather than transported into the waterbody. The sorption efficiency of the biochar for Cd increased as the addition level increased to 3%, which showed better performance than the 5% addition level under some initial concentration and rainfall conditions. The research indicated that biochar is a potential material to prevent diffuse heavy metal pollution and that a lower addition makes the application more feasible. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2010-01-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

South Asian Summer Monsoon Rainfall Variability and Trend: Its Links to Indo-Pacific SST Anomalies and Moist Processes

NASA Astrophysics Data System (ADS)

Prasanna, V.

2016-06-01

The warm (cold) phase of El Niño (La Niña) and its impact on all Indian Summer Monsoon rainfall (AISMR) relationship is explored for the past 100 years. The 103-year (1901-2003) data from the twentieth century reanalysis datasets (20CR) and other major reanalysis datasets for southwest monsoon season (JJAS) is utilized to find out the simultaneous influence of the El Niño Southern Oscillation (ENSO)-AISMR relationship. Two cases such as wet, dry monsoon years associated with ENSO(+) (El Niño), ENSO(-) (La Niña) and Non-ENSO (neutral) events have been discussed in detail using observed rainfall and three-dimensional 20CR dataset. The dry and wet years associated with ENSO and Non-ENSO periods show significant differences in the spatial pattern of rainfall associated with three-dimensional atmospheric composite, the 20CR dataset has captured the anomalies quite well. During wet (dry) years, the rainfall is high (low), i.e. 10 % above (below) average from the long-term mean and this wet or dry condition occur both during ENSO and Non-ENSO phases. The Non-ENSO year dry or wet composites are also focused in detail to understand, where do the anomalous winds come from unlike in the ENSO case. The moisture transport is coherent with the changes in the spatial pattern of AISMR and large-scale feature in the 20CR dataset. Recent 50-year trend (1951-2000) is also analyzed from various available observational and reanalysis datasets to see the influence of Indo-Pacific SST and moist processes on the South Asian summer monsoon rainfall trend. Apart from the Indo-Pacific sea surface temperatures (SST), the moisture convergence and moisture transport among India (IND), Equatorial Indian Ocean (IOC) and tropical western pacific (WNP) is also important in modifying the wet or dry cycles over India. The mutual interaction among IOC, WNP and IND in seasonal timescales is significant in modifying wet and dry cycles over the Indian region and the seasonal anomalies.

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

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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

2015-03-26

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

Debris-flow and flooding hazards associated with the December 1999 storm in coastal Venezuela and strategies for mitigation

USGS Publications Warehouse

Wieczorek, G.F.; Larsen, M.C.; Eaton, L.S.; Morgan, B.A.; Blair, J.L.

2001-01-01

Heavy rainfall from the storm of December 14-16, 1999 triggered thousands of landslides on steep slopes of the Sierra de Avila north of Caracas, Venezuela. In addition to landslides, heavy rainfall caused flooding and massive debris flows that damaged coastal communities in the State of Vargas along the Caribbean Sea. Examination of the rainfall pattern obtained from the GOES-8 satellite showed that the pattern of damage was generally consistent with the area of heaviest rainfall. Field observations of the severely affected drainage basins and historical records indicate that previous flooding and massive debris-flow events of similar magnitude to that of December 1999 have occurred throughout this region. The volume of debris-flow deposits and the large boulders that the flows transported qualifies the 1999 event amongst the largest historical rainfall-induced debris flows documented worldwide.

Impact of low intensity summer rainfall on E. coli-discharge event dynamics with reference to sample acquisition and storage.

PubMed

Oliver, David M; Porter, Kenneth D H; Heathwaite, A Louise; Zhang, Ting; Quilliam, Richard S

2015-07-01

Understanding the role of different rainfall scenarios on faecal indicator organism (FIO) dynamics under variable field conditions is important to strengthen the evidence base on which regulators and land managers can base informed decisions regarding diffuse microbial pollution risks. We sought to investigate the impact of low intensity summer rainfall on Escherichia coli-discharge (Q) patterns at the headwater catchment scale in order to provide new empirical data on FIO concentrations observed during baseflow conditions. In addition, we evaluated the potential impact of using automatic samplers to collect and store freshwater samples for subsequent microbial analysis during summer storm sampling campaigns. The temporal variation of E. coli concentrations with Q was captured during six events throughout a relatively dry summer in central Scotland. The relationship between E. coli concentration and Q was complex with no discernible patterns of cell emergence with Q that were repeated across all events. On several occasions, an order of magnitude increase in E. coli concentrations occurred even with slight increases in Q, but responses were not consistent and highlighted the challenges of attempting to characterise temporal responses of E. coli concentrations relative to Q during low intensity rainfall. Cross-comparison of E. coli concentrations determined in water samples using simultaneous manual grab and automated sample collection was undertaken with no difference in concentrations observed between methods. However, the duration of sample storage within the autosampler unit was found to be more problematic in terms of impacting on the representativeness of microbial water quality, with unrefrigerated autosamplers exhibiting significantly different concentrations of E. coli relative to initial samples after 12-h storage. The findings from this study provide important empirical contributions to the growing evidence base in the field of catchment microbial dynamics.

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

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

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

2012-10-29

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

Combined effects of constant versus variable intensity simulated rainfall and reduced tillage management on cotton preemergence herbicide runoff.

PubMed

Potter, Thomas L; Truman, Clint C; Strickland, Timothy C; Bosch, David D; Webster, Theodore M; Franklin, Dorcas H; Bednarz, Craig W

2006-01-01

Pesticide runoff research relies heavily on rainfall simulation experiments. Most are conducted at a constant intensity, i.e., at a fixed rainfall rate; however, large differences in natural rainfall intensity is common. To assess implications we quantified runoff of two herbicides, fluometuron and pendimethalin, and applied preemergence after planting cotton on Tifton loamy sand. Rainfall at constant and variable intensity patterns representative of late spring thunderstorms in the Atlantic Coastal Plain region of Georgia (USA) were simulated on 6-m2 plots under strip- (ST) and conventional-tillage (CT) management. The variable pattern produced significantly higher runoff rates of both compounds from CT but not ST plots. However, on an event-basis, runoff totals (% applied) were not significantly different, with one exception: fluometuron runoff from CT plots. There was about 25% more fluometuron runoff with the variable versus the constant intensity pattern (P = 0.10). Study results suggest that conduct of simulations using variable intensity storm patterns may provide more representative rainfall simulation-based estimates of pesticide runoff and that the greatest impacts will be observed with CT. The study also found significantly more fluometuron in runoff from ST than CT plots. Further work is needed to determine whether this behavior may be generalized to other active ingredients with similar properties [low K(oc) (organic carbon partition coefficient) approximately 100 mL g(-1); high water solubility approximately 100 mg L(-1)]. If so, it should be considered when making tillage-specific herbicide recommendations to reduce runoff potential.

Time trend of malaria in relation to climate variability in Papua New Guinea.

PubMed

Park, Jae-Won; Cheong, Hae-Kwan; Honda, Yasushi; Ha, Mina; Kim, Ho; Kolam, Joel; Inape, Kasis; Mueller, Ivo

2016-01-01

This study was conducted to describe the regional malaria incidence in relation to the geographic and climatic conditions and describe the effect of altitude on the expansion of malaria over the last decade in Papua New Guinea. Malaria incidence was estimated in five provinces from 1996 to 2008 using national health surveillance data. Time trend of malaria incidence was compared with rainfall and minimum/maximum temperature. In the Eastern Highland Province, time trend of malaria incidence over the study period was stratified by altitude. Spatio-temporal pattern of malaria was analyzed. Nationwide, malaria incidence was stationary. Regionally, the incidence increased markedly in the highland region (292.0/100000/yr, p =0.021), and remained stationary in the other regions. Seasonality of the malaria incidence was related with rainfall. Decreasing incidence of malaria was associated with decreasing rainfall in the southern coastal region, whereas it was not evident in the northern coastal region. In the Eastern Highland Province, malaria incidence increased in areas below 1700 m, with the rate of increase being steeper at higher altitudes. Increasing trend of malaria incidence was prominent in the highland region of Papua New Guinea, while long-term trend was dependent upon baseline level of rainfall in coastal regions.

Tree rings and rainfall in the equatorial Amazon

NASA Astrophysics Data System (ADS)

Granato-Souza, Daniela; Stahle, David W.; Barbosa, Ana Carolina; Feng, Song; Torbenson, Max C. A.; de Assis Pereira, Gabriel; Schöngart, Jochen; Barbosa, Joao Paulo; Griffin, Daniel

2018-05-01

The Amazon basin is a global center of hydroclimatic variability and biodiversity, but there are only eight instrumental rainfall stations with continuous records longer than 80 years in the entire basin, an area nearly the size of the coterminous US. The first long moisture-sensitive tree-ring chronology has been developed in the eastern equatorial Amazon of Brazil based on dendrochronological analysis of Cedrela cross sections cut during sustainable logging operations near the Rio Paru. The Rio Paru chronology dates from 1786 to 2016 and is significantly correlated with instrumental precipitation observations from 1939 to 2016. The strength and spatial scale of the precipitation signal vary during the instrumental period, but the Rio Paru chronology has been used to develop a preliminary reconstruction of February to November rainfall totals from 1786 to 2016. The reconstruction is related to SSTs in the Atlantic and especially the tropical Pacific, similar to the stronger pattern of association computed for the instrumental rainfall data from the eastern Amazon. The tree-ring data estimate extended drought and wet episodes in the mid- to late-nineteenth century, providing a valuable, long-term perspective on the moisture changes expected to emerge over the Amazon in the coming century due to deforestation and anthropogenic climate change.

Temporal variation of Mexiconema cichlasomae (Nematoda: Daniconematidae) in the Mayan cichlid fish Cichlasoma urophthalmus and its intermediate host Argulus yucatanus from a tropical coastal lagoon.

PubMed

May-Tec, A L; Pech, D; Aguirre-Macedo, M L; Lewis, J W; Vidal-Martínez, V M

2013-03-01

The aim of the present investigation was to determine whether temporal variation in environmental factors such as rainfall or temperature influence long-term fluctuations in the prevalence and mean abundance of the nematode Mexiconema cichlasomae in the cichlid fish Cichlasoma uropthalmus and its crustacean intermediate host, Argulus yucatanus. The study was undertaken in a tropical coastal lagoon in the Yucatan Peninsula (south-eastern Mexico) over an 8-year period. Variations in temperature, rainfall and monthly infection levels for both hosts were analysed using time series and cross-correlations to detect possible recurrent patterns. Infections of M. cichlasomae in A. yucatanus showed annual peaks, while in C. urophthalmus peaks were bi-annual. The latter appear to be related to the accumulation of several generations of this nematode in C. urophthalmus. Rainfall and temperature appear to be key environmental factors in influencing temporal variation in the infection of M. cichlasomae over periods longer than a year together with the accumulation of larval stages throughout time.

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.

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.

Spatio-Temporal Variability of Summer Precipitation in Mexico under the Influence of the MJO, with Emphasis on the Bimodal Pattern

NASA Astrophysics Data System (ADS)

Perdigón, J.; Romero-Centeno, R.; Barrett, B.; Ordoñez-Perez, P.

2017-12-01

In many regions of Mexico, precipitation occurs in a very well defined annual cycle with peaks in May-June and September-October and a relative minimum in the middle of the rainy season known as the midsummer drought (MSD). The MJO is the most important mode of intraseasonal variability in the tropics, and, although some studies have shown its evident influence on summer precipitation in Mexico, its role in modulating the bimodal pattern of the summer precipitation cycle is still an open question. The spatio-temporal variability of summer precipitation in Mexico is analyzed through composite analysis according to the phases of the MJO, using the very high resolution CHIRPS precipitation data base and gridded data from the CFSR reanalysis to analyzing the MJO influence on the atmospheric circulation over Mexico and its adjacent basins. In general, during MJO phases 8-2 (4-6) rainfall is above-normal (below-normal), although, in some cases, the summer rainfall patterns during the same phase present considerable differences. The atmospheric circulation shows low (high) troposphere southwesterly (northeasterly) wind anomalies in southern Mexico under wetter conditions compared with climatological patterns, while the inverse pattern is observed under drier conditions. Composite anomalies of several variables also agreed well with those rainfall anomalies. Finally, a MJO complete cycle that reinforces (weakens) the bimodal pattern of summer rainfall in Mexico was found.

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

Different impacts of mega-ENSO and conventional ENSO on the Indian summer rainfall: developing phase

NASA Astrophysics Data System (ADS)

Zhang, Lei; Wu, Zhiwei; Zhou, Yefan

2016-04-01

Mega-El Niño-Southern Oscillation (ENSO), a boarder version of conventional ENSO, is found to be a main driving force of Northern Hemisphere summer monsoon rainfall including the Indian summer rainfall (ISR). The simultaneous impacts of "pure" mega-ENSO and "pure" conventional ENSO events on the ISR in its developing summer remains unclear. This study examines the different linkages between mega-ENSO-ISR and conventional ENSO-ISR. During the developing summer of mega-El Niño, negative rainfall anomalies are seen over the northeastern Indian subcontinent, while the anomalous rainfall pattern is almost the opposite for mega-La Niña; as for the conventional ENSO, the approximate "linear opposite" phenomenon vanishes. Furthermore, the global zonal wave trains anomalous are found at mid-latitude zones, with a local triple circulation pattern over the central-east Eurasia during mega-ENSO events, which might be an explanation of corresponding rainfall response over the Indian Peninsula. Among 106-year historical run (1900-2005) of 9 state-of-the-art models from the Coupled Model Inter-comparison Project Phase 5 (CMIP5), HadGEM2-ES performs a promising skill in simulating the anomalous circulation pattern over mid-latitude and central-east Eurasia while CanESM2 cannot. Probably, it is the models' ability of capturing the mega-ENSO-ISR linkage and the characteristic of mega-ENSO that make the difference.

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

PubMed

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

2018-05-01

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

Development of Representative Rainfall Periods for Green Infrastructure Design: Connecting the Dots Between Climate, Urban Hydrology and Resilience

NASA Astrophysics Data System (ADS)

Albright, C. M.; Traver, R.; Wadzuk, B.

2017-12-01

Analysis of local-to-regional climate data is critical in understanding how changing patterns in rainfall and other atmospheric conditions can affect urban hydrology. Urbanization has caused hydrologic and ecologic modifications to our land surfaces, and altered the dynamics of urban water cycle in complex ways. Green infrastructure (GI) systems, in their simplest form, reduce runoff and flooding, prevent combined sewer overflows and improve quality of receiving waters. However, when viewed through a more holistic lens, GI systems sit at the nexus of hydrology, climate and energy, yet are rarely designed to account for the impacts of these intersections. We must assess urban hydrologic systems beyond their response to a single event or design storm, incorporating multiple temporal scales and all hydrologic processes. This is of utmost importance to design and characterization of urban GI systems because the resilience of these systems will be dictated by their ability to adapt to future behavior of extreme weather patterns and climate. In this study, we characterize long-term hydrologic conditions in Philadelphia to identify periods of record that are most representative of regional climate characteristics, including a representative rainfall year and longer representative periods. Utility of these datasets will be demonstrated by showing that GI systems are able to sustain effective performance for most expected annual precipitation events. Connections between atmospheric (precipitation and temperature) patterns, GI systems and potential removal mechanisms in the urban hydrologic cycle will be presented for Philadelphia and cities with similar climate characteristics. Establishing such connections is critically needed to not only validate what is already known about urban GI, but more importantly, to advance theory and practice by linking the hydrologic benefits of urban GI to broader concepts such as risk, mitigation of extreme events and sustainable communities.

Impacts of different rainfall patterns on hyporheic zone under transient conditions

NASA Astrophysics Data System (ADS)

Liu, S.; Chui, T. F. M.

2017-12-01

The hyporheic zone (HZ), the region beneath or alongside a streambed, can play a vital role in stream ecology. Several previous studies have investigated the influential factors on the HZ in the steady state. However, the exchange between surface water and groundwater in the HZ can be dynamic and transient, during a transient event such as a storm. Therefore, this study investigates the changes of the HZ under the transient conditions of a storm, and examines the impacts of different rainfall patterns (i.e., intensity and duration) on the HZ. A two-dimensional groundwater-stream model is developed with a domain of 10-meter long and 2-meter deep. The streambed consists of a series of dunes that induce hyporheic exchanges. Brinkman-Darcy and Navier-Stokes equations are respectively employed for the subsurface and stream water, and the velocity and the pressure are coupled at the interface (i.e., the streambed). To compare the results from different rainfall patterns, the influential duration (IT) and the influential depth (ID) are proposed and evaluated. IT is the time required for the HZ to return to its intial stage, once it starts to change. ID is the maximum increment in the depth of the HZ. To accurately detect the region of the HZ in different situations, the moving split-window analysis method is used. The region of the HZ is found to vary significantly under different rainfall intensities. Rainfall intensity displays logarithmic relationships with both the IT and ID with high coefficients of determination (r2=0.98). The derived relationships can be used to predict the influrence of a rainfall event on the HZ. However, the influence of rainfall duration on the HZ depends on other factors such as groundwater response. Rainfall duration displays positive realionships with the IT and ID, but only between certain lower and upper thresholds of rainfall duration. If rainfall duration is shorter than the lower threshold value or longer than the upper value, the IT and ID will have little change with rainfall duration.

Monthly Rainfall Erosivity Assessment for Switzerland

NASA Astrophysics Data System (ADS)

Schmidt, Simon; Meusburger, Katrin; Alewell, Christine

2016-04-01

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

Monitoring Multitemporal Soil Moisture, Rainfall, and ET in Lake Manatee Watershed, South Florida under Global Changes

NASA Astrophysics Data System (ADS)

Chang, N.

2009-12-01

Ni-Bin Chang1, Ammarin Daranpob 1, and Y. Jeffrey Yang2 1Civil, Environmental, and Construction Engineering Department, University of Central Florida, Orlando FL, USA 2Water Supply and Water Resources Division, National Risk Management Research Laboratory, U.S. EPA, Cincinnati, Ohio, USA ASBTRACT: Global climate change and its related impacts on water supply are universally recognized. The Atlantic Multidecadal Oscillation (AMO), which is based on long term changes in the temperature of the surface of the North Atlantic Ocean, is a source of changes in river flow patterns in Florida. The AMO has a multi-decadal frequency. Under its impact, several distinct types of river patterns were identified within Florida, including a Southern River Pattern (SRP), a Northern River Pattern (NRP), a Bimodal River Pattern (BRP), etc. (Kelley and Gore, 2008). Some SRPs are present in the South Florida Water Management District (SFWMD). Changes in river flows occur because significant sea surface temperature (SST) changes affect continental rainfall patterns. It had been observed that, between AMO warm (i.e., from 1939 to 1968) and cold phases (i.e., from 1969 to 1993), the average daily inflow to Lake Okeechobee varies by 40% in the transition from the warm to cold phases in South Florida. The Manatee County is located in the Southern Water Use Caution Area (SWUCA) due to the depletion of the Upper Floridian Aquifer and its entire western portion of the County is designated as part of the Most Impacted Area (MIA) within the Eastern Tampa Bay Water Use Caution Area relative to the SWUCA. Major source of Manatee County’s water is an 332 Km2 (82,000-acre) watershed (i.e., Lake Manatee Watershed) that drains into the man-made Lake Manatee Reservoir. The lake has a total volume of 0.21 billion m3 (7.5 billion gallons) and will cover 7.3 Km2 (1,800 acres) when full. The proper use of remote sensing images and sensor network technologies can provide information on both spatial and temporal distributions of key variables in the hydrological cycle, such as soil moisture, evapotranspiration (ET) and precipitation. The multi-sensor platform may include not only in-situ sensor network, ground-based radar, air-borne aircraft, but also even space-borne satellites. The use of a decadal-scale historical record from 1998 to 2008 to support such a trend analysis via NEXRAD (Rainfall), GOES (ET), and MODIS (soil moisture) satellite images may uniquely support middle-term and long-term water resources management in the near future. This study confirms that the potential of using remotely sensed time-series biophysical and ecohydrological states of landscape to characterize soil moisture condition, ET, and other states should be further investigated based on the pros and cons of each type of satellite imageries so as to maximize the beneficial use of remote sensing.

Bivariate at-site frequency analysis of simulated flood peak-volume data using copulas

NASA Astrophysics Data System (ADS)

Gaál, Ladislav; Viglione, Alberto; Szolgay, Ján.; Blöschl, Günter; Bacigál, Tomáå.¡

2010-05-01

In frequency analysis of joint hydro-climatological extremes (flood peaks and volumes, low flows and durations, etc.), usually, bivariate distribution functions are fitted to the observed data in order to estimate the probability of their occurrence. Bivariate models, however, have a number of limitations; therefore, in the recent past, dependence models based on copulas have gained increased attention to represent the joint probabilities of hydrological characteristics. Regardless of whether standard or copula based bivariate frequency analysis is carried out, one is generally interested in the extremes corresponding to low probabilities of the fitted joint cumulative distribution functions (CDFs). However, usually there is not enough flood data in the right tail of the empirical CDFs to derive reliable statistical inferences on the behaviour of the extremes. Therefore, different techniques are used to extend the amount of information for the statistical inference, i.e., temporal extension methods that allow for making use of historical data or spatial extension methods such as regional approaches. In this study, a different approach was adopted which uses simulated flood data by rainfall-runoff modelling, to increase the amount of data in the right tail of the CDFs. In order to generate artificial runoff data (i.e. to simulate flood records of lengths of approximately 106 years), a two-step procedure was used. (i) First, the stochastic rainfall generator proposed by Sivapalan et al. (2005) was modified for our purpose. This model is based on the assumption of discrete rainfall events whose arrival times, durations, mean rainfall intensity and the within-storm intensity patterns are all random, and can be described by specified distributions. The mean storm rainfall intensity is disaggregated further to hourly intensity patterns. (ii) Secondly, the simulated rainfall data entered a semi-distributed conceptual rainfall-runoff model that consisted of a snow routine, a soil moisture routine and a flow routing routine (Parajka et al., 2007). The applicability of the proposed method was demonstrated on selected sites in Slovakia and Austria. The pairs of simulated flood volumes and flood peaks were analysed in terms of their dependence structure and different families of copulas (Archimedean, extreme value, Gumbel-Hougaard, etc.) were fitted to the observed and simulated data. The question to what extent measured data can be used to find the right copula was discussed. The study is supported by the Austrian Academy of Sciences and the Austrian-Slovak Co-operation in Science and Education "Aktion". Parajka, J., Merz, R., Blöschl, G., 2007: Uncertainty and multiple objective calibration in regional water balance modeling - Case study in 320 Austrian catchments. Hydrological Processes, 21, 435-446. Sivapalan, M., Blöschl, G., Merz, R., Gutknecht, D., 2005: Linking flood frequency to long-term water balance: incorporating effects of seasonality. Water Resources Research, 41, W06012, doi:10.1029/2004WR003439.

Effects of natural flooding and manual trapping on the facilitation of invasive crayfish-native amphibian coexistence in a semi-arid perennial stream

USGS Publications Warehouse

Kats, Lee B.; Bucciarelli, Gary; Vandergon, Thomas L.; Honeycutt, Rodney L.; Mattiasen, Evan; Sanders, Arthur; Riley, Seth P.D.; Kerby, Jacob L.; Fisher, Robert N.

2013-01-01

Aquatic amphibians are known to be vulnerable to a myriad of invasive predators. Invasive crayfish are thought to have eliminated native populations of amphibians in some streams in the semi-arid Santa Monica Mountains of southern California. Despite their toxic skin secretions that defend them from native predators, newts are vulnerable to crayfish attacks, and crayfish have been observed attacking adult newts, and eating newt egg masses and larvae. For 15 years, we have observed invasive crayfish and native California newts coexisting in one stream in the Santa Monica Mountains. During that period, we monitored the densities of both crayfish and newt egg mass densities and compared these to annual rainfall totals. After three seasons of below average rainfall, we reduced crayfish numbers by manual trapping. Our long-term data indicated that crayfish did not fare well in years when rainfall is above the historic average. This invasive predator did not evolve with high velocity streams, and observations indicated that southern California storm events washed crayfish downstream, killing many of them. Newts exhibit increased reproduction in years when crayfish numbers were reduced. A comparison with a nearby stream that does not contain crayfish indicated that newt reproduction positively responded to increased rainfall, but that fluctuations were much greater in the stream that contains crayfish. We suggest that rainfall patterns help explain invasive crayfish/newt coexistence and that management for future coexistence may benefit from manual trapping.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

The 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.

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

USDA-ARS?s Scientific Manuscript database

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

Forecasting of Seasonal Rainfall using ENSO and IOD teleconnection with Classification Models

NASA Astrophysics Data System (ADS)

De Silva, T.; Hornberger, G. M.

2017-12-01

Seasonal to annual forecasts of precipitation patterns are very important for water infrastructure management. In particular, such forecasts can be used to inform decisions about the operation of multipurpose reservoir systems in the face of changing climate conditions. Success in making useful forecasts often is achieved by considering climate teleconnections such as the El-Nino-Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) as related to sea surface temperature variations. We present an analysis to explore the utility of using rainfall relationships in Sri Lanka with ENSO and IOD to predict rainfall to the Mahaweli, river basin. Forecasting of rainfall as classes - above normal, normal, and below normal - can be useful for water resource management decision making. Quadratic discrimination analysis (QDA) and random forest models are used to identify the patterns of rainfall classes with respect to ENSO and IOD indices. These models can be used to forecast the likelihood of areal rainfall anomalies using predicted climate indices. Results can be used for decisions regarding allocation of water for agriculture and electricity generation within the Mahaweli project of Sri Lanka.

Streamflow prediction using multi-site rainfall obtained from hydroclimatic teleconnection

NASA Astrophysics Data System (ADS)

Kashid, S. S.; Ghosh, Subimal; Maity, Rajib

2010-12-01

SummarySimultaneous variations in weather and climate over widely separated regions are commonly known as "hydroclimatic teleconnections". Rainfall and runoff patterns, over continents, are found to be significantly teleconnected, with large-scale circulation patterns, through such hydroclimatic teleconnections. Though such teleconnections exist in nature, it is very difficult to model them, due to their inherent complexity. Statistical techniques and Artificial Intelligence (AI) tools gain popularity in modeling hydroclimatic teleconnection, based on their ability, in capturing the complicated relationship between the predictors (e.g. sea surface temperatures) and predictand (e.g., rainfall). Genetic Programming is such an AI tool, which is capable of capturing nonlinear relationship, between predictor and predictand, due to its flexible functional structure. In the present study, gridded multi-site weekly rainfall is predicted from El Niño Southern Oscillation (ENSO) indices, Equatorial Indian Ocean Oscillation (EQUINOO) indices, Outgoing Longwave Radiation (OLR) and lag rainfall at grid points, over the catchment, using Genetic Programming. The predicted rainfall is further used in a Genetic Programming model to predict streamflows. The model is applied for weekly forecasting of streamflow in Mahanadi River, India, and satisfactory performance is observed.

Beamwidth effects on Z-R relations and area-integrated rainfall

NASA Technical Reports Server (NTRS)

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

1992-01-01

The effective radar reflectivity Ze measured by a radar is the convolution of the actual distribution of reflectivity with the beam radiation pattern. Because of the nonlinearity between Z and rain rate R, Ze gives a biased estimator of R whenever the reflectivity field is nonuniform. In the presence of sharp horizontal reflectivity gradients, the measured pattern of Ze extends beyond the actual precipitation boundaries to produce false precipitation echoes. When integrated across the radar image of the storm, the false echo areas contribute to the sum to produce overestimates of the areal rainfall. As the range or beamwidth increases, the ratio of measured to actual rainfall increases. Beyond some range, the normal decrease of reflectivity with height dominates and the measured rainfall underestimates the actual amount.

Teleconnection between sea ice in the Barents Sea in June and the Silk Road, Pacific-Japan and East Asian rainfall patterns in August

NASA Astrophysics Data System (ADS)

He, Shengping; Gao, Yongqi; Furevik, Tore; Wang, Huijun; Li, Fei

2018-01-01

In contrast to previous studies that have tended to focus on the influence of the total Arctic sea-ice cover on the East Asian summer tripole rainfall pattern, the present study identifies the Barents Sea as the key region where the June sea-ice variability exerts the most significant impacts on the East Asian August tripole rainfall pattern, and explores the teleconnection mechanisms involved. The results reveal that a reduction in June sea ice excites anomalous upward air motion due to strong near-surface thermal forcing, which further triggers a meridional overturning wave-like pattern extending to midlatitudes. Anomalous downward motion therefore forms over the Caspian Sea, which in turn induces zonally oriented overturning circulation along the subtropical jet stream, exhibiting the east-west Rossby wave train known as the Silk Road pattern. It is suggested that the Bonin high, a subtropical anticyclone predominant near South Korea, shows a significant anomaly due to the eastward extension of the Silk Road pattern to East Asia. As a possible descending branch of the Hadley cell, the Bonin high anomaly ultimately triggers a meridional overturning, establishing the Pacific-Japan pattern. This in turn induces an anomalous anticyclone and cyclone pair over East Asia, and a tripole vertical convection anomaly meridionally oriented over East Asia. Consequently, a tripole rainfall anomaly pattern is observed over East Asia. Results from numerical experiments using version 5 of the Community Atmosphere Model support the interpretation of this chain of events.

Teleconnection between Sea Ice in the Barents Sea in June and the Silk Road, Pacific-Japan and East Asian Rainfall Patterns in August

NASA Astrophysics Data System (ADS)

He, S.; Gao, Y.; Furevik, T.; Huijun, W.; Li, F.

2017-12-01

In contrast to previous studies that have tended to focus on the influence of the total Arctic sea-ice cover on the East Asian summer tripole rainfall pattern, the present study identifies the Barents Sea as the key region where the June sea-ice variability exerts the most significant impacts on the East Asian August tripole rainfall pattern, and explores the teleconnection mechanisms involved. The results reveal that a reduction in June sea ice excites anomalous upward air motion due to strong near-surface thermal forcing, which further triggers a meridional overturning wave-like pattern extending to midlatitudes. Anomalous downward motion therefore forms over the Caspian Sea, which in turn induces zonally oriented overturning circulation along the subtropical jet stream, exhibiting the east-west Rossby wave train known as the Silk Road pattern. It is suggested that the Bonin high, a subtropical anticyclone predominant near South Korea, shows a significant anomaly due to the eastward extension of the Silk Road pattern to East Asia. As a possible descending branch of the Hadley cell, the Bonin high anomaly ultimately triggers a meridional overturning, establishing the Pacific-Japan pattern. This in turn induces an anomalous anticyclone and cyclone pair over East Asia, and a tripole vertical convection anomaly meridionally oriented over East Asia. Consequently, a tripole rainfall anomaly pattern is observed over East Asia. Results from numerical experiments using version 5 of the Community Atmosphere Model support the interpretation of this chain of events.

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

NASA Astrophysics Data System (ADS)

Xu, Zhiqing; Fan, Ke; Wang, HuiJun

2017-09-01

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

Climate driven changes to rainfall and streamflow patterns in a model tropical island hydrological system

Treesearch

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

2015-01-01

Rising atmospheric CO2 and resulting warming are expected to impact freshwater resources in the tropics, but few studies have documented how natural stream flow regimes in tropical watersheds will respond to changing rainfall patterns. To address this data gap, we utilized a space-for-time substitution across a naturally occurring and highly...

Unidirectional trends in annual and seasonal climate and extremes in Egypt

NASA Astrophysics Data System (ADS)

Nashwan, Mohamed Salem; Shahid, Shamsuddin; Abd Rahim, Norhan

2018-05-01

The presence of short- and long-term autocorrelations can lead to considerable change in significance of trend in hydro-climatic time series. Therefore, past findings of climatic trend studies that did not consider autocorrelations became a questionable issue. The spatial patterns in the trends of annual and seasonal temperature, rainfall, and related extremes in Egypt have been assessed in this paper using modified Mann-Kendal (MMK) trend test which can detect unidirectional trends in time series in the presence of short- and long-term autocorrelations. The trends obtained using the MMK test was compared with that obtained using standard Mann-Kendall (MK) test to show how natural variability in climate affects the trends. The daily rainfall and temperature data of Princeton Global Meteorological Forcing for the period 1948-2010 having a spatial resolution of 0.25° × 0.25° was used for this purpose. The results showed a large difference between the trends obtained using MMK and MK tests. The MMK test showed increasing trends in temperature and a number of temperature extremes in Egypt, but almost no change in rainfall and rainfall extremes. The minimum temperature was found to increase (0.08-0.29 °C/decade) much faster compared to maximum temperature (0.07-0.24 °C/decade) and therefore, a decrease in diurnal temperature range (- 0.01 to - 0.16 °C/decade) in most part of Egypt. The number of winter hot days and nights are increasing, while the number of cold days is decreasing in most part of the country. The study provides a more realistic scenario of the changes in climate and weather extremes of Egypt.

Effect of climate change on agriculture sustainability in Jordan

NASA Astrophysics Data System (ADS)

Khresat, S.

2009-04-01

Jordan is a vulnerable country in terms of climate change impact. In the latest assessment report published by the Intergovernmental Panel on Climate Change. Jordan will suffer from reduced agricultural productivity due to more erratic rainfall patterns, reduced freshwater resources and increased temperatures. The Initial National Communication (INC) to the United Nations Framework Convention to Climate Change (UNFCCC) foresees that over the next three decades, Jordan will witness a rise in temperature, drop in rainfall, reduced ground cover, reduced water availability, heat-waves, and more frequent dust storms. Coupled with the effect of continuing drought incidents, plant cover removal was greatly accelerated. Climate change can impact agricultural sustainability in Jordan in two interrelated ways: first, by diminishing the long-term ability of agroecosystems to provide food and fiber locally; and second, by inducing shifts in agricultural regions that may encroach upon natural habitats, at the expense of floral and faunal diversity. Global warming may encourage the expansion of agricultural activities into regions now occupied by natural ecosystems such as rangelands in the Badia region and forests. Such encroachment will have adverse effects on the fragile ecosystem in those areas (Badia and steppe areas). Primary model test results showed that the reduction of rainfall by 10 to 20% had a negative impact while the increase in rainfall by 10 to 20% had a positive impact on grain yield for both barley and wheat at the different temperature regimes. This is due to the fact that water is the main limiting growth factor for wheat and barley under rainfed agriculture on Jordan. The warming (increase in temperature by 1 to 4˚ C) had negative impact on barley grain yield while it had a positive impact on grain yield of wheat.

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

USGS Publications Warehouse

Scholl, Martha A.; Murphy, Sheila F.

2014-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Scaling Linguistic Characterization of Precipitation Variability

NASA Astrophysics Data System (ADS)

Primo, C.; Gutierrez, J. M.

2003-04-01

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

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Documentary reconstruction of monsoon rainfall variability over western India, 1781-1860

NASA Astrophysics Data System (ADS)

Adamson, George C. D.; Nash, David J.

2014-02-01

Investigations into the climatic forcings that affect the long-term variability of the Indian summer monsoon are constrained by a lack of reliable rainfall data prior to the late nineteenth century. Extensive qualitative and quantitative meteorological information for the pre-instrumental period exists within historical documents, although these materials have been largely unexplored. This paper presents the first reconstruction of monsoon variability using documentary sources, focussing on western India for the period 1781-1860. Three separate reconstructions are generated, for (1) Mumbai, (2) Pune and (3) the area of Gujarat bordering the Gulf of Khambat. A composite chronology is then produced from the three reconstructions, termed the Western India Monsoon Rainfall reconstruction (WIMR). The WIMR exhibits four periods of generally deficient monsoon rainfall (1780-1785, 1799-1806, 1830-1838 and 1845-1857) and three of above-normal rainfall (1788-1794, 1813-1828 and 1839-1844). The WIMR shows good correspondence with a dendroclimatic drought reconstruction for Kerala, although agreement with the western Indian portion of the tree-ring derived Monsoon Asia Drought Atlas is less strong. The reconstruction is used to examine the long-term relationship between the El Nino-Southern Oscillation (ENSO) and monsoon rainfall over western India. This exhibits peaks and troughs in correlation over time, suggesting a regular long-term fluctuation. This may be an internal oscillation in the ENSO-monsoon system or may be related to volcanic aerosol forcings. Further reconstructions of monsoon rainfall are necessary to validate this. The study highlights uncertainties in existing published rainfall records for 1817-1846 for western India.

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.

The partitioning of litter carbon during litter decomposition under different rainfall patterns: a laboratory study

NASA Astrophysics Data System (ADS)

Yang, X.; Szlavecz, K. A.; Langley, J. A.; Pitz, S.; Chang, C. H.

2017-12-01

Quantifying litter C into different C fluxes during litter decomposition is necessary to understand carbon cycling under changing climatic conditions. Rainfall patterns are predicted to change in the future, and their effects on the fate of litter carbon are poorly understood. Soils from deciduous forests in Smithsonian Environmental Research Center (SERC) in Maryland, USA were collected to reconstruct soil columns in the lab. 13C labeled tulip poplar leaf litter was used to trace carbon during litter decomposition. Top 1% and the mean of 15-minute historical precipitation data from nearby weather stations were considered as extreme and control rainfall intensity, respectively. Both intensity and frequency of rainfall were manipulated, while the total amount was kept constant. A pulse of CO2 efflux was detected right after each rainfall event in the soil columns with leaf litter. After the first event, CO2 efflux of the control rainfall treatment soils increased to threefold of the CO2 efflux before rain event and that of the extreme treatment soils increased to fivefold. However, in soils without leaf litter, CO2 efflux was suppressed right after rainfall events. After each rainfall event, the leaf litter contribution to CO2 efflux first showed an increase, decreased sharply in the following two days, and then stayed relatively constant. In soil columns with leaf litter, the order of cumulative CO2 efflux was control > extreme > intermediate. The order of cumulative CO2 efflux in the bare soil treatment was extreme > intermediate > control. The order of volume of leachate from different treatments was extreme > intermediate > control. Our initial results suggest that more intense rainfall events result in larger pulses of CO2, which is rarely measured in the field. Additionally, soils with and without leaf litter respond differently to precipitation events. This is important to consider in temperate regions where leaf litter cover changes throughout the year. Including the rainfall pattern as a parameter to the partitioning of litter carbon could help better project soil carbon cycling in the Mid-Atlantic region.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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.

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.

Towards a debris-flow warning system based on hydrological measurements of the triggering conditions. A study of El Rebaixader catchment (Central Pyrenees, Spain)

NASA Astrophysics Data System (ADS)

Abancó, Clàudia; Hürlimann, Marcel; Moya, José

2014-05-01

Debris flows represent a risk to the society due to their high destructive power. Rainfall is the main debris-flow triggering factor. Rainfall thresholds are generally used for warning of debris flow occurrence in susceptible catchments. However, the efficiency of such thresholds for real time hazard assessment is often conditioned by many factors, such as: the location and number of the rain gauges used (both to define the thresholds, and for setting off warnings); the temporal and spatial evolution of rainfall's convective cells or the effect of snow cover melting. These factors affect the length of the warning time, which is of crucial importance for issuing alert messages or alarms to the people and infrastructures at risk. The Rebaixader catchment (Central Pyrenees, Spain) is being monitored since 2009 by six stations recording information on initiation (4 stations) and flow detection and cinematic behaviour (2 stations). Until December 2013, 7 debris flows, 17 debris floods and 4 rockfalls have been recorded. The objectives of this work were: a) the definition of rainfall thresholds at two different rain gauges; b) the analysis of the infiltration patterns in order to define their potential use for warning systems and c) preliminary testing of rainfall thresholds' efficiency in terms of warning time, in this catchment. This last goal consisted in the comparison of the time elapsed between the rainfall threshold was exceeded and the event occurrence was detected by the stations at the channel area. The results suggest that the intensity-duration rainfall thresholds sometimes provide warning times which would be too short for an adequate reaction in the Rebaixader catchment (less than 10 minutes). The combination of such rainfall thresholds with infiltration measurements is useful to increase the warning time. This occurs especially in the events triggered in spring, when the snowmelt plays an important role in the event's triggering conditions. However, the effects of infiltration associated to the summer convective rainfalls are almost imperceptible; therefore their importance in warning systems decreases.

Precipitation variability of the Grand Canyon region, 1893 through 2009, and its implications for studying effects of gullying of Holocene terraces and associated archeological sites in Grand Canyon, Arizona

USGS Publications Warehouse

Hereford, Richard; Bennett, Glenn E.; Fairley, Helen C.

2014-01-01

A daily precipitation dataset covering a large part of the American Southwest was compiled for online electronic distribution (http://pubs.usgs.gov/of/2014/1006/). The dataset contains 10.8 million observations spanning January 1893 through January 2009 from 846 weather stations in six states and 13 climate divisions. In addition to processing the data for distribution, water-year totals and other statistical parameters were calculated for each station with more than 2 years of observations. Division-wide total precipitation, expressed as the average deviation from the individual station means of a climate division, shows that the region—including the Grand Canyon, Arizona, area—has been affected by alternating multidecadal episodes of drought and wet conditions. In addition to compiling and analyzing the long-term regional precipitation data, a second dataset consisting of high-temporal-resolution precipitation measurements collected between November 2003 and January 2009 from 10 localities along the Colorado River in Grand Canyon was compiled. An exploratory study of these high-temporal-resolution precipitation measurements suggests that on a daily basis precipitation patterns are generally similar to those at a long-term weather station in the canyon, which in turn resembles the patterns at other long-term stations on the canyon rims; however, precipitation amounts recorded by the individual inner canyon weather stations can vary substantially from station to station. Daily and seasonal rainfall patterns apparent in these data are not random. For example, the inner canyon record, although short and fragmented, reveals three episodes of widespread, heavy precipitation in late summer 2004, early winter 2005, and summer 2007. The 2004 event and several others had sufficient rainfall to initiate potentially pervasive erosion of the late Holocene terraces and related archeological features located along the Colorado River in Grand Canyon.

Short Term Patterns of Landslides Causing Death in Latin America and the Caribbean

NASA Astrophysics Data System (ADS)

Sepulveda, S. A.; Petley, D. N.

2015-12-01

Among natural hazards, landslides represent a significant source of loss of life in mountainous terrains. Many regions of Latin America and the Caribbean are prone to landslide activity, due to strong topographic relief, high tectonic uplift rates, seismicity and/or climate. Further, vulnerable populations are often concentrated in deep valleys or mountain foothills susceptible to catastrophic landslides, with vulnerability further increased by dense urbanization and precarious settlements in some large cities. While historic extremely catastrophic events such as the 1999 Vargas flows in Venezuela or the 1970 Huascaran rock avalanche in Peru are commonly cited to characterize landslide hazards in this region, less known is the landslide activity in periods without such large disasters. This study assesses the occurrence of fatal landslides in Latin America and the Caribbean between 2004 and 2013. Over this time period we recorded 611 landslides that caused 11,631 deaths in 25 countries, mostly as a result of rainfall triggers. The countries with the highest number of fatal landslides are Brazil, Colombia, Mexico, Guatemala, Peru and Haiti. The highest death toll for a single event was ca.3000. The dataset has not captured a strong El Niño event or large earthquakes in landslide prone areas, thus the analysis is indicative of short term rather than long term spatial and temporal patterns. Results show that at continental scale, the spatial distribution of landslides in the 2004-2013 period correlates well with relief, precipitation and population density, while the temporal distribution reflects the regional annual rainfall patterns. In urban areas, the presence of informal settlements has a big impact on the number of fatalities, while at national level weaker correlations with gross income, human development and corruption indices can be found. This work was funded by the Durham International Fellowships for Research and Enterprise and Fondecyt project 1140317.

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.;

Environmental controls of temporal and spatial variability in CO2 and CH4 fluxes in a neotropical peatland.

PubMed

Wright, Emma L; Black, Colin R; Turner, Benjamin L; Sjögersten, Sofie

2013-12-01

Tropical peatlands play an important role in the global storage and cycling of carbon (C) but information on carbon dioxide (CO2) and methane (CH4) fluxes from these systems is sparse, particularly in the Neotropics. We quantified short and long-term temporal and small scale spatial variation in CO2 and CH4 fluxes from three contrasting vegetation communities in a domed ombrotrophic peatland in Panama. There was significant variation in CO2 fluxes among vegetation communities in the order Campnosperma panamensis > Raphia taedigera > Cyperus. There was no consistent variation among sites and no discernible seasonal pattern of CH4 flux despite the considerable range of values recorded (e.g. -1.0 to 12.6 mg m(-2) h(-1) in 2007). CO2 fluxes varied seasonally in 2007, being greatest in drier periods (300-400 mg m(-2) h(-1)) and lowest during the wet period (60-132 mg m(-2) h(-1)) while very high emissions were found during the 2009 wet period, suggesting that peak CO2 fluxes may occur following both low and high rainfall. In contrast, only weak relationships between CH4 flux and rainfall (positive at the C. panamensis site) and solar radiation (negative at the C. panamensis and Cyperus sites) was found. CO2 fluxes showed a diurnal pattern across sites and at the Cyperus sp. site CO2 and CH4 fluxes were positively correlated. The amount of dissolved carbon and nutrients were strong predictors of small scale within-site variability in gas release but the effect was site-specific. We conclude that (i) temporal variability in CO2 was greater than variation among vegetation communities; (ii) rainfall may be a good predictor of CO2 emissions from tropical peatlands but temporal variation in CH4 does not follow seasonal rainfall patterns; and (iii) diurnal variation in CO2 fluxes across different vegetation communities can be described by a Fourier model. © 2013 John Wiley & Sons Ltd.

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.

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.

Spatial and Temporal Patterns of Throughfall Amounts and Solutes in a Tropical Montane Forest - Comparisons with Findings From Lowland Rain Forests

NASA Astrophysics Data System (ADS)

Zimmermann, A.

2007-05-01

The diverse tree species composition, irregular shaped tree crowns and a multi-layered forest structure affect the redistribution of rainfall in lower montane rain forests. In addition, abundant epiphyte biomass and associated canopy humus influence spatial patterns of throughfall. The spatial variability of throughfall amounts controls spatial patterns of solute concentrations and deposition. Moreover, the living and dead biomass interacts with the rainwater during the passage through the canopy and creates a chemical variability of its own. Since spatial and temporal patterns are intimately linked, the analysis of temporal solute concentration dynamics is an important step to understand the emerging spatial patterns. I hypothesized that: (1) the spatial variability of volumes and chemical composition of throughfall is particularly high compared with other forests because of the high biodiversity and epiphytism, (2) the temporal stability of the spatial pattern is high because of stable structures in the canopy (e.g. large epiphytes) that show only minor changes during the short term observation period, and (3) the element concentrations decrease with increasing rainfall because of exhausting element pools in the canopy. The study area at 1950 m above sea level is located in the south Ecuadorian Andes far away from anthropogenic emission sources and marine influences. Rain and throughfall were collected from August to October 2005 on an event and within-event basis for five precipitation periods and analyzed for pH, K, Na, Ca, Mg, NH4+, Cl-, NO3-, PO43-, TN, TP and TOC. Throughfall amounts and most of the solutes showed a high spatial variability, thereby the variability of H+, K, Ca, Mg, Cl- and NO3- exceeded those from a Brazilian tropical rain forest. The temporal persistence of the spatial patterns was high for throughfall amounts and varied depending on the solute. Highly persistent time stability patterns were detected for K, Mg and TOC concentrations. Time stability patterns of solute deposition were somewhat weaker than for concentrations for most of the solutes. Epiphytes strongly affected time stability patterns in that collectors situated below thick moss mats or arboreal bromeliads were in large part responsible for the extreme persistence with low throughfall amounts and high ion concentrations (H+ showed low concentrations). Rainfall solute concentrations were low compared with a variety of other tropical lowland and montane forest sites and showed a small temporal variability during the study period for both between and within-event dynamics, respectively. Throughfall solute concentrations were more within the range when compared with other sites and showed highly variable within-event dynamics. For most of the solutes, within-event concentrations did not reach low, constant concentrations in later event stages, rather concentrations fluctuated (e.g. Cl-) or increased (e.g. K and TOC). The within-event throughfall solute concentration dynamics in this lower montane rain forest contrast to recent observations from lowland tropical rain forests in Panama and Brazil. The observed within-event patterns are attributed (1) to the influence of epiphytes and associated canopy humus, and (2) to low rainfall intensities.

Influence of different rates of rainfall in the basin of the Uruguay River

NASA Astrophysics Data System (ADS)

Bohrer, M.; Zaparoli, B.; Saldanha, C. B.

2013-04-01

In the state of Rio Grande do Sul, the rainfall pattern is fairly regular and precipitation is well distributed throughout the year. The aim of this study was to evaluate the spatial and temporal distribution of precipitation in the Uruguay River basin from the determination of homogeneous regions based on the rainfall pattern. Values of 47 meteorological stations of the ANA (National Water Agency) from 1975 to 2005 were used, and values of Pacific sea surface temperature were collected from the National Oceanic and Atmospheric Administration, which is based on observed anomalies for different regions' niños (1 + niño 2, 3 niño, niño 4, niño 3 + 4). From the analysis of the results it was found that the study region showed five homogeneous regions. Knowing the time series of each region, it was possible to verify the regional variability in precipitation, indicating which regions have values above and below the climatological normal, and how the different indexes influence the rainfall pattern in the region.

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

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

Modeling climate change impacts on combined sewer overflow using synthetic precipitation time series.

PubMed

Bendel, David; Beck, Ferdinand; Dittmer, Ulrich

2013-01-01

In the presented study climate change impacts on combined sewer overflows (CSOs) in Baden-Wuerttemberg, Southern Germany, were assessed based on continuous long-term rainfall-runoff simulations. As input data, synthetic rainfall time series were used. The applied precipitation generator NiedSim-Klima accounts for climate change effects on precipitation patterns. Time series for the past (1961-1990) and future (2041-2050) were generated for various locations. Comparing the simulated CSO activity of both periods we observe significantly higher overflow frequencies for the future. Changes in overflow volume and overflow duration depend on the type of overflow structure. Both values will increase at simple CSO structures that merely divide the flow, whereas they will decrease when the CSO structure is combined with a storage tank. However, there is a wide variation between the results of different precipitation time series (representative for different locations).

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

Treesearch

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

2016-01-01

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

Global warming induced hybrid rainy seasons in the Sahel

NASA Astrophysics Data System (ADS)

Salack, Seyni; Klein, Cornelia; Giannini, Alessandra; Sarr, Benoit; Worou, Omonlola N.; Belko, Nouhoun; Bliefernicht, Jan; Kunstman, Harald

2016-10-01

The small rainfall recovery observed over the Sahel, concomitant with a regional climate warming, conceals some drought features that exacerbate food security. The new rainfall features include false start and early cessation of rainy seasons, increased frequency of intense daily rainfall, increasing number of hot nights and warm days and a decreasing trend in diurnal temperature range. Here, we explain these mixed dry/wet seasonal rainfall features which are called hybrid rainy seasons by delving into observed data consensus on the reduction in rainfall amount, its spatial coverage, timing and erratic distribution of events, and other atmospheric variables crucial in agro-climatic monitoring and seasonal forecasting. Further composite investigations of seasonal droughts, oceans warming and the regional atmospheric circulation nexus reveal that the low-to-mid-level atmospheric winds pattern, often stationary relative to either strong or neutral El-Niño-Southern-Oscillations drought patterns, associates to basin warmings in the North Atlantic and the Mediterranean Sea to trigger hybrid rainy seasons in the Sahel. More challenging to rain-fed farming systems, our results suggest that these new rainfall conditions will most likely be sustained by global warming, reshaping thereby our understanding of food insecurity in this region.

Soil Carbon Recovery of Degraded Steppe Ecosystems of the Mongolian Plateau

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Togtohyn, C.; Qi, J.

2013-12-01

Mongolian steppe grassland systems are critical source of ecosystem services to societal groups in temperate East Asia. These systems are characterized by their arid and semiarid environments where rainfall tends to be too variable or evaporative losses reduce water availability to reliably support cropping systems or substantial forest cover. These steppe ecosystems have supported land use practices to accommodate the variable rainfall patterns, and seasonal and spatial patterns of forage production displayed by the nomadic pastoral systems practiced across Asia. These pastoral systems are dependent on grassland ecosystem services, including forage production, wool, skins, meat and dairy products, and in many systems provide critical biodiversity and land and water protection services which serve to maintain pastoral livelihoods. Precipitation variability and associated drought conditions experienced frequently in these grassland systems are key drivers of these systems. However, during the past several decades climate change and grazing and land use conversion have resulted in degradation of ecosystem services and loss of soil organic matter. Recent efforts in China and Mongolia are investigating different grazing management practices to restore soil organic matter in these degraded systems. Simulation modeling is being applied to evaluate the long-term benefits of different grazing management regimes under various climate scenarios.

Conservative water management in the widespread conifer genus Callitris

PubMed Central

Brodribb, Timothy J.; Bowman, David M. J. S.; Grierson, Pauline F.; Murphy, Brett P.; Nichols, Scott; Prior, Lynda D.

2013-01-01

Water management by woody species encompasses characters involved in seeking, transporting and evaporating water. Examples of adaptation of individual characters to water availability are common, but little is known about the adaptability of whole-plant water management. Here we use plant hydration and growth to examine variation in whole-plant water management characteristics within the conifer genus Callitris. Using four species that cover the environmental extremes in the Australian continent, we compare seasonal patterns of growth and hydration over 2 years to determine the extent to which species exhibit adaptive variation to the local environment. Detailed measurements of gas exchange in one species are used to produce a hydraulic model to predict changes in leaf water potential throughout the year. This same model, when applied to the remaining three species, provided a close representation of the measured patterns of water potential gradient at all sites, suggesting strong conservation in water management, a conclusion supported by carbon and oxygen isotope measurements in Callitris from across the continent. We conclude that despite its large range in terms of rainfall, Callitris has a conservative water management strategy, characterized by a high sensitivity of growth to rainfall and a delayed (anisohydric) closure of stomata during soil drying.

Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

[Analysis on nitrogen and phosphorus loading of non-point sources in Shiqiao river watershed based on L-THIA model].

PubMed

Li, Kai; Zeng, Fan-Tang; Fang, Huai-Yang; Lin, Shu

2013-11-01

Based on the Long-term Hydrological Impact Assessment (L-THIA) model, the effect of land use and rainfall change on nitrogen and phosphorus loading of non-point sources in Shiqiao river watershed was analyzed. The parameters in L-THIA model were revised according to the data recorded in the scene of runoff plots, which were set up in the watershed. The results showed that the distribution of areas with high pollution load was mainly concentrated in agricultural land and urban land. Agricultural land was the biggest contributor to nitrogen and phosphorus load. From 1995 to 2010, the load of major pollutants, namely TN and TP, showed an obviously increasing trend with increase rates of 17.91% and 25.30%, respectively. With the urbanization in the watershed, urban land increased rapidly and its area proportion reached 43.94%. The contribution of urban land to nitrogen and phosphorus load was over 40% in 2010. This was the main reason why pollution load still increased obviously while the agricultural land decreased greatly in the past 15 years. The rainfall occurred in the watershed was mainly concentrated in the flood season, so the nitrogen and phosphorus load of the flood season was far higher than that of the non-flood season and the proportion accounting for the whole year was over 85%. Pearson regression analysis between pollution load and the frequency of different patterns of rainfall demonstrated that rainfall exceeding 20 mm in a day was the main rainfall type causing non-point source pollution.

Assessment of rainfall thresholds for landslide triggering in the Pacific Northwest: extreme short-term rainfall and long-term trends

NASA Astrophysics Data System (ADS)

Stanley, T.; Kirschbaum, D.; Sobieszczyk, S.; Jasinski, M. F.; Borak, J.; Yatheendradas, S.

2017-12-01

Landslides occur every year in the U.S. Pacific Northwest due to extreme rainfall, snow cover, and rugged topography. Data for 15,000 landslide events in Washington and Oregon were assembled from State Surveys, Departments of Transportation, a Global Landslide Catalog compiled by NASA, and other sources. This new inventory was evaluated against rainfall data from the National Climate Assessment (NCA) Land Data Assimilation System to characterize the regional rainfall conditions that trigger landslides. Analysis of these data sets indicates clear differences in triggering thresholds between extreme weather systems such as a Pineapple Express and the more typical peak seasonal rainfall between November and February. The study also leverages over 30 years of precipitation and land surface information to inform variability of landslide triggering over multiple decades and landslide trends within the region.

On the Comparison of the Global Surface Soil Moisture product and Land Surface Modeling

NASA Astrophysics Data System (ADS)

Delorme, B., Jr.; Ottlé, C.; Peylin, P.; Polcher, J.

2016-12-01

Thanks to its large spatio-temporal coverage, the new ESA CCI multi-instruments dataset offers a good opportunity to assess and improve land surface models parametrization. In this study, the ESA CCI surface soil moisture (SSM) combined product (v2.2) has been compared to the simulated top first layers of the ORCHIDEE LSM (the continental part of the IPSL earth system model), in order to evaluate its potential of improvements with data assimilation techniques. The ambition of the work was to develop a comprehensive comparison methodology by analyzing simultaneously the temporal and spatial structures of both datasets. We analyzed the SSM synoptic, seasonal, and inter-annual variations by decomposing the signals into fast and slow components. ORCHIDEE was shown to adequately reproduce the observed SSM dynamics in terms of temporal correlation. However, these correlation scores are supposed to be strongly influenced by SSM seasonal variability and the quality of the model input forcing. Autocorrelation and spectral analyses brought out disagreements in the temporal inertia of the upper soil moisture reservoirs. By linking our results to land cover maps, we found that ORCHIDEE is more dependent on rainfall events compared to the observations in regions with sparse vegetation cover. These diflerences might be due to a wrong partition of rainfall between soil evaporation, transpiration, runofl and drainage in ORCHIDEE. To refine this analysis, a single value decomposition (SVD) of the co-variability between rainfall provided by WFDEI and soil moisture was pursued over Central Europe and South Africa. It showed that spatio-temporal co-varying patterns between ORCHIDEE and rainfall and the ESA-CCI product and rainfall are in relatively good agreement. However, the leading SVD pattern, which exhibits a strong annual cycle and explains the same portion of covariance for both datasets, explains a much larger fraction of variance for ORCHIDEE than for the ESA-CCI product. These results highlight that the role of other surface variables presenting a strong seasonal variability (like vegetation cover, possibly irrigation) is not accounted for similarly in both the model and the product, and that further work is needed to explore these discrepancies.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

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 trends in the South Asian summer monsoon and its related large-scale dynamics with focus over Pakistan

NASA Astrophysics Data System (ADS)

Latif, M.; Syed, F. S.; Hannachi, A.

2017-06-01

The study of regional rainfall trends over South Asia is critically important for food security and economy, as both these factors largely depend on the availability of water. In this study, South Asian summer monsoon rainfall trends on seasonal and monthly (June-September) time scales have been investigated using three observational data sets. Our analysis identify a dipole-type structure in rainfall trends over the region north of the Indo-Pak subcontinent, with significant increasing trends over the core monsoon region of Pakistan and significant decreasing trends over the central-north India and adjacent areas. The dipole is also evident in monthly rainfall trend analyses, which is more prominent in July and August. We show, in particular, that the strengthening of northward moisture transport over the Arabian Sea is a likely reason for the significant positive trend of rainfall in the core monsoon region of Pakistan. In contrast, over the central-north India region, the rainfall trends are significantly decreasing due to the weakening of northward moisture transport over the Bay of Bengal. The leading empirical orthogonal functions clearly show the strengthening (weakening) patterns of vertically integrated moisture transport over the Arabian Sea (Bay of Bengal) in seasonal and monthly interannual time scales. The regression analysis between the principal components and rainfall confirm the dipole pattern over the region. Our results also suggest that the extra-tropical phenomena could influence the mean monsoon rainfall trends over Pakistan by enhancing the cross-equatorial flow of moisture into the Arabian Sea.

[Characteristics of soil phosphorous loss under different ecological planting patterns in hilly red soil regions of southern Hunan Province, China].

PubMed

Yuan, Min; Wen, Shi-Lin; Xu, Ming-Gang; Dong, Chun-Hua; Qin, Lin; Zhang, Lu

2013-11-01

Taking a large standard runoff plot on a red soil slope in Qiyang County, southern Hunan Province as a case, this paper studied the surface soil phosphorus loss characteristics in the hilly red soil regions of southern Hunan under eight ecological planting patterns. The phosphorus loss from wasteland (T1) was most serious, followed by that from natural sloped cropping patterns (T2 and T3), while the phosphorus loss amount from terrace cropping patterns (T4-T8) was the least, only occupying 9.9%, 37%, 0.7%, 2.3%, and 1.9% of T1, respectively. The ecological planting patterns directly affected the forms of surface-lost soil phosphorus, with the particulate phosphorus (PP) as the main lost form. Under the condition of rainstorm (daily rainfall > 50 mm), rainfall had lesser effects on the phosphorus loss among different planting patterns. However, the phosphorus loss increased with increasing rain intensity. The surface soil phosphorus loss mainly occurred from June to September. Both the rainfall and the rain intensity were the factors directly affected the time distribution of surface soil phosphorus loss in hilly red soil regions of southern Hunan.

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.

Impact of the rainfall pattern on synthetic pesticides and copper runoff from a vineyard catchment

NASA Astrophysics Data System (ADS)

Payraudeau, Sylvain; Meite, Fatima; Wiegert, Charline; Imfeld, Gwenaël

2017-04-01

Runoff is a major process of pesticide transport from agricultural land to downstream aquatic ecosystems. The impact of rainfall characteristics on the transport of runoff-related pesticide is rarely evaluated at the catchment scale. Here, we evaluate the influence of rainfall pattern on the mobilization of synthetic pesticides and copper fungicides in runoff from a small vineyard catchment, both at the plot and catchment scales. During two vineyard growing seasons in 2015 and 2016 (from March to October), we monitored rainfall, runoff, and concentrations of copper and 20 fungicides and herbicides applied by winegrowers at the Rouffach vineyard catchment (France, Alsace; 42.5 ha). Rainfall data were recorded within the catchment while runoff measurement and flow-proportional water sampling were carried out at the outlet of the plot (1486 m2; 87.5 × 17 m) and the catchment. In total, discharges of the 14 runoff events were continuously monitored between March and October 2015 using bubbler flow modules combined with Venturi channels. Detailed and distributed dataset on pesticide applications were extracted from survey (copper formulations and type of pesticides, amount and application dates). Pools of copper and synthetic pesticides were quantified weekly in the topsoil (0-3 cm) by systematic sampling across the catchment. The concentrations of copper (10 mg.kg-1 dried soil) and synthetic pesticides (close to the quantification limit, i.e. 0.05 µg.L-1) available in the top soil for off-site transport largely differed over time. Between March and October, an accumulation of copper of 10% was observed in the top-soil while pesticide concentration decreased below the quantification limits after a few days or weeks following application, depending of the compounds. The average runoff generated at the plot scale was very low (0.13% ± 0.30). The maximum runoff reached 1.37% during the storm of July 22, 2015. Synthetic pesticides exported by runoff was less than 1‰ of the applications. The copper mass exported represented about 1% (i.e. 2,085 g at the plot's scale) of the seasonal input, and mainly occurred during the major storm event. Copper were mainly exported in association with suspended particulate matter (SPM) (>80% of the total load). The partitioning between dissolved and SPM phases differs for the synthetic pesticides as expected by their properties. The rainfall pattern influences concentrations and loads of copper and the pesticides. Dissolved pesticide loads normalized by the pesticide mass in soil varied with larger rainfall intensities, runoff discharges and volumes. Contrasted relationships between rainfall characteristics (i.e. intensity, duration and total amount) and the load exported suggest that mechanisms of contaminant delivery from the vineyard soil differs among the pesticides and for copper. The results support the idea that, even in small catchment areas, the rainfall pattern (i.e. rainfall intensity and duration) partly controls the transport of pesticide and copper loads in runoff. Though other factors, such as the chemical characteristics and the amount and timing of applications, are important drivers for pesticide runoff, the rainfall patterns also determine the transport of pesticides from catchment to downstream aquatic ecosystems, and thus the ecotoxicological risk.

The Relative Importance of Convective and Trade-wind Orographic Precipitation to Streamflow in the Luquillo Mountains, Eastern Puerto Rico

NASA Astrophysics Data System (ADS)

Scholl, M. A.; Shanley, J. B.; Occhi, M.; Scatena, F. N.

2012-12-01

Like many mountainous areas in the tropics, watersheds in the Luquillo Mountains of Puerto Rico (18.3° N) have abundant rainfall and stream discharge, but relatively little storage capacity. Therefore, the water supply is vulnerable to drought and water availability may be affected by projected changes in regional temperature and atmospheric dynamics due to global warming. To help determine the links between climate and water availability, precipitation patterns were analyzed, and stable-isotope signatures of precipitation from different seasonal weather systems were established to identify those that are most important in maintaining streamflow and groundwater recharge. Stable isotope data include cloud water, rainfall, throughfall, streamflow, and groundwater from the Rio Mameyes and Rio Icacos/ Rio Blanco watersheds. Precipitation inputs have a wide range of stable isotope values, from fog/cloud water with δ2H and δ18O averaging +3.2‰, -1.74‰ respectively, to tropical storm rain with values as low as -154‰, -20.4‰. Spatial and temporal patterns of water isotopic values on this Caribbean island are different than higher latitude, continental watersheds. The data exhibit a 'reverse seasonality', with higher isotopic values in winter and lower values in summer; and stable isotope values of stream water do not decrease as expected with increasing altitude, because of cloud water input. Rain isotopic values vary predictably with local and mesoscale weather patterns and correlate strongly with cloud altitude. This correlation allows us to assign isotopic signatures to different sources of precipitation, and to investigate which climate patterns contribute to streamflow and groundwater recharge. At a measurement site at 615 m in the Luquillo Mountains, the average length of time between rain events was 15 h, and 45% of the rain events were <2 mm, reflecting the frequent small rain events of the trade-wind orographic rainfall weather pattern. Long-term average streamflow isotopic composition indicates a disproportionately large contribution of this trade-wind precipitation to streamflow, highlighting the importance of this climate pattern to the hydrology of the watersheds. Isotopic composition of groundwater suggests a slightly higher proportion of convective precipitation, but still smaller than in total rainfall. Hydrograph separation experiments yielded information on stormflow characteristics, with quantification of contributing sources determined from water isotopes and solute chemistry. The evidence that intense convective rain events run off and light trade-wind showers appear to contribute much of the baseflow indicates that the area may undergo a change in water supply if the trade-wind orographic precipitation dynamics in the Caribbean are affected by future climate change.

Climatological determinants of woody cover in Africa.

PubMed

Good, Stephen P; Caylor, Kelly K

2011-03-22

Determining the factors that influence the distribution of woody vegetation cover and resolving the sensitivity of woody vegetation cover to shifts in environmental forcing are critical steps necessary to predict continental-scale responses of dryland ecosystems to climate change. We use a 6-year satellite data record of fractional woody vegetation cover and an 11-year daily precipitation record to investigate the climatological controls on woody vegetation cover across the African continent. We find that-as opposed to a relationship with only mean annual rainfall-the upper limit of fractional woody vegetation cover is strongly influenced by both the quantity and intensity of rainfall events. Using a set of statistics derived from the seasonal distribution of rainfall, we show that areas with similar seasonal rainfall totals have higher fractional woody cover if the local rainfall climatology consists of frequent, less intense precipitation events. Based on these observations, we develop a generalized response surface between rainfall climatology and maximum woody vegetation cover across the African continent. The normalized local gradient of this response surface is used as an estimator of ecosystem vegetation sensitivity to climatological variation. A comparison between predicted climate sensitivity patterns and observed shifts in both rainfall and vegetation during 2009 reveals both the importance of rainfall climatology in governing how ecosystems respond to interannual fluctuations in climate and the utility of our framework as a means to forecast continental-scale patterns of vegetation shifts in response to future climate change.

Assessment on inflow and infiltration in sewerage systems of Kuantan, Pahang.

PubMed

Yap, Hiew Thong; Ngien, Su Kong

2017-12-01

Inflow and infiltration are important aspects of sewerage systems that need to be considered during the design stage and constantly monitored once the sewerage system is in operation. The aim of this research is to analyse the relationship of rainfall as well as inflow infiltration with sewage flow patterns through data collected from fieldwork. Three sewer pipelines were selected at the residential areas of Taman Lepar Hilir Saujana, Bandar Putra and Kota Sas for data collection. Sewage flow data were collected in terms of flowrate, velocity and depth of flow using flowmeters with ultrasonic sensors that utilize the continuous Doppler effect in the sewer pipelines, while rainfall intensity data were collected using rain gauges installed at the study locations. Based on the result, the average infiltration rates of Q peak and Q ave for the locations were 17% and 21%, which exceeded the respective values of 5% and 10% stated in Hammer and Hammer. The flowrate of wastewater in the sewer pipelines was found to be directly proportional to rainfall. These findings indicate that the sewer pipelines in the study areas may have been affected by capacity reduction, whereas the sewerage treatment plants receiving the wastewater influent may have been overloaded.

Methods to evvaluate normal rainfall for short-term wetland hydrology assessment

Treesearch

Jaclyn Sumner; Michael J. Vepraskas; Randall K. Kolka

2009-01-01

Identifying sites meeting wetland hydrology requirements is simple when long-term (>10 years) records are available. Because such data are rare, we hypothesized that a single-year of hydrology data could be used to reach the same conclusion as with long-term data, if the data were obtained during a period of normal or below normal rainfall. Long-term (40-45 years)...

Simulation of the effects of rainfall and groundwater use on historical lake water levels, groundwater levels, and spring flows in central Florida

USGS Publications Warehouse

O'Reilly, Andrew M.; Roehl, Edwin A.; Conrads, Paul; Daamen, Ruby C.; Petkewich, Matthew D.

2014-01-01

The urbanization of central Florida has progressed substantially in recent decades, and the total population in Lake, Orange, Osceola, Polk, and Seminole Counties more than quadrupled from 1960 to 2010. The Floridan aquifer system is the primary source of water for potable, industrial, and agricultural purposes in central Florida. Despite increases in groundwater withdrawals to meet the demand of population growth, recharge derived by infiltration of rainfall in the well-drained karst terrain of central Florida is the largest component of the long-term water balance of the Floridan aquifer system. To complement existing physics-based groundwater flow models, artificial neural networks and other data-mining techniques were used to simulate historical lake water level, groundwater level, and spring flow at sites throughout the area. Historical data were examined using descriptive statistics, cluster analysis, and other exploratory analysis techniques to assess their suitability for more intensive data-mining analysis. Linear trend analyses of meteorological data collected by the National Oceanic and Atmospheric Administration at 21 sites indicate 67 percent of sites exhibited upward trends in air temperature over at least a 45-year period of record, whereas 76 percent exhibited downward trends in rainfall over at least a 95-year period of record. Likewise, linear trend analyses of hydrologic response data, which have varied periods of record ranging in length from 10 to 79 years, indicate that water levels in lakes (307 sites) were about evenly split between upward and downward trends, whereas water levels in 69 percent of wells (out of 455 sites) and flows in 68 percent of springs (out of 19 sites) exhibited downward trends. Total groundwater use in the study area increased from about 250 million gallons per day (Mgal/d) in 1958 to about 590 Mgal/d in 1980 and remained relatively stable from 1981 to 2008, with a minimum of 559 Mgal/d in 1994 and a maximum of 773 Mgal/d in 2000. The change in groundwater-use trend in the early 1980s and the following period of relatively slight trend is attributable to the concomitant effects of increasing public-supply withdrawals and decreasing use of water by the phosphate industry and agriculture. On the basis of available historical data and exploratory analyses, empirical lake water-level, groundwater-level, and spring-flow models were developed for 22 lakes, 23 wells, and 6 springs. Input time series consisting of various frequencies and frequency-band components of daily rainfall (1942 to 2008) and monthly total groundwater use (1957 to 2008) resulted in hybrid signal-decomposition artificial neural network models. The final models explained much of the variability in observed hydrologic data, with 43 of the 51 sites having coefficients of determination exceeding 0.6, and the models matched the magnitude of the observed data reasonably well, such that models for 32 of the 51 sites had root-mean-square errors less than 10 percent of the measured range of the data. The Central Florida Artificial Neural Network Decision Support System was developed to integrate historical databases and the 102 site-specific artificial neural network models, model controls, and model output into a spreadsheet application with a graphical user interface that allows the user to simulate scenarios of interest. Overall, the data-mining analyses indicate that the Floridan aquifer system in central Florida is a highly conductive, dynamic, open system that is strongly influenced by external forcing. The most important external forcing appears to be rainfall, which explains much of the multiyear cyclic variability and long-term downward trends observed in lake water levels, groundwater levels, and spring flows. For most sites, groundwater use explains less of the observed variability in water levels and flows than rainfall. Relative groundwater-use impacts are greater during droughts, however, and long-term trends in water levels and flows were identified that are consistent with historical groundwater-use patterns. The sensitivity of the hydrologic system to rainfall is expected, owing to the well-drained karst terrain and relatively thin confinement of the Floridan aquifer system in much of central Florida. These characteristics facilitate the relatively rapid transmission of infiltrating water from rainfall to the water table and contribute to downward leakage of water to the Floridan aquifer system. The areally distributed nature of rainfall, as opposed to the site-specific nature of groundwater use, and the generally high transmissivity and low storativity properties of the semiconfined Floridan aquifer system contribute to the prevalence of water-level and flow patterns that mimic rainfall patterns. In general, the data-mining analyses demonstrate that the hydrologic system in central Florida is affected by groundwater use differently during wet periods, when little or no system storage is available (high water levels), compared to dry periods, when there is excess system storage (low water levels). Thus, by driving the overall behavior of the system, rainfall indirectly influences the degree to which groundwater use will effect persistent trends in water levels and flows, with groundwater-use impacts more prevalent during periods of low water levels and spring flows caused by low rainfall and less prevalent during periods of high water levels and spring flows caused by high rainfall. Differences in the magnitudes of rainfall and groundwater use during wet and dry periods also are important determinants of hydrologic response. An important implication of the data-mining analyses is that rainfall variability at subannual to multidecadal timescales must be considered in combination with groundwater use to provide robust system-response predictions that enhance sustainable resource management in an open karst aquifer system. The data-driven approach was limited, however, by the confounding effects of correlation between rainfall and groundwater use, the quality and completeness of the historical databases, and the spatial variations in groundwater use. The data-mining analyses indicate that available historical data when used alone do not contain sufficient information to definitively quantify the related individual effects of rainfall and groundwater use on hydrologic response. The knowledge gained from data-driven modeling and the results from physics-based modeling, when compared and used in combination, can yield a more comprehensive assessment and a more robust understanding of the hydrologic system than either of the approaches used separately.

Assessing vegetation structure and ANPP dynamics in a grassland-shrubland Chihuahuan ecotone using NDVI-rainfall relationships

NASA Astrophysics Data System (ADS)

Moreno-de las Heras, M.; Diaz-Sierra, R.; Turnbull, L.; Wainwright, J.

2015-01-01

Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. A classic case of vegetation change is the shrub-encroachment process that has been taking place over the last 150 years in the Chihuahuan Desert, where large areas of grasslands dominated by perennial grass species (black grama, Bouteloua eriopoda, and blue grama, B. gracilis) have transitioned to shrublands dominated by woody species (creosotebush, Larrea tridentata, and mesquite, Prosopis glandulosa), accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including exogenous triggering factors such as precipitation variations and land-use change, and endogenous amplifying mechanisms brought about by soil erosion-vegetation feedbacks. In this study, simulations of plant biomass dynamics with a simple modelling framework indicate that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation-rainfall relationships. We analyze the structure and dynamics of vegetation at an 18 km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000-2013) records of medium-resolution remote sensing of vegetation greenness (MODIS NDVI) and precipitation. Spatial evaluation of NDVI-rainfall relationship at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation, and to (b) decompose the NDVI signal into partial primary production components for herbaceous vegetation and shrubs across the study site. We further apply remote-sensed annual net primary production (ANPP) estimations and landscape type classification to explore the influence of inter-annual variations in seasonal precipitation on the production of herbaceous and shrub vegetation. Our results suggest that changes in the amount and temporal pattern of precipitation comprising reductions in monsoonal summer rainfall and/or increases in winter precipitation may enhance the shrub-encroachment process in desert grasslands of the American Southwest.

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

Treesearch

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

2011-01-01

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

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.

Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations

NASA Technical Reports Server (NTRS)

Iguchi, Takamichi; Tao, Wei-Kuo; Wu, Di; Peters-Lidard, Christa; Santanello, Joseph A.; Kemp, Eric; Tian, Yudong; Case, Jonathan; Wang, Weile; Ferraro, Robert;

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

STEP-TRAMM - A modeling interface for simulating localized rainfall induced shallow landslides and debris flow runout pathways

NASA Astrophysics Data System (ADS)

von Ruette, Jonas; Lehmann, Peter; Fan, Linfeng; Bickel, Samuel; Or, Dani

2017-04-01

Landslides and subsequent debris-flows initiated by rainfall represent a ubiquitous natural hazard in steep mountainous regions. We integrated a landslide hydro-mechanical triggering model and associated debris flow runout pathways with a graphical user interface (GUI) to represent these natural hazards in a wide range of catchments over the globe. The STEP-TRAMM GUI provides process-based locations and sizes of landslides patterns using digital elevation models (DEM) from SRTM database (30 m resolution) linked with soil maps from global database SoilGrids (250 m resolution) and satellite based information on rainfall statistics for the selected region. In a preprocessing step STEP-TRAMM models soil depth distribution and complements soil information that jointly capture key hydrological and mechanical properties relevant to local soil failure representation. In the presentation we will discuss feature of this publicly available platform and compare landslide and debris flow patterns for different regions considering representative intense rainfall events. Model outcomes will be compared for different spatial and temporal resolutions to test applicability of web-based information on elevation and rainfall for hazard assessment.

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

NASA Astrophysics Data System (ADS)

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

2012-08-01

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

Changing character of rainfall in eastern China, 1951-2007.

PubMed

Day, Jesse A; Fung, Inez; Liu, Weihan

2018-02-27

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call "frontal rain events." In spring and early summer (known as "Meiyu Season"), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951-2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the "South Flood-North Drought" pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994-2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

Techniques for estimating magnitude and frequency of floods on streams in Indiana

USGS Publications Warehouse

Glatfelter, D.R.

1984-01-01

A rainfall-runoff model was tlsed to synthesize long-term peak data at 11 gaged locations on small streams. Flood-frequency curves developed from the long-term synthetic data were combined with curves based on short-term observed data to provide weighted estimates of flood magnitude and frequency at the rainfall-runoff stations.

Trends in Streamflow Characteristics at Long-Term Gaging Stations, Hawaii

USGS Publications Warehouse

Oki, Delwyn S.

2004-01-01

The surface-water resources of Hawaii have significant cultural, aesthetic, ecologic, and economic importance. Proper management of the surface-water resources of the State requires an understanding of the long- and short-term variability in streamflow characteristics that may occur. The U.S. Geological Survey maintains a network of stream-gaging stations in Hawaii, including a number of stations with long-term streamflow records that can be used to evaluate long-term trends and short-term variability in flow characteristics. The overall objective of this study is to obtain a better understanding of long-term trends and variations in streamflow on the islands of Hawaii, Maui, Molokai, Oahu, and Kauai, where long-term stream-gaging stations exist. This study includes (1) an analysis of long-term trends in flows (both total flow and estimated base flow) at 16 stream-gaging stations, (2) a description of patterns in trends within the State, and (3) discussion of possible regional factors (including rainfall) that are related to the observed trends and variations. Results of this study indicate the following: 1. From 1913 to 2002 base flows generally decreased in streams for which data are available, and this trend is consistent with the long-term downward trend in annual rainfall over much of the State during that period. 2. Monthly mean base flows generally were above the long-term average from 1913 to the early 1940s and below average after the early 1940s to 2002, and this pattern is consistent with the detected downward trends in base flows from 1913 to 2002. 3. Long-term downward trends in base flows of streams may indicate a reduction in ground-water discharge to streams caused by a long-term decrease in ground-water storage and recharge. 4. From 1973 to 2002, trends in streamflow were spatially variable (up in some streams and down in others) and, with a few exceptions, generally were not statistically significant. 5. Short-term variability in streamflow is related to the seasons and to the EL Ni?o-Southern Oscillation phenomenon that may be partly modulated by the phase of the Pacific Decadal Oscillation. 6. At almost all of the long-term stream-gaging stations considered in this study, average total flow (and to a lesser extent average base flow) during the winter months of January to March tended to be low following El Ni?o periods and high following La Ni?a periods, and this tendency was accentuated during positive phases of the Pacific Decadal Oscillation. 7. The El Ni?o-Southern Oscillation phenomenon occurs at a relatively short time scale (a few to several years) and appears to be more strongly related to processes controlling rainfall and direct runoff than ground-water storage and base flow. Long-term downward trends in base flows of streams may indicate a reduction in ground-water storage and recharge. Because ground water provides about 99 percent of Hawaii's domestic drinking water, a reduction in ground-water storage and recharge has serious implications for drinking-water availability. In addition, reduction in stream base flows may reduce habitat availability for native stream fauna and water availability for irrigation purposes. Further study is needed to determine (1) whether the downward trends in base flows from 1913 to 2002 will continue or whether the observed pattern is part of a long-term cycle in which base flows may eventually return to levels measured during 1913 to the early 1940s, (2) the physical causes for the detected trends and variations in streamflow, and (3) whether regional climate indicators successfully can be used to predict streamflow trends and variations throughout the State. These needs for future study underscore the importance of maintaining a network of long-term-trend stream-gaging stations in Hawaii.

[Effects of rainfall intensity on rainfall infiltration and redistribution in soil on Loess slope land].

PubMed

Li, Yi; Shao, Ming'an

2006-12-01

With simulation test, this paper studied the patterns of rainfall infiltration and redistribution in soil on typical Loess slope land, and analyzed the quantitative relations between the infiltration and redistribution and the movement of soil water and mass, with rainfall intensity as the main affecting factor. The results showed that rainfall intensity had significant effects on the rainfall infiltration and water redistribution in soil, and the microcosmic movement of soil water. The larger the rainfall intensity, the deeper the wetting front of rainfall infiltration and redistribution was, and the wetting front of soil water redistribution had a slower increase velocity than that of rainfall infiltration. The power function of the wetting front with time, and also with rainfall intensity, was fitted well. There was also a quantitative relation between the wetting front of rainfall redistribution and the duration of rainfall. The larger the rainfall intensity, the higher the initial and steady infiltration rates were, and the cumulative infiltration increased faster with time. Moreover, the larger the rainfall intensity, the smaller the wetting front difference was at the top and the end of the slope. With the larger rainfall intensity, both the difference of soil water content and its descending trend between soil layers became more obvious during the redistribution process on slope land.

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

PubMed

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

2015-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-02-01

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

Sensitivity of extreme precipitation to temperature: the variability of scaling factors from a regional to local perspective

NASA Astrophysics Data System (ADS)

Schroeer, K.; Kirchengast, G.

2018-06-01

Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale.

New features of global climatology revealed by satellite-derived oceanic rainfall maps

NASA Technical Reports Server (NTRS)

Rao, M. S. V.; Theon, J. S.

1977-01-01

Quantitative rainfall maps over the oceanic areas of the globe were derived from the Nimbus 5 Electrically Scanning Microwave Radiometer (ESMR) data. Analysis of satellite derived oceanic rainfall maps reveal certain distinctive characteristics of global patterns for the years 1973-74. The main ones are (1) the forking of the Intertropical Convergence Zone in the Pacific, (2) a previously unrecognized rain area in the South Atlantic, (3) the bimodal behavior of rainbelts in the Indian Ocean and (4) the large interannual variability in oceanic rainfall. These features are discussed.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

Multi-century cool- and warm-season rainfall reconstructions for Australia's major climatic regions

NASA Astrophysics Data System (ADS)

Freund, Mandy; Henley, Benjamin J.; Karoly, David J.; Allen, Kathryn J.; Baker, Patrick J.

2017-11-01

Australian seasonal rainfall is strongly affected by large-scale ocean-atmosphere climate influences. In this study, we exploit the links between these precipitation influences, regional rainfall variations, and palaeoclimate proxies in the region to reconstruct Australian regional rainfall between four and eight centuries into the past. We use an extensive network of palaeoclimate records from the Southern Hemisphere to reconstruct cool (April-September) and warm (October-March) season rainfall in eight natural resource management (NRM) regions spanning the Australian continent. Our bi-seasonal rainfall reconstruction aligns well with independent early documentary sources and existing reconstructions. Critically, this reconstruction allows us, for the first time, to place recent observations at a bi-seasonal temporal resolution into a pre-instrumental context, across the entire continent of Australia. We find that recent 30- and 50-year trends towards wetter conditions in tropical northern Australia are highly unusual in the multi-century context of our reconstruction. Recent cool-season drying trends in parts of southern Australia are very unusual, although not unprecedented, across the multi-century context. We also use our reconstruction to investigate the spatial and temporal extent of historical drought events. Our reconstruction reveals that the spatial extent and duration of the Millennium Drought (1997-2009) appears either very much below average or unprecedented in southern Australia over at least the last 400 years. Our reconstruction identifies a number of severe droughts over the past several centuries that vary widely in their spatial footprint, highlighting the high degree of diversity in historical droughts across the Australian continent. We document distinct characteristics of major droughts in terms of their spatial extent, duration, intensity, and seasonality. Compared to the three largest droughts in the instrumental period (Federation Drought, 1895-1903; World War II Drought, 1939-1945; and the Millennium Drought, 1997-2005), we find that the historically documented Settlement Drought (1790-1793), Sturt's Drought (1809-1830) and the Goyder Line Drought (1861-1866) actually had more regionalised patterns and reduced spatial extents. This seasonal rainfall reconstruction provides a new opportunity to understand Australian rainfall variability by contextualising severe droughts and recent trends in Australia.

A multi-sensor approach to landslide monitoring of rainfall-induced failures in Scotland.

NASA Astrophysics Data System (ADS)

Gilles, Charlie; Hoey, Trevor; Williams, Richard

2017-04-01

Landslides are of significant interest in upland areas of the United Kingdom due to their: complex mechanics, potential to channelize into hazardous debris flows and their costly potential impacts on infrastructure. The British Geological Survey National Landslide Database contains an average of 367 landslides per year (from 1970). Slope failures in the UK are typically triggered by extended periods of intense rainfall, and can occur at any time of year. In any given rainfall event that triggers landslides, most potentially vulnerable slopes remain stable. Accurate warning systems would be facilitated by identifying landslide precursors prior to failure events. This project tests whether such precursors can be identified in the valley of Glen Ogle, Scotland (87 km north-west of Edinburgh), where in summer 2004 two debris flows blocked the main road (A85), trapping fifty-seven people. Two adjacent sites have been selected on a west facing slope in Glen Ogle, one of which (the control) has been stable since at least 2004 and the other failed in 2004 and remains unstable. Understanding the immediate causes and antecedent conditions responsible for landslides requires a multi-scale approach. This project uses multiple sensors to assess failure mechanisms of landslides in Glen Ogle: (1) 3-monthly, high (1.8 arcsec) resolution terrestrial laser scanning of topography to detect changes and identify patterns of movement prior to major failure, using the Riegl VZ-1000 (NERC Geophysical Equipment Fund); (2) rainfall and soil moisture data to monitor pore pressure of landslide failure prior to and after hydrologically triggered events; (3) monitoring ground motion using grain-scale sensors which are becoming lower cost, more efficient in terms of power, and can be wirelessly networked these will be used to detect small scale movement of the landslide. Comparative data from the control and test sites will be presented, from which patterns of surface deformation between failure events will be derived.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

The stable isotope amount effect: New insights from NEXRAD echo tops, Luquillo Mountains, Puerto Rico

USGS Publications Warehouse

Scholl, Martha A.; Shanley, James B.; Zegarra, Jan Paul; Coplen, Tyler B.

2009-01-01

The stable isotope amount effect has often been invoked to explain patterns of isotopic composition of rainfall in the tropics. This paper describes a new approach, correlating the isotopic composition of precipitation with cloud height and atmospheric temperature using NEXRAD radar echo tops, which are a measure of the maximum altitude of rainfall within the clouds. The seasonal differences in echo top altitudes and their corresponding temperatures are correlated with the isotopic composition of rainfall. These results offer another factor to consider in interpretation of the seasonal variation in isotopic composition of tropical rainfall, which has previously been linked to amount or rainout effects and not to temperature effects. Rain and cloud water isotope collectors in the Luquillo Mountains in northeastern Puerto Rico were sampled monthly for three years and precipitation was analyzed for δ18O and δ2H. Precipitation enriched in 18O and 2H occurred during the winter dry season (approximately December–May) and was associated with a weather pattern of trade wind showers and frontal systems. During the summer rainy season (approximately June–November), precipitation was depleted in 18O and 2H and originated in low pressure systems and convection associated with waves embedded in the prevailing easterly airflow. Rain substantially depleted in 18O and 2H compared to the aforementioned weather patterns occurred during large low pressure systems. Weather analysis showed that 29% of rain input to the Luquillo Mountains was trade wind orographic rainfall, and 30% of rainfall could be attributed to easterly waves and low pressure systems. Isotopic signatures associated with these major climate patterns can be used to determine their influence on streamflow and groundwater recharge and to monitor possible effects of climate change on regional water resources.

Developing New Rainfall Estimates to Identify the Likelihood of Agricultural Drought in Mesoamerica

NASA Astrophysics Data System (ADS)

Pedreros, D. H.; Funk, C. C.; Husak, G. J.; Michaelsen, J.; Peterson, P.; Lasndsfeld, M.; Rowland, J.; Aguilar, L.; Rodriguez, M.

2012-12-01

The population in Central America was estimated at ~40 million people in 2009, with 65% in rural areas directly relying on local agricultural production for subsistence, and additional urban populations relying on regional production. Mapping rainfall patterns and values in Central America is a complex task due to the rough topography and the influence of two oceans on either side of this narrow land mass. Characterization of precipitation amounts both in time and space is of great importance for monitoring agricultural food production for food security analysis. With the goal of developing reliable rainfall fields, the Famine Early warning Systems Network (FEWS NET) has compiled a dense set of historical rainfall stations for Central America through cooperation with meteorological services and global databases. The station database covers the years 1900-present with the highest density between 1970-2011. Interpolating station data by themselves does not provide a reliable result because it ignores topographical influences which dominate the region. To account for this, climatological rainfall fields were used to support the interpolation of the station data using a modified Inverse Distance Weighting process. By blending the station data with the climatological fields, a historical rainfall database was compiled for 1970-2011 at a 5km resolution for every five day interval. This new database opens the door to analysis such as the impact of sea surface temperature on rainfall patterns, changes to the typical dry spell during the rainy season, characterization of drought frequency and rainfall trends, among others. This study uses the historical database to identify the frequency of agricultural drought in the region and explores possible changes in precipitation patterns during the past 40 years. A threshold of 500mm of rainfall during the growing season was used to define agricultural drought for maize. This threshold was selected based on assessments of crop conditions from previous seasons, and was identified as an amount roughly corresponding to significant crop loss for maize, a major crop in most of the region. Results identify areas in central Honduras and Nicaragua as well as the Altiplano region in Guatemala that experienced 15 seasons of agricultural drought for the period May-July during the years 1970-2000. Preliminary results show no clear trend in rainfall, but further investigation is needed to confirm that agricultural drought is not becoming more frequent in this region.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

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.

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.

Intensity-Duration-Frequency (IDF) rainfall curves, for data series and climate projection in African cities.

PubMed

De Paola, Francesco; Giugni, Maurizio; Topa, Maria Elena; Bucchignani, Edoardo

2014-01-01

Changes in the hydrologic cycle due to increase in greenhouse gases cause variations in intensity, duration, and frequency of precipitation events. Quantifying the potential effects of climate change and adapting to them is one way to reduce urban vulnerability. Since rainfall characteristics are often used to design water structures, reviewing and updating rainfall characteristics (i.e., Intensity-Duration-Frequency (IDF) curves) for future climate scenarios is necessary (Reg Environ Change 13(1 Supplement):25-33, 2013). The present study regards the evaluation of the IDF curves for three case studies: Addis Ababa (Ethiopia), Dar Es Salaam (Tanzania) and Douala (Cameroon). Starting from daily rainfall observed data, to define the IDF curves and the extreme values in a smaller time window (10', 30', 1 h, 3 h, 6 h, 12 h), disaggregation techniques of the collected data have been used, in order to generate a synthetic sequence of rainfall, with statistical properties similar to the recorded data. Then, the rainfall pattern of the three test cities was analyzed and IDF curves were evaluated. In order to estimate the contingent influence of climate change on the IDF curves, the described procedure was applied to the climate (rainfall) simulations over the time period 2010-2050, provided by CMCC (Centro Euro-Mediterraneo sui Cambiamenti Climatici). The evaluation of the IDF curves allowed to frame the rainfall evolution of the three case studies, considering initially only historical data, then taking into account the climate projections, in order to verify the changes in rainfall patterns. The same set of data and projections was also used for evaluating the Probable Maximum Precipitation (PMP).

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

PubMed

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

2018-02-01

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

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.

Dynamical downscaling of historical climate over CORDEX East Asia domain: A comparison of regional ocean-atmosphere coupled model to stand-alone RCM simulations

NASA Astrophysics Data System (ADS)

Zou, Liwei; Zhou, Tianjun; Peng, Dongdong

2016-02-01

The FROALS (flexible regional ocean-atmosphere-land system) model, a regional ocean-atmosphere coupled model, has been applied to the Coordinated Regional Downscaling Experiment (CORDEX) East Asia domain. Driven by historical simulations from a global climate system model, dynamical downscaling for the period from 1980 to 2005 has been conducted at a uniform horizontal resolution of 50 km. The impacts of regional air-sea couplings on the simulations of East Asian summer monsoon rainfall have been investigated, and comparisons have been made to corresponding simulations performed using a stand-alone regional climate model (RCM). The added value of the FROALS model with respect to the driving global climate model was evident in terms of both climatology and the interannual variability of summer rainfall over East China by the contributions of both the high horizontal resolution and the reasonably simulated convergence of the moisture fluxes. Compared with the stand-alone RCM simulations, the spatial pattern of the simulated low-level monsoon flow over East Asia and the western North Pacific was improved in the FROALS model due to its inclusion of regional air-sea coupling. The results indicated that the simulated sea surface temperature (SSTs) resulting from the regional air-sea coupling were lower than those derived directly from the driving global model over the western North Pacific north of 15°N. These colder SSTs had both positive and negative effects. On the one hand, they strengthened the western Pacific subtropical high, which improved the simulation of the summer monsoon circulation over East Asia. On the other hand, the colder SSTs suppressed surface evaporation and favored weaker local interannual variability in the SST, which led to less summer rainfall and weaker interannual rainfall variability over the Korean Peninsula and Japan. Overall, the reference simulation performed using the FROALS model is reasonable in terms of rainfall over the land area of East Asia and will become the basis for the generation of climate change scenarios for the CORDEX East Asia domain that will be described in future reports.

Hydrology of the coastal springs ground-water basin and adjacent parts of Pasco, Hernando, and Citrus Counties, Florida

USGS Publications Warehouse

Knochenmus, Lari A.; Yobbi, Dann K.

2001-01-01

The coastal springs in Pasco, Hernando, and Citrus Counties, Florida consist of three first-order magnitude springs and numerous smaller springs, which are points of substantial ground-water discharge from the Upper Floridan aquifer. Spring flow is proportional to the water-level altitude in the aquifer and is affected primarily by the magnitude and timing of rainfall. Ground-water levels in 206 Upper Floridan aquifer wells, and surface-water stage, flow, and specific conductance of water from springs at 10 gaging stations were measured to define the hydrologic variability (temporally and spatially) in the Coastal Springs Ground-Water Basin and adjacent parts of Pasco, Hernando, and Citrus Counties. Rainfall at 46 stations and ground-water withdrawals for three counties, were used to calculate water budgets, to evaluate long-term changes in hydrologic conditions, and to evaluate relations among the hydrologic components. Predictive equations to estimate daily spring flow were developed for eight gaging stations using regression techniques. Regression techniques included ordinary least squares and multiple linear regression techniques. The predictive equations indicate that ground-water levels in the Upper Floridan aquifer are directly related to spring flow. At tidally affected gaging stations, spring flow is inversely related to spring-pool altitude. The springs have similar seasonal flow patterns throughout the area. Water-budget analysis provided insight into the relative importance of the hydrologic components expected to influence spring flow. Four water budgets were constructed for small ground-water basins that form the Coastal Springs Ground-Water Basin. Rainfall averaged 55 inches per year and was the only source of inflow to the Basin. The pathways for outflow were evapotranspiration (34 inches per year), runoff by spring flow (8 inches per year), ground-water outflow from upward leakage (11 inches per year), and ground-water withdrawal (2 inches per year). Recharge (rainfall minus evapotranspiration) to the Upper Floridan aquifer consists of vertical leakage through the surficial deposits. Discharge is primarily through springs and diffuse upward leakage that maintains the extensive swamps along the Gulf of Mexico. The ground-water basins had slightly different partitioning of hydrologic components, reflecting variation among the regions. Trends in hydrologic data were identified using nonparametric statistical techniques to infer long-term changes in hydrologic conditions, and yielded mixed results. No trend in rainfall was detected during the past century. No trend in spring flow was detected in 1931-98. Although monotonic trends were not detected, rainfall patterns are naturally variable from month to month and year to year; this variability is reflected in ground-water levels and spring flows. A decreasing trend in ground-water levels was detected in the Weeki Wachee well (1966-98), but the trend was statistically weak. At current ground-water withdrawal rates, there is no discernible affect on ground-water levels and spring flows. Sporadic data records, lack of continuous data, and inconsistent periods of record among the hydrologic components impeded analysis of long-term changes to the hydrologic system and interrelations among components. The ongoing collection of hydrologic data from index sites could provide much needed information to assess the hydrologic factors affecting the quantity and quality of spring flow in the Coastal Springs Ground-Water Basin.

Interannual and Decadal Variability of Summer Rainfall over South America

NASA Technical Reports Server (NTRS)

Zhou, Jiayu; Lau, K.-M.

1999-01-01

Using the CPC (Climate Prediction Center) Merged Analysis of Precipitation product along with the Goddard Earth Observing System reanalysis and the Climate Analysis Center sea surface temperature (SST) data, we conduct a diagnostic study of the interannual and decadal scale variability of summer rainfall over South America. Results show three leading modes of rainfall variation identified with interannual, decadal, and long-term trend variability. Together, these modes explain more than half the total variance. The first mode is highly correlated with El Nino/southern oscillation (ENSO), showing severe drought over Northeast Brazil and copious rainfall over the Ecuador coast and the area of Uruguay-Southern Brazil in El Nino years. This pattern is attributed to the large scale zonal shift of the Walker circulation and local Hadley cell anomaly induced by positive (negative) SST anomaly over the eastern (western) equatorial Pacific. In El Nino years, two convective belts indicated by upper tropospheric velocity potential trough and mid-tropospheric rising motion, which are somewhat symmetric about the equator, extend toward the northeast and the southeast into the tropical North and South Atlantic respectively. Sandwiched between the ascent is a region of descending motion over Northeast Brazil. The southern branch of the anomalous Hadley cell is dynamically linked to the increase of rainfall over Uruguay-Southern Brazil. The regional response of anomalous circulation shows a stronger South American summer monsoon and an enhanced (weakened) subtropical high over the South Atlantic (South Pacific) Ocean. The decadal variation displays a meridional shift of the Intertropical Convergence Zone (ITCZ), which is tie to the anomalous cross-equatorial SST gradient over the Atlantic and the eastern Pacific. In conjunction with this mode is a large scale mass swing between the polar regions and midlatitudes in both hemispheres. Over the South Atlantic and the South Pacific, the changes of the strength of the subtropical high and the associated surface wind are dynamically consistent with the distribution of local SST anomalies, suggesting the importance of the atmospheric forcing in the decadal time scale. The decadal mode also presents a weak summer monsoon in its positive phase, which reduces the moisture supply from the equatorial Atlantic and the Amazon Basin and results in negative rainfall anomalies over the central Andes and Gran Chaco. The long-term trend shows decrease of rainfall from the northwest coast to the southeast subtropical region and a southward shift of Atlantic ITCZ that leads to increased rainfall over northern and eastern Brazil. Our result shows a close link of this mode to the observed SST warming trend over the subtropical South Atlantic and a remote connection to the interdecadal SST variation over the extratropical North Atlantic found in previous studies.

High-Resolution Simulation of Hurricane Bonnie (1998). Part 1; The Organization of Vertical Motion

NASA Technical Reports Server (NTRS)

Braun, Scott A.; Montgomery, Michael T.; Pu, Zhaoxia

2003-01-01

Hurricanes are well known for their strong winds and heavy rainfall, particularly in the intense rainband (eyewall) surrounding the calmer eye of the storm. In some hurricanes, the rainfall is distributed evenly around the eye so that it has a donut shape on radar images. In other cases, the rainfall is concentrated on one side of the eyewall and nearly absent on the other side and is said to be asymmetric. This study examines how the vertical air motions that produce the rainfall are distributed within the eyewall of an asymmetric hurricane and the factors that cause this pattern of rainfall. We use a sophisticated numerical forecast model to simulate Hurricane Bonnie, which occurred in late August of 1998 during a special NASA field experiment designed to study hurricanes. The simulation results suggest that vertical wind shear (a rapid change in wind speed or direction with height) caused the asymmetric rainfall and vertical air motion patterns by tilting the hurricane vortex and favoring upward air motions in the direction of tilt. Although the rainfall in the hurricane eyewall may surround more than half of the eye, the updrafts that produce the rainfall are concentrated in very small-scale, intense updraft cores that occupy only about 10% of the eyewall area. The model simulation suggests that the timing and location of individual updraft cores are controlled by intense, small-scale vortices (regions of rapidly swirling flow) in the eyewall and that the updrafts form when the vortices encounter low-level air moving into the eyewall.

Addressing the mischaracterization of extreme rainfall in regional climate model simulations - A synoptic pattern based bias correction approach

NASA Astrophysics Data System (ADS)

Li, Jingwan; Sharma, Ashish; Evans, Jason; Johnson, Fiona

2018-01-01

Addressing systematic biases in regional climate model simulations of extreme rainfall is a necessary first step before assessing changes in future rainfall extremes. Commonly used bias correction methods are designed to match statistics of the overall simulated rainfall with observations. This assumes that change in the mix of different types of extreme rainfall events (i.e. convective and non-convective) in a warmer climate is of little relevance in the estimation of overall change, an assumption that is not supported by empirical or physical evidence. This study proposes an alternative approach to account for the potential change of alternate rainfall types, characterized here by synoptic weather patterns (SPs) using self-organizing maps classification. The objective of this study is to evaluate the added influence of SPs on the bias correction, which is achieved by comparing the corrected distribution of future extreme rainfall with that using conventional quantile mapping. A comprehensive synthetic experiment is first defined to investigate the conditions under which the additional information of SPs makes a significant difference to the bias correction. Using over 600,000 synthetic cases, statistically significant differences are found to be present in 46% cases. This is followed by a case study over the Sydney region using a high-resolution run of the Weather Research and Forecasting (WRF) regional climate model, which indicates a small change in the proportions of the SPs and a statistically significant change in the extreme rainfall over the region, although the differences between the changes obtained from the two bias correction methods are not statistically significant.

Observational evidence of European summer weather patterns predictable from spring

NASA Astrophysics Data System (ADS)

Ossó, Albert; Sutton, Rowan; Shaffrey, Len; Dong, Buwen

2018-01-01

Forecasts of summer weather patterns months in advance would be of great value for a wide range of applications. However, seasonal dynamical model forecasts for European summers have very little skill, particularly for rainfall. It has not been clear whether this low skill reflects inherent unpredictability of summer weather or, alternatively, is a consequence of weaknesses in current forecast systems. Here we analyze atmosphere and ocean observations and identify evidence that a specific pattern of summertime atmospheric circulation––the summer East Atlantic (SEA) pattern––is predictable from the previous spring. An index of North Atlantic sea-surface temperatures in March–April can predict the SEA pattern in July–August with a cross-validated correlation skill above 0.6. Our analyses show that the sea-surface temperatures influence atmospheric circulation and the position of the jet stream over the North Atlantic. The SEA pattern has a particularly strong influence on rainfall in the British Isles, which we find can also be predicted months ahead with a significant skill of 0.56. Our results have immediate application to empirical forecasts of summer rainfall for the United Kingdom, Ireland, and northern France and also suggest that current dynamical model forecast systems have large potential for improvement.

Parameter Estimation for a Model of Space-Time Rainfall

NASA Astrophysics Data System (ADS)

Smith, James A.; Karr, Alan F.

1985-08-01

In this paper, parameter estimation procedures, based on data from a network of rainfall gages, are developed for a class of space-time rainfall models. The models, which are designed to represent the spatial distribution of daily rainfall, have three components, one that governs the temporal occurrence of storms, a second that distributes rain cells spatially for a given storm, and a third that determines the rainfall pattern within a rain cell. Maximum likelihood and method of moments procedures are developed. We illustrate that limitations on model structure are imposed by restricting data sources to rain gage networks. The estimation procedures are applied to a 240-mi2 (621 km2) catchment in the Potomac River basin.

Removal Effectiveness of Co-mingling Off-site Flows with FDOT Right-of-Way Stormwater : [Summary].

DOT National Transportation Integrated Search

2017-11-10

Because designers have many options in designing runoff systems, the researchers studied and simulated many scenarios. They considered five Florida regions, each with a characteristic rainfall pattern. For each location, assuming rainfall of one inch...

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...

Atmospheric water distribution in a midlatitude cyclone observed by the Seasat Scanning Multichannel Microwave Radiometer

NASA Technical Reports Server (NTRS)

Mcmurdie, L. A.; Katsaros, K. B.

1985-01-01

Patterns in the horizontal distribution of integrated water vapor, integrated liquid water and rainfall rate derived from the Seasat Scanning Multichannel Microwave Radiometer (SMMR) during a September 10-12, 1978 North Pacific cyclone are studied. These patterns are compared with surface analyses, ship reports, radiosonde data, and GOES-West infrared satellite imagery. The SMMR data give a unique view of the large mesoscale structure of a midlatitude cyclone. The water vapor distribution is found to have characteristic patterns related to the location of the surface fronts throughout the development of the cyclone. An example is given to illustrate that SMMR data could significantly improve frontal analysis over data-sparse oceanic regions. The distribution of integrated liquid water agrees qualitatively well with corresponding cloud patterns in satellite imagery and appears to provide a means to distinguish where liquid water clouds exist under a cirrus shield. Ship reports of rainfall intensity agree qualitatively very well with SMMR-derived rainrates. Areas of mesoscale rainfall, on the order of 50 km x 50 km or greater are detected using SMMR derived rainrates.

Effects of climatic variation on field metabolism and water relations of desert tortoises

USGS Publications Warehouse

Henen, B.T.; Peterson, C.C.; Wallis, I.R.; Berry, K.H.; Nagy, K.A.

1998-01-01

We used the doubly labeled water method to measure the field metabolic rates (FMRs, in kJ kg-1 day-1) and water flux rates (WIRs, in ml H2O kg-1 day-1) of adult desert tortoises (Gopherus agassizii) in three parts of the Mojave Desert in California over a 3.5-year period, in order to develop insights into the physiological responses of this threatened species to climate variation among sites and years. FMR, WIR, and the water economy index (WEI, in ml H2O kJ-1, an indicator of drinking of free water) differed extensively among seasons, among study sites, between sexes, and among years. In high-rainfall years, males had higher FMRs than females. Average daily rates of energy and water use by desert tortoises were extraordinarily variable: 28-fold differences in FMR and 237-fold differences in WIR were measured. Some of this variation was due to seasonal conditions, with rates being low during cold winter months and higher in the warm seasons. However, much of the variation was due to responses to year-to-year variation in rainfall. Annual spring peaks in FMR and WIR were higher in wet years than in drought years. Site differences in seasonal patterns were apparently due to geographic differences in rainfall patterns (more summer rain at eastern Mojave sites). In spring 1992, during an El Nino (ENSO) event, the WEI was greater than the maximal value obtainable from consuming succulent vegetation, indicating copious drinking of rainwater at that time. The physiological and behavioral flexibility of desert tortoises, evident in individuals living at all three study sites, appears central to their ability to survive droughts and benefit from periods of resource abundance. The strong effects of the El Nino (ENSO) weather pattern on tortoise physiology, reproduction, and survival elucidated in this and other studies suggest that local manifestations of global climate events could have a long-term influence on the tortoise populations in the Mojave Desert.

Understanding spatio-temporal variation of vegetation phenology and rainfall seasonality in the monsoon Southeast Asia.

PubMed

Suepa, Tanita; Qi, Jiaguo; Lawawirojwong, Siam; Messina, Joseph P

2016-05-01

The spatio-temporal characteristics of remote sensing are considered to be the primary advantage in environmental studies. With long-term and frequent satellite observations, it is possible to monitor changes in key biophysical attributes such as phenological characteristics, and relate them to climate change by examining their correlations. Although a number of remote sensing methods have been developed to quantify vegetation seasonal cycles using time-series of vegetation indices, there is limited effort to explore and monitor changes and trends of vegetation phenology in the Monsoon Southeast Asia, which is adversely affected by changes in the Asian monsoon climate. In this study, MODIS EVI and TRMM time series data, along with field survey data, were analyzed to quantify phenological patterns and trends in the Monsoon Southeast Asia during 2001-2010 period and assess their relationship with climate change in the region. The results revealed a great regional variability and inter-annual fluctuation in vegetation phenology. The phenological patterns varied spatially across the region and they were strongly correlated with climate variations and land use patterns. The overall phenological trends appeared to shift towards a later and slightly longer growing season up to 14 days from 2001 to 2010. Interestingly, the corresponding rainy season seemed to have started earlier and ended later, resulting in a slightly longer wet season extending up to 7 days, while the total amount of rainfall in the region decreased during the same time period. The phenological shifts and changes in vegetation growth appeared to be associated with climate events such as EL Niño in 2005. Furthermore, rainfall seemed to be the dominant force driving the phenological changes in naturally vegetated areas and rainfed croplands, whereas land use management was the key factor in irrigated agricultural areas. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Atmospheric circulation feedback on west Asian dust and Indian monsoon rainfall

NASA Astrophysics Data System (ADS)

Kaskaoutis, Dimitris; Houssos, Elias; Gautam, Ritesh; Singh, Ramesh; Rashki, Alireza; Dumka, Umesh

2016-04-01

Classification of the atmospheric circulation patterns associated with high aerosol loading events over the Ganges valley, via the synergy of Factor and Cluster analysis techniques, has indicated six different synoptic weather patterns, two of which mostly occur during late pre-monsoon and monsoon seasons (May to September). The current study focuses on examining these two specific clusters that are associated with different mean sea level pressure (MSLP), geopotential height at 700 hPa (Z700) and wind fields that seem to affect the aerosol (mostly dust) emissions and precipitation distribution over the Indian sub-continent. Furthermore, the study reveals that enhanced aerosol presence over the Arabian Sea is positively associated with increased rainfall over the Indian landmass. The increased dust over the Arabian Sea and rainfall over India are associated with deepening of the northwestern Indian and Arabian lows that increase thermal convection and convergence of humid air masses into Indian landmass, resulting in larger monsoon precipitation. For this cluster, negative MSLP and Z700 anomalies are observed over the Arabian Peninsula that enhance the dust outflow from Arabia and, concurrently, the southwesterly air flow resulting in increase in monsoon precipitation over India. The daily precipitation over India is found to be positively correlated with the aerosol loading over the Arabian Sea for both weather clusters, thus verifying recent results from satellite observations and model simulations concerning the modulation of the Indian summer monsoon rainfall by the Arabian dust. The present work reveals that in addition to the radiative impacts of dust on modulating the monsoon rainfall, differing weather patterns favor changes in dust emissions, accumulation as well as rainfall distribution over south Asia.

Thermal and water regime of green roof segments filled with Technosol

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Potential effects of climate change on Florida's Everglades.

PubMed

Nungesser, M; Saunders, C; Coronado-Molina, C; Obeysekera, J; Johnson, J; McVoy, C; Benscoter, B

2015-04-01

Restoration efforts in Florida's Everglades focus on preserving and restoring this unique wetland's natural landscape. Because most of the Everglades is a freshwater peatland, it requires surplus rainfall to remain a peatland. Restoration plans generally assume a stable climate, yet projections of altered climate over a 50-year time horizon suggest that this assumption may be inappropriate. Using a legacy regional hydrological model, we simulated combinations of a temperature rise of 1.5 °C, a ± 10% change in rainfall, and a 0.46 m sea level rise relative to base conditions. The scenario of increased evapotranspiration and increased rainfall produced a slight increase in available water. In contrast, the more likely scenario of increased evapotranspiration and decreased rainfall lowered median water depths by 5-114 cm and shortened inundation duration periods by 5-45%. Sea level rise increased stages and inundation duration in southern Everglades National Park. These ecologically significant decreases in water depths and inundation duration periods would greatly alter current ecosystems through severe droughts, peat loss and carbon emissions, wildfires, loss of the unique ridge and slough patterns, large shifts in plant and animal communities, and increased exotic species invasions. These results suggest using adaptive restoration planning, a method that explicitly incorporates large climatic and environmental uncertainties into long-term ecosystem restoration plans, structural design, and management. Anticipated water constraints necessitate alternative approaches to restoration, including maintaining critical landscapes and facilitating transitions in others. Accommodating these uncertainties may improve the likelihood of restoration success.

Forecasting paediatric malaria admissions on the Kenya Coast using rainfall.

PubMed

Karuri, Stella Wanjugu; Snow, Robert W

2016-01-01

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

Altered precipitation regime affects the function and composition of soil microbial communities on multiple time scales.

PubMed

Zeglin, L H; Bottomley, P J; Jumpponen, A; Rice, C W; Arango, M; Lindsley, A; McGowan, A; Mfombep, P; Myrold, D D

2013-10-01

Climate change models predict that future precipitation patterns will entail lower-frequency but larger rainfall events, increasing the duration of dry soil conditions. Resulting shifts in microbial C cycling activity could affect soil C storage. Further, microbial response to rainfall events may be constrained by the physiological or nutrient limitation stress of extended drought periods; thus seasonal or multiannual precipitation regimes may influence microbial activity following soil wet-up. We quantified rainfall-driven dynamics of microbial processes that affect soil C loss and retention, and microbial community composition, in soils from a long-term (14-year) field experiment contrasting "Ambient" and "Altered" (extended intervals between rainfalls) precipitation regimes. We collected soil before, the day following, and five days following 2.5-cm rainfall events during both moist and dry periods (June and September 2011; soil water potential = -0.01 and -0.83 MPa, respectively), and measured microbial respiration, microbial biomass, organic matter decomposition potential (extracellular enzyme activities), and microbial community composition (phospholipid fatty acids). The equivalent rainfall events caused equivalent microbial respiration responses in both treatments. In contrast, microbial biomass was higher and increased after rainfall in the Altered treatment soils only, thus microbial C use efficiency (CUE) was higher in Altered than Ambient treatments (0.70 +/- 0.03 > 0.46 +/- 0.10). CUE was also higher in dry (September) soils. C-acquiring enzyme activities (beta-glucosidase, cellobiohydrolase, and phenol oxidase) increased after rainfall in moist (June), but not dry (September) soils. Both microbial biomass C:N ratios and fungal:bacterial ratios were higher at lower soil water contents, suggesting a functional and/or population-level shift in the microbiota at low soil water contents, and microbial community composition also differed following wet-up and between seasons and treatments. Overall, microbial activity may directly (C respiration) and indirectly (enzyme potential) reduce soil organic matter pools less in drier soils, and soil C sequestration potential (CUE) may be higher in soils with a history of extended dry periods between rainfall events. The implications include that soil C loss may be reduced or compensated for via different mechanisms at varying time scales, and that microbial taxa with better stress tolerance or growth efficiency may be associated with these functional shifts.

Changing character of rainfall in eastern China, 1951–2007

NASA Astrophysics Data System (ADS)

Day, Jesse A.; Fung, Inez; Liu, Weihan

2018-03-01

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call “frontal rain events.” In spring and early summer (known as “Meiyu Season”), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951–2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the “South Flood–North Drought” pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994–2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Drought stress suppresses phytoalexin production against Fusarium verticilliodes

USDA-ARS?s Scientific Manuscript database

Global climate change involves rising temperatures and potentially decreased rainfall or changes in rainfall patterns, which could dramatically decrease the yield of food crops. Drought alone can impair plant growth and development, but in nature plants are continuously exposed to both abiotic and b...

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.

Understanding Climate Change Impacts in a Cholera Endemic Megacity: Disease Trends, Hydroclimatic Indicators and Near Future-Term Projections

NASA Astrophysics Data System (ADS)

Akanda, A. S. S.; Hasan, M. A.; Serman, E. A.; Jutla, A.; Huq, A.; Colwell, R. R.

2015-12-01

The last three decades of surveillance data shows a drastic increase of cholera prevalence in the largest cholera-endemic city in the world - Dhaka, Bangladesh. While an endemic trend is getting stronger in the dry season, the post-monsoon season shows increased variability and is epidemic in nature. The pre-monsoon dry season is becoming the dominant cholera season of the year, followed by monsoon flood related propagation in later months of the year. Although the heavily populated and rapidly urbanizing Dhaka region has experienced noticeable shifts in pre monsoon temperature and precipitation patterns and subsequent monsoon variations, to date, there has not been any systematic study on linking the long-term disease trends with observed changes in hydroclimatic indicators. Here, we focus on the past 30-year dynamics of urban cholera prevalence in Dhaka with changes in climatic or anthropogenic forcings to develop projections for the next 30-year period. We focus on the dry and the wet season indicators individually, and develop trends of maximum rainfall intensity, lowest rainfall totals in the pre-monsoon period, number of consecutive dry days, number of wet days, and number of rainy days with greater than 500mm rainfall using a recently developed gridded data product - and compare with regional hydrology, flooding, water usage, changes in distribution systems, population growth and density in urban settlements, and frequency of natural disasters. We then use a bias correction method to develop the next 30 years projections of CMIP5 Regional Climate Model outputs and impacts on cholera prevalence using a probabilistic forecasting approach.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Mentoring Temporal and Spatial Variations in Rainfall across Wadi Ar-Rumah, Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, T.; Ahmed, M.

2015-12-01

Across the Kingdom of Saudi Arabia (KSA), the fresh water resources are limited only to those found in aquifer systems. Those aquifers were believed to be recharged during the previous wet climatic period but still receiving modest local recharge in interleaving dry periods such as those prevailing at present. Quantifying temporal and spatial variabilities in rainfall patterns, magnitudes, durations, and frequencies is of prime importance when it comes to sustainable management of such aquifer systems. In this study, an integrated approach, using remote sensing and field data, was used to assess the past, the current, and the projected spatial and temporal variations in rainfall over one of the major watersheds in KSA, Wadi Ar-Rumah. This watershed was selected given its larger areal extent and population intensity. Rainfall data were extracted from (1) the Climate Prediction Centers (CPC) Merged Analysis of Precipitation (CMAP; spatial coverage: global; spatial resolution: 2.5° × 2.5°; temporal coverage: January 1979 to April 2015; temporal resolution: monthly), and (2) the Tropical Rainfall Measuring Mission (TRMM; spatial coverage: 50°N to 50°S; spatial resolution: 0.25° × 0.25°; temporal coverage: January 1998 to March 2015; temporal resolution: 3 hours) and calibrated against rainfall measurements extracted from rain gauges. Trends in rainfall patterns were examined over four main investigation periods: period I (01/1979 to 12/1985), period II (01/1986 to 12/1992), period III (01/1993 to 12/2002), and period IV (01/2003 to 12/2014). Our findings indicate: (1) a significant increase (+14.19 mm/yr) in rainfall rates were observed during period I, (2) a significant decrease in rainfall rates were observed during periods II (-5.80 mm/yr), III (-9.38 mm/yr), and IV (-2.46 mm/yr), and (3) the observed variations in rainfall rates are largely related to the temporal variations in the northerlies (also called northwesterlies) and the monsoonal wind regimes.

Quality-control of an hourly rainfall dataset and climatology of extremes for the UK.

PubMed

Blenkinsop, Stephen; Lewis, Elizabeth; Chan, Steven C; Fowler, Hayley J

2017-02-01

Sub-daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non-operation of gauges. Given the prospect of an intensification of short-duration rainfall in a warming climate, the identification of such errors is essential if sub-daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near-complete hourly records for 1992-2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n-largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north-south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub-daily rainfall, with convection dominating during summer. The resulting quality-controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality-control procedures for sub-daily data, the validation of the new generation of very high-resolution climate models and improved understanding of the drivers of extreme rainfall.

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

NASA Astrophysics Data System (ADS)

Prasetyo, Yudo; Nabilah, Farras

2017-12-01

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

Quality‐control of an hourly rainfall dataset and climatology of extremes for the UK

PubMed Central

Lewis, Elizabeth; Chan, Steven C.; Fowler, Hayley J.

2016-01-01

ABSTRACT Sub‐daily rainfall extremes may be associated with flash flooding, particularly in urban areas but, compared with extremes on daily timescales, have been relatively little studied in many regions. This paper describes a new, hourly rainfall dataset for the UK based on ∼1600 rain gauges from three different data sources. This includes tipping bucket rain gauge data from the UK Environment Agency (EA), which has been collected for operational purposes, principally flood forecasting. Significant problems in the use of such data for the analysis of extreme events include the recording of accumulated totals, high frequency bucket tips, rain gauge recording errors and the non‐operation of gauges. Given the prospect of an intensification of short‐duration rainfall in a warming climate, the identification of such errors is essential if sub‐daily datasets are to be used to better understand extreme events. We therefore first describe a series of procedures developed to quality control this new dataset. We then analyse ∼380 gauges with near‐complete hourly records for 1992–2011 and map the seasonal climatology of intense rainfall based on UK hourly extremes using annual maxima, n‐largest events and fixed threshold approaches. We find that the highest frequencies and intensities of hourly extreme rainfall occur during summer when the usual orographically defined pattern of extreme rainfall is replaced by a weaker, north–south pattern. A strong diurnal cycle in hourly extremes, peaking in late afternoon to early evening, is also identified in summer and, for some areas, in spring. This likely reflects the different mechanisms that generate sub‐daily rainfall, with convection dominating during summer. The resulting quality‐controlled hourly rainfall dataset will provide considerable value in several contexts, including the development of standard, globally applicable quality‐control procedures for sub‐daily data, the validation of the new generation of very high‐resolution climate models and improved understanding of the drivers of extreme rainfall. PMID:28239235

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.

River sedimentation and channel bed characteristics in northern Ethiopia

NASA Astrophysics Data System (ADS)

Demissie, Biadgilgn; Billi, Paolo; Frankl, Amaury; Haile, Mitiku; Lanckriet, Sil; Nyssen, Jan

2016-04-01

Excessive sedimentation and flood hazard are common in ephemeral streams which are characterized by flashy floods. The purposes of this study was to investigate the temporal variability of bio-climatic factors in controlling sediment supply to downstream channel reaches and the effect of bridges on local hydro-geomorphic conditions in causing the excess sedimentation and flood hazard in ephemeral rivers of the Raya graben (northern Ethiopia). Normalized Difference Vegetation Index (NDVI) was analyzed for the study area using Landsat imageries of 1972, 1986, 2000, 2005, 2010, and 2012). Middle term, 1993-2011, daily rainfall data of three meteorological stations, namely, Alamata, Korem and Maychew, were considered to analyse the temporal trends and to calculate the return time intervals of rainfall intensity in 24 hours for 2, 5, 10 and 20 years using the log-normal and the Gumbel extreme events method. Streambed gradient and bed material grain size were measured in 22 river reaches (at bridges and upstream). In the study catchments, the maximum NDVI values were recorded in the time interval from 2000 to 2010, i.e. the decade during which the study bridges experienced the most severe excess sedimentation problems. The time series analysis for a few rainfall parameters do not show any evidence of rainfall pattern accountable for an increase in sediment delivery from the headwaters nor for the generation of higher floods with larger bedload transport capacities. Stream bed gradient and bed material grain size data were measured in order to investigate the effect of the marked decrease in width from the wide upstream channels to the narrow recently constructed bridges. The study found the narrowing of the channels due to the bridges as the main cause of the thick sedimentation that has been clogging the study bridges and increasing the frequency of overbank flows during the last 15 years. Key terms: sedimentation, ephemeral streams, sediment size, bridge clogging

Fingerprinting the Impacts of Aerosols on Long-Term Trends of the Indian Summer Monsoon Regional Rainfall

NASA Technical Reports Server (NTRS)

Laul, K. M.; Kim, K. M.

2010-01-01

In this paper, we present corroborative observational evidences from satellites, in-situ observations, and re-analysis data showing possible impacts of absorbing aerosols (black carbon and dust) on subseasonal and regional summer monsoon rainfall over India. We find that increased absorbing aerosols in the Indo-Gangetic Plain in recent decades may have lead to long-term warming of the upper troposphere over northern India and the Tibetan Plateau, enhanced rainfall in northern India and the Himalayas foothill regions in the early part (may-June) of the monsoon season, followed by diminished rainfall over central and southern India in the latter part (July-August) of the monsoon season. These signals which are consistent with current theories of atmospheric heating and solar dimming by aerosol and induced cloudiness in modulating the Indian monsoon, would have been masked by conventional method of using al-India rainfall averaged over the entire monsoon season.

Catchment-scale herbicides transport: Theory and application

NASA Astrophysics Data System (ADS)

Bertuzzo, E.; Thomet, M.; Botter, G.; Rinaldo, A.

2013-02-01

This paper proposes and tests a model which couples the description of hydrologic flow and transport of herbicides at catchment scales. The model accounts for streamflow components' age to characterize short and long term fluctuations of herbicide flux concentrations in stream waters, whose peaks exceeding a toxic threshold are key to exposure risk of aquatic ecosystems. The model is based on a travel time formulation of transport embedding a source zone that describes near surface herbicide dynamics. To this aim we generalize a recently proposed scheme for the analytical derivation of travel time distributions to the case of solutes that can be partially taken up by transpiration and undergo chemical degradation. The framework developed is evaluated by comparing modeled hydrographs and atrazine chemographs with those measured in the Aabach agricultural catchment (Switzerland). The model proves reliable in defining complex transport features shaped by the interplay of long term processes, related to the persistence of solute components in soils, and short term dynamics related to storm inter-arrivals. The effects of stochasticity in rainfall patterns and application dates on concentrations and loads in runoff are assessed via Monte Carlo simulations, highlighting the crucial role played by the first rainfall event occurring after herbicide application. A probabilistic framework for critical determinants of exposure risk to aquatic communities is defined. Modeling of herbicides circulation at catchment scale thus emerges as essential tools for ecological risk assessment.

Identification of anomalous motion of thunderstorms using daily rainfall fields

NASA Astrophysics Data System (ADS)

del Moral, Anna; Llasat, Maria Carmen; Rigo, Tomeu

2016-04-01

Adverse weather phenomena in Catalonia (NE of the Iberian Peninsula) is commonly associated to heavy rains, large hail, strong winds, and/or tornados, all of them caused by thunderstorms. In most of the cases with adverse weather, thunderstorms vary sharply their trajectories in a concrete moment, changing completely the motion directions that have previously followed. Furthermore, it is possible that a breaking into several cells may be produced, or, in the opposite, it can be observed a joining of different thunderstorms into a bigger system. In order to identify the main features of the developing process of thunderstorms and the anomalous motions that these may follow in some cases, this contribution presents a classification of the events using daily rainfall fields, with the purpose of distinguishing quickly anomalous motion of thunderstorms. The methodology implemented allows classifying the daily rainfall fields in three categories by applying some thresholds related with the daily precipitation accumulated values and their extension: days with "no rain", days with "potentially convective" rain and days with "non-potentially convective" rain. Finally, for those "potentially convective" daily rainfall charts, it also allows a geometrical identification and classification of all the convective structures into "ellipse" and "non-ellipse", obtaining then the structures with "normal" or "anomalous" motion pattern, respectively. The work is focused on the period 2008-2015, and presents some characteristics of the rainfall behaviour in terms of the seasonal distribution of convective rainfall or the geographic variability. It shows that convective structures are mainly found during late spring and summer, even though they can be recorded in any time of the year. Consequently, the maximum number of convective structures with anomalous motion is recorded between July and November. Furthermore, the contribution shows the role of the orography of Catalonia in the development of convective structures. This work has been developed in the framework of the Spanish project HOPE.

Urban RoGeR: Merging process-based high-resolution flash flood model for urban areas with long-term water balance predictions

NASA Astrophysics Data System (ADS)

Weiler, M.

2016-12-01

Heavy rain induced flash floods are still a serious hazard and generate high damages in urban areas. In particular in the spatially complex urban areas, the temporal and spatial pattern of runoff generation processes at a wide spatial range during extreme rainfall events need to be predicted including the specific effects of green infrastructure and urban forests. In addition, the initial conditions (soil moisture pattern, water storage of green infrastructure) and the effect of lateral redistribution of water (run-on effects and re-infiltration) have to be included in order realistically predict flash flood generation. We further developed the distributed, process-based model RoGeR (Runoff Generation Research) to include the relevant features and processes in urban areas in order to test the effects of different settings, initial conditions and the lateral redistribution of water on the predicted flood response. The uncalibrated model RoGeR runs at a spatial resolution of 1*1m² (LiDAR, degree of sealing, landuse), soil properties and geology (1:50.000). In addition, different green infrastructures are included into the model as well as the effect of trees on interception and transpiration. A hydraulic model was included into RoGeR to predict surface runoff, water redistribution, and re-infiltration. During rainfall events, RoGeR predicts at 5 min temporal resolution, but the model also simulates evapotranspiration and groundwater recharge during rain-free periods at a longer time step. The model framework was applied to several case studies in Germany where intense rainfall events produced flash floods causing high damage in urban areas and to a long-term research catchment in an urban setting (Vauban, Freiburg), where a variety of green infrastructures dominates the hydrology. Urban-RoGeR allowed us to study the effects of different green infrastructures on reducing the flood peak, but also its effect on the water balance (evapotranspiration and groundwater recharge). We could also show that infiltration of surface runoff from areas with a low infiltration (lateral redistribution) reduce the flood peaks by over 90% in certain areas and situations. Finally, we also evaluated the model to long-term runoff observations (surface runoff, ET, roof runoff) and to flood marks in the selected case studies.

Intra-storm temporal patterns of rainfall in China using Huff curves

USDA-ARS?s Scientific Manuscript database

The intra-storm temporal distributions of precipitation are important to infiltration, runoff and erosion processes and models. A convenient and established method for characterizing precipitation hyetographs is with the use of Huff curves. In this study, 11,801 erosive rainfall events with one-mi...

Increase of Coastal Cliff Rockfall Trigerred By Rainfall On The Chalk Coast of NW France During The Year 2001

NASA Astrophysics Data System (ADS)

Duperret, A.; Genter, A.; Daigneault, M.; Mortimore, R. N.

Coastal chalk cliffs exposed on each part of the English Channel suffer numerous collapses, with mean volumes varying between 10 000 and 100 000 cubic meters. Between October 1998 and October 2001, a minimum of 52 collapses have been ob- served along 120 km of the French chalk coastline located in Upper-Normandy and Picardy. The chalk coastline has evidenced 4 collapses in 1999 and 6 collapses in 2000 (winter and spring), whereas 28 collapses with volume greater than 1000 m3 was recorded in 2001 (winter, spring and summer). The increase of large-scale collapses during 2001 is interpreted as an excess of rainfalls recorded previously. Most of these collapses extend all over the vertical cliff height and are mainly controlled by ground- water infiltration. The modality of water circulation through the chalk rock depends on the chalk lithology and the hydrogeological properties of pre-existing fractures. In the framework of the European scientific project named ROCC (Risk of Cliff Col- lapse), the chalk lithology and the pre-existing fracture pattern have been investigated in order to determine the response of the rock mass to subaerial and marine solicita- tions, including rainfall conditions. Such data have been reported in a GIS system in order to determine the degree of cliff sensibility to collapses. Some rainfall-triggered collapses will be presented to illustrate the diversity of the rock mass response to rain- fall excess, in terms of rock mass characteristics and time delay: (1) a collapse was witnessed at Puys, the 17th May 2000, after two periods of intense rainfall inducing floods, during the two previous months. The occurrence of impervious marl seams levels within the chalk and its low fracture content may have generated water over- pressure and consequently stress concentration on the marl seams, which conduct to the rupture. The delay between rainfall and the rupture may be explained by the low velocity of groundwater through a poorly fractured porous chalk. (2) a series of large- scale collapses has been evidenced at Yport in June 2001, at Grandes Dalles the 15th July 2001 and at Benouville the 24th July 2001. These collapses occurred after a dry period, during the previous three months. A collapse occurred again at Yport the 27th August 2001, after an increase of rainfall during August 2001. All these sites present the same lithological chalk succession than at Puys, but their fracture pattern is made of large-scale subvertical fractures expanding all over the cliff height. Some of them 1 which correspond to dissolution pipes are filled with clays-with-flints. The sharp in- crease of collapses during the summer 2001 could be related to the superimposition of dry periods which alternate with heavy rainfalls, in karst environment. 2

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

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.

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

NASA Astrophysics Data System (ADS)

Barros, A.; simoes, s

2002-05-01

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

Rainfall-triggered shallow landslides at catchment scale: Threshold mechanics-based modeling for abruptness and localization

NASA Astrophysics Data System (ADS)

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

2013-10-01

Rainfall-induced shallow landslides may occur abruptly without distinct precursors and could span a wide range of soil mass released during a triggering event. We present a rainfall-induced landslide-triggering model for steep catchments with surfaces represented as an assembly of hydrologically and mechanically interconnected soil columns. The abruptness of failure was captured by defining local strength thresholds for mechanical bonds linking soil and bedrock and adjacent columns, whereby a failure of a single bond may initiate a chain reaction of subsequent failures, culminating in local mass release (a landslide). The catchment-scale hydromechanical landslide-triggering model (CHLT) was applied to results from two event-based landslide inventories triggered by two rainfall events in 2002 and 2005 in two nearby catchments located in the Prealps in Switzerland. Rainfall radar data, surface elevation and vegetation maps, and a soil production model for soil depth distribution were used for hydromechanical modeling of failure patterns for the two rainfall events at spatial and temporal resolutions of 2.5 m and 0.02 h, respectively. The CHLT model enabled systematic evaluation of the effects of soil type, mechanical reinforcement (soil cohesion and lateral root strength), and initial soil water content on landslide characteristics. We compared various landslide metrics and spatial distribution of simulated landslides in subcatchments with observed inventory data. Model parameters were optimized for the short but intense rainfall event in 2002, and the calibrated model was then applied for the 2005 rainfall, yielding reasonable predictions of landslide events and volumes and statistically reproducing localized landslide patterns similar to inventory data. The model provides a means for identifying local hot spots and offers insights into the dynamics of locally resolved landslide hazards in mountainous regions.

Extent of Night Warming Differentiates the Temporal Trend of Tropical Greenness over 2001-2015

NASA Astrophysics Data System (ADS)

Yu, M.; Gao, Q.; Gao, C.; Wang, C.

2016-12-01

Tropical forests have essential functions in global C dynamic but vulnerable to changes in land cover land use (LCLUC) and climate. The tropics of Caribbean are experiencing warming and drying climate and diverse LCLUC. However, large-scale studies to detect long-term trends of C and associated mechanisms are still rare. Using MODIS Enhanced Vegetation Index (EVI), we investigated trend of greenness in the Greater Antilles Caribbean during 2000 - 2015 and further analyzed the trend of vegetation patches without LCLUC to separate the climate impacts. We hypothesized that rainfall decrease or/and warming would reduce EVI in this tropical region. All five countries showed significantly decreasing EVI except Cuba of which EVI was increasing partly due to strong reforestation. Haiti has the steepest decreasing EVI due to its deforestation for charcoals. EVI trend varied greatly even for patches without LCLUC, tending to decrease in the windward but increase in the leeward of the island Puerto Rico. Contrary to our intuition, the rainfall was mostly increasing. However the rising night temperature significantly and negatively correlates with the spatial pattern of EVI trends. Although the cooled daytime and increased rainfall might enhance EVI, night warming dominated the climate impacts and differentiated the EVI trend.

Short-term precipitation exclusion alters microbial responses to soil moisture in a wet tropical forest.

PubMed

Waring, Bonnie G; Hawkes, Christine V

2015-05-01

Many wet tropical forests, which contain a quarter of global terrestrial biomass carbon stocks, will experience changes in precipitation regime over the next century. Soil microbial responses to altered rainfall are likely to be an important feedback on ecosystem carbon cycling, but the ecological mechanisms underpinning these responses are poorly understood. We examined how reduced rainfall affected soil microbial abundance, activity, and community composition using a 6-month precipitation exclusion experiment at La Selva Biological Station, Costa Rica. Thereafter, we addressed the persistent effects of field moisture treatments by exposing soils to a controlled soil moisture gradient in the lab for 4 weeks. In the field, compositional and functional responses to reduced rainfall were dependent on initial conditions, consistent with a large degree of spatial heterogeneity in tropical forests. However, the precipitation manipulation significantly altered microbial functional responses to soil moisture. Communities with prior drought exposure exhibited higher respiration rates per unit microbial biomass under all conditions and respired significantly more CO2 than control soils at low soil moisture. These functional patterns suggest that changes in microbial physiology may drive positive feedbacks to rising atmospheric CO2 concentrations if wet tropical forests experience longer or more intense dry seasons in the future.

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.

A simple stochastic rainstorm generator for simulating spatially and temporally varying rainfall

NASA Astrophysics Data System (ADS)

Singer, M. B.; Michaelides, K.; Nichols, M.; Nearing, M. A.

2016-12-01

In semi-arid to arid drainage basins, rainstorms often control both water supply and flood risk to marginal communities of people. They also govern the availability of water to vegetation and other ecological communities, as well as spatial patterns of sediment, nutrient, and contaminant transport and deposition on local to basin scales. All of these landscape responses are sensitive to changes in climate that are projected to occur throughout western North America. Thus, it is important to improve characterization of rainstorms in a manner that enables statistical assessment of rainfall at spatial scales below that of existing gauging networks and the prediction of plausible manifestations of climate change. Here we present a simple, stochastic rainstorm generator that was created using data from a rich and dense network of rain gauges at the Walnut Gulch Experimental Watershed (WGEW) in SE Arizona, but which is applicable anywhere. We describe our methods for assembling pdfs of relevant rainstorm characteristics including total annual rainfall, storm area, storm center location, and storm duration. We also generate five fitted intensity-duration curves and apply a spatial rainfall gradient to generate precipitation at spatial scales below gauge spacing. The model then runs by Monte Carlo simulation in which a total annual rainfall is selected before we generate rainstorms until the annual precipitation total is reached. The procedure continues for decadal simulations. Thus, we keep track of the hydrologic impact of individual storms and the integral of precipitation over multiple decades. We first test the model using ensemble predictions until we reach statistical similarity to the input data from WGEW. We then employ the model to assess decadal precipitation under simulations of climate change in which we separately vary the distribution of total annual rainfall (trend in moisture) and the intensity-duration curves used for simulation (trends in storminess). We demonstrate the model output through spatial maps of rainfall and through statistical comparisons of relevant parameters and distributions. Finally, discuss how the model can be used to understand basin-scale hydrology in terms of soil moisture, runoff, and erosion.

Identification of homogeneous regions for rainfall regional frequency analysis considering typhoon event in South Korea

NASA Astrophysics Data System (ADS)

Heo, J. H.; Ahn, H.; Kjeldsen, T. R.

2017-12-01

South Korea is prone to large, and often disastrous, rainfall events caused by a mixture of monsoon and typhoon rainfall phenomena. However, traditionally, regional frequency analysis models did not consider this mixture of phenomena when fitting probability distributions, potentially underestimating the risk posed by the more extreme typhoon events. Using long-term observed records of extreme rainfall from 56 sites combined with detailed information on the timing and spatial impact of past typhoons from the Korea Meteorological Administration (KMA), this study developed and tested a new mixture model for frequency analysis of two different phenomena; events occurring regularly every year (monsoon) and events only occurring in some years (typhoon). The available annual maximum 24 hour rainfall data were divided into two sub-samples corresponding to years where the annual maximum is from either (1) a typhoon event, or (2) a non-typhoon event. Then, three-parameter GEV distribution was fitted to each sub-sample along with a weighting parameter characterizing the proportion of historical events associated with typhoon events. Spatial patterns of model parameters were analyzed and showed that typhoon events are less commonly associated with annual maximum rainfall in the North-West part of the country (Seoul area), and more prevalent in the southern and eastern parts of the country, leading to the formation of two distinct typhoon regions: (1) North-West; and (2) Southern and Eastern. Using a leave-one-out procedure, a new regional frequency model was tested and compared to a more traditional index flood method. The results showed that the impact of typhoon on design events might previously have been underestimated in the Seoul area. This suggests that the use of the mixture model should be preferred where the typhoon phenomena is less frequent, and thus can have a significant effect on the rainfall-frequency curve. This research was supported by a grant(2017-MPSS31-001) from Supporting Technology Development Program for Disaster Management funded by Ministry of Public Safety and Security(MPSS) of the Korean government.

Feedback of observed interannual vegetation change: a regional climate model analysis for the West African monsoon

NASA Astrophysics Data System (ADS)

Klein, Cornelia; Bliefernicht, Jan; Heinzeller, Dominikus; Gessner, Ursula; Klein, Igor; Kunstmann, Harald

2017-05-01

West Africa is a hot spot region for land-atmosphere coupling where atmospheric conditions and convective rainfall can strongly depend on surface characteristics. To investigate the effect of natural interannual vegetation changes on the West African monsoon precipitation, we implement satellite-derived dynamical datasets for vegetation fraction (VF), albedo and leaf area index into the Weather Research and Forecasting model. Two sets of 4-member ensembles with dynamic and static land surface description are used to extract vegetation-related changes in the interannual difference between August-September 2009 and 2010. The observed vegetation patterns retain a significant long-term memory of preceding rainfall patterns of at least 2 months. The interannual vegetation changes exhibit the strongest effect on latent heat fluxes and associated surface temperatures. We find a decrease (increase) of rainy hours over regions with higher (lower) VF during the day and the opposite during the night. The probability that maximum precipitation is shifted to nighttime (daytime) over higher (lower) VF is 12 % higher than by chance. We attribute this behaviour to horizontal circulations driven by differential heating. Over more vegetated regions, the divergence of moist air together with lower sensible heat fluxes hinders the initiation of deep convection during the day. During the night, mature convective systems cause an increase in the number of rainy hours over these regions. We identify this feedback in both water- and energy-limited regions of West Africa. The inclusion of observed dynamical surface information improved the spatial distribution of modelled rainfall in the Sahel with respect to observations, illustrating the potential of satellite data as a boundary constraint for atmospheric models.

Variations of Sea Surface Temperature, Wind Stress, and Rainfall over the Tropical Atlantic and South America.

NASA Astrophysics Data System (ADS)

Nobre, Paulo; Srukla, J.

1996-10-01

Empirical orthogonal functions (E0Fs) and composite analyses are used to investigate the development of sea surface temperature (SST) anomaly patterns over the tropical Atlantic. The evolution of large-scale rainfall anomaly patterns over the equatorial Atlantic and South America are also investigated. 71e EOF analyses revealed that a pattern of anomalous SST and wind stress asymmetric relative to the equator is the dominant mode of interannual and longer variability over the tropical Atlantic. The most important findings of this study are as follows.Atmospheric circulation anomalies precede the development of basinwide anomalous SST patterns over the tropical Atlantic. Anomalous SST originate off the African coast simultaneously with atmospheric circulation anomalies and expand westward afterward. The time lag between wind stress relaxation (strengthening) and maximum SST warming (cooling) is about two months.Anomalous atmospheric circulation patterns over northern tropical Atlantic are phase locked to the seasonal cycle. Composite fields of SLP and wind stress over northern tropical Atlantic can be distinguished from random only within a few months preceding the March-May (MAM) season. Observational evidence is presented to show that the El Niño-Southern Oscillation phenomenon in the Pacific influences atmospheric circulation and SST anomalies over northern tropical Atlantic through atmospheric teleconnection patterns into higher latitudes of the Northern Hemisphere.The well-known droughts over northeastern Brazil (Nordeste) are a local manifestation of a much larger-scale rainfall anomaly pattern encompassing the whole equatorial Atlantic and Amazon region. Negative rainfall anomalies to the south of the equator during MAM, which is the rainy season for the Nordeste region, are related to an early withdrawal of the intertropical convergence zone toward the warm SST anomalies over the northern tropical Atlantic. Also, it is shown that precipitation anomalies over southern and northern parts of the Nordeste are out of phase: drought years over the northern Nordeste are commonly preceded by wetter years over the southern Nordeste, and vice versa.

Using Mathematical Transmission Modelling to Investigate Drivers of Respiratory Syncytial Virus Seasonality in Children in the Philippines

PubMed Central

Paynter, Stuart; Yakob, Laith; Simões, Eric A. F.; Lucero, Marilla G.; Tallo, Veronica; Nohynek, Hanna; Ware, Robert S.; Weinstein, Philip; Williams, Gail; Sly, Peter D.

2014-01-01

We used a mathematical transmission model to estimate when ecological drivers of respiratory syncytial virus (RSV) transmissibility would need to act in order to produce the observed seasonality of RSV in the Philippines. We estimated that a seasonal peak in transmissibility would need to occur approximately 51 days prior to the observed peak in RSV cases (range 49 to 67 days). We then compared this estimated seasonal pattern of transmissibility to the seasonal patterns of possible ecological drivers of transmissibility: rainfall, humidity and temperature patterns, nutritional status, and school holidays. The timing of the seasonal patterns of nutritional status and rainfall were both consistent with the estimated seasonal pattern of transmissibility and these are both plausible drivers of the seasonality of RSV in this setting. PMID:24587222

Rainfall Intensity Effects on Runoff and Sediment Losses From a Colorado Alfisol

USDA-ARS?s Scientific Manuscript database

For the Front Range region of Colorado, quantifying rainfall partitioning under current and/or proposed farming practices and changing precipitation patterns is the first step to understanding how to efficiently conserve water and soil resources to meet crop water demands. We quantified the effects ...

Migration Related to Climate Change: Impact, Challenges and Proposed Policy Initiatives

NASA Astrophysics Data System (ADS)

Sarkar, A.

2015-12-01

Migration of human population possesses a great threat to human development and nation building. A significant cause for migration is due to change in climatic conditions and vulnerabilities associated with it. Our case study focuses on the consequent reason and impact of such migration in the coastal areas of West Bengal, India. The changes in rainfall pattern and the variation of temperature have been considered as parameters which have resulted in migration. It is worthy to note that the agricultural pattern has subsequently changed over the last two decades due to change in rainfall and temperature. India being an agriculture oriented economy, the changes in the meteorological variables have not only altered the rate of agricultural pattern but also the rate of migration. A proposed framework depicting relationship between changes in meteorological variables and the migration pattern, and an estimate of how the migration pattern is expected to change over the next century by utilizing the downscaled values of future rainfall and temperature has been analyzed. Moreover, various public policy frameworks has also been proposed through the study for addressing the challenges of migration related to climate change. The proposed public policy framework has been streamlined along the lines of various international treaties and conventions in order to integrate the policy initiatives through universalization of law and policy research.

Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries

NASA Astrophysics Data System (ADS)

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

2018-07-01

To simulate the impacts of within-storm rainfall variabilities on fast hydrological processes, long precipitation time series with high temporal resolution are required. Due to limited availability of observed data such time series are typically obtained from stochastic models. However, most existing rainfall models are limited in their ability to conserve rainfall event statistics which are relevant for hydrological processes. Poisson rectangular pulse models are widely applied to generate long time series of alternating precipitation events durations and mean intensities as well as interstorm period durations. Multiplicative microcanonical random cascade (MRC) models are used to disaggregate precipitation time series from coarse to fine temporal resolution. To overcome the inconsistencies between the temporal structure of the Poisson rectangular pulse model and the MRC model, we developed a new coupling approach by introducing two modifications to the MRC model. These modifications comprise (a) a modified cascade model ("constrained cascade") which preserves the event durations generated by the Poisson rectangular model by constraining the first and last interval of a precipitation event to contain precipitation and (b) continuous sigmoid functions of the multiplicative weights to consider the scale-dependency in the disaggregation of precipitation events of different durations. The constrained cascade model was evaluated in its ability to disaggregate observed precipitation events in comparison to existing MRC models. For that, we used a 20-year record of hourly precipitation at six stations across Germany. The constrained cascade model showed a pronounced better agreement with the observed data in terms of both the temporal pattern of the precipitation time series (e.g. the dry and wet spell durations and autocorrelations) and event characteristics (e.g. intra-event intermittency and intensity fluctuation within events). The constrained cascade model also slightly outperformed the other MRC models with respect to the intensity-frequency relationship. To assess the performance of the coupled Poisson rectangular pulse and constrained cascade model, precipitation events were stochastically generated by the Poisson rectangular pulse model and then disaggregated by the constrained cascade model. We found that the coupled model performs satisfactorily in terms of the temporal pattern of the precipitation time series, event characteristics and the intensity-frequency relationship.

The use of distributed hydrological models for the Gard 2002 flash flood event: Analysis of associated hydrological processes

NASA Astrophysics Data System (ADS)

Braud, Isabelle; Roux, Hélène; Anquetin, Sandrine; Maubourguet, Marie-Madeleine; Manus, Claire; Viallet, Pierre; Dartus, Denis

2010-11-01

SummaryThis paper presents a detailed analysis of the September 8-9, 2002 flash flood event in the Gard region (southern France) using two distributed hydrological models: CVN built within the LIQUID® hydrological platform and MARINE. The models differ in terms of spatial discretization, infiltration and water redistribution representation, and river flow transfer. MARINE can also account for subsurface lateral flow. Both models are set up using the same available information, namely a DEM and a pedology map. They are forced with high resolution radar rainfall data over a set of 18 sub-catchments ranging from 2.5 to 99 km2 and are run without calibration. To begin with, models simulations are assessed against post field estimates of the time of peak and the maximum peak discharge showing a fair agreement for both models. The results are then discussed in terms of flow dynamics, runoff coefficients and soil saturation dynamics. The contribution of the subsurface lateral flow is also quantified using the MARINE model. This analysis highlights that rainfall remains the first controlling factor of flash flood dynamics. High rainfall peak intensities are very influential of the maximum peak discharge for both models, but especially for the CVN model which has a simplified overland flow transfer. The river bed roughness also influences the peak intensity and time. Soil spatial representation is shown to have a significant role on runoff coefficients and on the spatial variability of saturation dynamics. Simulated soil saturation is found to be strongly related with soil depth and initial storage deficit maps, due to a full saturation of most of the area at the end of the event. When activated, the signature of subsurface lateral flow is also visible in the spatial patterns of soil saturation with higher values concentrating along the river network. However, the data currently available do not allow the assessment of both patterns. The paper concludes with a set of recommendations for enhancing field observations in order to progress in process understanding and gather a larger set of data to improve the realism of distributed models.

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.

Characterizing land surface phenology and responses to rainfall in the Sahara desert

NASA Astrophysics Data System (ADS)

Yan, Dong; Zhang, Xiaoyang; Yu, Yunyue; Guo, Wei; Hanan, Niall P.

2016-08-01

Land surface phenology (LSP) in the Sahara desert is poorly understood due to the difficulty in detecting subtle variations in vegetation greenness. This study examined the spatial and temporal patterns of LSP and its responses to rainfall seasonality in the Sahara desert. We first generated daily two-band enhanced vegetation index (EVI2) from half-hourly observations acquired by the Spinning Enhanced Visible and Infrared Imager on board the Meteosat Second Generation series of geostationary satellites from 2006 to 2012. The EVI2 time series was used to retrieve LSP based on the Hybrid Piecewise Logistic Model. We further investigated the associations of spatial and temporal patterns in LSP with those in rainfall seasonality derived from the daily rainfall time series of the Tropical Rainfall Measurement Mission. Results show that the spatial shifts in the start of the vegetation growing season generally follow the rainy season onset that is controlled by the summer rainfall regime in the southern Sahara desert. In contrast, the end of the growing season significantly lags the end of the rainy season without any significant dependence. Vegetation growing season can unfold during the dry seasons after onset is triggered during rainy seasons. Vegetation growing season can be as long as 300 days or more in some areas and years. However, the EVI2 amplitude and accumulation across the Sahara region was very low indicating sparse vegetation as expected in desert regions. EVI2 amplitude and accumulated EVI2 strongly depended on rainfall received during the growing season and the preceding dormancy period.

A simplified rainfall-runoff stochastic simulation method for an application of the SCHADEX method to ungauged catchments.

NASA Astrophysics Data System (ADS)

Penot, David; Paquet, Emmanuel; Lang, Michel

2014-05-01

SCHADEX is a probabilistic method for extreme flood estimation, developed and applied since 2006 at Electricité de France (EDF) for dam spillway design [Paquet et al., 2013]. SCHADEX is based on a semi-continuous rainfall-runoff simulation process. The method has been built around two models: a Multi-Exponential Weather Pattern (MEWP) distribution for rainfall probability estimation [Garavaglia et al., 2010] and the MORDOR hydrological model. To use SCHADEX in ungauged context, rainfall distribution and hydrological model must be regionalized. The regionalization of the MEWP rainfall distribution can be managed with SPAZM, a daily rainfall interpolator [Gottardi et al., 2012] which provides reasonable estimates of point and areal rainfall up to hight quantiles. The main issue remains to regionalize MORDOR which is heavily parametrized. A much more simple model has been considered: the SCS model. It is a well known model for event simulation [USDA SCS, 1985; Beven, 2003] and it relies on only one parameter. Then, the idea is to use the SCS model instead of MORDOR within a simplified stochastic simulation scheme to produce a distribution of flood volume from an exhaustive crossing between rainy events and catchment saturation hazards. The presentation details this process and its capacity to generate a runoff distribution based on catchment areal rainfall distribution. The simulation method depends on a unique parameter Smax, the maximum initial loss of the catchment. Then an initial loss S (between zero and Smax) can be drawn to account for the variability of catchment state (between dry and saturated). The distribution of initial loss (or conversely, of catchment saturation, as modeled by MORDOR) seems closely linked to the catchment's regime, therefore easily to regionalize. The simulation takes into account a snow contribution for snow driven catchments, and an antecedent runoff. The presentation shows the results of this stochastic procedure applied on 80 French catchments and its capacity to represent the asymptotic behaviour of the runoff distribution. References: K. J. Beven. Rainfall-Runoff modelling The Primer, British Library, 2003. F. Garavaglia, J. Gailhard, E. Paquet, M. Lang, R. Garçon, and P. Bernardara. Introducing a rainfall compound distribution model based on weather patterns sub-sampling. Hydrology and Earth System Sciences, 14(6):951-964, 2010. F. Gottardi, C. Obled, J. Gailhard, and E. Paquet. Statistical reanalysis of precipitation fields based on ground network data and weather patterns : Application over french mountains. Journal of Hydrology, 432-433:154-167, 2012. ISSN 0022-1694. E. Paquet, F. Garavaglia, R Garçon, and J. Gailhard. The schadex method : a semi-continuous rainfall-runoff simulation for extreme flood estimation. Journal of Hydrology, 2013. USDA SCS, National Engineering Handbook, Supplement A, Section 4, Chapter 10. Whashington DC, 1985.

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 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

Causes of Long-Term Drought in the United States Great Plains

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Suarez, Max J.; Pegion, Philip J.; Koster, Randal

2002-01-01

The United States Great Plains (USGP) experienced a number of multi-year droughts during the last century, most notably the droughts of the 1930s and 1950s. This study examines the causes of such droughts using ensembles of long term (1930-1999) simulations carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTs). The results show that the model produces long-term (multi-year) variations in the USGP precipitation that are similar to those observed. A correlative analysis suggests that the ensemble mean low frequency (time scales longer than about 6 years) rainfall variations in the USGP are linked to a pan-Pacific pattern of SST variability that is the leading empirical orthogonal function (EOF) in the low frequency SST data. The link between the SST and the Great Plains precipitation is confirmed in idealized AGCM simulations, in which the model is forced by the 2 polarities of the pan-Pacific SST pattern. The idealized simulations further show that it is primarily the tropical part of the SST anomalies that influence the USGP. As such, the USGP tend to have above normal precipitation when the tropical Pacific SSTs are above normal, while there is a tendency for drought when the tropical SSTs are cold. The upper tropospheric response to the pan-Pacific SST EOF shows a global-scale pattern with a strong wave response in the Pacific and a substantial zonally-symmetric component in which USGP pluvial (drought) conditions are associated with reduced (enhanced) heights throughout the extra-tropics. The potential predictability of rainfall in the USGP associated with SSTs is rather modest, with on average about 1/3 of the total low frequency rainfall variance forced by SST anomalies. Further idealized experiments with climatological SST, suggest that the remaining low frequency variance in the USGP precipitation is the result of interactions with soil moisture. In particular, simulations with soil moisture feedback show a six-fold increase in the variance in annual USGP precipitation compared with simulations in which the soil feedback is excluded. In addition to increasing variance, the interactions with the soil introduce year-to-year memory in the hydrological cycle that is consistent with a red noise process, in which the low frequencies in the deep soil are the result of integrating a net forcing (precipitation-evaporation-runoff) that is white noise on interannual time scales. As such, the role of low frequency SST variability is to introduce a bias to the net forcing on the soil moisture that drives the random process preferentially to either wet or dry conditions.

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

NASA Technical Reports Server (NTRS)

Sikdar, D. M.

1984-01-01

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

A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part I: Interannual variability

NASA Astrophysics Data System (ADS)

Stephan, Claudia Christine; Klingaman, Nicholas Pappas; Vidale, Pier Luigi; Turner, Andrew George; Demory, Marie-Estelle; Guo, Liang

2018-06-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. To improve its understanding and prediction, many studies have associated precipitation variability with particular causes for specific seasons and regions. Here, a consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to 1951-2007 high-resolution precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. The EOT method is validated by the reproduction of known relationships to the El Niño Southern Oscillation (ENSO): high positive correlations with ENSO are found in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that wintertime rainfall variability along the southeast coast is associated with anomalous convection over the tropical eastern Atlantic and communicated to China through a zonal wavenumber-three Rossby wave. Furthermore, spring rainfall variability in the Yangtze valley is related to upper-tropospheric midlatitude perturbations that are part of a Rossby wave pattern with its origin in the North Atlantic. A circumglobal wave pattern in the northern hemisphere is also associated with autumn precipitation variability in eastern areas. The analysis is objective, comprehensive, and produces timeseries that are tied to specific locations in China. This facilitates the interpretation of associated dynamical processes, is useful for understanding the regional hydrological cycle, and allows the results to serve as a benchmark for assessing general circulation models.

El Niño and the shifting geography of cholera in Africa.

PubMed

Moore, Sean M; Azman, Andrew S; Zaitchik, Benjamin F; Mintz, Eric D; Brunkard, Joan; Legros, Dominique; Hill, Alexandra; McKay, Heather; Luquero, Francisco J; Olson, David; Lessler, Justin

2017-04-25

The El Niño Southern Oscillation (ENSO) and other climate patterns can have profound impacts on the occurrence of infectious diseases ranging from dengue to cholera. In Africa, El Niño conditions are associated with increased rainfall in East Africa and decreased rainfall in southern Africa, West Africa, and parts of the Sahel. Because of the key role of water supplies in cholera transmission, a relationship between El Niño events and cholera incidence is highly plausible, and previous research has shown a link between ENSO patterns and cholera in Bangladesh. However, there is little systematic evidence for this link in Africa. Using high-resolution mapping techniques, we find that the annual geographic distribution of cholera in Africa from 2000 to 2014 changes dramatically, with the burden shifting to continental East Africa-and away from Madagascar and portions of southern, Central, and West Africa-where almost 50,000 additional cases occur during El Niño years. Cholera incidence during El Niño years was higher in regions of East Africa with increased rainfall, but incidence was also higher in some areas with decreased rainfall, suggesting a complex relationship between rainfall and cholera incidence. Here, we show clear evidence for a shift in the distribution of cholera incidence throughout Africa in El Niño years, likely mediated by El Niño's impact on local climatic factors. Knowledge of this relationship between cholera and climate patterns coupled with ENSO forecasting could be used to notify countries in Africa when they are likely to see a major shift in their cholera risk.

Variations in extreme precipitation on the Loess Plateau using a high-resolution dataset and their linkages with atmospheric circulation indices

NASA Astrophysics Data System (ADS)

Zhao, Guangju; Zhai, Jianqing; Tian, Peng; Zhang, Limei; Mu, Xingmin; An, Zhengfeng; Han, Mengwei

2017-08-01

Assessing regional patterns and trends in extreme precipitation is crucial for facilitating flood control and drought adaptation because extreme climate events have more damaging impacts on society and ecosystems than simple shifts in the mean values. In this study, we employed daily precipitation data from 231 climate stations spanning 1961 to 2014 to explore the changes in precipitation extremes on the Loess Plateau, China. Nine of the 12 extreme precipitation indices suggested decreasing trends, and only the annual total wet-day precipitation (PRCPTOT) and R10 declined significantly: - 0.69 mm/a and - 0.023 days/a at the 95% confidence level. The spatial patterns in all of the extreme precipitation indices indicated mixed trends on the Loess Plateau, with decreasing trends in the precipitation extremes at the majority of the stations examined in the Fen-Wei River valley and high-plain plateau. Most of extreme precipitation indices suggested apparent regional differences, whereas R25 and R20 had spatially similar patterns on the Loess Plateau, with many stations revealing no trends. In addition, we found a potential decreasing trend in rainfall amounts and rainy days and increasing trends in rainfall intensities and storm frequencies in some regions due to increasing precipitation events in recent years. The relationships between extreme rainfall events and atmospheric circulation indices suggest that the weakening trend in the East Asia summer monsoon has limited the northward extension of the rainfall belt to northern China, thereby leading to a decrease in rainfall on the Loess Plateau.

Influence of climatic variables, forest type, and condition on activity patterns of Geoffroyi's spider monkeys throughout Mesoamerica.

PubMed

González-Zamora, Arturo; Arroyo-Rodríguez, Víctor; Chaves, Oscar M; Sánchez-López, Sónia; Aureli, Filippo; Stoner, Kathryn E

2011-12-01

Understanding how species cope with variations in climatic conditions, forest types and habitat amount is a fundamental challenge for ecologists and conservation biologists. We used data from 18 communities of Mesoamerican spider monkeys (Ateles geoffroyi) throughout their range to determine whether their activity patterns are affected by climatic variables (temperature and rainfall), forest types (seasonal and nonseasonal forests), and forest condition (continuous and fragmented). Data were derived from 15 published and unpublished studies carried out in four countries (Mexico, El Salvador, Costa Rica, and Panama), cumulatively representing more than 18 years (221 months, >3,645 hr) of behavioral observations. Overall, A. geoffroyi spent most of their time feeding (38.4 ± 14.0%, mean ± SD) and resting (36.6 ± 12.8%) and less time traveling (19.8 ± 11.3%). Resting and feeding were mainly affected by rainfall: resting time increased with decreasing rainfall, whereas feeding time increased with rainfall. Traveling time was negatively related to both rainfall and maximum temperature. In addition, both resting and traveling time were higher in seasonal forests (tropical dry forest and tropical moist forest) than in nonseasonal forests (tropical wet forest), but feeding time followed the opposite pattern. Furthermore, spider monkeys spent more time feeding and less time resting (i.e., higher feeding effort) in forest fragments than in continuous forest. These findings suggest that global climate changes and habitat deforestation and fragmentation in Mesoamerica will threaten the survival of spider monkeys and reduce the distributional range of the species in the coming decades. © 2011 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

Suryadi, Yadi; Sugianto, Denny Nugroho; Hadiyanto

2018-02-01

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

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

PubMed

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

2013-01-01

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

Low Frequency Oscillations in Assimilated Global Datasets Using TRMM Rainfall Observations

NASA Technical Reports Server (NTRS)

Tao, Li; Yang, Song; Zhang, Zhan; Hou, Arthur; Olson, William S.

2004-01-01

Global datasets for the period May-August 1998 from the Goddard Earth Observing System (GEOS) data assimilation system (DAS) with/without assimilated Tropical Rainfall Measuring Mission (TRMM) precipitation are analyzed against European Center for Medium-Range Weather Forecast (ECMWF) output, NOAA observed outgoing longwave radiation (OLR) data, and TRMM measured rainfall. The purpose of this study is to investigate the representation of the Madden-Julian Oscillation (MJO) in GEOS assimilated global datasets, noting the impact of TRMM observed rainfall on the MJO in GEOS data assimilations. A space-time analysis of the OLR data indicates that the observed OLR exhibits a spectral maximum for eastward-propagating wavenumber 1-3 disturbances with periods of 20-60 days in the 0deg-30degN latitude band. The assimilated OLR has a similar feature but with a smaller magnitude. However, OLR spectra from assimilations including TRMM rainfall data show better agreement with observed OLR spectra than spectra from assimilations without TRMM rainfall. Similar results are found for wavenumber 4-6 disturbances. There is a spectral peak for eastward-propagating wavenumber 4-6 disturbances with periods of 20-40 days near the equator, while for westward-moving disturbances, a spectral peak is noted for periods of 30-50 days near 25degN. To isolate the MJO, a 30-50 day band filter is selected for this study. It was found that the eastward-propagating waves from the band-filtered observed OLR between 10degs- 10degN are located in the eastern hemisphere. Similar patterns are evident in surface rainfall and the 850 hPa wind field. Assimilation of TRMM-observed rainfall reveals more distinct MJO features in the analysis than without rainfall assimilation. Similar analyses are also conducted over the Indian summer monsoon and East Asia summer monsoon regions, where the MJO is strongly related to the summer monsoon active-break patterns.

A spatio-temporal evaluation of the WRF physical parameterisations for numerical rainfall simulation in semi-humid and semi-arid catchments of Northern China

NASA Astrophysics Data System (ADS)

Tian, Jiyang; Liu, Jia; Wang, Jianhua; Li, Chuanzhe; Yu, Fuliang; Chu, Zhigang

2017-07-01

Mesoscale Numerical Weather Prediction systems can provide rainfall products at high resolutions in space and time, playing an increasingly more important role in water management and flood forecasting. The Weather Research and Forecasting (WRF) model is one of the most popular mesoscale systems and has been extensively used in research and practice. However, for hydrologists, an unsolved question must be addressed before each model application in a different target area. That is, how are the most appropriate combinations of physical parameterisations from the vast WRF library selected to provide the best downscaled rainfall? In this study, the WRF model was applied with 12 designed parameterisation schemes with different combinations of physical parameterisations, including microphysics, radiation, planetary boundary layer (PBL), land-surface model (LSM) and cumulus parameterisations. The selected study areas are two semi-humid and semi-arid catchments located in the Daqinghe River basin, Northern China. The performance of WRF with different parameterisation schemes is tested for simulating eight typical 24-h storm events with different evenness in space and time. In addition to the cumulative rainfall amount, the spatial and temporal patterns of the simulated rainfall are evaluated based on a two-dimensional composed verification statistic. Among the 12 parameterisation schemes, Scheme 4 outperforms the other schemes with the best average performance in simulating rainfall totals and temporal patterns; in contrast, Scheme 6 is generally a good choice for simulations of spatial rainfall distributions. Regarding the individual parameterisations, Single-Moment 6 (WSM6), Yonsei University (YSU), Kain-Fritsch (KF) and Grell-Devenyi (GD) are better choices for microphysics, planetary boundary layers (PBL) and cumulus parameterisations, respectively, in the study area. These findings provide helpful information for WRF rainfall downscaling in semi-humid and semi-arid areas. The methodologies to design and test the combination schemes of parameterisations can also be regarded as a reference for generating ensembles in numerical rainfall predictions using the WRF model.

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.

Impacts of climate variability and extreme events on soil hydrological processes

NASA Astrophysics Data System (ADS)

Ramos, M. C.; Mulligan, M.

2003-04-01

The Mediterranean climate (dry subhumid), characterised by a high variability, produces in many situations an insufficient water supply to support stable agriculture. Not only is there insufficient rainfall, but its occurrence is also highly variable between years, during the year, and spatially, during a single rainfall event. One of the main climatic characteristics affecting the vulnerability of the Mediterranean region is the high intensity rainfalls which fall after a very dry summer and the high degree of climatic fluctuation in the short and long term, especially in rainfall quantity. In addition, the rainwater penetration and storage of water in the soil are conditioned by the soil characteristics, in some cases modified by changes in land use and with new management practices. The aim of this study was to evaluate the impact of this high variability, from year to year and through the year, on soil hydrological processes, in fields resulted of the mechanisation works in vineyards in a Mediterranean environment. The PATTERNlight model, a simplified two-dimensional version of the hydrological and growth PATTERN model (Mulligan, 1996) is used here to simulate the water balance for three situations: normal, wet and dry years. Ssignificant differences in soil moisture and recharge were observed under vine culture from year to year, giving rise very often, to critical situations for the development of the crops. The distribution of the rainfall through the year together with the intensity of the recorded rainfalls is much very significant for soil hydrology than the total annual rainfall. Very low soil moisture conditions are raised when spring rainfall is scarce, which contribute to exhaustion of profile soil water over the summer, especially if the antecedent soil moisture is low. This low soil moisture has a significant effect on the development of the vine crop. The simulations of leaf and root biomass carried out with the PATTERNLIGHT model indicate the differences in the development of the leaf biomass between wet and dry conditions, especially with dry springs. Wet conditions favour the development of root and leaf biomass in a significant way. Mulligan, M., 1996. Modelling the hydrology of vegetation competition in a degrade semiarid environment. PhD Theses. Department of Geography, King's College London, University of London.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Design of the primary pre-TRMM and TRMM ground truth site

NASA Technical Reports Server (NTRS)

Garstang, Michael

1988-01-01

The primary objective of the Tropical Rain Measuring Mission (TRMM) were to: integrate the rain gage measurements with radar measurements of rainfall using the KSFC/Patrick digitized radar and associated rainfall network; delineate the major rain bearing systems over Florida using the Weather Service reported radar/rainfall distributions; combine the integrated measurements with the delineated rain bearing systems; use the results of the combined measurements and delineated rain bearing systems to represent patterns of rainfall which actually exist and contribute significantly to the rainfall to test sampling strategies and based on the results of these analyses decide upon the ground truth network; and complete the design begun in Phase 1 of a multi-scale (space and time) surface observing precipitation network centered upon KSFC. Work accomplished and in progress is discussed.

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

USDA-ARS?s Scientific Manuscript database

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

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.

[Runoff Pollution Experiments of Paddy Fields Under Different Irrigation Patterns].

PubMed

Zhou, Jing-wen; Su, Bao-lin; Huang, Ning-bo; Guan, Yu-tang; Zhao, Kun

2016-03-15

To study runoff and non-point source pollution of paddy fields and to provide a scientific basis for agricultural water management of paddy fields, paddy plots in the Jintan City and the Liyang City were chosen for experiments on non-point source pollution, and flood irrigation and intermittent irrigation patterns were adopted in this research. The surface water level and rainfall were observed during the growing season of paddies, and the runoff amount from paddy plots and loads of total nitrogen (TN) and total phosphorus (TP) were calculated by different methods. The results showed that only five rain events of totally 27 rainfalls and one artificially drainage formed non-point source pollution from flood irrigated paddy plot, which resulted in a TN export coefficient of 49.4 kg · hm⁻² and a TP export coefficient of 1.0 kg · hm⁻². No any runoff event occurred from the paddy plot with intermittent irrigation even in the case of maximum rainfall of 95.1 mm. Runoff from paddy fields was affected by water demands of paddies and irrigation or drainage management, which was directly correlated to surface water level, rainfall amount and the lowest ridge height of outlets. Compared with the flood irrigation, intermittent irrigation could significantly reduce non-point source pollution caused by rainfall or artificial drainage.

Short-term effect of nutrient availability and rainfall distribution on biomass production and leaf nutrient content of savanna tree species.

PubMed

Barbosa, Eduardo R M; Tomlinson, Kyle W; Carvalheiro, Luísa G; Kirkman, Kevin; de Bie, Steven; Prins, Herbert H T; van Langevelde, Frank

2014-01-01

Changes in land use may lead to increased soil nutrient levels in many ecosystems (e.g. due to intensification of agricultural fertilizer use). Plant species differ widely in their response to differences in soil nutrients, and for savannas it is uncertain how this nutrient enrichment will affect plant community dynamics. We set up a large controlled short-term experiment in a semi-arid savanna to test how water supply (even water supply vs. natural rainfall) and nutrient availability (no fertilisation vs. fertilisation) affects seedlings' above-ground biomass production and leaf-nutrient concentrations (N, P and K) of broad-leafed and fine-leafed tree species. Contrary to expectations, neither changes in water supply nor changes in soil nutrient level affected biomass production of the studied species. By contrast, leaf-nutrient concentration did change significantly. Under regular water supply, soil nutrient addition increased the leaf phosphorus concentration of both fine-leafed and broad-leafed species. However, under uneven water supply, leaf nitrogen and phosphorus concentration declined with soil nutrient supply, this effect being more accentuated in broad-leafed species. Leaf potassium concentration of broad-leafed species was lower when growing under constant water supply, especially when no NPK fertilizer was applied. We found that changes in environmental factors can affect leaf quality, indicating a potential interactive effect between land-use changes and environmental changes on savanna vegetation: under more uneven rainfall patterns within the growing season, leaf quality of tree seedlings for a number of species can change as a response to changes in nutrient levels, even if overall plant biomass does not change. Such changes might affect herbivore pressure on trees and thus savanna plant community dynamics. Although longer term experiments would be essential to test such potential effects of eutrophication via changes in leaf nutrient concentration, our findings provide important insights that can help guide management plans that aim to preserve savanna biodiversity.

Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

NASA Astrophysics Data System (ADS)

Dakhlaoui, H.; Ruelland, D.; Tramblay, Y.; Bargaoui, Z.

2017-07-01

To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that must be fairly reliable under changing climate conditions. The aim of this study was thus to assess the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in northern Tunisia under long-term climate variability, in the light of available future climate scenarios for this region. The robustness of the models was evaluated using a differential split sample test based on a climate classification of the observation period that simultaneously accounted for precipitation and temperature conditions. The study catchments include the main hydrographical basins in northern Tunisia, which produce most of the surface water resources in the country. A 30-year period (1970-2000) was used to capture a wide range of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while model transferability was evaluated based on the Nash-Sutcliffe efficiency criterion and volume error. The three hydrological models were shown to behave similarly under climate variability. The models simulated the runoff pattern better when transferred to wetter and colder conditions than to drier and warmer ones. It was shown that their robustness became unacceptable when climate conditions involved a decrease of more than 25% in annual precipitation and an increase of more than +1.75 °C in annual mean temperatures. The reduction in model robustness may be partly due to the climate dependence of some parameters. When compared to precipitation and temperature projections in the region, the limits of transferability obtained in this study are generally respected for short and middle term. For long term projections under the most pessimistic emission gas scenarios, the limits of transferability are generally not respected, which may hamper the use of conceptual models for hydrological projections in northern Tunisia.

Runoff prediction using rainfall data from microwave links: Tabor case study.

PubMed

Stransky, David; Fencl, Martin; Bares, Vojtech

2018-05-01

Rainfall spatio-temporal distribution is of great concern for rainfall-runoff modellers. Standard rainfall observations are, however, often scarce and/or expensive to obtain. Thus, rainfall observations from non-traditional sensors such as commercial microwave links (CMLs) represent a promising alternative. In this paper, rainfall observations from a municipal rain gauge (RG) monitoring network were complemented by CMLs and used as an input to a standard urban drainage model operated by the water utility of the Tabor agglomeration (CZ). Two rainfall datasets were used for runoff predictions: (i) the municipal RG network, i.e. the observation layout used by the water utility, and (ii) CMLs adjusted by the municipal RGs. The performance was evaluated in terms of runoff volumes and hydrograph shapes. The use of CMLs did not lead to distinctively better predictions in terms of runoff volumes; however, CMLs outperformed RGs used alone when reproducing a hydrograph's dynamics (peak discharges, Nash-Sutcliffe coefficient and hydrograph's rising limb timing). This finding is promising for number of urban drainage tasks working with dynamics of the flow. Moreover, CML data can be obtained from a telecommunication operator's data cloud at virtually no cost. That makes their use attractive for cities unable to improve their monitoring infrastructure for economic or organizational reasons.

High-frequency DOC and nitrate measurements provide new insights into their export and their relationships to rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Schwab, Michael; Klaus, Julian; Pfister, Laurent; Weiler, Markus

2015-04-01

Over the past decades, stream sampling protocols for environmental tracers were often limited by logistical and technological constraints. Long-term sampling programs would typically rely on weekly sampling campaigns, while high-frequency sampling would remain restricted to a few days or hours at best. We stipulate that the currently predominant sampling protocols are too coarse to capture and understand the full amplitude of rainfall-runoff processes and its relation to water quality fluctuations. Weekly sampling protocols are not suited to get insights into the hydrological system during high flow conditions. Likewise, high frequency measurements of a few isolated events do not allow grasping inter-event variability in contributions and processes. Our working hypothesis is based on the potential of a new generation of field-deployable instruments for measuring environmental tracers at high temporal frequencies over an extended period. With this new generation of instruments we expect to gain new insights into rainfall-runoff dynamics, both at intra- and inter-event scales. Here, we present the results of one year of DOC and nitrate measurements with the field deployable UV-Vis spectrometer spectro::lyser (scan Messtechnik GmbH). The instrument measures the absorption spectrum from 220 to 720 nm in situ and at high frequencies and derives DOC and nitrate concentrations. The measurements were carried out at 15 minutes intervals in the Weierbach catchment (0.47 km2) in Luxemburg. This fully forested catchment is characterized by cambisol soils and fractured schist as underlying bedrock. The time series of DOC and nitrate give insights into the high frequency dynamics of stream water. Peaks in DOC concentrations are closely linked to discharge peaks that occur during or right after a rainfall event. Those first discharge peaks can be linked to fast near surface runoff processes and are responsible for a remarkable amount of DOC export. A special characterisation of the Weierbach catchment are the delayed second peaks a few days after the rainfall event. Nitrate concentrations are following this second peak. We assume that this delayed response is going back to subsurface or upper groundwater flows, with nitrate enriched water. On an inter-event scale during low flow / base flow conditions, we observe interesting diurnal patterns of both DOC and nitrate concentrations. Overall, the long-term high-frequency measurements of DOC and nitrate provide us the opportunity to separate different rainfall-runoff processes and link the amount of DOC and nitrate export to them to quantify the overall relevance of the different processes.

Hydroclimate of the western Indo-Pacific Warm Pool during the past 24,000 years

PubMed Central

Niedermeyer, Eva M.; Sessions, Alex L.; Feakins, Sarah J.; Mohtadi, Mahyar

2014-01-01

The Indo-Pacific Warm Pool (IPWP) is a key site for the global hydrologic cycle, and modern observations indicate that both the Indian Ocean Zonal Mode (IOZM) and the El Niño Southern Oscillation exert strong influence on its regional hydrologic characteristics. Detailed insight into the natural range of IPWP dynamics and underlying climate mechanisms is, however, limited by the spatial and temporal coverage of climate data. In particular, long-term (multimillennial) precipitation patterns of the western IPWP, a key location for IOZM dynamics, are poorly understood. To help rectify this, we have reconstructed rainfall changes over Northwest Sumatra (western IPWP, Indian Ocean) throughout the past 24,000 y based on the stable hydrogen and carbon isotopic compositions (δD and δ13C, respectively) of terrestrial plant waxes. As a general feature of western IPWP hydrology, our data suggest similar rainfall amounts during the Last Glacial Maximum and the Holocene, contradicting previous claims that precipitation increased across the IPWP in response to deglacial changes in sea level and/or the position of the Intertropical Convergence Zone. We attribute this discrepancy to regional differences in topography and different responses to glacioeustatically forced changes in coastline position within the continental IPWP. During the Holocene, our data indicate considerable variations in rainfall amount. Comparison of our isotope time series to paleoclimate records from the Indian Ocean realm reveals previously unrecognized fluctuations of the Indian Ocean precipitation dipole during the Holocene, indicating that oscillations of the IOZM mean state have been a constituent of western IPWP rainfall over the past ten thousand years. PMID:24979768

The Potential for Snow to Supply Human Water Demand in the Present and Future

NASA Technical Reports Server (NTRS)

Mankin, Justin S.; Viviroli, Daniel; Singh, Deepti; Hoekstra, Arjen Y.; Diffenbaugh, Noah S.

2015-01-01

Runoff from snowmelt is regarded as a vital water source for people and ecosystems throughout the Northern Hemisphere (NH). Numerous studies point to the threat global warming poses to the timing and magnitude of snow accumulation and melt. But analyses focused on snow supply do not show where changes to snowmelt runoff are likely to present the most pressing adaptation challenges, given sub-annual patterns of human water consumption and water availability from rainfall. We identify the NH basins where present spring and summer snowmelt has the greatest potential to supply the human water demand that would otherwise be unmet by instantaneous rainfall runoff. Using a multi-model ensemble of climate change projections, we find that these basins - which together have a present population of approx. 2 billion people - are exposed to a 67% risk of decreased snow supply this coming century. Further, in the multi-model mean, 68 basins (with a present population of more than 300 million people) transition from having sufficient rainfall runoff to meet all present human water demand to having insufficient rainfall runoff. However, internal climate variability creates irreducible uncertainty in the projected future trends in snow resource potential, with about 90% of snow-sensitive basins showing potential for either increases or decreases over the near-term decades. Our results emphasize the importance of snow for fulfilling human water demand in many NH basins, and highlight the need to account for the full range of internal climate variability in developing robust climate risk management decisions.

Effect of Erosion on Productivity in Subtropical Red Soil Hilly Region: A Multi-Scale Spatio-Temporal Study by Simulated Rainfall

PubMed Central

Li, Zhongwu; Huang, Jinquan; Zeng, Guangming; Nie, Xiaodong; Ma, Wenming; Yu, Wei; Guo, Wang; Zhang, Jiachao

2013-01-01

The effects of water erosion (including long-term historical erosion and single erosion event) on soil properties and productivity in different farming systems were investigated. A typical sloping cropland with homogeneous soil properties was designed in 2009 and then protected from other external disturbances except natural water erosion. In 2012, this cropland was divided in three equally sized blocks. Three treatments were performed on these blocks with different simulated rainfall intensities and farming methods: (1) high rainfall intensity (1.5 - 1.7 mm min−1), no-tillage operation; (2) low rainfall intensity (0.5 - 0.7 mm min−1), no-tillage operation; and (3) low rainfall intensity, tillage operation. All of the blocks were divided in five equally sized subplots along the slope to characterize the three-year effects of historical erosion quantitatively. Redundancy analysis showed that the effects of long-term historical erosion significantly caused most of the variations in soil productivity in no-tillage and low rainfall erosion intensity systems. The intensities of the simulated rainfall did not exhibit significant effects on soil productivity in no-tillage systems. By contrast, different farming operations induced a statistical difference in soil productivity at the same single erosion intensity. Soil organic carbon (SOC) was the major limiting variable that influenced soil productivity. Most explanations of long-term historical erosion for the variation in soil productivity arose from its sharing with SOC. SOC, total nitrogen, and total phosphorus were found as the regressors of soil productivity because of tillage operation. In general, this study provided strong evidence that single erosion event could also impose significant constraints on soil productivity by integrating with tillage operation, although single erosion is not the dominant effect relative to the long-term historical erosion. Our study demonstrated that an effective management of organic carbon pool should be the preferred option to maintain soil productivity in subtropical red soil hilly region. PMID:24147090

Understanding Survival And Abundance Of Overwintering Warblers: Does Rainfall Matter?

Treesearch

Katie M. Dugger; John G Faaborg; Wayne J. Arendt; Keith A. Hobson

2004-01-01

We investigated relationships between warbler abundance and survival rates measured on a Puerto Rican wintering site and rainfall patterns measured on the wintering site and in regions where these warblers breed, as estimated using stable-isotope analysis (δD) of feathers collected from wintering birds. We banded birds using constant-effort mist netting...

Rainfall, El Niño, and reproduction of red-cockaded woodpeckers

Treesearch

Richard N. Conner; Daniel Saenz; Richard R. Schaefer; James R. McCormick; D. Craig Rudolph; D. Brent Burt

2005-01-01

This study examines the relationship between Red-cockaded Woodpecker (Picoides borealis Vieillot) reproduction and rainfall during May when group members are provisioning nestlings with food. Patterns of variation over a 4-year period of approximately 30 woodpecker groups suggested that the mean number of hatchling deaths was positively related to...

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

NASA Astrophysics Data System (ADS)

Gaitan, S.; ten Veldhuis, J. A. E.

2015-06-01

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

Could the long term cover change of three Mediterranean shrubs be explained by their photosynthetic responses to drought in a rainfall exclusion experiment ?

NASA Astrophysics Data System (ADS)

Liberati, Dario; De Dato, Giovanbattista; Guidolotti, Gabriele; De Angelis, Paolo

2013-04-01

In the Mediterranean climates water stress is considered to be the main environmental factor limiting plant growth. In front of water limitations plants have developed a wide diversity of adaptation mechanism, and co-occurring species often display different physiological, functional, and life history strategies. In the contest of a rainfall exclusion experiment (project INCREASE), the present work is aimed to assess if the seasonal response of photosynthesis to the water stress (based on gas exchange data collected during 2010) can explain the long term change in the cover degree (assessed by seven pin point survey carried out from 2001 to 2012) of the three main species present in the Italian experimental site, Cistus monspeliensis L. (Cistaceae), Dorycnium pentaphyllum Scop. (Fabaceae) and Helichrysum italicum subsp. microphyllum (Willd.) Nyman (Asteraceae) From 2001 to 2012, in the untreated plots, the cover degree increased in C. monspeliensis (+ 0.34% per year), did not show any significant trend in D. pentaphyllum and decreased in H. italicum (- 1.54% per year). In the same period the rainfall exclusion system has worked during Spring and Autumn, mainly reducing the soil water content of the drought plots in Autumn: this treatment did not affect the cover trend of D. pentaphyllum and H. italicum, whereas C. monspeliensis displayed in the drought plots an opposite dynamic (- 1.23% per year) compared to the natural conditions. During 2010 all monitored species reached the maximum photosynthesis rates in spring, with a depression during summer drought and a recovery after the first Autumn rainfalls. The recovery of the spring rates was almost complete in C. monspeliensis and D. pentaphyllum, while in H. italicum did not exceed the 30% of the spring value. The rainfall exclusion reduced the photosynthesis rates in C. monspeliensis and H. italicum in Autumn. In the control plots the opposite cover trend observed in C. monspeliensis and H.italicum could be connected to the different ability of the two species in keeping high photosynthesis rates during the Autumn period, that could imply a limitation in the growth and therefore in the competitive ability of H. italicum. The lower ability of D. pentaphyllum in gain cover with respect to C. monspeliensis, despite the similar photosynthetic seasonal trend, could be related to the different resource allocation pattern connected to the deep root system, that only characterize this species. The strong effect of the rainfall exclusion on the cover trend of C. monspeliensis , compared to no effect observed in H. italicum, could be explained by the timing of the drought treatment, affecting C. monspeliensis during one of the two annual photosynthetic peaks, H. italicum during a period of low photosynthetic activity. It seems therefore possible to find some connection between the population dynamics of the studied species and their ability in recovering after the drought stress; furthermore, the lengthening of the dry season, as simulated by the rainfall exclusion system, in the long term seems to impact more on those species, like C. monspeliensis, relying on Autumn period to perform a significant part of their annual assimilation.

Nonlinear response in runoff magnitude to fluctuating rain patterns.

PubMed

Curtu, R; Fonley, M

2015-03-01

The runoff coefficient of a hillslope is a reliable measure for changes in the streamflow response at the river link outlet. A high runoff coefficient is a good indicator of the possibility of flash floods. Although the relationship between runoff coefficient and streamflow has been the subject of much study, the physical mechanisms affecting runoff coefficient including the dependence on precipitation pattern remain open topics for investigation. In this paper, we analyze a rainfall-runoff model at the hillslope scale as that hillslope is forced with different rain patterns: constant rain and fluctuating rain with different frequencies and amplitudes. When an oscillatory precipitation pattern is applied, although the same amount of water may enter the system, its response (measured by the runoff coefficient) will be maximum for a certain frequency of precipitation. The significant increase in runoff coefficient after a certain pattern of rainfall can be a potential explanation for the conditions preceding flash-floods.

Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables

NASA Astrophysics Data System (ADS)

Lodoun, Tiganadaba; Sanon, Moussa; Giannini, Alessandra; Traoré, Pierre Sibiry; Somé, Léopold; Rasolodimby, Jeanne Millogo

2014-08-01

In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May-July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920-2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.

Modeling rainfall-runoff relationship using multivariate GARCH model

NASA Astrophysics Data System (ADS)

Modarres, R.; Ouarda, T. B. M. J.

2013-08-01

The traditional hydrologic time series approaches are used for modeling, simulating and forecasting conditional mean of hydrologic variables but neglect their time varying variance or the second order moment. This paper introduces the multivariate Generalized Autoregressive Conditional Heteroscedasticity (MGARCH) modeling approach to show how the variance-covariance relationship between hydrologic variables varies in time. These approaches are also useful to estimate the dynamic conditional correlation between hydrologic variables. To illustrate the novelty and usefulness of MGARCH models in hydrology, two major types of MGARCH models, the bivariate diagonal VECH and constant conditional correlation (CCC) models are applied to show the variance-covariance structure and cdynamic correlation in a rainfall-runoff process. The bivariate diagonal VECH-GARCH(1,1) and CCC-GARCH(1,1) models indicated both short-run and long-run persistency in the conditional variance-covariance matrix of the rainfall-runoff process. The conditional variance of rainfall appears to have a stronger persistency, especially long-run persistency, than the conditional variance of streamflow which shows a short-lived drastic increasing pattern and a stronger short-run persistency. The conditional covariance and conditional correlation coefficients have different features for each bivariate rainfall-runoff process with different degrees of stationarity and dynamic nonlinearity. The spatial and temporal pattern of variance-covariance features may reflect the signature of different physical and hydrological variables such as drainage area, topography, soil moisture and ground water fluctuations on the strength, stationarity and nonlinearity of the conditional variance-covariance for a rainfall-runoff process.

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.

Mapping extreme rainfall in the Northwest Portugal region: statistical analysis and spatial modelling

NASA Astrophysics Data System (ADS)

Santos, Monica; Fragoso, Marcelo

2010-05-01

Extreme precipitation events are one of the causes of natural hazards, such as floods and landslides, making its investigation so important, and this research aims to contribute to the study of the extreme rainfall patterns in a Portuguese mountainous area. The study area is centred on the Arcos de Valdevez county, located in the northwest region of Portugal, the rainiest of the country, with more than 3000 mm of annual rainfall at the Peneda-Gerês mountain system. This work focus on two main subjects related with the precipitation variability on the study area. First, a statistical analysis of several precipitation parameters is carried out, using daily data from 17 rain-gauges with a complete record for the 1960-1995 period. This approach aims to evaluate the main spatial contrasts regarding different aspects of the rainfall regime, described by ten parameters and indices of precipitation extremes (e.g. mean annual precipitation, the annual frequency of precipitation days, wet spells durations, maximum daily precipitation, maximum of precipitation in 30 days, number of days with rainfall exceeding 100 mm and estimated maximum daily rainfall for a return period of 100 years). The results show that the highest precipitation amounts (from annual to daily scales) and the higher frequency of very abundant rainfall events occur in the Serra da Peneda and Gerês mountains, opposing to the valleys of the Lima, Minho and Vez rivers, with lower precipitation amounts and less frequent heavy storms. The second purpose of this work is to find a method of mapping extreme rainfall in this mountainous region, investigating the complex influence of the relief (e.g. elevation, topography) on the precipitation patterns, as well others geographical variables (e.g. distance from coast, latitude), applying tested geo-statistical techniques (Goovaerts, 2000; Diodato, 2005). Models of linear regression were applied to evaluate the influence of different geographical variables (altitude, latitude, distance from sea and distance to the highest orographic barrier) on the rainfall behaviours described by the studied variables. The techniques of spatial interpolation evaluated include univariate and multivariate methods: cokriging, kriging, IDW (inverse distance weighted) and multiple linear regression. Validation procedures were used, assessing the estimated errors in the analysis of descriptive statistics of the models. Multiple linear regression models produced satisfactory results in relation to 70% of the rainfall parameters, suggested by lower average percentage of error. However, the results also demonstrates that there is no an unique and ideal model, depending on the rainfall parameter in consideration. Probably, the unsatisfactory results obtained in relation to some rainfall parameters was motivated by constraints as the spatial complexity of the precipitation patterns, as well as to the deficient spatial coverage of the territory by the rain-gauges network. References Diodato, N. (2005). The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain. Internacional Journal of Climatology, 25(3), 351-363. Goovaerts, P. (2000). Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall. Journal of Hydrology, 228, 113 - 129.

Herbivory and drought generate short-term stochasticity and long-term stability in a savanna understory community.

PubMed

Riginos, Corinna; Porensky, Lauren M; Veblen, Kari E; Young, Truman P

2018-03-01

Rainfall and herbivory are fundamental drivers of grassland plant dynamics, yet few studies have examined long-term interactions between these factors in an experimental setting. Understanding such interactions is important, as rainfall is becoming increasingly erratic and native wild herbivores are being replaced by livestock. Livestock grazing and episodic low rainfall are thought to interact, leading to greater community change than either factor alone. We examined patterns of change and stability in herbaceous community composition through four dry periods, or droughts, over 15 years of the Kenya Long-term Exclosure Experiment (KLEE), which consists of six different combinations of cattle, native wild herbivores (e.g., zebras, gazelles), and mega-herbivores (giraffes, elephants). We used principal response curves to analyze the trajectory of change in each herbivore treatment relative to a common initial community and asked how droughts contributed to community change in these treatments. We examined three measures of stability (resistance, variability, and turnover) that correspond to different temporal scales and found that each had a different response to grazing. Treatments that included both cattle and wild herbivores had higher resistance (less net change over 15 years) but were more variable on shorter time scales; in contrast, the more lightly grazed treatments (no herbivores or wild herbivores only) showed lower resistance due to the accumulation of consistent, linear, short-term change. Community change was greatest during and immediately after droughts in all herbivore treatments. But, while drought contributed to directional change in the less grazed treatments, it contributed to both higher variability and resistance in the more heavily grazed treatments. Much of the community change in lightly grazed treatments (especially after droughts) was due to substantial increases in cover of the palatable grass Brachiaria lachnantha. These results illustrate how herbivory and drought can act together to cause change in grassland communities at the moderate to low end of a grazing intensity continuum. Livestock grazing at a moderate intensity in a system with a long evolutionary history of grazing contributed to long-term stability. This runs counter to often-held assumptions that livestock grazing leads to directional, destabilizing shifts in grassland systems. © 2017 by the Ecological Society of America.

Two decades of climate driving the dynamics of functional and taxonomic diversity of a tropical small mammal community in western Mexico.

PubMed

Mason-Romo, Edgard David; Farías, Ariel A; Ceballos, Gerardo

2017-01-01

Understanding the effects of global climate disruption on biodiversity is important to future conservation efforts. While taxonomic diversity is widely studied, functional diversity of plants, and recently animals, is receiving increasing attention. Most studies of mammals are short-term, focus on temperate habitats, and rely on traits described in the literature rather than generating traits from observations. Unlike previous studies, this long-term field study assessed the factors driving the functional and taxonomic diversity of small-mammal assemblages in dry tropical forests using both traits recorded from literature and a demographic database. We assessed the drivers (abundance and biomass, temperature and rainfall) of taxonomic richness and functional diversity for two rain-driven seasons in two adjacent but distinct forests-upland and lowland (arroyo or riparian) forests. Our analysis found that rainfall, both seasonal and atypical, was the primary factor driving functional and taxonomic diversity of small-mammal assemblages. Functional responses differed between the two types of forests, however, with effects being stronger in the harsher conditions of the upland forests than in the less severe conditions prevailing in the arroyo (riparian) forest. The latter also supports a richer, more diverse, and more stable small-mammal assemblage. These findings highlight the importance of climate to tropical biological diversity, as extreme climate events (hurricanes, droughts and floods) and disruption of rainfall patterns were shown to decrease biodiversity. They also support the need to preserve these habitats, as their high taxonomic diversity and functional redundancy makes them resilient against global climate disruption and local extreme events. Tropical dry forests constitute a potential reservoir for biodiversity and the ecosystem services they provide. Unfortunately, these forests are among the most endangered terrestrial ecosystems because of deforestation and the likely impacts of global climate disruption.

Evaluating satellite-derived long-term historical precipitation datasets for drought monitoring in Chile

NASA Astrophysics Data System (ADS)

Zambrano, Francisco; Wardlow, Brian; Tadesse, Tsegaye

2016-10-01

Precipitation is a key parameter for the study of climate change and variability and the detection and monitoring of natural disaster such as drought. Precipitation datasets that accurately capture the amount and spatial variability of rainfall is critical for drought monitoring and a wide range of other climate applications. This is challenging in many parts of the world, which often have a limited number of weather stations and/or historical data records. Satellite-derived precipitation products offer a viable alternative with several remotely sensed precipitation datasets now available with long historical data records (+30 years), which include the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) datasets. This study presents a comparative analysis of three historical satellite-based precipitation datasets that include Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B43 version 7 (1998-2015), PERSIANN-CDR (1983-2015) and CHIRPS 2.0 (1981-2015) over Chile to assess their performance across the country and evaluate their applicability for agricultural drought evaluation when used in the calculation of commonly used drought indicator as the Standardized Precipitation Index (SPI). In this analysis, 278 weather stations of in-situ rainfall measurements across Chile were initially compared to the satellite-based precipitation estimates. The study area (Chile) was divided into five latitudinal zones: North, North-Central, Central, South-Central and South to determine if there were a regional difference among these satellite-based estimates. Nine statistics were used to evaluate the performance of satellite products to estimate the amount and spatial distribution of historical rainfall across Chile. Hierarchical cluster analysis, k-means and singular value decomposition were used to analyze these datasets to better understand their similarities and differences in characterizing rainfall patterns across Chile. Monthly analysis showed that all satellite products highly overestimated precipitation in the arid North zone. However, there were no major difference between all three products from North to South-Central zones. Though, in the South zone, PERSIANN-CDR shows the lowest fit with high underestimation, further CHIRPS 2.0 and TMPA 3B43 v7 had better agreement with in-situ measurements. The accuracy of satellite products were highly dependent on the amount of monthly rainfall with the best results found during winter seasons and in zones (Central to South) with higher amounts of precipitation. PERSIANN-CDR and CHIRPS 2.0 were used to derive SPI at time-scale of 1, 3 and 6 months, both satellite products presented similar results when it was compared in-situ against satellite SPI's. Because of its higher spatial resolution that allows better characterizing of spatial variation in precipitation pattern, the CHIRPS 2.0 was used to mapping the SPI-3 over Chile. The results of this study show that in order to use the CHIRPS 2.0 and PERSIANN-CDR data sets in Chile to monitor spatial patterns in the rainfall and drought intensity conditions, these products should be calibrated to adjust for the overestimation/underestimation of precipitation geographically specially in the North zone and seasonally during the summer and spring months in the other zones.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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.

TRMM Applications for Rainfall-Induced Landslide Early Warning

NASA Astrophysics Data System (ADS)

Dok, A.; Fukuoka, H.; Hong, Y.

2012-04-01

Early warning system (EWS) is the most effective method in saving lives and reducing property damages resulted from the catastrophic landslides if properly implemented in populated areas of landslide-prone nations. For predicting the occurrence of landslides, it requires examination of empirical relationship between rainfall characteristics and past landslide occurrence. In developed countries like Japan and the US, precipitation is monitored by rain radars and ground-based rain gauge matrix. However, in developing regions like Southeast Asian countries, very limited number of rain gauges is available, and there is no implemented methodology for issuing effective warming of landslides yet. Correspondingly, satellite precipitation monitoring could be therefore a possible and promising solution for launching landslide quasi-real-time early warning system in those countries. It is due to the fact that TMPA (TRMM Multi-satellite Precipitation Analysis) can provides a globally calibration-based sequential scheme for combining precipitation estimates from multiple satellites, and gauge analyses where feasible, at fine scales (3-hourly with 0.25°x0.25° spatial resolution). It is available both after and in quasi-real time, calibrated by TRMM Combined Instrument and TRMM Microwave Imager precipitation product. However, validation of ground based rain gauge and TRMM satellite data in the vulnerable regions is still not yet operative. Snake-line/Critical-line and Soil Water Index (SWI) are used for issuing warning of landslide occurrence in Japan; whereas, Caine criterion is preferable in Europe and western nations. Herewith, it presents rainfall behavior which took place in Beichuan city (located on the 2008 Chinese Wenchuan earthquake fault), Hofu and Shobara cities in Japan where localized heavy rainfall attacked in 2009 and 2010, respectively, from TRMM 3B42RT correlated with ground based rain gauge data. The 1-day rainfall intensity and 15-day cumulative rainfall (snake line) were independently plotted to investigate the impact of short-term rainfall intensity and accumulated effective rainfall volume respectively for obtaining some probabilistic threshold. Japanese SWI was also tested to distribute threshold regarding to highly nonlinear rainfall patterns in predicting the landslide occurrence through the plot of total water of 3 serial tank models and daily precipitation. As a result, the snake line plots using TMPA work well for landslide warning in the selected cities; while SWI plots shows unusual peak value on the day of the debris flow occurrence. Graph of daily precipitation vs SWI implies possible zone of critical line, and second peak appearance 1 day before, indicating possibility of early warning.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Reference intervals and physiologic alterations in hematologic and biochemical values of free-ranging desert tortoises in the Mojave Desert

USGS Publications Warehouse

Christopher, Mary M.; Berry, Kristin H.; Wallis, I.R.; Nagy, K.A.; Henen, B.T.; Peterson, C.C.

1999-01-01

Desert tortoise (Gopherus agassizii) populations have experienced precipitous declines resulting from the cumulative impact of habitat loss, and human and disease-related mortality. Evaluation of hematologic and biochemical responses of desert tortoises to physiologic and environmental factors can facilitate the assessment of stress and disease in tortoises and contribute to management decisions and population recovery. The goal of this study was to obtain and analyze clinical laboratory data from free-ranging desert tortoises at three sites in the Mojave Desert (California, USA) between October 1990 and October 1995, to establish reference intervals, and to develop guidelines for the interpretation of laboratory data under a variety of environmental and physiologic conditions. Body weight, carapace length, and venous blood samples for a complete blood count and clinical chemistry profile were obtained from 98 clinically healthy adult desert tortoises of both sexes at the Desert Tortoise Research Natural area (western Mojave), Goffs (eastern Mojave) and Ivanpah Valley (northeastern Mojave). Samples were obtained four times per year, in winter (February/March), spring (May/June), summer (July/August), and fall (October). Years of near-, above- and below-average rainfall were represented in the 5 yr period. Minimum, maximum and median values, and central 95 percentiles were used as reference intervals and measures of central tendency for tortoises at each site and/or season. Data were analyzed using repeated measures analysis of variance for significant (P < 0.01) variation on the basis of sex, site, season, and interactions between these variables. Significant sex differences were observed for packed cell volume, hemoglobin concentration, aspartate transaminase activity, and cholesterol, triglyceride, calcium, and phosphorus concentrations. Marked seasonal variation was observed in most parameters in conjunction with reproductive cycle, hibernation, or seasonal rainfall. Year-to-year differences and long-term alterations primarily reflected winter rainfall amounts. Site differences were minimal, and largely reflected geographic differences in precipitation patterns, such that results from these studies can be applied to other tortoise populations in environments with known rainfall and forage availability patterns.

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.

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.

Understanding flood-induced water chemistry variability extracting temporal patterns with the LDA method

NASA Astrophysics Data System (ADS)

Aubert, A. H.; Tavenard, R.; Emonet, R.; De Lavenne, A.; Malinowski, S.; Guyet, T.; Quiniou, R.; Odobez, J.; Merot, P.; Gascuel-odoux, C.

2013-12-01

Studying floods has been a major issue in hydrological research for years, both in quantitative and qualitative hydrology. Stream chemistry is a mix of solutes, often used as tracers, as they originate from various sources in the catchment and reach the stream by various flow pathways. Previous studies (for instance (1)) hypothesized that stream chemistry reaction to a rainfall event is not unique but varies seasonally, and according to the yearly meteorological conditions. Identifying a typology of flood temporal chemical patterns is a way to better understand catchment processes at the flood and seasonal time scale. We applied a probabilistic model (Latent Dirichlet Allocation or LDA (2)) mining recurrent sequential patterns from a dataset of floods. A set of 472 floods was automatically extracted from a daily 12-year long record of nitrate, dissolved organic carbon, sulfate and chloride concentrations. Rainfall, discharge, water table depth and temperature are also considered. Data comes from a long-term hydrological observatory (AgrHys, western France) located at Kervidy-Naizin. From each flood, a document has been generated that is made of a set of "hydrological words". Each hydrological word corresponds to a measurement: it is a triplet made of the considered variable, the time at which the measurement is made (relative to the beginning of the flood), and its magnitude (that can be low, medium or high). The documents and the number of pattern to be mined are used as input data to the LDA algorithm. LDA relies on spotting co-occurrences (as an alternative to the more traditional study of correlation) between words that appear within the flood documents. It has two nice properties that are its ability to easily deal with missing data and its additive property that allows a document to be seen as a mixture of several flood patterns. The output of LDA is a set of patterns easily represented in graphics. These patterns correspond to typical reactions to rainfall events. The patterns themselves are carefully studied, as well as their repartition along the year and along the 12 years of the dataset. We would recommend the use of such model to any study based on patterns or signature extraction. It could be well suited to compare different geographical locations and analyzing the resulting different pattern distributions. (1) Aubert, A.H., Gascuel-Odoux, C., Gruau, G., Akkal, N., Faucheux, M., Fauvel, Y., Grimaldi, C., Hamon, Y., Jaffrezic, A., Lecoz Boutnik, M., Molenat, J., Petitjean, P., Ruiz, L., Merot, Ph. (2013), Solute transport dynamics in small, shallow groundwater-dominated agricultural catchments: insights from a high-frequency, multisolute 10 yr-long monitoring study. Hydrol. Earth Syst. Sci., 17(4): 1379-1391. (2) Aubert, A.H., Tavenard, R, Emonet, R., de Lavenne, A., Malinowski, S., Guyet, T., Quiniou, R., Odobez, J.-M., Merot, Ph., Gascuel-Odoux, C., submitted to WRR. Clustering with a probabilistic method newly applied in hydrology: application on flood events from water quality time-series.

Fire patterns in the Amazonian biome

NASA Astrophysics Data System (ADS)

Aragao, Luiz E. O. C.; Shimabukuro, Yosio E.; Lima, Andre; Anderson, Liana O.; Barbier, Nicolas; Saatchi, Sassan

2010-05-01

This paper aims to provide an overview of our recent findings on the interplay between climate and land use dynamics in defining fire patterns in Amazonia. Understanding these relationships is currently a fundamental concern for assessing the vulnerability of Amazonia to climate change and its potential for mitigating current increases in atmospheric greenhouse gases. Reducing carbon emissions from tropical deforestation and forest degradation (REDD), for instance, could contribute to a cumulative emission reduction of 13-50 billion tons of carbon (GtC) by 2100. In Amazonia, though, forest fires can release similar quantities of carbon to the atmosphere (~0.2 GtC yr-1) as deforestation alone. Therefore, to achieve carbon savings through REDD mechanism there is an urgent need of understanding and subsequently restraining related Amazonian fire drivers. In this study, we analyze satellite-derived monthly and annual time-series of fires, rainfall and deforestation in Amazonia to: (1) quantify the seasonal patterns and relationships between these variables; (2) quantify fire and rainfall anomalies to evaluate the impact of recent drought on fire patterns; (3) quantify recent trends in fire and deforestation to understand how land use affects fire patterns in Amazonia. Our results demonstrate a marked seasonality of fires. The majority of fires occurs along the Arc of Deforestation, the expanding agricultural frontier in southern and eastern Amazonia, indicating humans are the major ignition sources determining fire seasonality, spatial distribution and long-term patterns. There is a marked seasonality of fires, which is highly correlated (p<0.05) with monthly rainfall and deforestation rates. Deforestation and fires reach their highest values three and six months, respectively, after the peak of the rainy season. This result clearly describes the impact of major human activities on fire incidence, which is generally characterized by the slash-and-burn of Amazonian vegetation for implementation of pastures and agricultural fields. The cumulative number of hot pixels is exponentially related to the monthly rainfall, which ultimately defines where and when fire can potentially strike. During the 2005 Amazonian drought, the number of hot pixels increased 33% in relation to mean 1998-2005. However, even with a large fraction of the basin experiencing considerable water deficits, fires have only affect areas with extensive human activity. Our spatially explicit trend analysis on deforestation and fire data revealed that more than half of the area experiencing increased fire occurrence have reduced deforestation rates. This reverse pattern is likely to be associated with the slash-and-burn of secondary forests and the increase of fragmentation and forest edges, favouring the leakage of fires from deforested lands into forests. Finally, our analysis points towards a reduction of fire incidence due to land use intensification in this region. In this study, we demonstrated that anthropogenic forcing, such as deforestation rates, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region exacerbating human impacts in Amazonia. Due to ongoing deforestation and the predicted intensification of climate change induced droughts, it is anticipated that a large area of forest edge will be under increased risk of fires and carbon savings from REDD may be partially offset by increased emissions following fire events. Improved fire-free land management practices may provide a sustainable solution for reducing emissions from the world's largest rainforest. Acknowledges The first author would like to thank the financial support of the Natural Environment Research Council (NERC-UK/grant NE/F015356/1).

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-01-01

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

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).

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Understanding the Central Equatorial African long-term drought using AMIP-type simulations

NASA Astrophysics Data System (ADS)

Hua, Wenjian; Zhou, Liming; Chen, Haishan; Nicholson, Sharon E.; Jiang, Yan; Raghavendra, Ajay

2018-02-01

Previous studies show that Indo-Pacific sea surface temperature (SST) variations may help to explain the observed long-term drought during April-May-June (AMJ) since the 1990s over Central equatorial Africa (CEA). However, the underlying physical mechanisms for this drought are still not clear due to observation limitations. Here we use the AMIP-type simulations with 24 ensemble members forced by observed SSTs from the ECHAM4.5 model to explore the likely physical processes that determine the rainfall variations over CEA. We not only examine the ensemble mean (EM), but also compare the "good" and "poor" ensemble members to understand the intra-ensemble variability. In general, EM and the "good" ensemble member can simulate the drought and associated reduced vertical velocity and anomalous anti-cyclonic circulation in the lower troposphere. However, the "poor" ensemble members cannot simulate the drought and associated circulation patterns. These contrasts indicate that the drought is tightly associated with the tropical Walker circulation and atmospheric teleconnection patterns. If the observational circulation patterns cannot be reproduced, the CEA drought will not be captured. Despite the large intra-ensemble spread, the model simulations indicate an essential role of SST forcing in causing the drought. These results suggest that the long-term drought may result from tropical Indo-Pacific SST variations associated with the enhanced and westward extended tropical Walker circulation.

East Asian Summer Monsoon Rainfall: A Historical Perspective of the 1998 Flood over Yangtze River

NASA Technical Reports Server (NTRS)

Weng, H.-Y.; Lau, K.-M.

1999-01-01

One of the main factors that might have caused the disastrous flood in China during 1998 summer is long-term variations that include a trend indicating increasing monsoon rainfall over the Yangtze River Valley. China's 160-station monthly rainfall anomaly for the summers of 1955-98 is analyzed for exploring such long-term variations. Singular value decomposition (SVD) between the summer rainfall and the global sea surface temperature (SST) anomalies reveals that the rainfall over Yangtze River Valley is closely related to global and regional SST variabilities at both interannual and interdecadal timescales. SVD1 mode links the above normal rainfall condition in central China to an El Nino-like SSTA distribution, varying on interannual timescale modified by a trend during the period. SVD3 mode links positive rainfall anomaly in Yangtze River Valley to the warm SST anomaly in the subtropical western Pacific, varying on interannual timescales modified by interdecadal timescales. This link tends to be stronger when the Nino3 area becomes colder and the western subtropical Pacific becomes warmer. The 1998 summer is a transition season when the 1997/98 El Nino event was in its decaying phase, and the SST in the Nino3 area emerged below normal anomaly while the subtropical western Pacific SST above normal. Thus, the first and third SVD modes become dominant in 1998 summer, favoring more Asian summer monsoon rainfall over the Yangtze River Valley.

Climate change impact and potential adaptation strategies under alternate realizations of climate scenarios for three major crops in Europe

NASA Astrophysics Data System (ADS)

Donatelli, Marcello; Srivastava, Amit Kumar; Duveiller, Gregory; Niemeyer, Stefan; Fumagalli, Davide

2015-07-01

This study presents an estimate of the effects of climate variables and CO2 on three major crops, namely wheat, rapeseed and sunflower, in EU27 Member States. We also investigated some technical adaptation options which could offset climate change impacts. The time-slices 2000, 2020 and 2030 were chosen to represent the baseline and future climate, respectively. Furthermore, two realizations within the A1B emission scenario proposed by the Special Report on Emissions Scenarios (SRES), from the ECHAM5 and HadCM3 GCM, were selected. A time series of 30 years for each GCM and time slice were used as input weather data for simulation. The time series were generated with a stochastic weather generator trained over GCM-RCM time series (downscaled simulations from the ENSEMBLES project which were statistically bias-corrected prior to the use of the weather generator). GCM-RCM simulations differed primarily for rainfall patterns across Europe, whereas the temperature increase was similar in the time horizons considered. Simulations based on the model CropSyst v. 3 were used to estimate crop responses; CropSyst was re-implemented in the modelling framework BioMA. The results presented in this paper refer to abstraction of crop growth with respect to its production system, and consider growth as limited by weather and soil water. How crop growth responds to CO2 concentrations; pests, diseases, and nutrients limitations were not accounted for in simulations. The results show primarily that different realization of the emission scenario lead to noticeably different crop performance projections in the same time slice. Simple adaptation techniques such as changing sowing dates and the use of different varieties, the latter in terms of duration of the crop cycle, may be effective in alleviating the adverse effects of climate change in most areas, although response to best adaptation (within the techniques tested) differed across crops. Although a negative impact of climate scenarios is evident in most areas, the combination of rainfall patterns and increased photosynthesis efficiency due to CO2 concentrations showed possible improvements of production patterns in some areas, including Southern Europe. The uncertainty deriving from GCM realizations with respect to rainfall suggests that articulated and detailed testing of adaptation techniques would be redundant. Using ensemble simulations would allow for the identification of areas where adaptation, like those simulated, may be run autonomously by farmers, hence not requiring specific intervention in terms of support policies.

Early summer southern China rainfall variability and its oceanic drivers

NASA Astrophysics Data System (ADS)

Li, Weijing; Ren, Hong-Chang; Zuo, Jinqing; Ren, Hong-Li

2018-06-01

Rainfall in southern China reaches its annual peak in early summer (May-June) with strong interannual variability. Using a combination of observational analysis and numerical modeling, the present study investigates the leading modes of this variability and its dynamic drivers. A zonal dipole pattern termed the southern China Dipole (SCD) is found to be the dominant feature in early summer during 1979-2014, and is closely related to a low-level anomalous anticyclone over the Philippine Sea (PSAC) and a Eurasian wave-train pattern over the mid-high latitudes. Linear regressions based on observations and numerical experiments using the CAM5 model suggest that the associated atmospheric circulation anomalies in early summer are linked to decaying El Niño-Southern Oscillation-like sea surface temperature (SST) anomalies in the tropical Pacific, basin-scale SST anomalies in the tropical Indian Ocean, and meridional tripole-like SST anomalies in the North Atlantic in the previous winter to early summer. The tropical Pacific and Indian Ocean SST anomalies primarily exert an impact on the SCD through changing the polarity of the PSAC, while the North Atlantic tripole-like SST anomalies mainly exert a downstream impact on the SCD by inducing a Eurasian wave-train pattern. The North Atlantic tripole-like SST anomalies also make a relatively weak contribution to the variations of the PSAC and SCD through a subtropical teleconnection. Modeling results indicate that the three-basin combined forcing has a greater impact on the SCD and associated circulation anomalies than the individual influence from any single oceanic basin.

Winter Precipitation Forecast in the European and Mediterranean Regions Using Cluster Analysis

NASA Astrophysics Data System (ADS)

Totz, Sonja; Tziperman, Eli; Coumou, Dim; Pfeiffer, Karl; Cohen, Judah

2017-12-01

The European climate is changing under global warming, and especially the Mediterranean region has been identified as a hot spot for climate change with climate models projecting a reduction in winter rainfall and a very pronounced increase in summertime heat waves. These trends are already detectable over the historic period. Hence, it is beneficial to forecast seasonal droughts well in advance so that water managers and stakeholders can prepare to mitigate deleterious impacts. We developed a new cluster-based empirical forecast method to predict precipitation anomalies in winter. This algorithm considers not only the strength but also the pattern of the precursors. We compare our algorithm with dynamic forecast models and a canonical correlation analysis-based prediction method demonstrating that our prediction method performs better in terms of time and pattern correlation in the Mediterranean and European regions.

[Effect of precipitation and seasonal period on the patterns of commuting to school in children and adolescents from Granada].

PubMed

Segura-Díaz, José Manuel; Herrador-Colmenero, Manuel; Martínez-Téllez, Borja; Chillón Garzón, Palma

2014-12-17

Active commuting (walking or cycling) to school contributes to increase physical activity levels in young people. Meteorological conditions might have a remarkable influence on this behaviour. The aim is to study the impact of the rainfall and seasonality on the mode of commuting to primary school or secondary school in children and adolescents from Granada. A total of 384 students (166 children and 218 adolescents) between 8-18 years from 2 different schools (primary and secondary schools) of Granada took part in the research. Participants filled a questionnaire about their weekly pattern on the mode of commuting to school in the three seasons of the academic year. Data about the rainfall in those three weeks was obtained from the National Agency of Meteorology. The association between rainfall and seasonality with mode of commuting to school was studied by McNemar test. No significant associations were spotted between the rainfall and the seasonality with mode of commuting in children and adolescents (p>0.05) except for: a) a positive effect of rainfall in the percentage of children who usually walked to school between a rainy day and a non-rainy day in spring (p=0.031) and b) a weak effect of the seasonality on the percentage of children and adolescents who usually walk between autumn and winter (45.8% and 37.5% walk to school) and between autumn and spring (59.7% and 56%) respectively (p=0.07). The meteorological conditions do not seem to influence the mode of commuting to school in children and adolescents from Granada, which might indicate that this behavior keeps a constant pattern throughout the whole academic year. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Effects of season, rainfall, and hydrogeomorphic setting on mangrove tree growth in Micronesia

USGS Publications Warehouse

Krauss, K.W.; Keeland, B.D.; Allen, J.A.; Ewel, K.C.; Johnson, Daniel J.

2007-01-01

Seasonal patterns of tree growth are often related to rainfall, temperature, and relative moisture regimes. We asked whether diameter growth of mangrove trees in Micronesia, where seasonal changes are minimal, is continuous throughout a year or conforms to an annual cycle. We installed dendrometer bands on Sonneratia alba and Bruguiera gymnorrhiza trees growing naturally within mangrove swamps on the islands of Kosrae, Federated States of Micronesia (FSM), Pohnpei, FSM, and Butaritari, Republic of Kiribati, in the eastern Caroline Islands of the western Pacific Ocean. Trees were remeasured monthly or quarterly for as long as 6 yr. Annual mean individual tree basal area increments ranged from 7.0 to 79.6 cm2/yr for all S. alba trees and from 4.8 to 27.4 cm2/yr for all B. gymnorrhiza trees from Micronesian high islands. Diameter increment for S. alba on Butaritari Atoll was lower at 7.8 cm 2/yr for the one year measured. Growth rates differed significantly by hydrogeomorphic zone. Riverine and interior zones maintained up to seven times the annual diameter growth rate of fringe forests, though not on Pohnpei, where basal area increments for both S. alba and B. gymnorrhiza were approximately 1.5 times greater in the fringe zone than in the interior zone. Time-series modeling indicated that there were no consistent and statistically significant annual diameter growth patterns. Although rainfall has some seasonality in some years on Kosrae and Pohnpei and overall growth of mangroves was sometimes related positively to quarterly rainfall depths, seasonal diameter growth patterns were not distinctive. A reduced chance of moisture-related stress in high-rainfall, wetland environments may serve to buffer growth of Micronesian mangroves from climatic extremes. ?? 2007 The Author(s) Journal compilation ?? 2007 by The Association for Tropical Biology and Conservation.

El Niño and the shifting geography of cholera in Africa

PubMed Central

Moore, Sean M.; Azman, Andrew S.; Zaitchik, Benjamin F.; Mintz, Eric D.; Brunkard, Joan; Legros, Dominique; Hill, Alexandra; McKay, Heather; Luquero, Francisco J.; Olson, David; Lessler, Justin

2017-01-01

The El Niño Southern Oscillation (ENSO) and other climate patterns can have profound impacts on the occurrence of infectious diseases ranging from dengue to cholera. In Africa, El Niño conditions are associated with increased rainfall in East Africa and decreased rainfall in southern Africa, West Africa, and parts of the Sahel. Because of the key role of water supplies in cholera transmission, a relationship between El Niño events and cholera incidence is highly plausible, and previous research has shown a link between ENSO patterns and cholera in Bangladesh. However, there is little systematic evidence for this link in Africa. Using high-resolution mapping techniques, we find that the annual geographic distribution of cholera in Africa from 2000 to 2014 changes dramatically, with the burden shifting to continental East Africa—and away from Madagascar and portions of southern, Central, and West Africa—where almost 50,000 additional cases occur during El Niño years. Cholera incidence during El Niño years was higher in regions of East Africa with increased rainfall, but incidence was also higher in some areas with decreased rainfall, suggesting a complex relationship between rainfall and cholera incidence. Here, we show clear evidence for a shift in the distribution of cholera incidence throughout Africa in El Niño years, likely mediated by El Niño’s impact on local climatic factors. Knowledge of this relationship between cholera and climate patterns coupled with ENSO forecasting could be used to notify countries in Africa when they are likely to see a major shift in their cholera risk. PMID:28396423

Throughfall and its spatial variability beneath xerophytic shrub canopies within water-limited arid desert ecosystems

NASA Astrophysics Data System (ADS)

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

2016-08-01

Throughfall is known to be a critical component of the hydrological and biogeochemical cycles of forested ecosystems with inherently temporal and spatial variability. Yet little is understood concerning the throughfall variability of shrubs and the associated controlling factors in arid desert ecosystems. Here we systematically investigated the variability of throughfall of two morphological distinct xerophytic shrubs (Caragana korshinskii and Artemisia ordosica) within a re-vegetated arid desert ecosystem, and evaluated the effects of shrub structure and rainfall characteristics on throughfall based on heavily gauged throughfall measurements at the event scale. We found that morphological differences were not sufficient to generate significant difference (P < 0.05) in throughfall between two studied shrub species under the same rainfall and meteorological conditions in our study area, with a throughfall percentage of 69.7% for C. korshinskii and 64.3% for A. ordosica. We also observed a highly variable patchy pattern of throughfall beneath individual shrub canopies, but the spatial patterns appeared to be stable among rainfall events based on time stability analysis. Throughfall linearly increased with the increasing distance from the shrub base for both shrubs, and radial direction beneath shrub canopies had a pronounced impact on throughfall. Throughfall variability, expressed as the coefficient of variation (CV) of throughfall, tended to decline with the increase in rainfall amount, intensity and duration, and stabilized passing a certain threshold. Our findings highlight the great variability of throughfall beneath the canopies of xerophytic shrubs and the time stability of throughfall pattern among rainfall events. The spatially heterogeneous and temporally stable throughfall is expected to generate a dynamic patchy distribution of soil moisture beneath shrub canopies within arid desert ecosystems.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

SM2RAIN-CCI: a new global long-term rainfall data set derived from ESA CCI soil moisture

NASA Astrophysics Data System (ADS)

Ciabatta, Luca; Massari, Christian; Brocca, Luca; Gruber, Alexander; Reimer, Christoph; Hahn, Sebastian; Paulik, Christoph; Dorigo, Wouter; Kidd, Richard; Wagner, Wolfgang

2018-02-01

Accurate and long-term rainfall estimates are the main inputs for several applications, from crop modeling to climate analysis. In this study, we present a new rainfall data set (SM2RAIN-CCI) obtained from the inversion of the satellite soil moisture (SM) observations derived from the ESA Climate Change Initiative (CCI) via SM2RAIN (Brocca et al., 2014). Daily rainfall estimates are generated for an 18-year long period (1998-2015), with a spatial sampling of 0.25° on a global scale, and are based on the integration of the ACTIVE and the PASSIVE ESA CCI SM data sets.The quality of the SM2RAIN-CCI rainfall data set is evaluated by comparing it with two state-of-the-art rainfall satellite products, i.e. the Tropical Measurement Mission Multi-satellite Precipitation Analysis 3B42 real-time product (TMPA 3B42RT) and the Climate Prediction Center Morphing Technique (CMORPH), and one modeled data set (ERA-Interim). A quality check is carried out on a global scale at 1° of spatial sampling and 5 days of temporal sampling by comparing these products with the gauge-based Global Precipitation Climatology Centre Full Data Daily (GPCC-FDD) product. SM2RAIN-CCI shows relatively good results in terms of correlation coefficient (median value > 0.56), root mean square difference (RMSD, median value < 10.34 mm over 5 days) and bias (median value < -14.44 %) during the evaluation period. The validation has been carried out at original resolution (0.25°) over Europe, Australia and five other areas worldwide to test the capabilities of the data set to correctly identify rainfall events under different climate and precipitation regimes.The SM2RAIN-CCI rainfall data set is freely available at https://doi.org/10.5281/zenodo.846259.

Altering rainfall patterns through aerosol dispersion

NASA Astrophysics Data System (ADS)

Emetere, M. E.; Bakeko, M.; Onyechekwa, L.; Ayara, W.

2017-05-01

The possibility of recirculation mechanism on rainfall patterns is salient for sustenance of the human race through agricultural produce. The peculiarity of the lower atmosphere of south west region of Nigeria was explored using theoretical and experimental approach. In the theoretical approach, the reconstruction of 1D model as an extraction from the 3D aerosol dispersion model was used to examine the physics of the recirculation theory. The experimental approach which consists of obtaining dataset from ground instruments was used to provide on-site guide for developing the new recirculation theories. The data set was obtained from the Davis weather station, Nigeria Meteorological agency and Multi-angle Imaging Spectro-radiometer (MISR). We looked at the main drivers of recirculation and propounded that recirculation is a complex process which triggers a reordering of the mixing layer- a key factor for initiating the type of rainfall in this region.

Climate change effects on landslides in southern B.C.

NASA Astrophysics Data System (ADS)

Jakob, M.

2009-04-01

Two mechanisms that contribute to the temporal occurrence of landslides in coastal British Columbia are ante¬cedent rainfall and short-term intense rainfall. These two quantities can be extracted from the precipitation regimes simulated by climate models. This makes such models an attractive tool for use in the investigation of the effect of global warming on landslide fre¬quencies. In order to provide some measure of the reliability of models used to address the landslide question, the present-day simulation of the antecedent precipitation and short- term rainfall using the daily data from the Canadian Centre for Climate Modelling and Analysis model (CGCM) is compared to observations along the south coast of British Colum¬bia. This evaluation showed that the model was reasonably successful in simulating sta¬tistics of the antecedent rainfall but was less successful in simulating the short-term rainfall. The monthly mean precipitation data from an ensemble of 19 of the world's global climate models were available to study potential changes in landslide frequencies with global warming. Most of the models were used to produce simulations with three scenar¬ios with different levels of prescribed greenhouse gas concentrations during the twenty-first century. The changes in the antecedent precipitation were computed from the resulting monthly and seasonal means. In order to deal with models' suspected difficulties in sim¬ulating the short-term precipitation and lack of daily data, a statistical procedure was used to relate the short-term precipitation to the monthly means. The qualitative model results agree reasonably well, and when averaged over all models and the three scenarios, the change in the antecedent precipitation is predicted to be about 10% and the change in the short-term precipitation about 6%. Because the antecedent precipitation and the short-term precipitation contribute to the occurrence of landslides, the results of this study support the prediction of increased landslide frequency along the British Columbia south coast during the twenty-first century.

Component Analysis of Errors on PERSIANN Precipitation Estimates over Urmia Lake Basin, IRAN

NASA Astrophysics Data System (ADS)

Ghajarnia, N.; Daneshkar Arasteh, P.; Liaghat, A. M.; Araghinejad, S.

2016-12-01

In this study, PERSIANN daily dataset is evaluated from 2000 to 2011 in 69 pixels over Urmia Lake basin in northwest of Iran. Different analytical approaches and indexes are used to examine PERSIANN precision in detection and estimation of rainfall rate. The residuals are decomposed into Hit, Miss and FA estimation biases while continues decomposition of systematic and random error components are also analyzed seasonally and categorically. New interpretation of estimation accuracy named "reliability on PERSIANN estimations" is introduced while the changing manners of existing categorical/statistical measures and error components are also seasonally analyzed over different rainfall rate categories. This study yields new insights into the nature of PERSIANN errors over Urmia lake basin as a semi-arid region in the middle-east, including the followings: - The analyzed contingency table indexes indicate better detection precision during spring and fall. - A relatively constant level of error is generally observed among different categories. The range of precipitation estimates at different rainfall rate categories is nearly invariant as a sign for the existence of systematic error. - Low level of reliability is observed on PERSIANN estimations at different categories which are mostly associated with high level of FA error. However, it is observed that as the rate of precipitation increase, the ability and precision of PERSIANN in rainfall detection also increases. - The systematic and random error decomposition in this area shows that PERSIANN has more difficulty in modeling the system and pattern of rainfall rather than to have bias due to rainfall uncertainties. The level of systematic error also considerably increases in heavier rainfalls. It is also important to note that PERSIANN error characteristics at each season varies due to the condition and rainfall patterns of that season which shows the necessity of seasonally different approach for the calibration of this product. Overall, we believe that different error component's analysis performed in this study, can substantially help any further local studies for post-calibration and bias reduction of PERSIANN estimations.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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.

Entropy of stable seasonal rainfall distribution in Kelantan

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Soil microbial and nutrient responses to 7 years of seasonally altered precipitation in a Chihuahuan Desert grassland.

PubMed

Bell, Colin W; Tissue, David T; Loik, Michael E; Wallenstein, Matthew D; Acosta-Martinez, Veronica; Erickson, Richard A; Zak, John C

2014-05-01

Soil microbial communities in Chihuahuan Desert grasslands generally experience highly variable spatiotemporal rainfall patterns. Changes in precipitation regimes can affect belowground ecosystem processes such as decomposition and nutrient cycling by altering soil microbial community structure and function. The objective of this study was to determine if increased seasonal precipitation frequency and magnitude over a 7-year period would generate a persistent shift in microbial community characteristics and soil nutrient availability. We supplemented natural rainfall with large events (one/winter and three/summer) to simulate increased precipitation based on climate model predictions for this region. We observed a 2-year delay in microbial responses to supplemental precipitation treatments. In years 3-5, higher microbial biomass, arbuscular mycorrhizae abundance, and soil enzyme C and P acquisition activities were observed in the supplemental water plots even during extended drought periods. In years 5-7, available soil P was consistently lower in the watered plots compared to control plots. Shifts in soil P corresponded to higher fungal abundances, microbial C utilization activity, and soil pH. This study demonstrated that 25% shifts in seasonal rainfall can significantly influence soil microbial and nutrient properties, which in turn may have long-term effects on nutrient cycling and plant P uptake in this desert grassland. © 2013 John Wiley & Sons Ltd.

Descriptive Statistics and Cluster Analysis for Extreme Rainfall in Java Island

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

PubMed Central

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

2017-01-01

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

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

PubMed Central

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

2013-01-01

The Congo Basin is one of three key convective regions on the planet which, during the transition seasons, dominates global tropical rainfall. There is little agreement as to the distribution and quantity of rainfall across the basin with datasets differing by an order of magnitude in some seasons. The location of maximum rainfall is in the far eastern sector of the basin in some datasets but the far western edge of the basin in others during March to May. There is no consistent pattern to this rainfall distribution in satellite or model datasets. Resolving these differences is difficult without ground-based data. Moisture flux nevertheless emerges as a useful variable with which to study these differences. Climate models with weak (strong) or even divergent moisture flux over the basin are dry (wet). The paper suggests an approach, via a targeted field campaign, for generating useful climate information with which to confront rainfall products and climate models. PMID:23878328

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.

Hotter and drier conditions in the near future (2010-2035) might paradoxically improve the general adaptive capacity of a viticultural social-ecological system in Roussillon, southern France, exposed to long-term climatic and economic changes

NASA Astrophysics Data System (ADS)

Lereboullet, Anne-Laure; Beltrando, Gérard

2014-05-01

Background: Wine production in Roussillon, southern France, has been subjected to deep structural changes in cultural practices since the 1970's, due to changes in demand and market organization. In this Mediterranean region, temperature and rainfall parameters have long been adapted to fortified wine production, but might be less suited to dry wine production, which is nowadays prevailing. The wine industry in Roussillon can be studied as a social-ecological system where local economical and social characteristics are strongly linked to physical inputs. Thus changes in climate, especially warming and drying trends that have been detected and projected by the IPCC in the Mediterranean basin, may disrupt the local economy and social organization in the long term. The aim of our study is to assess the role played by recent (1956-2010) and near-future (2010-2035) changes in temperature and rainfall inputs in the evolution of the system's adaptive capacity to combined long term climatic and economic changes. Methods: Our study combined quantitative and qualitative data. We first assessed recent exposure to climate change by analysing change in daily data of temperature and rainfall observed in Perpignan weather station from 1956 to 2010. Thirty-nine in-depth interviews with local producers and key stakeholders of the local wine industry helped us understand the impacts of recent climatic conditions in the system's adaptive capacity. Then, we measured future changes in temperature and rainfall based on daily data simulated by ARPEGE-Climat (SCRATCH10 dataset) at an 8-km spatial scale, for emission scenarios A2, A1B and B1, up to 2060. Based on the impacts of recent changes in the system, we inferred the possible impacts of future climate change on the system's equilibrium. Results and discussion: Climate data analyses show that changes in temperatures and rainfall patterns have occurred in Perpignan since the mid-1980's, and that current (2001-2010) conditions are likely to remain the same until the 2040's, then followed by a second step of warming and drying trend. During the last ten years, local farmers have been experiencing difficulties to combine challenges from an increasing competition in markets and from hotter and drier conditions. Helped by public subsidies, almost one-third of the vineyard was pulled out during that period. Up until the 2040's, with similar conditions, the local viticultural system should continue its transformation, favouring dynamic, proactive and enterprising farmers. Thus the composition of the farming community might change gradually, and count in the 2040's a majority of producers with a higher individual adaptive capacity than now. The timing and intensity of near-future climate change as measured by the climate model, combined to regional economic change, might thus be an asset to prepare and facilitate adaptation in the longer term.

Use of soil moisture dynamics and patterns for the investigation of runoff generation processes with emphasis on preferential flow

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2007-08-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2009-07-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

[Responses of plant community structure and species composition to warming and N addition in an alpine meadow, northern Tibetan Plateau, China].

PubMed

Zong, Ning; Chai, Xi; Shi, Pei Li; Jiang, Jing; Niu, Ben; Zhang, Xian Zhou; He, Yong Tao

2016-12-01

Global climate warming and increasing nitrogen (N) deposition, as controversial global environmental issues, may distinctly affect the functions and processes of terrestrial ecosystems. It has been reported that the Qinghai-Tibet Plateau has been experiencing significant warming in recent decades, especially in winter. Previous studies have mainly focused on the effects of warming all the year round; however, few studies have tested the effects of winter warming. To investigate the effects of winter warming and N addition on plant community structure and species composition of alpine meadow, long-term N addition and simulated warming experiment was conducted in alpine meadow from 2010 in Damxung, northern Tibet. The experiment consisted of three warming patterns: Year-round warming (YW), winter warming (WW) and control (NW), crossed respectively with five N gradients: 0, 10, 20, 40, 80 kg N·hm -2 ·a -1 . From 2012 to 2014, both warming and N addition significantly affected the total coverage of plant community. Specifically, YW significantly decreased the total coverage of plant community. Without N addition, WW remarkably reduced the vegetation coverage. However, with N addition, the total vegetation coverage gradually increased with the increase of N level. Warming and N addition had different effects on plants from different functional groups. Warming significantly reduced the plant coverage of grasses and sedges, while N addition significantly enhanced the plant coverage of grasses. Regression analyses showed that the total coverage of plant community was positively related to soil water content in vigorous growth stages, indicating that the decrease in soil water content resulted from warming during dry seasons might be the main reason for the decline of total community coverage. As soil moisture in semi-arid alpine meadow is mainly regulated by rainfalls, our results indicated that changes in spatial and temporal patterns of rainfalls under the future climate change scenarios would dramatically influence the vegetation coverage and species composition. Additionally, the effects of increasing atmospheric N deposition on vegetation community might also depend on the change of rainfall patterns.

Spatial-temporal variability of soil moisture and its estimation across scales

NASA Astrophysics Data System (ADS)

Brocca, L.; Melone, F.; Moramarco, T.; Morbidelli, R.

2010-02-01

The soil moisture is a quantity of paramount importance in the study of hydrologic phenomena and soil-atmosphere interaction. Because of its high spatial and temporal variability, the soil moisture monitoring scheme was investigated here both for soil moisture retrieval by remote sensing and in view of the use of soil moisture data in rainfall-runoff modeling. To this end, by using a portable Time Domain Reflectometer, a sequence of 35 measurement days were carried out within a single year in seven fields located inside the Vallaccia catchment, central Italy, with area of 60 km2. Every sampling day, soil moisture measurements were collected at each field over a regular grid with an extension of 2000 m2. The optimization of the monitoring scheme, with the aim of an accurate mean soil moisture estimation at the field and catchment scale, was addressed by the statistical and the temporal stability. At the field scale, the number of required samples (NRS) to estimate the field-mean soil moisture within an accuracy of 2%, necessary for the validation of remotely sensed soil moisture, ranged between 4 and 15 for almost dry conditions (the worst case); at the catchment scale, this number increased to nearly 40 and it refers to almost wet conditions. On the other hand, to estimate the mean soil moisture temporal pattern, useful for rainfall-runoff modeling, the NRS was found to be lower. In fact, at the catchment scale only 10 measurements collected in the most "representative" field, previously determined through the temporal stability analysis, can reproduce the catchment-mean soil moisture with a determination coefficient, R2, higher than 0.96 and a root-mean-square error, RMSE, equal to 2.38%. For the "nonrepresentative" fields the accuracy in terms of RMSE decreased, but similar R2 coefficients were found. This insight can be exploited for the sampling in a generic field when it is sufficient to know an index of soil moisture temporal pattern to be incorporated in conceptual rainfall-runoff models. The obtained results can address the soil moisture monitoring network design from which a reliable soil moisture temporal pattern at the catchment scale can be derived.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Blow me down: A new perspective on Aloe dichotoma mortality from windthrow

PubMed Central

2014-01-01

Background Windthrow, the uprooting of trees during storms associated with strong winds, is a well-established cause of mortality in temperate regions of the world, often with large ecological consequences. However, this phenomenon has received little attention within arid regions and is not well documented in southern Africa. Slow rates of post-disturbance recovery and projected increases in extreme weather events in arid areas mean that windthrow could be more common and have bigger impacts on these ecosystems in the future. This is of concern due to slow rates of post-disturbance recovery in arid systems and projected increases in extreme weather events in these areas. This study investigated the spatial pattern, magnitude and likely causes of windthrown mortality in relation to other forms of mortality in Aloe dichotoma, an iconic arid-adapted arborescent succulent and southern Africa climate change indicator species. Results We found that windthrown mortality was greatest within the equatorward summer rainfall zone (SRZ) of its distribution (mean = 31%, n = 11), and was derived almost exclusively from the larger adult age class. A logistic modelling exercise indicated that windthrown mortality was strongly associated with greater amounts of warm season (summer) rainfall in the SRZ, higher wind speeds, and leptosols. A statistically significant interaction term between higher summer rainfall and wind speeds further increased the odds of being windthrown. While these results would benefit from improvements in the resolution of wind and substrate data, they do support the hypothesised mechanism for windthrow in A. dichotoma. This involves powerful storm gusts associated with either the current or subsequent rainfall event, heavy convective rainfall, and an associated increase in soil malleability. Shallow rooting depths in gravel-rich soils and an inflexible, top-heavy canopy structure make individuals especially prone to windthrown mortality during storms. Conclusions Results highlight the importance of this previously unrecognised form of mortality in A. dichotoma, especially since it seems to disproportionately affect reproductively mature adult individuals in an infrequently recruiting species. Smaller, more geographically isolated and adult dominated populations in the summer rainfall zone are likely to be more vulnerable to localised extinction due to windthrow events. PMID:24641794

Blow me down: a new perspective on Aloe dichotoma mortality from windthrow.

PubMed

Jack, Samuel Linton; Hoffman, Michael Timm; Rohde, Rick Frederick; Durbach, Ian; Archibald, Margaret

2014-03-18

Windthrow, the uprooting of trees during storms associated with strong winds, is a well-established cause of mortality in temperate regions of the world, often with large ecological consequences. However, this phenomenon has received little attention within arid regions and is not well documented in southern Africa. Slow rates of post-disturbance recovery and projected increases in extreme weather events in arid areas mean that windthrow could be more common and have bigger impacts on these ecosystems in the future. This is of concern due to slow rates of post-disturbance recovery in arid systems and projected increases in extreme weather events in these areas. This study investigated the spatial pattern, magnitude and likely causes of windthrown mortality in relation to other forms of mortality in Aloe dichotoma, an iconic arid-adapted arborescent succulent and southern Africa climate change indicator species. We found that windthrown mortality was greatest within the equatorward summer rainfall zone (SRZ) of its distribution (mean = 31%, n = 11), and was derived almost exclusively from the larger adult age class. A logistic modelling exercise indicated that windthrown mortality was strongly associated with greater amounts of warm season (summer) rainfall in the SRZ, higher wind speeds, and leptosols. A statistically significant interaction term between higher summer rainfall and wind speeds further increased the odds of being windthrown. While these results would benefit from improvements in the resolution of wind and substrate data, they do support the hypothesised mechanism for windthrow in A. dichotoma. This involves powerful storm gusts associated with either the current or subsequent rainfall event, heavy convective rainfall, and an associated increase in soil malleability. Shallow rooting depths in gravel-rich soils and an inflexible, top-heavy canopy structure make individuals especially prone to windthrown mortality during storms. Results highlight the importance of this previously unrecognised form of mortality in A. dichotoma, especially since it seems to disproportionately affect reproductively mature adult individuals in an infrequently recruiting species. Smaller, more geographically isolated and adult dominated populations in the summer rainfall zone are likely to be more vulnerable to localised extinction due to windthrow events.

Assessment of satellite rainfall products over the Andean plateau

NASA Astrophysics Data System (ADS)

Satgé, Frédéric; Bonnet, Marie-Paule; Gosset, Marielle; Molina, Jorge; Hernan Yuque Lima, Wilson; Pillco Zolá, Ramiro; Timouk, Franck; Garnier, Jérémie

2016-01-01

Nine satellite rainfall estimations (SREs) were evaluated for the first time over the South American Andean plateau watershed by comparison with rain gauge data acquired between 2005 and 2007. The comparisons were carried out at the annual, monthly and daily time steps. All SREs reproduce the salient pattern of the annual rain field, with a marked north-south gradient and a lighter east-west gradient. However, the intensity of the gradient differs among SREs: it is well marked in the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42 (TMPA-3B42), Precipitation Estimation from remotely Sensed Information using Artificial Neural Networks (PERSIANN) and Global Satellite Mapping of Precipitation (GSMaP) products, and it is smoothed out in the Climate prediction center MORPHing (CMORPH) products. Another interesting difference among products is the contrast in rainfall amounts between the water surfaces (Lake Titicaca) and the surrounding land. Some products (TMPA-3B42, PERSIANN and GSMaP) show a contradictory rainfall deficit over Lake Titicaca, which may be due to the emissivity contrast between the lake and the surrounding lands and warm rain cloud processes. An analysis differentiating coastal Lake Titicaca from inland pixels confirmed this trend. The raw or Real Time (RT) products have strong biases over the study region. These biases are strongly positive for PERSIANN (above 90%), moderately positive for TMPA-3B42 (28%), strongly negative for CMORPH (- 42%) and moderately negative for GSMaP (- 18%). The biases are associated with a deformation of the rain rate frequency distribution: GSMaP underestimates the proportion of rainfall events for all rain rates; CMORPH overestimates the proportion of rain rates below 2 mm day- 1; and the other products tend to overestimate the proportion of moderate to high rain rates. These biases are greatly reduced by the gauge adjustment in the TMPA-3B42, PERSIANN and CMORPH products, whereas a negative bias becomes positive for GSMaP. TMPA-3B42 Adjusted (Adj) version 7 demonstrates the best overall agreement with gauges in terms of correlation, rain rate distribution and bias. However, PERSIANN-Adj's bias in the southern part of the domain is very low.

Recent variations in geopotential height associated with West African monsoon variability

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Assessment of hydrochemical processes and groundwater hydrodynamics in a multilayer aquifer system under long-term irrigation condition: A case study of Nefzaoua basin, southern Tunisia.

PubMed

Tarki, M; Ben Hammadi, M; El Mejri, H; Dassi, L

2016-04-01

The hydrochemical and isotopic investigation of the Nefzaoua aquifer system demonstrates that groundwater mineralization in is controlled by natural and anthropogenic processes including water-rock interaction and irrigation return flow. It identifies all of the water bodies that flow within the aquifer system and their circulation patterns. The isotopically depleted paleowaters, identified within the deep and intermediate aquifers, undergo significant enrichment by evaporation during irrigation and recharged the shallow aquifer by return flow. Subsequently, they infiltrate to the intermediate aquifer which receives also rainfall modern recharge. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Effects of shifting seasonal rainfall patterns on net primary productivity and carbon storage in tropical seasonally dry ecosystems

NASA Astrophysics Data System (ADS)

Rohr, T.; Manzoni, S.; Feng, X.; Menezes, R.; Porporato, A. M.

2013-12-01

Although seasonally dry ecosystems (SDEs), identified by prolonged drought followed by a short, but intense, rainy season, cover large regions of the tropics, their biogeochemical response to seasonal rainfall and soil carbon (C) sequestration potential are not well characterized. Both productivity and soil respiration are positively affected by seasonal soil moisture availability, creating a delicate balance between C deposition through litterfall and C losses through heterotrophic respiration. As climate change projections for the tropics predict decreased annual rainfall and increased dry season length, it is critical to understand how variations in seasonal rainfall distributions control this balance. To address this question, we develop a minimal model linking the seasonal behavior of the ensemble soil moisture, plant productivity, the related soil C inputs through litterfall, and soil C dynamics. The model is parameterized for a case study from a drought-deciduous caatinga ecosystem in northeastern Brazil. Results indicate that when altering the seasonal rainfall patterns for a fixed annual rainfall, both plant productivity and soil C sequestration potential are largely, and nonlinearly, dependent on wet season duration. Moreover, total annual rainfall plays a dominant role in describing this relationship, leading at times to the emergence of distinct optima in both primary production and C sequestration. Examining these results in the context of climate-driven changes to wet season duration and mean annual precipitation indicate that the initial hydroclimatic regime of a particular ecosystem is an important factor to predict both the magnitude and direction of the effects of shifting seasonal distributions on productivity and C storage. Although highly productive ecosystems will likely experience declining C storage with predicted climate shifts, those currently operating well below peak production can potentially see improved C stocks with the onset of declining rainfall due to reduced soil respiration. a) Annual average net primary productivity and b) the temporally averaged ensemble soil carbon concentration <(C_yr )> are plotted against the length of the wet season T_W, for six annual rainfall rates (m yr-1).

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.

Global Precipitation Patterns Associated with ENSO and Tropical Circulations

NASA Technical Reports Server (NTRS)

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

1999-01-01

Tropical precipitation and the accompanying latent heat release is the engine that drives the global circulation. An increase or decrease in rainfall in the tropics not only leads to the local effects of flooding or drought, but contributes to changes in the large scale circulation and global climate system. Rainfall in the tropics is highly variable, both seasonally (monsoons) and interannually (ENSO). Two experimental observational data sets, developed under the auspices of the Global Precipitation Climatology Project (GPCP), are used in this study to examine the relationships between global precipitation and ENSO and extreme monsoon events over the past 20 years. The V2x79 monthly product is a globally complete, 2.5 deg x 2.5 deg, satellite-gauge merged data set that covers the period 1979 to the present. Indices based on patterns of satellite-derived rainfall anomalies in the Pacific are used to analyze the teleconnections between ENSO and global precipitation, with emphasis on the monsoon systems. It has been well documented that dry (wet) Asian monsoons accompany warm (cold) ENSO events. However, during the summer seasons of the 1997/98 ENSO the precipitation anomalies were mostly positive over India and the Bay of Bengal, which may be related to an epoch-scale variability in the Asian monsoon circulation. The North American monsoon may be less well linked to ENSO, but a positive precipitation anomaly was observed over Mexico around the September following the 1997/98 event. For the twenty-year record, precipitation and SST patterns in the tropics are analyzed during wet and dry monsoons. For the Asian summer monsoon, positive rainfall anomalies accompany two distinct patterns of tropical precipitation and a warm Indian Ocean. Negative anomalies coincide with a wet Maritime Continent.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Long term changes in flooding and heavy rainfall associated with North Atlantic tropical cyclones: Roles of the North Atlantic Oscillation and El Niño-Southern Oscillation

NASA Astrophysics Data System (ADS)

Aryal, Yog N.; Villarini, Gabriele; Zhang, Wei; Vecchi, Gabriel A.

2018-04-01

The aim of this study is to examine the contribution of North Atlantic tropical cyclones (TCs) to flooding and heavy rainfall across the continental United States. Analyses highlight the spatial variability in these hazards, their temporal changes in terms of frequency and magnitude, and their connection to large-scale climate, in particular to the North Atlantic Oscillation (NAO) and El Niño-Southern Oscillation (ENSO). We use long-term stream and rain gage measurements, and our analyses are based on annual maxima (AMs) and peaks-over-threshold (POTs). TCs contribute to ∼20-30% of AMs and POTs over Florida and coastal areas of the eastern United States, and the contribution decreases as we move inland. We do not detect statistically significant trends in the magnitude or frequency of TC floods. Regarding the role of climate, NAO and ENSO do not play a large role in controlling the frequency and magnitude of TC flooding. The connection between heavy rainfall and TCs is comparable to what observed in terms of flooding. Unlike flooding, NAO plays a significant role in TC-related extreme rainfall along the U.S. East Coast, while ENSO is most strongly linked to the TC precipitation in Texas.

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

NASA Technical Reports Server (NTRS)

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

2006-01-01

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

Evaluation of High-Resolution Precipitation Estimates from Satellites during July 2012 Beijing Flood Event Using Dense Rain Gauge Observations

PubMed Central

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing. PMID:24691358

Evaluation of high-resolution precipitation estimates from satellites during July 2012 Beijing flood event using dense rain gauge observations.

PubMed

Chen, Sheng; Liu, Huijuan; You, Yalei; Mullens, Esther; Hu, Junjun; Yuan, Ye; Huang, Mengyu; He, Li; Luo, Yongming; Zeng, Xingji; Tang, Guoqiang; Hong, Yang

2014-01-01

Satellite-based precipitation estimates products, CMORPH and PERSIANN-CCS, were evaluated with a dense rain gauge network over Beijing and adjacent regions for an extremely heavy precipitation event on July 21 2012. CMORPH and PEERSIANN-CSS misplaced the region of greatest rainfall accumulation, and failed to capture the spatial pattern of precipitation, evidenced by a low spatial correlation coefficient (CC). CMORPH overestimated the daily accumulated rainfall by 22.84% while PERSIANN-CCS underestimated by 72.75%. In the rainfall center, both CMORPH and PERSIANN-CCS failed to capture the temporal variation of the rainfall, and underestimated rainfall amounts by 43.43% and 87.26%, respectively. Based on our results, caution should be exercised when using CMORPH and PERSIANN-CCS as input for monitoring and forecasting floods in Beijing urban areas, and the potential for landslides in the mountainous zones west and north of Beijing.

Carbaryl washoff from soybean plants.

PubMed

Willis, G H; Smith, S; McDowell, L L; Southwick, L M

1996-08-01

Both the efficacy and fate of most foliar-applied pesticides may be affected by weather variables, especially rain. A multiple-intensity rainfall simulator was used to determine the effects of rainfall intensity and amount on concentrations of carbaryl (Sevin(R) XLS Plus) washed from soybean plants. Two hours after carbaryl was applied at 1.12 kg/ha, 25 mm of rain was applied at intensities of 13.0, 27.4, 53.8, or 105.1 mm/h. About 67% of the carbaryl on the plants was washed off by 25 mm of rain. Rainfall intensity affected carbaryl concentrations in washoff; higher concentrations occurred at lower intensities. Even though the experimental conditions were designed for "worst-case" conditions, washoff patterns suggested improved carbaryl rainfastness when compared to carbaryl (formulated as a wettable powder) washoff from cotton plants in earlier studies. Rainfall amount had a greater effect on carbaryl concentrations in washoff than rainfall intensity.

Review and meta-analysis of trends in precipitation regime in Italy

NASA Astrophysics Data System (ADS)

Caporali, Enrica; Chiarello, Valentina; Defina, Ilaria; Fatichi, Simone

2017-04-01

Research to detect changes in climatic variables has become a topic of particular interest to observe signals of climate change as well as to understand drivers of modifications in water resources availability and suggest management adaptations. We specifically focus on Italy, outlining the "state of the art" of the Italian precipitation regime through a review of 46 published studies on rainfall trend analyses. The aim is to combine a large body of knowledge in a single review and to explain the main patterns of rainfall changes occurred in the last decades. The review results are analyzed for the entire Italian peninsula and separately for three macro areas: North, Central and South&Islands. The attention is focused on three indexes at the annual and seasonal scale: mean Total Precipitation (TP), number of Wet Days (WDs) and Precipitation Intensity (PI). Two other aspects are briefly investigated: drought and extreme rainfall events. Different geographic areas, time series length and number of stations, are taken into account using a "weight factor Fi". Subsequently, for each index, findings in terms of increasing or decreasing trends are collected into five principal categories: Negative (N), Negative Significant (NS), Positive (P), Positive Significant (PS), and No Trend (NT). Overall, there is an agreement about the tendency of the WDs that are decreasing on the whole Italy, with some discrepancies regarding the spring and the summer seasons. This is substantially in agreement with the tendency of the TP, especially at annual scale where the presence of a decreasing trend is detected. An opposite behavior is detected for PI, which increases both on an annual and on a seasonal basis. It is worth to point out that PI is analyzed just in few studies and it is strongly influenced on the classification in precipitation intensity intervals. A general finding is that signal to noise ratio on precipitation metrics is quite low, which hampers a clear definition of changes in rainfall occurred in Italy, especially for extreme events the large variability in space and time precludes robust conclusions despite the long-term records available.

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.

Testing the reliability of δ13C of tree rings as climate tool in Pistacia khinjuk of Syrian desert

NASA Astrophysics Data System (ADS)

Caracuta, Valentina; Fiorentino, Girolamo

2010-05-01

High-resolution measures of past climate variations have been found to be of a critical importance for understanding anthropic resilience in drought-sensitive areas. The hills (Jebels) Abu-Rujmain and Abd al Aziz, with their 350 millimetre of rain and their steppe-forest spreading in the middle of the flat syrian desert, represent an unicum where analysing the effect of short term climate changes on pastoral communities. Thanks to a cooperation project in Syrian Arab republic with CIHEAM-Mediterranean Agronomic Institute of Bari -Italy (Rationalization of Ras El Ain Irrigation systems), we were allowed to carry out dendroclimate and carbon isotope analyses on tree-rings of local Pistacia khinjuk, a long-lived wood taxon, in order to test their reliability as tool for determining annual and seasonal rainfall/temperature variations. Comparison between the last 25 year rainfall and temperature values of the nearby meteorological stations and dendro-isotopes values have been carried out to point out which factor mostly affect the growth pattern of the trees in that particular area.

Weakening of Indian Summer Monsoon Rainfall due to Changes in Land Use Land Cover

PubMed Central

Paul, Supantha; Ghosh, Subimal; Oglesby, Robert; Pathak, Amey; Chandrasekharan, Anita; Ramsankaran, RAAJ

2016-01-01

Weakening of Indian summer monsoon rainfall (ISMR) is traditionally linked with large-scale perturbations and circulations. However, the impacts of local changes in land use and land cover (LULC) on ISMR have yet to be explored. Here, we analyzed this topic using the regional Weather Research and Forecasting model with European Center for Medium range Weather Forecast (ECMWF) reanalysis data for the years 2000–2010 as a boundary condition and with LULC data from 1987 and 2005. The differences in LULC between 1987 and 2005 showed deforestation with conversion of forest land to crop land, though the magnitude of such conversion is uncertain because of the coarse resolution of satellite images and use of differential sources and methods for data extraction. We performed a sensitivity analysis to understand the impacts of large-scale deforestation in India on monsoon precipitation and found such impacts are similar to the observed changes in terms of spatial patterns and magnitude. We found that deforestation results in weakening of the ISMR because of the decrease in evapotranspiration and subsequent decrease in the recycled component of precipitation. PMID:27553384

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.

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.

Temperature and rainfall interact to control carbon cycling in tropical forests.

PubMed

Taylor, Philip G; Cleveland, Cory C; Wieder, William R; Sullivan, Benjamin W; Doughty, Christopher E; Dobrowski, Solomon Z; Townsend, Alan R

2017-06-01

Tropical forests dominate global terrestrial carbon (C) exchange, and recent droughts in the Amazon Basin have contributed to short-term declines in terrestrial carbon dioxide uptake and storage. However, the effects of longer-term climate variability on tropical forest carbon dynamics are still not well understood. We synthesised field data from more than 150 tropical forest sites to explore how climate regulates tropical forest aboveground net primary productivity (ANPP) and organic matter decomposition, and combined those data with two existing databases to explore climate - C relationships globally. While previous analyses have focused on the effects of either temperature or rainfall on ANPP, our results highlight the importance of interactions between temperature and rainfall on the C cycle. In cool forests (< 20 °C), high rainfall slowed rates of C cycling, but in warm tropical forests (> 20 °C) it consistently enhanced both ANPP and decomposition. At the global scale, our analysis showed an increase in ANPP with rainfall in relatively warm sites, inconsistent with declines in ANPP with rainfall reported previously. Overall, our results alter our understanding of climate - C cycle relationships, with high precipitation accelerating rates of C exchange with the atmosphere in the most productive biome on earth. © 2017 John Wiley & Sons Ltd/CNRS.

Establishing a method of short-term rainfall forecasting based on GNSS-derived PWV and its application.

PubMed

Yao, Yibin; Shan, Lulu; Zhao, Qingzhi

2017-09-29

Global Navigation Satellite System (GNSS) can effectively retrieve precipitable water vapor (PWV) with high precision and high-temporal resolution. GNSS-derived PWV can be used to reflect water vapor variation in the process of strong convection weather. By studying the relationship between time-varying PWV and rainfall, it can be found that PWV contents increase sharply before raining. Therefore, a short-term rainfall forecasting method is proposed based on GNSS-derived PWV. Then the method is validated using hourly GNSS-PWV data from Zhejiang Continuously Operating Reference Station (CORS) network of the period 1 September 2014 to 31 August 2015 and its corresponding hourly rainfall information. The results show that the forecasted correct rate can reach about 80%, while the false alarm rate is about 66%. Compared with results of the previous studies, the correct rate is improved by about 7%, and the false alarm rate is comparable. The method is also applied to other three actual rainfall events of different regions, different durations, and different types. The results show that the method has good applicability and high accuracy, which can be used for rainfall forecasting, and in the future study, it can be assimilated with traditional weather forecasting techniques to improve the forecasted accuracy.

Effect of DEM resolution on rainfall-triggered landslide modeling within a triangulated network-based model. A case study in the Luquillo Forest, Puerto Rico

NASA Astrophysics Data System (ADS)

Arnone, E.; Dialynas, Y. G.; Noto, L. V.; Bras, R. L.

2013-12-01

Catchment slope distribution is one of the topographic characteristics that significantly control rainfall-triggered landslide modeling, in both direct and indirect ways. Slope directly determines the soil volume associated with instability. Indirectly slope also affects the subsurface lateral redistribution of soil moisture across the basin, which in turn determines the water pore pressure conditions that impact slope stability. In this study, we investigate the influence of DEM resolution on slope stability and the slope stability analysis by using a distributed eco-hydrological and landslide model, the tRIBS-VEGGIE (Triangulated Irregular Network (TIN)-based Real-time Integrated Basin Simulator - VEGetation Generator for Interactive Evolution). The model implements a triangulated irregular network to describe the topography, and it is capable of evaluating vegetation dynamics and predicting shallow landslides triggered by rainfall. The impact of DEM resolution on the landslide prediction was studied using five TINs derived from five grid DEMs at different resolutions, i.e. 10, 20, 30, 50 and 70 m respectively. The analysis was carried out on the Mameyes Basin, located in the Luquillo Experimental Forest in Puerto Rico, where previous landslide analyses have been carried out. Results showed that the use of the irregular mesh reduced the loss of accuracy in the derived slope distribution when coarser resolutions were used. The impact of the different resolutions on soil moisture patterns was important only when the lateral redistribution was considerable, depending on hydrological properties and rainfall forcing. In some cases, the use of different DEM resolutions did not significantly affect tRIBS-VEGGIE landslide output, in terms of landslide locations, and values of slope and soil moisture at failure.

Concurrency and climate change signal in Scottish flooding

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

To what extent does variability of historical rainfall series influence extreme event statistics of sewer system surcharge and overflows?

PubMed

Schaarup-Jensen, K; Rasmussen, M R; Thorndahl, S

2009-01-01

In urban drainage modelling long-term extreme statistics has become an important basis for decision-making e.g. in connection with renovation projects. Therefore it is of great importance to minimize the uncertainties with regards to long-term prediction of maximum water levels and combined sewer overflow (CSO) in drainage systems. These uncertainties originate from large uncertainties regarding rainfall inputs, parameters, and assessment of return periods. This paper investigates how the choice of rainfall time series influences the extreme events statistics of max water levels in manholes and CSO volumes. Traditionally, long-term rainfall series, from a local rain gauge, are unavailable. In the present case study, however, long and local rain series are available. 2 rainfall gauges have recorded events for approximately 9 years at 2 locations within the catchment. Beside these 2 gauges another 7 gauges are located at a distance of max 20 kilometers from the catchment. All gauges are included in the Danish national rain gauge system which was launched in 1976. The paper describes to what extent the extreme events statistics based on these 9 series diverge from each other and how this diversity can be handled, e.g. by introducing an "averaging procedure" based on the variability within the set of statistics. All simulations are performed by means of the MOUSE LTS model.

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

PubMed Central

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

2014-01-01

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

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.

Identification of statistically independent climatic pattern in GRACE and hydrological model data over West-Africa

NASA Astrophysics Data System (ADS)

Kusche, J.; Forootan, E.; Eicker, A.; Hoffmann-Dobrev, H.

2012-04-01

West-African countries have been exposed to changes in rainfall patterns over the last decades, including a significant negative trend. This causes adverse effects on water resources, for instance reduced freshwater availability, and changes in the frequency, duration and magnitude of droughts and floods. Extracting the main patterns of water storage change in West Africa from remote sensing and linking them to climate variability, is therefore an essential step to understand the hydrological aspects of the region. In this study, the higher order statistical method of Independent Component Analysis (ICA) is employed to extract statistically independent water storage patterns from monthly Gravity Recovery And Climate Experiment (GRACE), from the WaterGAP Global Hydrology Model (WGHM) and from Tropical Rainfall Measuring Mission (TRMM) products over West Africa, for the period 2002-2012. Then, to reveal the influences of climatic teleconnections on the individual patterns, these results were correlated to the El Nino-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) indices. To study the predictability of water storage changes, advanced statistical methods were applied on the main independent Sea Surface Temperature (SST) patterns over the Atlantic and Indian Oceans for the period 2002-2012 and the ICA results. Our results show a water storage decrease over the coastal regions of West Africa (including Sierra Leone, Liberia, Togo and Nigeria), associated with rainfall decrease. The comparison between GRACE estimations and WGHM results indicates some inconsistencies that underline the importance of forcing data for hydrological modeling of West Africa. Keywords: West Africa; GRACE-derived water storage; ICA; ENSO; IOD

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.

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.

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.

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.

Using Empirical Orthogonal Teleconnections to Analyze Interannual Precipitation Variability in China

NASA Astrophysics Data System (ADS)

Stephan, C.; Klingaman, N. P.; Vidale, P. L.; Turner, A. G.; Demory, M. E.; Guo, L.

2017-12-01

Interannual rainfall variability in China affects agriculture, infrastructure and water resource management. A consistent and objective method, Empirical Orthogonal Teleconnection (EOT) analysis, is applied to precipitation observations over China in all seasons. Instead of maximizing the explained space-time variance, the method identifies regions in China that best explain the temporal variability in domain-averaged rainfall. It produces known teleconnections, that include high positive correlations with ENSO in eastern China in winter, along the Yangtze River in summer, and in southeast China during spring. New findings include that variability along the southeast coast in winter, in the Yangtze valley in spring, and in eastern China in autumn, are associated with extratropical Rossby wave trains. The same analysis is applied to six climate simulations of the Met Office Unified Model with and without air-sea coupling and at various horizontal resolutions of 40, 90 and 200 km. All simulations reproduce the observed patterns of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are all patterns associated with the observed physical mechanism. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. Finer resolution does not improve the fidelity of these patterns or their associated mechanisms. Evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient; attention must be paid to associated mechanisms.

Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

NASA Technical Reports Server (NTRS)

Anyamba, Assaf; Linthicum, Kenneth J.; Small, Jennifer L.; Collins, Katherine M.; Tucker, Compton J.; Pak, Edwin W.; Britch, Seth C.; Eastman, James Ronald; Pinzon, Jorge E.; Russell, Kevin L.

2011-01-01

Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Extremes in rainfall (drought and flood) during the period 2004 - 2009 have privileged different disease vectors. Chikungunya outbreaks occurred during the severe drought from late 2004 to 2006 over coastal East Africa and the western Indian Ocean islands and in the later years India and Southeast Asia. The chikungunya pandemic was caused by a Central/East African genotype that appears to have been precipitated and then enhanced by global-scale and regional climate conditions in these regions. Outbreaks of Rift Valley fever occurred following excessive rainfall period from late 2006 to late 2007 in East Africa and Sudan, and then in 2008 - 2009 in Southern Africa. The shift in the outbreak patterns of Rift Valley fever from East Africa to Southern Africa followed a transition of the El Nino/Southern Oscillation (ENSO) phenomena from the warm El Nino phase (2006-2007) to the cold La Nina phase (2007-2009) and associated patterns of variability in the greater Indian Ocean basin that result in the displacement of the centres of above normal rainfall from Eastern to Southern Africa. Understanding the background patterns of climate variability both at global and regional scale and their impacts on ecological drivers of vector borne-diseases is critical in long-range planning of appropriate response and mitigation measures.

Planting Patterns and Deficit Irrigation Strategies to Improve Wheat Production and Water Use Efficiency under Simulated Rainfall Conditions

PubMed Central

Ali, Shahzad; Xu, Yueyue; Ma, Xiangcheng; Ahmad, Irshad; Kamran, Muhammad; Dong, Zhaoyun; Cai, Tie; Jia, Qianmin; Ren, Xiaolong; Zhang, Peng; Jia, Zhikuan

2017-01-01

The ridge furrow (RF) rainwater harvesting system is an efficient way to enhance rainwater accessibility for crops and increase winter wheat productivity in semi-arid regions. However, the RF system has not been promoted widely in the semi-arid regions, which primarily exist in remote hilly areas. To exploit its efficiency on a large-scale, the RF system needs to be tested at different amounts of simulated precipitation combined with deficit irrigation. Therefore, in during the 2015–16 and 2016–17 winter wheat growing seasons, we examined the effects of two planting patterns: (1) the RF system and (2) traditional flat planting (TF) with three deficit irrigation levels (150, 75, 0 mm) under three simulated rainfall intensity (1: 275, 2: 200, 3: 125 mm), and determined soil water storage profile, evapotranspiration rate, grain filling rate, biomass, grain yield, and net economic return. Over the two study years, the RF treatment with 200 mm simulated rainfall and 150 mm deficit irrigation (RF2150) significantly (P < 0.05) increased soil water storage in the depth of (200 cm); reduced ET at the field scale by 33%; increased total dry matter accumulation per plant; increased the grain-filling rate; and improved biomass (11%) and grain (19%) yields. The RF2150 treatment thus achieved a higher WUE (76%) and RIWP (21%) compared to TF. Grain-filling rates, grain weight of superior and inferior grains, and net economic profit of winter wheat responded positively to simulated rainfall and deficit irrigation under both planting patterns. The 200 mm simulated rainfall amount was more economical than other precipitation amounts, and led to slight increases in soil water storage, total dry matter per plant, and grain yield; there were no significant differences when the simulated rainfall was increased beyond 200 mm. The highest (12,593 Yuan ha−1) net income profit was attained using the RF system at 200 mm rainfall and 150 mm deficit irrigation, which also led to significantly higher grain yield, WUE, and RIWP than all other treatments. Thus, we recommend the RF2150 treatment for higher productivity, income profit, and improve WUE in the dry-land farming system of China. PMID:28878787

Geographic patterns of networks derived from extreme precipitation over the Indian subcontinent

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Bookhagen, Bodo; Marwan, Norbert; Kurths, Juergen

2014-05-01

Complex networks (CN) and event synchronization (ES) methods have been applied to study a number of climate phenomena such as Indian Summer Monsoon (ISM), South-American Monsoon, and African Monsoon. These methods proved to be powerful tools to infer interdependencies in climate dynamics between geographical sites, spatial structures, and key regions of the considered climate phenomenon. Here, we use these methods to study the spatial temporal variability of the extreme rainfall over the Indian subcontinent, in order to filter the data by coarse-graining the network, and to identify geographic patterns that are signature features (spatial signatures) of the ISM. We find four main geographic patterns of networks derived from extreme precipitation over the Indian subcontinent using up-to-date satellite-derived, and high temporal and spatial resolution rain-gauge interpolated daily rainfall datasets. In order to prove that our results are also relevant for other climatic variables like pressure and temperature, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). We find that two of the patterns revealed from the CN extreme rainfall analysis coincide with those obtained for the pressure and temperature fields, and all four above mentioned patterns can be explained by topography, winds, and monsoon circulation. CN and ES enable to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to infer geographic pattern that are spatial signatures of the ISM. These patterns deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

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.

Nitrogen and phosphorus runoff losses from variable and constant intensity rainfall simulations on loamy sand under conventional and strip tillage systems.

PubMed

Franklin, D; Truman, C; Potter, T; Bosch, D; Strickland, T; Bednarz, C

2007-01-01

Further studies on the quality of runoff from tillage and cropping systems in the southeastern USA are needed to refine current risk assessment tools for nutrient contamination. Our objective was to quantify and compare effects of constant (Ic) and variable (Iv) rainfall intensity patterns on inorganic nitrogen (N) and phosphorus (P) losses from a Tifton loamy sand (Plinthic Kandiudult) cropped to cotton (Gossypium hirsutum L.) and managed under conventional (CT) or strip-till (ST) systems. We simulated rainfall at a constant intensity and a variable intensity pattern (57 mm h(-1)) and collected runoff continuously at 5-min intervals for 70 min. For cumulative runoff at 50 min, the Iv pattern lost significantly greater amounts (p < 0.05) of total Kjeldahl N (TKN) and P (TKP) (849 g N ha(-1) and 266 g P ha(-1) for Iv; 623 g N ha(-1) and 192 g P ha(-1) for Ic) than did the Ic pattern. However, at 70 min, no significant differences in total losses were evident for TKN or TKP from either rainfall intensity pattern. In contrast, total cumulative losses of dissolved reactive P (DRP) and NO3-N were greatest for ST-Ic, followed by ST-Iv, CT-Ic, and CT-Iv in diminishing order (69 g DRP ha(-1) and 361 g NO3-N ha(-1); 37 g DRP ha(-1) and 133 g NO3-N ha(-1); 3 g DRP ha(-1) and 58 g NO3-N ha(-1); 1 g DRP ha(-1) and 49 g NO3-N ha(-1)). Results indicate that constant-rate rainfall simulations may overestimate the amount of dissolved nutrients lost to the environment in overland flow from cropping systems in loamy sand soils. We also found that CT treatments lost significantly greater amounts of TKN and TKP than ST treatments and in contrast, ST treatments lost significantly greater amounts of DRP and NO3-N than CT treatments. These results indicate that ST systems may be losing more soluble fractions than CT systems, but only a fraction the total N (33%) and total P (11%) lost through overland flow from CT systems.

Landslides induced by heavy rainfall in July 2012 in Northern Kyushu District, Japan and the influence of long term rainfall increase comparing with the slope destabilization due to strong seismic shaking

NASA Astrophysics Data System (ADS)

Kubota, Tetsuya; Shinohara, Yoshinori; Aditian, Aril

2013-04-01

1. Objective We had a deluge in July 2012 in the northern Kyushu district with intense rainfall of 800mm and 108mm/hr. This intensity yielded countless traces of debris flow and landslides, slope failures that induced tremendous damage and causalities in the area. Hence, several field investigations and reconnaissance tasks were conducted to delve into this sediment-related disaster. The various results and the information obtained through this investigation were reported, mentioning the damage, the meteorological condition, geologic-geomorphologic features and hydraulic characteristics of the debris flows, vegetation effects, and the influence of the climate change. Increase in rainfall that may be induced by the global climate change is obvious in Kyushu district, Japan, according to the analysis of rain data observed in various locations including mountainside points that are not influenced by local warming due to urbanization. On this point of view, we are intrigued to elucidate the response of landslide to this increase in rainfall. Hence, its long term impact on this landslide disaster is also analyzed comparing with the slope destabilization due to strong seismic shaking. 2. Method and target areas Field investigation on landslides slopes, slope failures and torrents where debris flows occurred are conducted to obtain the geologic data, geo-structure, vegetation feature, soil samples and topographic data i.e. cross sections, then soil shear tests and soil permeability tests are also conducted. The rainfall data at the nearest rain observatory were obtained from the database of Japan meteorological agency. The long term impact on the slope stability at some slopes in the area is analyzed by the finite element method (FEM) combined with rain infiltration and seepage analysis with the long term rainfall fluctuation data, obtaining factor of safety ( Fs) on real landslide slopes. The results are compared with the destabilized influence on the slopes due to the soil strength reduction by seismic shaking. The target areas are located in northern Kyushu district, western Japan where they often have severe landslide disasters. The geology in research areas consists of Paleozoic and Mesozoic rocks (mainly schist, slate) and Quaternary volcanic sediment such as Aso volcano body. The vegetation consists of mainly Japanese cypress, cedar or bamboo. 3. Result and consideration Consequently, the long term rainfall increase in the region such as increment of approximately 20 mm/hr for rain intensity Ri in 36 years is confirmed statistically using Kendall's rank correlation, and it is found that its impact on slope stability is considerable and critical in other cases. In the sample landslide slopes, even the increase in rain of duration for only 10 years has impact to a certain extent on their stabilities in terms of Fs. The Fs calculated with rains in previous decade is higher than 1.0 that corresponds to stable state, whereas the Fs with present rains is lower than 1.0 such as 0.99 which means unstable state. Extremely heavy rainfall with this impact is generally cause extreme ground water pressure in the slope. It is also obvious that the extreme ground water content rendered even small landslides liquefied to be source of destructive debris flows. In this disaster, especially in the Aso volcanic region, tremendous number of debris flow occurred and even the talus cone slopes which are usually stable collapsed to flow down. However, the influence of the long term rainfall increase on the slopes (such as 1% decrease in Fs) is not relatively small compared with the destabilization of the slopes due to the reduction of soil strength by seismic shaking (8~9 % reduction in Fs after seismic shaking of even 490gal). 4. Conclusion In the disaster in July 2012, many landslides and debris flows originated from landslides induced by concentrated underground water supplied by the heavy rainfall occurred. The increase of rainfall due to climate change with the increasing rate such as 20 mm/hr surely has impact on almost landslide slopes in aspects of slope stability, although the influence of the long term rainfall increase on the slopes is relatively small compared with the destabilization of the slopes due to the reduction of soil strength by seismic shakings. Therefore, with this rain increase rate, it is possible for many forest slopes or natural slopes to become unstable and cause landslide disasters especially after potential strong earthquake in the near future.

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.

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.

The potential vulnerability of the Namib and Nama Aquifers due to low recharge levels in the area surrounding the Naukluft Mountains, SW Namibia

NASA Astrophysics Data System (ADS)

Kambinda, Winnie N.; Mapani, Benjamin

2017-12-01

The Naukluft Mountains in the Namib Desert are a high rainfall-high discharge area. It sees increased stream-, spring-flow as well as waterfalls during the rainy season. The mountains are a major resource for additional recharge to the Namib and Nama aquifers that are adjacent to the mountains. This paper aimed to highlight the potential vulnerability of the aquifers that surround the Naukluft Mountain area; if the strategic importance of the Naukluft Karst Aquifer (NKA) for bulk water supply becomes necessary. Chloride Mass Balance Method (CMBM) was applied to estimate rainfall available for recharge as well as actual recharge thereof. This was applied using chloride concentration in precipitation, borehole and spring samples collected from the study area. Groundwater flow patterns were mapped from hydraulic head values. A 2D digital elevation model was developed using Arc-GIS. Results highlighted the influence of the NKA on regional groundwater flow. This paper found that groundwater flow was controlled by structural dip and elevation. Groundwater was observed to flow predominantly from the NKA to the south west towards the Namib Aquifer in two distinct flow patterns that separate at the center of the NKA. A distinct groundwater divide was defined between the two flow patterns. A minor flow pattern from the northern parts of the NKA to the north east towards the Nama Aquifer was validated. Due to the substantial water losses, the NKA is not a typical karst aquifer. While the project area receives an average rainfall of 170.36 mm/a, it was estimated that 1-14.24% (maximum 24.43 mm/a) rainfall was available for recharge to the NKA. Actual recharge to the NKA was estimated to be less than 1-18.21% (maximum 4.45 mm/a) reflecting the vast losses incurred by the NKA via discharge. This paper concluded that groundwater resources of the NKA were potentially finite. The possibility of developing the aquifer for bulk water supply would therefore drastically lower recharge to surrounding aquifers that sustain local populations because all received rainfall will be utilized to maximise recharge to the NKA instead of surrounding aquifers.

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.

Monitoring the subsurface hydrologic response to shallow landsliding in the San Francisco Bay Area, California

NASA Astrophysics Data System (ADS)

Collins, B. D.; Stock, J. D.; Foster, K. A.; Knepprath, N.; Reid, M. E.; Schmidt, K. M.; Whitman, M. W.

2011-12-01

Intense or prolonged rainfall triggers shallow landslides in steeplands of the San Francisco Bay Area each year. These landslides cause damage to built infrastructure and housing, and in some cases, lead to fatalities. Although our ability to forecast and map the distribution of rainfall has improved (e.g., NEXRAD, SMART-R), our ability to estimate landslide susceptibility is limited by a lack of information about the subsurface response to rainfall. In particular, the role of antecedent soil moisture content in setting the timing of shallow landslide failures remains unconstrained. Advances in instrumentation and telemetry have substantially reduced the cost of such monitoring, making it feasible to set up and maintain networks of such instruments in areas with a documented history of shallow landslides. In 2008, the U.S. Geological Survey initiated a pilot project to establish a series of shallow landslide monitoring stations in the San Francisco Bay area. The goal of this project is to obtain a long-term (multi-year) record of subsurface hydrologic conditions that occur from winter storms. Three monitoring sites are now installed in key landslide prone regions of the Bay Area (East Bay Hills, Marin County, and San Francisco Peninsula Hills) each consisting of a rain gage and multiple nests of soil-moisture sensors, matric-potential sensors, and piezometers. The sites were selected with similar characteristics in mind consisting of: (1) convergent bedrock hollow topographic settings located near ridge tops, (2) underlying sandstone bedrock substrates, (3) similar topographic gradients (~30°), (4) vegetative assemblages of grasses with minor chaparral, and (5) a documented history of landsliding in the vicinity of each site. These characteristics are representative of shallow-landslide-prone regions of the San Francisco Bay Area and also provide some constraint on the ability to compare and contrast subsurface response across different regions. Data streams from two of the sites, one operational in 2009 and one in 2010 have been analyzed and showcase both the seasonal patterns of moisture increase and decrease between summer-winter-summer conditions, as well as patterns of cyclical short-term wetting and drying as storms pass through the region. Further, the data show that at one location (East Bay Hills), storm-generated antecedent soil moisture conditions led to positive pore water pressures that correlate directly to shallow landsliding observed in the immediate vicinity of the monitoring site. This information, along with more extensive and continued monitoring and analysis should provide a basis and methodology for performing future shallow landslide assessments which depend not only on forecast rainfall, but also on pre-storm antecedent, subsurface soil moisture conditions.

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

NASA Astrophysics Data System (ADS)

Unnikrishnan, Poornima; Jothiprakash, V.

2018-06-01

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

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.

The impact of annual and seasonal rainfall patterns on growth and phenology of emergent tree species in Southeastern Amazonia, Brazil

Treesearch

James Grogan; Mark Schulze

2012-01-01

Understanding tree growth in response to rainfall distribution is critical to predicting forest and species population responses to climate change. We investigated inter-annual and seasonal variation in stem diameter by three emergent tree species in a seasonally dry tropical forest in southeast Pará, Brazil. Annual diameter growth rates by Swietenia macrophylla...

Consideration of online rainfall measurement and nowcasting for RTC of the combined sewage system.

PubMed

Rouault, P; Schroeder, K; Pawlowsky-Reusing, E; Reimer, E

2008-01-01

In Berlin, Germany, the demand for enhanced protection of the environment and the growing economic pressure have led to an increased application of control concepts within the sewage system. A global control strategy to regulate the pumpage of the combined sewage system to the treatment plant was developed and evaluated in a theoretical study. The objective was to reduce CSO. In this paper an extension of the existing control algorithm by information from online rainfall measurement and radar nowcasting is described. The rainfall information is taken into account by two additive terms describing the predicted volume from rainfall runoff. On the basis of numerical simulation the potential of these two complementary forecast terms in the global control algorithm to further reduce CSO is evaluated. The investigations are based on long-time simulations that are conducted with the dynamic flow routing model InfoWorks for three subcatchments of the Berlin drainage system. The results show that at the current Berlin system a CSO reduction of only 0.8% is possible. The effect of the forecast terms is limited by operational constraints. Limits are set to both, the delivery from each individual pump station and the total pumpage to the treatment plant.

Indian summer monsoon rainfall: Dancing with the tunes of the sun

NASA Astrophysics Data System (ADS)

Hiremath, K. M.; Manjunath, Hegde; Soon, Willie

2015-02-01

There is strong statistical evidence that solar activity influences the Indian summer monsoon rainfall. To search for a physical link between the two, we consider the coupled cloud hydrodynamic equations, and derive an equation for the rate of precipitation that is similar to the equation of a forced harmonic oscillator, with cloud and rain water mixing ratios as forcing variables. Those internal forcing variables are parameterized in terms of the combined effect of external forcing as measured by sunspot and coronal hole activities with several well known solar periods (9, 13 and 27 days; 1.3, 5, 11 and 22 years). The equation is then numerically solved and the results show that the variability of the simulated rate of precipitation captures very well the actual variability of the Indian monsoon rainfall, yielding vital clues for a physical understanding that has so far eluded analyses based on statistical correlations alone. We also solved the precipitation equation by allowing for the effects of long-term variation of aerosols. We tentatively conclude that the net effects of aerosols variation are small, when compared to the solar factors, in terms of explaining the observed rainfall variability covering the full Indian monsoonal geographical domains.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Technical Report Series on Global Modeling and Data Assimilation. Volume 12; Comparison of Satellite Global Rainfall Algorithms

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Chang, Alfred T. C.; Chiu, Long S.

1997-01-01

Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates.

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.

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.

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.

The short-term association of temperature and rainfall with mortality in Vadu Health and Demographic Surveillance System: a population level time series analysis

PubMed Central

Ingole, Vijendra; Juvekar, Sanjay; Muralidharan, Veena; Sambhudas, Somnath; Rocklöv, Joacim

2012-01-01

Background Research in mainly developed countries has shown that some changes in weather are associated with increased mortality. However, due to the lack of accessible data, few studies have examined such effects of weather on mortality, particularly in rural regions in developing countries. Objective In this study, we aimed to investigate the relationship between temperature and rainfall with daily mortality in rural India. Design Daily mortality data were obtained from the Health and Demographic Surveillance System (HDSS) in Vadu, India. Daily mean temperature and rainfall data were obtained from a regional meteorological center, India Meteorological Department (IMD), Pune. A Poisson regression model was established over the study period (January 2003–May 2010) to assess the short-term relationship between weather variables and total mortality, adjusting for time trends and stratifying by both age and sex. Result Mortality was found to be significantly associated with daily ambient temperatures and rainfall, after controlling for seasonality and long-term time trends. Children aged 5 years or below appear particularly susceptible to the effects of warm and cold temperatures and heavy rainfall. The population aged 20–59 years appeared to face increased mortality on hot days. Most age groups were found to have increased mortality rates 7–13 days after rainfall events. This association was particularly evident in women. Conclusion We found the level of mortality in Vadu HDSS in rural India to be highly affected by both high and low temperatures and rainfall events, with time lags of up to 2 weeks. These results suggest that weather-related mortality may be a public health problem in rural India today. Furthermore, as changes in local climate occur, adaptation measures should be considered to mitigate the potentially negative impacts on public health in these rural communities. PMID:23195513

Long term high resolution rainfall runoff observations for improved water balance uncertainty and database QA-QC in the Walnut Gulch Experimental Watershed.

NASA Astrophysics Data System (ADS)

Bitew, M. M.; Goodrich, D. C.; Demaria, E.; Heilman, P.; Kautz, M. A.

2017-12-01

Walnut Gulch is a semi-arid environment experimental watershed and Long Term Agro-ecosystem Research (LTAR) site managed by USDA-ARS Southwest Watershed Research Center for which high-resolution long-term hydro-climatic data are available across its 150 km2 drainage area. In this study, we present the analysis of 50 years of continuous hourly rainfall data to evaluate runoff control and generation processes for improving the QA-QC plans of Walnut Gulch to create high-quality data set that is critical for reducing water balance uncertainties. Multiple linear regression models were developed to relate rainfall properties, runoff characteristics and watershed properties. The rainfall properties were summarized to event based total depth, maximum intensity, duration, the location of the storm center with respect to the outlet, and storm size normalized to watershed area. We evaluated the interaction between the runoff and rainfall and runoff as antecedent moisture condition (AMC), antecedent runoff condition (ARC) and, runoff depth and duration for each rainfall events. We summarized each of the watershed properties such as contributing area, slope, shape, channel length, stream density, channel flow area, and percent of the area of retention stock ponds for each of the nested catchments in Walnut Gulch. The evaluation of the model using basic and categorical statistics showed good predictive skill throughout the watersheds. The model produced correlation coefficients ranging from 0.4-0.94, Nash efficiency coefficients up to 0.77, and Kling-Gupta coefficients ranging from 0.4 to 0.98. The model predicted 92% of all runoff generations and 98% of no-runoff across all sub-watersheds in Walnut Gulch. The regression model also indicated good potential to complement the QA-QC procedures in place for Walnut Gulch dataset publications developed over the years since the 1960s through identification of inconsistencies in rainfall and runoff relations.

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

NASA Astrophysics Data System (ADS)

Mascaro, Giuseppe

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

PubMed

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

2016-12-15

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

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.

Deciduousness in a seasonal tropical forest in western Thailand: interannual and intraspecific variation in timing, duration and environmental cues.

PubMed

Williams, Laura J; Bunyavejchewin, Sarayudh; Baker, Patrick J

2008-03-01

Seasonal tropical forests exhibit a great diversity of leaf exchange patterns. Within these forests variation in the timing and intensity of leaf exchange may occur within and among individual trees and species, as well as from year to year. Understanding what generates this diversity of phenological behaviour requires a mechanistic model that incorporates rate-limiting physiological conditions, environmental cues, and their interactions. In this study we examined long-term patterns of leaf flushing for a large proportion of the hundreds of tree species that co-occur in a seasonal tropical forest community in western Thailand. We used the data to examine community-wide variation in deciduousness and tested competing hypotheses regarding the timing and triggers of leaf flushing in seasonal tropical forests. We developed metrics to quantify the nature of deciduousness (its magnitude, timing and duration) and its variability among survey years and across a range of taxonomic levels. Tree species varied widely in the magnitude, duration, and variability of leaf loss within species and across years. The magnitude of deciduousness ranged from complete crown loss to no crown loss. Among species that lost most of their crown, the duration of deciduousness ranged from 2 to 21 weeks. The duration of deciduousness in the majority of species was considerably shorter than in neotropical forests with similar rainfall periodicity. While the timing of leaf flushing varied among species, most ( approximately 70%) flushed during the dry season. Leaf flushing was associated with changes in photoperiod in some species and the timing of rainfall in other species. However, more than a third of species showed no clear association with either photoperiod or rainfall, despite the considerable length and depth of the dataset. Further progress in resolving the underlying internal and external mechanisms controlling leaf exchange will require targeting these species for detailed physiological and microclimatic studies.

Long-term environmental drivers of DOC fluxes: Linkages between management, hydrology and climate in a subtropical coastal estuary

NASA Astrophysics Data System (ADS)

Regier, Peter; Briceño, Henry; Jaffé, Rudolf

2016-12-01

Urban and agricultural development of the South Florida peninsula has disrupted historic freshwater flow in the Everglades, a hydrologically connected ecosystem stretching from central Florida to the Gulf of Mexico, USA. Current system-scale restoration efforts aim to restore natural hydrologic regimes to reestablish pre-drainage ecosystem functioning through increased water availability, quality and timing. Aquatic transport of carbon in this ecosystem, primarily as dissolved organic carbon (DOC), plays a critical role in biogeochemical cycling and food-web dynamics, and will be affected both by water management policies and climate change. To better understand DOC dynamics in South Florida estuaries and how hydrology, climate and water management may affect them, 14 years of monthly data collected in the Shark River estuary were used to examine DOC flux dynamics in a broader environmental context. Multivariate statistical methods were applied to long-term datasets for hydrology, water quality and climate to untangle the interconnected environmental drivers that control DOC export at monthly and annual scales. DOC fluxes were determined to be primarily controlled by hydrology but also by seasonality and long-term climate patterns and episodic weather events. A four-component model (salinity, rainfall, inflow, Atlantic Multidecadal Oscillation) capable of predicting DOC fluxes (R2 = 0.84, p < 0.0001, n = 155) was established and applied to potential climate change scenarios for the Everglades to assess DOC flux response to climate and restoration variables. The majority of scenario runs indicated that DOC export from the Everglades is expected to decrease due to future changes in rainfall, water management and salinity.

An Integrated Urban Flood Analysis System in South Korea

NASA Astrophysics Data System (ADS)

Moon, Young-Il; Kim, Min-Seok; Yoon, Tae-Hyung; Choi, Ji-Hyeok

2017-04-01

Due to climate change and the rapid growth of urbanization, the frequency of concentrated heavy rainfall has caused urban floods. As a result, we studied climate change in Korea and developed an integrated flood analysis system that systematized technology to quantify flood risk and flood forecasting in urban areas. This system supports synthetic decision-making through real-time monitoring and prediction on flash rain or short-term rainfall by using radar and satellite information. As part of the measures to deal with the increase of inland flood damage, we have found it necessary to build a systematic city flood prevention system that systematizes technology to quantify flood risk as well as flood forecast, taking into consideration both inland and river water. This combined inland-river flood analysis system conducts prediction on flash rain or short-term rainfall by using radar and satellite information and performs prompt and accurate prediction on the inland flooded area. In addition, flood forecasts should be accurate and immediate. Accurate flood forecasts signify that the prediction of the watch, warning time and water level is precise. Immediate flood forecasts represent the forecasts lead time which is the time needed to evacuate. Therefore, in this study, in order to apply rainfall-runoff method to medium and small urban stream for flood forecasts, short-term rainfall forecasting using radar is applied to improve immediacy. Finally, it supports synthetic decision-making for prevention of flood disaster through real-time monitoring. Keywords: Urban Flood, Integrated flood analysis system, Rainfall forecasting, Korea Acknowledgments This research was supported by a grant (16AWMP-B066744-04) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

Real-Time Application of Multi-Satellite Precipitation Analysis for Floods and Landslides

NASA Technical Reports Server (NTRS)

Adler, Robert; Hong, Yang; Huffman, George

2007-01-01

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets-- both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers, In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences.

Risk assessment of tropical cyclone rainfall flooding in the Delaware River Basin

NASA Astrophysics Data System (ADS)

Lu, P.; Lin, N.; Smith, J. A.; Emanuel, K.

2016-12-01

Rainfall-induced inland flooding is a leading cause of death, injury, and property damage from tropical cyclones (TCs). In the context of climate change, it has been shown that extreme precipitation from TCs is likely to increase during the 21st century. Assessing the long-term risk of inland flooding associated with landfalling TCs is therefore an important task. Standard risk assessment techniques, which are based on observations from rain gauges and stream gauges, are not broadly applicable to TC induced flooding, since TCs are rare, extreme events with very limited historical observations at any specific location. Also, rain gauges and stream gauges can hardly capture the complex spatial variation of TC rainfall and flooding. Furthermore, the utility of historically based assessments is compromised by climate change. Regional dynamical downscaling models can resolve many features of TC precipitation. In terms of risk assessment, however, it is computationally demanding to run such models to obtain long-term climatology of TC induced flooding. Here we apply a computationally efficient climatological-hydrological method to assess the risk of inland flooding associated with landfalling TCs. It includes: 1) a deterministic TC climatology modeling method to generate large numbers of synthetic TCs with physically correlated characteristics (i.e., track, intensity, size) under observed and projected climates; 2) a simple physics-based tropical cyclone rainfall model which is able to simulate rainfall fields associated with each synthetic storm; 3) a hydrologic modeling system that takes in rainfall fields to simulate flood peaks over an entire drainage basin. We will present results of this method applied to the Delaware River Basin in the mid-Atlantic US.

The influence of climate, topography and land-use on the hydrology of ephemeral upland catchments

NASA Astrophysics Data System (ADS)

Daly, E.; Webb, J.; Dresel, E.

2016-12-01

We report on an on-going project aimed at determining the effects of climate variability and land use change on water resources in ephemeral productive catchments. Meteorological data (including rainfall, solar radiation, air temperature, humidity and wind speed), streamflow and groundwater levels were collected continuously for over five years in seven ephemeral catchments in southeastern Australia. The catchments, dominated by either pasture for grazing (four) or Eucalyptus globulus (blue gum) plantations of different ages (three), were located in three different geological settings. Rainfall varied from higher than the long-term average of this area for the initial years of the study period to much drier than the long-term average for the last two years. Groundwater levels in the farm sites remained stable or slightly increased through the study period, while levels declined in all the plantation catchments, where evapotranspiration rates were greater than rainfall. The trees intercept groundwater recharge and in some areas of the catchments directly access groundwater. Streamflow occurred mainly during winter, with short-term flows in summer caused by sporadic large rainfall events. Despite the large annual rainfall variability, flow rates in each year were similar in most catchments, with the duration of flow being important in determining the annual flow. The frequency rather than the amount of rainfall events determines the generation of streamflow in the two catchments with steeper slopes. The effect of the tree plantations on streamflow varied from a substantial reduction in one catchment to no effect in another, where the tree rows are oriented predominantly downslope, allowing greater runoff. In the third plantation catchment, geology is the main driver of runoff due to capture into underlying karst conduits.

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.

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.

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

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

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

Modeling the roles of damage accumulation and mechanical healing on rainfall-induced landslides

NASA Astrophysics Data System (ADS)

Fan, Linfeng; Lehmann, Peter; Or, Dani

2014-05-01

The abrupt release of rainfall-induced shallow landslides is preceded by local failures that may abruptly coalesce and form a continuous failure plane within a hillslope. The mechanical status of hillslopes reflects a competition between the extent of severity of accumulated local damage during prior rainfall events and the rates of mechanically healing (i.e. regaining of strength) by closure of micro-cracks, regrowth of roots, etc. The interplay of these processes affects the initial conditions for landslide modeling and shapes potential failure patterns during future rainfall events. We incorporated these competing mechanical processes in a hydro-mechanical landslide triggering model subjected to a sequence of rainfall scenarios. The model employs the Fiber Bundle Model (FBM) with bonds (fiber bundle) with prescribed threshold linking adjacent soil columns and soil to bedrock. Prior damage was represented by a fraction of broken fibers during previous rainfall events, and the healing of broken fibers was described by strength regaining models for soil and roots at different characteristic time scales. Results show that prior damage and healing introduce highly nonlinear response to landslide triggering. For small prior damage, mechanical bonds at soil-bedrock interface may fail early in next rainfall event but lead to small perturbations onto lateral bonds without triggering a landslide. For more severe damage weakening lateral bonds, excess load due to failure at soil-bedrock interface accumulates at downslope soil columns resulting in early soil failure with patterns strongly correlated with prior damage distribution. Increasing prior damage over the hillslope decreases the volume of first landslide and prolongs the time needed to trigger the second landslide due to mechanical relaxation of the system. The mechanical healing of fibers diminishes effects of prior damage on the time of failure, and shortens waiting time between the first and second landslides. These findings highlight the need to improve definition of initial conditions and the shortcomings of assuming pristine hillslopes.