Regional analysis of annual maximum rainfall using TL-moments method

Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments.     

Trends in the annual extreme rainfall events of 1 to 3 days duration over India

Summary In this paper, the annual extreme rainfall series in the time scale of 1 to 3 days duration at 316 stations, well distributed over the Indian region, covering 80-years of rainfall data from 1901 to 1980 were analysed for trend and persistence using standard statistical tests. It has been found that the annual extreme rainfall records of most stations are free from trend and persistence. However, the extreme rainfall series at stations over the west coast north of 12°N and at some stations to the east of the Western Ghats over the central parts of the Peninsula showed a significant increasing trend at 95% level of confidence. Stations over the southern Peninsula and over the lower Ganga valley have been found to exhibit a decreasing trend at the same level of significance. The data series of the stations which showed trends were subjected to a 10-year moving average and the resulting smoothed series have been discussed. It may be said that this increasing or decreasing trend in the annual extreme rainfall events at a few places will have tremendous implications in the hydrologic studies and dam design projects.With 9 Figures     

The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment

This paper discusses patterns of annual and monthly precipitation variability at seven weather stations in east central Europe (1851–2007). Precipitation patterns were compared to three simple regional indices of atmospheric circulation, i.e., western circulation, southern circulation and the cyclonicity (C) index and a relationship between precipitation and the North Atlantic Oscillation index was identified. Correlations of the monthly records and multiple regression, using a principal components’ analysis, helped determine the statistical significance of the dependence of precipitation on the circulation indices. The Mann–Kendall test revealed no trend to change in any of the precipitation series, but a certain spatial regularity could be discerned in the phase of the annual periodic component. A common feature of the variability in central European annual precipitation is the dry period identified in the 1980s and the first half of the 1990s. In the northern part of the region, above-average precipitation was noted from the 1960s through to the mid-1970s as a result of the frequent prevalence of depressions. South of the divide, the wettest period was recorded at the turn of 1930s/1940s. After a number of very wet years in the last decade of the twentieth century and the beginning of the twenty-first century, precipitation began to fall at all of the region’s weather stations. The C index is the strongest circulation-linked factor influencing precipitation in central Europe and it accounts for more than 40% of the variance in spatially averaged wintertime precipitation.     

Statistical characterizations of rainfall structure over two tropical stations in southern India for microwave communication

Statistical characterizations of rainfall structure over two tropical stations in southern India are reported in this paper based on the 2-year rainfall data. The statistical characterizations has been based on cumulative distribution function, exceedance of threshold values, dependence of the intensity of rainfall on the event duration, seasonal variability, and worst months concept as well as diurnal variability. These results are needed to give the detailed insights to the system designers for the development of communication gadgets needed for better service, serve as a vital tool to estimate signal outages in a year over the region and for proper planning of radio communication in the region. Finally, the study shows that the recent International Telecommunications Union Recommendations (ITU-R) value underestimated rain rate for 0.01% exceedance for the two locations.     

Trend analysis for rainfall in Delhi and Mumbai, India

Urbanisation has burdened cities with many problems associated with growth and the physical environment. Some of the urban locations in India are becoming increasingly vulnerable to natural hazards related to precipitation and flooding. Thus it becomes increasingly important to study the characteristics of these events and their physical explanation. This work studies rainfall trends in Delhi and Mumbai, the two biggest Metropolitan cities of Republic of India, during the period from 1951 to 2004. Precipitation data was studied on basis of months, seasons and years, and the total period divided in the two different time periods of 1951–1980 and 1981–2004 for detailed analysis. Long-term trends in rainfall were determined by Man-Kendall rank statistics and linear regression. Further this study seeks for an explanation for precipitation trends during monsoon period by different global climate phenomena. Principal component analysis and Singular value decomposition were used to find relation between southwest monsoon precipitation and global climatic phenomena using climatic indices. Most of the rainfall at both the stations was found out to be taking place in Southwest monsoon season. The analysis revealed great degree of variability in precipitation at both stations. There is insignificant decrease in long term southwest monsoon rainfall over Delhi and slight significant decreasing trends for long term southwest monsoon rainfall in Mumbai. Decrease in average maximum rainfall in a day was also indicated by statistical analysis for both stations. Southwest monsoon precipitation in Delhi was found directly related to Scandinavian Pattern and East Atlantic/West Russia and inversely related to Pacific Decadal Oscillation, whereas precipitation in Mumbai was found inversely related to Indian ocean dipole, El Ni?o- Southern Oscillation and East Atlantic Pattern.     

Some features of the periods contributing specified percentages of rainfall to annual total in Kerala,India

Based on daily rainfall data over a period of 80 years (1901–1980) taken at 75 stations, this paper reports interannual and long term fluctuations of the following parameters of the periods contributing each of 2, 5, 10, 20–90 and 95% rainfall to annual total over each of North Kerala and South Kerala rainfall subregions of India:

Impact of the modulated annual cycle and intraseasonal oscillation on daily-to-interannual rainfall variability across monsoonal India

Variability of the Indian summer monsoon is decomposed into an interannually modulated annual cycle (MAC) and a northward-propagating, intraseasonal (30–60-day) oscillation (ISO). To achieve this decomposition, we apply multi-channel singular spectrum analysis (M-SSA) simultaneously to unfiltered daily fields of observed outgoing long-wave radiation (OLR) and to reanalyzed 925-hPa winds over the Indian region, from 1975 to 2008. The MAC is essentially given by the year-to-year changes in the annual and semi-annual components; it displays a slow northward migration of OLR anomalies coupled with an alternation between the northeast winter and southwest summer monsoons. The impact of these oscillatory modes on rainfall is then analyzed using a 1-degree gridded daily data set, focusing on Monsoonal India (north of 17°N and west of 90°E) during the months of June to September. Daily rainfall variability is partitioned into three states using a Hidden Markov Model. Two of these states are shown to agree well with previous classifications of “active” and “break” phases of the monsoon, while the third state exhibits a dipolar east–west pattern with abundant rainfall east of about 77°E and low rainfall to the west. Occurrence of the three rainfall states is found to be an asymmetric function of both the MAC and ISO components. On average, monsoon active phases are favored by large positive anomalies of MAC, and breaks by negative ones. ISO impact is decisive when the MAC is near neutral values during the onset and withdrawal phases of the monsoon. Active monsoon spells are found to require a synergy between the MAC and ISO, while the east–west rainfall dipole is less sensitive to interactions between the two. The driest years, defined from spatially averaged June–September rainfall anomalies, are found to be mostly a result of breaks occurring during the onset and withdrawal stages of the monsoon, e.g., mid-June to mid-July, and during September. These breaks are in turn associated with anomalously late MAC onset or early MAC withdrawal, often together with a large-amplitude, negative ISO event. The occurrence of breaks during the core of the monsoon—from late July to late August—is restricted to a few years when MAC was exceptionally weak, such as 1987 or 2002. Wet years are shown to be mostly associated with more frequent active spells and a stronger MAC than usual, especially at the end of the monsoon season. Taken together, our results suggest that monthly and seasonal precipitation?predictability is higher in the early and late stages of the summer monsoon season.     

An analysis of annual maximum streamflows in Terengganu, Malaysia using TL-moments approach

TL-moments approach has been used in an analysis to determine the best-fitting distributions to represent the annual series of maximum streamflow data over 12 stations in Terengganu, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: generalized pareto (GPA), generalized logistic, and generalized extreme value distribution. The influence of TL-moments on estimated probability distribution functions are examined by evaluating the relative root mean square error and relative bias of quantile estimates through Monte Carlo simulations. The boxplot is used to show the location of the median and the dispersion of the data, which helps in reaching the decisive conclusions. For most of the cases, the results show that TL-moments with one smallest value was trimmed from the conceptual sample (TL-moments (1,0)), of GPA distribution was the most appropriate in majority of the stations for describing the annual maximum streamflow series in Terengganu, Malaysia.     

Statistical analysis of daily maximum and monthly precipitation at Belgrade

Summary  A statistical analysis of monthly mean and daily maximum precipitation at Belgrade during the period 1888–1995 is presented. A very high correlation coefficient exists between the monthly and daily maximum precipitation. Weather types that are associated with the maximum daily precipitation at Belgrade are also analysed. Received July 19, 1999 Revised December 25, 1999     

Trend analysis of rainfall time series for Sindh river basin in India

The main goal of this paper is to estimate a set of optimal seasonal, daily, and hourly values of atmospheric turbidity and surface radiative parameters Ångström’s turbidity coefficient (β), Ångström’s wavelength exponent (α), aerosol single scattering albedo (ω_o), forward scatterance (F_c) and average surface albedo (ρ_g), using the Brute Force multidimensional minimization method to minimize the difference between measured and simulated solar irradiance components, expressed as cost functions. In order to simulate the components of short-wave solar irradiance (direct, diffuse and global) for clear sky conditions, incidents on a horizontal surface in the Metropolitan Area of Rio de Janeiro (MARJ), Brazil (22° 51′ 27″ S, 43° 13′ 58″ W), we use two parameterized broadband solar irradiance models, called CPCR2 and Iqbal C, based on synoptic information. The meteorological variables such as precipitable water (u_w) and ozone concentration (u_o) required by the broadband solar models were obtained from moderate-resolution imaging spectroradiometer (MODIS) sensor on Terra and Aqua NASA platforms. For the implementation and validation processes, we use global and diffuse solar irradiance data measured by the radiometric platform of LabMiM, located in the north area of the MARJ. The data were measured between the years 2010 and 2012 at 1-min intervals. The performance of solar irradiance models using optimal parameters was evaluated with several quantitative statistical indicators and a subset of measured solar irradiance data. Some daily results for Ångström’s wavelength exponent α were compared with Ångström’s parameter (440–870 nm) values obtained by aerosol robotic network (AERONET) for 11 days, showing an acceptable level of agreement. Results for Ångström’s turbidity coefficient β, associated with the amount of aerosols in the atmosphere, show a seasonal pattern according with increased precipitation during summer months (December–February) in the MARJ.     

Extreme monsoonal rainfall deficits in India

Summary Data from 306 stations in India, for the 70 years (1901–70) of summer (June–September) monsoonal rainfall, are grouped into 32 sub-regions. Extreme event theory is used to analyse the return periods of extreme rainfall deficits within each of these sub-regions, using the log-Pearson type III frequency distribution in a spatial rather than a temporal context. The resultant estimates for 2, 5 and 10 year return periods are compared with the patterns derived from the Gaussian frequency distribution applied to the 306 stations individually; the 50 and 100 year return period estimates are also considered.

---

Zusammenfassung Die Daten über den sommerlichen Monsunregen (Juni–September) aus 70 Jahren (1901–70) von 306 Stationen in Indien werden in 32 Teilgebiete gruppiert. Zur Analyse der wiederkehrenden Perioden extremen Regendefizits in jedem dieser Teilgebiete wird die Theorie extremer Ereignisse verwendet, wobei die log-Pearson-Häufigkeitsverteilung vom Typ III eher in einem räumlichen als zeitlichen Zusammenhang verwendet wird. Die sich daraus ergebenden Schätzungen für wiederkehrende Perioden von 2, 5 und 10 Jahren werden mit den Mustern verglichen, die mit Hilfe der auf alle 306 Stationen einzeln angewandten Gaußschen Häufigkeitsverteilung gewonnen wurden. Die Abschätzung 50jähriger und 100jähriger Ereignisse wird ebenfalls besprochen.

---

---

With 6 Figures     

Trend analysis of rainfall and temperature and its relationship over India

This study investigated the trends in rainfall and temperature and the possibility of any rational relationship between the trends over the homogeneous regions over India. Annual maximum temperature shows an increasing trend in all the homogeneous temperature regions and corresponding annual rainfall also follow the same pattern in all the regions, except North East. As far as monthly analysis is concerned, no definite pattern has been observed between trends in maximum and minimum temperature and rainfall, except during October. Increasing trends of maximum and minimum temperature during October accelerate the water vapor demand and most of the lakes, rivers, ponds and other water bodies with no limitation of water availability during this time fulfills the water vapor demand and shows an increasing trend of rainfall activity. This study shows there exists no direct relationship between increasing rainfall and increasing maximum temperature when monthly or seasonal pattern is concerned over meteorological subdivisions of India, however we can make a conclusion that the relation between the trends of rainfall and temperature have large scale spatial and temporal dependence.     

Public perceptions of rainfall change in India

People’s perceptions of changes in local weather patterns are an important precursor to proactive adaptation to climate change. In this paper, we consider public perceptions of changes in average rainfall in India, analyzing the relationship between perceptions and the instrumental record. Using data from a national sample survey, we find that local instrumental records of precipitation are a strong predictor of perceived declines in rainfall. Perceptions of decreasing rainfall were also associated with perceptions of changes in extreme weather events, such as decreasing frequency of floods and severe storms, increasing frequency of droughts, and decreasing predictability of the monsoon. Higher social vulnerability—including low perceived adaptive capacity and greater food and livelihood dependence on local weather—was also associated with perceptions of decreasing rainfall. While both urban and rural respondents were likely to perceive local changes in precipitation, we show that rural respondents in general were more sensitive to actual changes in precipitation. Individual perceptions of changes in local climate may play an important role in shaping vulnerability to global climate change, adaptive behavior, and support for adaptation and mitigation policies. Awareness of local climate change is therefore particularly important in regions where much of the population is highly exposed and sensitive to the impacts of climate change.     

一次人工增雨作业效果分析

2005—05—31-06-01,贵州省人工影响天气办公室在具备降雨条件而又非重点降雨区（据省气象台分析预测）的猫跳河流域及时组织实施了人工增雨作业试验。该文以此次试验为个例,对人工增雨作业效果进行了初步分析,为今后人工增雨作业条件和作业时机的掌握、作业组织实施积累经验,同时也为今后对猫跳河流域梯级发电开展增雨服务进行探索。     

Long-term changes in annual rainfall patterns in southern Israel

Summary Within the study region in southern Israel, the annual average rainfall during the period 1961–1990 increased by up to ~ 30%, with only minor changes in the control stations representing the central and northern parts of the country. The retreat of aridity is made even more pronounced by an appreciable decrease in the coefficient of variation (CV) in nearly all of the 30 rain stations within the study region. The geographical area where maximum CV reductions were found correlates well with the area where intensive land-use variations took place with the initial operation of the National Water Carrier in 1964. A global climate change in the sea surface temperatures starting in the early 1960's may have had an effect to increase seasonal rainfall. Current research is aimed at resolving this issue.With 6 Figures     

All India summer monsoon rainfall prediction using an artificial neural network

The prediction of Indian summer monsoon rainfall (ISMR) on a seasonal time scales has been attempted by various research groups using different techniques including artificial neural networks. The prediction of ISMR on monthly and seasonal time scales is not only scientifically challenging but is also important for planning and devising agricultural strategies. This article describes the artificial neural network (ANN) technique with error- back-propagation algorithm to provide prediction (hindcast) of ISMR on monthly and seasonal time scales. The ANN technique is applied to the five time series of June, July, August, September monthly means and seasonal mean (June + July + August + September) rainfall from 1871 to 1994 based on Parthasarathy data set. The previous five years values from all the five time-series were used to train the ANN to predict for the next year. The details of the models used are discussed. Various statistics are calculated to examine the performance of the models and it is found that the models could be used as a forecasting tool on seasonal and monthly time scales. It is observed by various researchers that with the passage of time the relationships between various predictors and Indian monsoon are changing, leading to changes in monsoon predictability. This issue is discussed and it is found that the monsoon system inherently has a decadal scale variation in predictability. Received: 13 March 1999 / Accepted: 31 August 1999     

Development of an artificial neural network based multi-model ensemble to estimate the northeast monsoon rainfall over south peninsular India: an application of extreme learning machine

The south peninsular part of India gets maximum amount of rainfall during the northeast monsoon (NEM) season [October to November (OND)] which is the primary source of water for the agricultural activities in this region. A nonlinear method viz., Extreme learning machine (ELM) has been employed on general circulation model (GCM) products to make the multi-model ensemble (MME) based estimation of NEM rainfall (NEMR). The ELM is basically is an improved learning algorithm for the single feed-forward neural network (SLFN) architecture. The 27 year (1982–2008) lead-1 (using initial conditions of September for forecasting the mean rainfall of OND) hindcast runs (1982–2008) from seven GCM has been used to make MME. The improvement of the proposed method with respect to other regular MME (simple arithmetic mean of GCMs (EM) and singular value decomposition based multiple linear regressions based MME) has been assessed through several skill metrics like Spread distribution, multiplicative bias, prediction errors, the yield of prediction, Pearson’s and Kendal’s correlation coefficient and Wilmort’s index of agreement. The efficiency of ELM estimated rainfall is established by all the stated skill scores. The performance of ELM in extreme NEMR years, out of which 4 years are characterized by deficit rainfall and 5 years are identified as excess, is also examined. It is found that the ELM could expeditiously capture these extremes reasonably well as compared to the other MME approaches.