Probability distribution of annual,seasonal and monthly precipitation in Japan

Abstract

The method of L-moment ratio diagrams and the average weighted distance (AWD) are used to determine the probability distribution type of annual, seasonal and monthly precipitation in Japan. For annual precipitation, the log-Pearson type III (LP3) distribution provides the best fit to the observations with the generalized-extreme value (GEV), three-parameter lognormal (LN3) and Pearson type III (P3) distributions as potential alternatives. For seasonal precipitation, the P3 distribution shows the best fit to the observations of spring precipitation; the LP3 the best fit for summer and winter precipitation; and the LN3 the best fit for autumn precipitation with the LP3 as a potential alternative. For monthly precipitation, the P3 distribution fits the precipitation best for January, February, March, May, July, October and December; the LP3 for June; and the LN3 for April, August, September and November. The identified probability distribution types of annual, seasonal and monthly precipitation are basically consistent. Overall, the P3 and LP3 distributions are acceptable distribution types for representing statistics of precipitation in Japan with the LN3 distribution as a potential alternative.     

Spatio-temporal heterogeneity and changes in extreme precipitation over eastern Himalayan catchments India

This study draws attention on the extreme precipitation changes over the eastern Himalayan region of the Teesta river catchment. To explore the precipitation variability and heterogeneity, observed (1979–2005) and statistically downscaled (2006–2100) Coupled Model Intercomparison Project Phase Five earth system model global circulation model daily precipitation datasets are used. The trend analysis is performed to analyze the long-term changes in precipitation scenarios utilizing non-parametric Mann–Kendall (MK) test, Kendall Tau test, and Sen’s slope estimation. A quantile regression (QR) method has been applied to assess the lower and upper tails changes in precipitation scenarios. Precipitation extreme indices were generated to quantify the extremity of precipitation in observed and projected time domains. To portrait the spatial heterogeneity, the standard deviation and skewness are computed for precipitation extreme indices. The results show that the overall precipitation amount will be increased in the future over the Himalayan region. The monthly time series trend analysis based results reflect an interannual variability in precipitation. The QR analysis results showed significant increments in precipitation amount in the upper and lower quantiles. The extreme precipitation events are increased during October to June months; whereas, it decreases from July to September months. The representative concentration pathway (RCP) 8.5 based experiments showed extreme changes in precipitation compared to RCP2.6 and RCP4.5. The precipitation extreme indices results reveal that the intensity of precipitation events will be enhanced in future time. The spatial standard deviation and skewness based observations showed a significant variability in precipitation over the selected Himalayan catchment.     

Analysis of trends of annual and seasonal precipitation from 1956 to 2000 in Guangdong Province,China

Abstract

The trends of annual, seasonal and monthly precipitation in southern China (Guangdong Province) for the period 1956–2000 are investigated, based on the data from 186 high-quality gauging stations. Statistical tests, including Mann-Kendall rank test and wavelet analysis, are employed to determine whether the precipitation series exhibit any regular trend and periodicity. The results indicate that the annual precipitation has a slightly decreasing trend in central Guangdong and slight increasing trends in the eastern and western areas of the province. However, all the annual trends are not statistically significant at the 95% confidence level. The average precipitation increases in the dry season in central Guangdong, but decreases in the wet season, meaning that the precipitation becomes more evenly distributed within the year. Furthermore, the analysis of monthly precipitation suggests that the distribution of intra-annual precipitation changes over time. The results of wavelet analysis show prominent precipitation with periods ranging from 10 to 12 years in every sub-region in Guangdong Province. Comparing with the sunspot cycle (11-year), the annual precipitation in every sub-region in Guangdong province correlates with Sunspot Number with a 3-year lag. The findings in this paper will be useful for water resources management.

Editor Z.W. Kundzewicz; Associate editor Sheng Yue

Citation Dedi Liu, Shenglian Guo, Xiaohong Chen and Quanxi Shao, 2012. Analysis of trends of annual and seasonal precipitation from 1956 to 2000 in Guangdong Province, China. Hydrological Sciences Journal, 57 (2), 358–369.     

The spatial and temporal characteristics of the seasonal precipitation over India

Three extreme cases of seasonal precipitation over 31 contiguous meteorological subdivisions of India were decomposed into orthogonal components using eigenvector technique to examine their spatial and temporal behaviour. The first two eigenvectors combined were found to represent the seasonal precipitation over India to a sufficient high degree of accuracy retaining 90–95 percent of the total variance. These two components show high spatial similarity in all the three cases of the precipitation examined.The first component is characterized by a coherent variation over the area with large coherent variation over the north-east India, Central India and the west coast of India. The coefficients of the component show annual behaviour with the peak values generally reached during July. This component is representative of the summer monsoon (June–September) mode.The second component characterizes out of phase variation in precipitation between Central India, adjoining parts of the area, and peninsular India. The coefficients of the component show the semi-annual oscillation. It appears that the role of the second eigenvector might be to represent regionality of the seasonal march of the monsoon rain.     

A global survey on the seasonal variation of the marginal distribution of daily precipitation

To characterize the seasonal variation of the marginal distribution of daily precipitation, it is important to find which statistical characteristics of daily precipitation actually vary the most from month-to-month and which could be regarded to be invariant. Relevant to the latter issue is the question whether there is a single model capable to describe effectively the nonzero daily precipitation for every month worldwide. To study these questions we introduce and apply a novel test for seasonal variation (SV-Test) and explore the performance of two flexible distributions in a massive analysis of approximately 170,000 monthly daily precipitation records at more than 14,000 stations from all over the globe. The analysis indicates that: (a) the shape characteristics of the marginal distribution of daily precipitation, generally, vary over the months, (b) commonly used distributions such as the Exponential, Gamma, Weibull, Lognormal, and the Pareto, are incapable to describe “universally” the daily precipitation, (c) exponential-tail distributions like the Exponential, mixed Exponentials or the Gamma can severely underestimate the magnitude of extreme events and thus may be a wrong choice, and (d) the Burr type XII and the Generalized Gamma distributions are two good models, with the latter performing exceptionally well.     

Soil Carbon and Nutrient Accumulation under Forest Plantations in Jharkhand State of India

The decrease and degradation of the tropical forests affect not only the production of timber but also the global environment in a large scale. The ability of soil to sustain and its supply of nutrients to a growing forest are controlled by a complex of biogeochemical processes. The purpose of the present study aims to assess the degraded forest fringe areas, to promote plantations of various types and to evaluate their impacts on the soil nutrients and carbon content accumulation. The soil organic carbon (SOC) and nutrient content were evaluated and compared between plantations of mixed native species (MNS), some native tree species as Shorea robusta, Dalbergia sissoo, Dendrocalamus spp., certain agro‐forestry species and some exotic varieties. The impacts of the plantations on the SOC and the nutrients were firstly analyzed through comprehensive chemical analyses and the results were compared with the soil samples collected prior to plantation forestry. Significant changes were observed in SOC content, in nutrients, and in amounts of exchangeable cations. Soil carbon levels were highest under the MNS, Dendrocalamus and Tectona grandis stands and lowest under D. sissoo and Terminalia arjuna. Total N showed highest levels under Dendrocalamus and Pongamia pinnata and significantly higher in stands of native species; lowest total N level was observed in D. sissoo plantations. The C/N ratios of the soil varied between 9.2 and 13.5 among the exchangeable cations. Ca²⁺ recorded the maximum levels and Na⁺ showed the lowest levels.     

Assessment of GCM simulations of annual and seasonal rainfall and daily rainfall distribution across south‐east Australia

Global warming can potentially lead to changes in future rainfall and runoff and can significantly impact the regional hydrology and future availability of water resources. All the large‐scale climate impact studies use the future climate projections from global climate models (GCMs) to estimate the impact on future water availability. This paper presents results from a detailed assessment to investigate the capability of 15 GCMs to reproduce the observed historical annual and seasonal mean rainfalls, the observed annual rainfall series and the observed daily rainfall distribution across south‐east Australia. The assessment shows that the GCMs can generally reproduce the spatial patterns of mean seasonal and annual rainfalls. However, there can be considerable differences between the mean rainfalls simulated by the GCMs and the observed rainfall. The results clearly show that none of the GCMs can simulate the actual annual rainfall time series or the trend in the annual rainfall. The GCMs can also generally reproduce the observed daily (ranked) rainfall distribution at the GCM scale. The GCMs are ranked against their abilities to reproduce the observed historical mean annual rainfall and daily rainfall distribution, and, based on the combined score, the better GCMs include MPI‐ECHAM5, MIUB, CCCMA_T47, INMCM, CSIRO‐MK3·0, CNRM, CCCMA_T63 and GFDL 2·0 and those with poorer performances are MRI, IPSL, GISS‐AOM, MIROC‐M, NCAR‐PCM1, IAP and NCAR‐CCSM. However, the reduction in the combined score as we move from the best‐ to the worst‐performing GCMs is gradual, and there is no evident cut‐off point or threshold to remove GCMs from climate impact studies. There is some agreement between the results here and many similar studies comparing the performance of GCMs in Australia, but the results are not always consistent and do significantly disagree with several of the studies. Copyright © 2010 John Wiley & Sons, Ltd.     

Spatial distribution and temporal trends in daily and monthly precipitation concentration indices in the upper reaches of the Huai River, China

Understanding precipitation variations on various timescales and their correlations is important for assessment of flood risk and utilization of water resources. In this study, the spatial and temporal patterns of precipitation concentration in the upper reaches of the Huai River, China, were investigated using two indices: the precipitation concentration index (PCI) and the concentration index (CI) for measuring seasonality and daily heterogeneity using monthly and daily precipitation series, respectively. In particular, the trends of PCI and CI were tested by the Mann–Kendall method, and relationship among PCI, CI and percentage of precipitation contributed by the rainiest days was analyzed by the linear correlation analysis. The results show a significant seasonality of the rainfall distribution and very in homogeneous temporal distribution of the daily rainfall in the south part of the study area, especially in the three reservoirs. Positive trends in the PCI and CI were found at most stations, although none of the PCI trends were statistically significant. Daily heterogeneity of the rainfall in a year is highly correlated with the heavy rainfall amount of the 15 % rainiest days, and seasonality in rainfall distribution over a year can be partly explained by the daily rainfall heterogeneity.     

Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima

The conventional approach to the frequency analysis of extreme precipitation is complicated by non-stationarity resulting from climate variability and change. This study utilized a non-stationary frequency analysis to better understand the time-varying behavior of short-duration (1-, 6-, 12-, and 24-h) precipitation extremes at 65 weather stations scattered across South Korea. Trends in precipitation extremes were diagnosed with respect to both annual maximum precipitation (AMP) and peaks-over-threshold (POT) extremes. Non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with model parameters made a linear function of time were applied to AMP and POT respectively. Trends detected using the Mann–Kendall test revealed that the stations showing an increasing trend in AMP extremes were concentrated in the mountainous areas (the northeast and southwest regions) of South Korea. Trend tests on POT extremes provided fairly different results, with a significantly reduced number of stations showing an increasing trend and with some stations showing a decreasing trend. For most of stations showing a statistically significant trend, non-stationary GEV and GPD models significantly outperformed their stationary counterparts, particularly for precipitation extremes with shorter durations. Due to a significant-increasing trend in the POT frequency found at a considerable number of stations (about 10 stations for each rainfall duration), the performance of modeling POT extremes was further improved with a non-homogeneous Poisson model. The large differences in design storm estimates between stationary and non-stationary models (design storm estimates from stationary models were significantly lower than the estimates of non-stationary models) demonstrated the challenges in relying on the stationary assumption when planning the design and management of water facilities. This study also highlighted the need of caution when quantifying design storms from POT and AMP extremes by showing a large discrepancy between the estimates from those two approaches.     

The spatial and temporal analysis of precipitation concentration and dry spell in Qinghai,northwest China

Understanding precipitation variations from various aspects is important for the assessment of drought risk and the utilization of water resources. The precipitation concentration index (PCI) and the concentration index (CI) were used to investigate/quantify the heterogeneity of the monthly and daily rainfall in Qinghai province that is part of northwestern China, respectively. The precipitation concentration in Qinghai shows a significant irregularity of the monthly rainfall distribution and highly homogeneous distribution of the daily rainfall. It is found that PCI and CI show negative trends at most stations. Meanwhile, the spatial and temporal variation of nine dry spell (DS) indices are analyzed. From the spatial perspective, drought in the northwestern area is much severer than that in other areas of Qinghai. According to the results of temporal analysis by using the Mann–Kendall test, the number of very long DSs, maximum length of DS, mean length of DSs, and the total dry days of extreme DS all decrease. All these results verify that the warm dry climatic pattern in Qinghai can be changed into the warm wet climatic pattern.     

Identification of the best architecture of a multilayer perceptron in modeling daily total ozone concentration over Kolkata,India

Autoregressive neural network (AR-NN) models of various orders have been generated in this work for the daily total ozone (TO) time series over Kolkata (22.56°N, 88.5°E). Artificial neural network in the form of multilayer perceptron (MLP) is implemented in order to generate the AR-NN models of orders varying from 1 to 13. An extensive variable selection method through multiple linear regression (MLR) is implemented while developing the AR-NNs. The MLPs are characterized by sigmoid non-linearity. The optimum size of the hidden layer is identified in each model and prediction are produced by validating it over the test cases using the coefficient of determination (R ²) and Willmott’s index (WI). It is observed that AR-NN model of order 7 having 6 nodes in the hidden layer has maximum prediction capacity. It is further observed that any increase in the orders of AR-NN leads to less accurate prediction.     

Spatio-temporal dynamics of sediment transport in lesser Himalayan catchments,India

Sediment transport from mountainous to lowland areas is considered one of the most important geomorphological processes. In the present study, variations in transported sediment loads and dissolved loads have been studied over 3 years (2008–2011) for two forested catchments located in the Lesser Himalayan region of India. Seasonal and annual suspended sediment flux was strongly influenced by amounts of rainfall and streamflow. On average, 93% of annual load was produced during the monsoon, of which 62–78% occurred in only five peak events. Sediment production by the degraded forest catchment (Bansigad) was 1.9-fold (suspended sediment load) to 5.9-fold (bedload) higher than the densely forested catchment (Arnigad). The dissolved organic matter potentially influences total dissolved solids in the stream. Heavy rainfall triggers both stream discharge and landslides, which lead to higher bedload transport. Total denudation rates for Arnigad and Bansigad were estimated at 0.68 and 1.02 mm?year^?1, respectively.     

Spatio-temporal downscaling of projected precipitation in the 21st century: indication of a wetter monsoon over the Upper Mahanadi Basin,India

An attempt is made to assess the future trend of spatio-temporal variation of precipitation over a medium-sized river basin. The Statistical Downscaling Model (SDSM, version 4.2) is used to downscale the outputs from two general circulation models (GCMs) for three future epochs: epoch-1 (2011–2040), epoch-2 (2041–2070) and epoch-3 (2071–2100). Considering the Upper Mahanadi Basin as a test bed, the study results indicate a “wetter” monsoon (June–September) and the annual increase in precipitation is 12% during epoch-3, which is consistent for both GCMs. Monthly analyses indicate that the precipitation totals are likely to increase and the magnitude of increase is greater during monsoon months than non-monsoon months. The number of month-wise daily extremes increases in most months in the year. However, the maximum percentage increase (with respect to baseline period, 1971–2000) in the number of extreme events is found in the non-monsoon months (specifically before and after the monsoon).     

大地电场台站日变幅年度变化趋势分析

为了直观展示大地电场日变幅年度变化趋势,获取多年尺度下数据变化形态及特征,选取2012-2015年,4个地电台网8个存在潮汐地电场变化的地电台站观测数据,进行去除台阶、异常数据及滤波处理,计算地电场日变幅。结果显示：①2012-2013年大多数台站存在春冬低、夏秋高的日变幅趋势性特征;②2014-2015年存在几种不同日变幅年度变化趋势,同时同一台站不同测道间日变幅变化趋势存在差异性,该变化趋势和差异性的存在可能与地下介质结构变化和介质的非均匀性有一定关系。     

Spatial and temporal variability of annual and seasonal precipitation over the desert region of China during 1951–2005

The spatial and temporal variations of precipitation in the desert region of China (DRC) from 1951 to 2005 were investigated using a rotated empirical orthogonal function (REOF), the precipitation concentration index (PCI) and the Mann–Kendall trend test method (M‐K method). In addition, the association between variation patterns of precipitation and large‐scale circulation were also explored using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data. The results indicated that the spatial pattern of precipitation was primarily the local climate effect significant type, with the first three EOFs explaining a total of 55·3% of the variance, and the large‐scale climate system effect type, which explained 9·8% of the variance. Prior to the 1970s, the East Asian summer monsoon was stronger, which resulted in abundant precipitation in the Inner Mongolia region. Conversely, the climate of the Xinjiang region was controlled by westerly circulation and had lower precipitation. However, this situation has been reversed since the 1980s. It is predicted that precipitation will decrease by 15–40 and 0–10 mm/year in the Inner Mongolia plateau and southern Xinjiang, respectively, whereas it will likely increase by 10–40 mm/year in northern Xinjiang. Additionally, 58–62% of the annual rainfall occurred during summer in the DRC, with precipitation increasing during spring and summer and decreasing in winter. The intra‐annual precipitation is becoming uniform, but the inter‐annual variability in precipitation has been increasing in the western portions of the DRC. The probability of precipitation during the study period increased by 30% and 22·2% in the extreme‐arid zones and arid zones, respectively. Conversely, the probability of precipitation during the study period decreased by 18·5% and 37·5% in the semi‐arid zones and semi‐wet zones, respectively. It is predicted that the northwest portion of the DRC will become warmer and wetter, while the central portion will become warmer and drier and the northeast portion will be subjected to drought. Copyright © 2010 John Wiley & Sons, Ltd.     

Spatio-temporal interpolation of precipitation during monsoon periods in Pakistan

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

Spatial variability and interpolation of daily precipitation amount

Daily precipitation amounts show spatial variation over sub-continential regions. Point measurements, representative for regions of land, have to be interpolated towards unobserved locations. In this study four days in 1984 were selected to investigate the spatial variability of daily precipitation amount in North-western Europe in relation to the meteorological conditions. Data were interpolated using Kriging. Crossvalidation was used to compare interpolated values with measured values. Large differences in the spatial structure of daily precipitation amount are obsered as a result of different meterological conditions. Stratification of the study area into a coastal, a mountainous and an interior stratum proved to be successful, reducing the Mean Squared Error of Prediction with up to 55%.     

Spatial variability and interpolation of daily precipitation amount

Daily precipitation amounts show spatial variation over sub-continential regions. Point measurements, represntative for regions of land, have to be interpolated towards unobserved locations. In this study four days in 1984 were selected to investigate the spatial variability of daily precipitation amount in north-western Europe in relation to the meteorological conditions. Data were interpolated using kriging. Crossvalidation was used to compare interpolated values with measured values. Large differences in the spatial structure of daily precipitation amount are observed as a result of different meteorological conditions. Stratification of the study area into a coast, a mountain and an interior stratum proved to be successful, reducing the Mean Squared Error of Prediction with up to 55%.This article was inadvertently printed in SHH 6(3) 1992 without figures and figure legends. The article is being reprinted in this issue in complete form. The editor apologizes for this error in publication.     

Geomagnetic solar and lunar daily variations at Alibag,India

Geomagnetic solar and lunar daily variationsS andL, at Alibag, India are derived, by the well-known Chapman-Miller method, from the series of homogeneous mean hourly magnetic data of the years 1932 to 1972. The data for all the three elements — declinationD and horizontal and vertical intensitiesH andZ — are analysed, by dividing the data suitably for a study of the seasonal variations, the effect of the changes in the solar and magnetic activities onS andL, the oceanic dynamo contribution toL, and their interactions with each other. The main results are as follows.

1. ForS the daily pattern and its seasonal progression conform to the type expected from a northern-hemisphere station. On the other hand, the amplitudes of all the four harmonics ofL systematically have higher values in winter, and inD andZ the harmonics show large phase differences between summer and winter. The pattern ofL in winter suggests that the lunar current system consists of a single set of vortices in the summer hemisphere rather than the conventional vortices, one set in each of the hemispheres.
2. Solar-cycle modulation on the solar ranges as well as on the amplitudes of the first three harmonics ofS is greater than that expected solely from the increase in E-region conductivity, whereas the corresponding modulation onL is comparable to that on the E-region conductivity.
3. With increasing magnetic activity the first harmonic ofS shows an increase, and the first three harmonics ofL indicate a general decrease, in amplitude.
4. Of the variability inS 96%, but inL only 32%, is found to be accounted for by the combined effect of the variations in the solar and magnetic activities.

     

Annual and seasonal fluctuations of precipitation and streamflow in the Aconcagua River basin, Chile

The El Niño-Southern Oscillation (ENSO) phenomenon has been shown to influence dramatically precipitation and streamflow in tropical western South America. The statistical properties of annual and winter precipitation totals and streamflow characteristics in the Aconcagua River basin, in temperate central Chile, are investigated in such a way as to permit the identification of flood- and drought-generating processes and their possible linkages to upset behavior in the tropical Pacific. Despite the considerable distance to those regions generally associated with ENSO events, the phenomenon produces marked effects upon the various physical processes which govern the surface hydrometeorology of the study area. El Niño years result in significant increases in annual and winter precipitation, particularly along the coastal margin. The likelihood of rain or rain-on-snow flooding, in the succeeding winter, increases, as does the size of spring snowmelt in the southern summer, 1 year after the upset conditions in the tropical region. Annual low flows are of higher magnitude and occur earlier in the year than is usual.