Distribution Of Monthly Rainfall Research Articles

Spatio-temporal analysis of rainfall trends over a maritime state (Kerala) of India during the last 100 years

Kerala, a maritime state of India is bestowed with abundant rainfall which is about three times the national average. This study is conducted to have a better understanding of rainfall variability and trend at regional level for this state during the last 100 years. It is found that the rainfall variation in northern and southern regions of Kerala is large and the deviation is on different timescales. There is a shifting of rainfall mean and variability during the seasons. The trend analysis on rainfall data over the last 100 years reveals that there is a significant (99%) decreasing trend in most of the regions of Kerala especially in the month of January, July and November. The annual and seasonal trends of rainfall in most regions of Kerala are also found to be decreasing significantly. This decreasing trend may be related to global anomalies as a result of anthropogenic green house gas (GHG) emissions due to increased fossil fuel use, land-use change due to urbanisation and deforestation, proliferation in transportation associated atmospheric pollutants. We have also conducted a study of the seasonality index (SI) and found that only one district in the northern region (Kasaragod) has seasonality index of more than 1 and that the distribution of monthly rainfall in this district is mostly attributed to 1 or 2 months. In rest of the districts, the rainfall is markedly seasonal. The trend in SI reveals that the rainfall distribution in these districts has become asymmetric with changes in rainfall distribution.

Change in Sahelian Rivers hydrograph: The case of recent red floods of the Niger River in the Niamey region

Changes in the hydrological regime of Sahelian Rivers are considered based upon the example of the Middle Niger River and its exceptional flood in 2010 near the city of Niamey. It is shown that rainfall in 2010 was only average with respect to the long term record, with neither the monthly rainfall distribution in terms of the amount of rainfall nor the distribution of rainy events changing significantly in the last few decades. Particularly, no increase in the number of extreme rainfall events is observed.In spite of this, the Niger River's right bank tributaries have shown a sharp increase in runoff since the 1970s, which is still ongoing, and has resulted in a modification of the Niger River's regime from a single hydrograph to a two flood hydrograph, the local flood, occurring during the rainy season being the more pronounced one. This modification is likely due to an increase of bare soils and crusted soil areas as a consequence of human pressure, resulting mostly from the spatial extension of crop areas and the shortening of fallow periods. Changes in connectivity of the river networks on both banks of the Niger such as endorheism bursting events also caused an increase in the contributing basin area. Policy makers should be alerted to the effects of intensive cropping, land clearing and overgrazing in some areas, on the hydrological regimes of Sahelian Rivers.

Trend detection in rainfall and evaluation of standardized precipitation index as a drought assessment index for rice–wheat productivity over IGR in India

AbstractThe frequency and intensity of meteorological droughts over the Indo‐Gangetic Region (IGR) of India pertaining to the rice crop during kharif season (June to July to October to November) and the wheat crop during the rabi season (November to December to March) were assessed using the standardized precipitation index (SPI). The monthly distribution of rainfall is more crucial than the cumulative seasonal rainfall on rice–wheat (RW) productivity. Consequently, an attempt was made to measure the effectiveness of using monthly SPI from June to September to assess drought on RW productivity over five major RW growing states of IGR in India. An attempt is also made to test the use of monthly SPI for the early kharif rice and rabi wheat forecasts for these states. The long‐term (1906–2005) mean annual rainfall of IGR is 1099.1 mm with a standard deviation of 115.7 mm and a coefficient of variation of 10.5%. It was observed that the kharif rice productivity index and monthly SPI from June to September have a significant (R2 = 0.44) multiple regression at 0.001 level over IGR. It was also observed that in the Indo‐Gangetic Region, the wheat productivity index and monthly SPI (June to September) have an insignificant (R2 = 0.21) multiple regression. It indicated that the monthly distribution of monsoon rainfall in terms of the SPI accounted for 44% yield variability in rice and 21% yield variability in wheat. Thus, these indices may be used for forecasting the productivity of the RW system over IGR states in India. Copyright © 2010 Royal Meteorological Society

Comparing water-vegetative indices for rice ( Oryza sativa L.)–wheat ( Triticum aestivum L.) drought assessment

Drought indices (DI) are an useful tool for assessing different sectarian droughts. Standardized Precipitation Index (SPI) has been used worldwide to assess/monitor the onset, active phase, cessation and severity of drought. Normalized Difference Vegetation Index (NDVI) provides a comprehensive vegetation dynamics, which directly linked with rainfall received in a particular region. Indo-Gangetic Region (IGR), providing employment and livelihood to tens of millions of rural families directly or indirectly and rice ( Oryza sativa L.)–wheat ( Triticum aestivum L.) (RW) system of the Indo-Gangetic Plains (IGP) contributes 80% of the total cereal production and is critical to food security of the region. This study tries to verify the applicability of water-vegetative indices viz., SPI, Rainfall Index (RI) and NDVI for drought assessment of rice–wheat system productivity over IGR-India. The relationship between monsoon rainfall and NDVI shows that at around 1100 mm rainfall, the NDVI reached saturation point and no further significant increase in NDVI with increase of rainfall is noticed. Even though, there was a positive correlation of seasonal monsoon rainfall and average NDVI, conflicting results are noticed between monthly distribution of rainfall and monthly anomaly of NDVI over IGR States. It is noticed that June dif NDVI (actual NDVI–mean NDVI) contributes more to rice productivity followed by July. However, the combined effect of June, July and August, explains 15% of the variation of Kharif Rice Productivity Index (KRPI). As far as wheat is concerned, statistically significant relation was found between Wheat Productivity Index (WPI) and anomaly NDVI during December–March. This explains 35% of the variability in WPI.

Entropy, consistency in rainfall distribution and potential water resource availability in Australia

AbstractUnderstanding the variability in monthly rainfall amounts is important for the management of water resources. We use entropy, a measure of variability, to quantify the rainfall variability in Australia. We define the entropy of stable rainfall (ESR) to measure the long‐term average rainfall variability across the months of the year. The stations in northern Australia observe substantially more variability in rainfall distributions and stations in southern Australia observe less variability in rainfall distribution across the months of the year. We also define the consistency index (CI) to compare the distribution of the monthly rainfall for a given year with the long‐term average monthly rainfall distribution. Higher value of the CI indicates the rainfall in the year is consistent with the overall long‐term average rainfall distribution. Areas close to the coastline in northern, southern and eastern Australia observe more consistent rainfall distribution in individual years with the long‐term average rainfall distribution. For the studied stations, we categorize the years into different potential water resource availability on the basis of annual rainfall amount and CI. For almost all Australian rainfall stations, El Niño years have a greater risk of having below median and relatively inconsistent rainfall distribution than La Niña years. The results may be helpful for developing area‐specific water usage strategies. Copyright © 2011 John Wiley & Sons, Ltd.

Recent changes in rainfall characteristics and their influence on thresholds for debris flow triggering in the Dolomitic area of Cortina d'Ampezzo, north-eastern Italian Alps

Abstract. In this paper, we examine variations in climate characteristics near the area of Cortina d'Ampezzo (Dolomites, Eastern Italian Alps), with particular reference to the possible implications for debris-flow occurrence. The study area is prone to debris-flow release in response to summer high-intensity short-duration rainfalls and, therefore, it is of the utmost importance to investigate the potential increase in debris-flow triggering rainfall events. The critical rainfall threshold is agreed to be a crucial triggering factor for debris-flows. Data from a monitoring system, placed in a catchment near Cortina (Acquabona), show that debris-flows were triggered by rainfalls with peak rainfall intensities ranging from 4.9 to 17.4 mm/10 min. The analyses of meteorological data, collected from 1921 to 1994 at several stations in the study area, show a negative trend of annual rainfall, a considerable variation in the monthly rainfall distribution, and an increase in the temperature range, possibly related to global climate changes. Moreover, high-intensity and short-duration rainfall events, derived from data collected from 1990 and 2008, show an increase in exceptional rainfall events. The results obtained in a peak-over-threshold framework, applied to the rainfall data measured at the Faloria rain gauge station from 1990 to 2008, clearly show that the interarrival time of over-threshold events computed for different threshold values decreased in the last decade. This suggests that local climatic changes might produce an increase in the frequency of rainfall events, potentially triggering debris flows in the study area.

Impacts of El Nino-Southern Oscillation events on China’s rice production

This paper aims to demonstrate the relationships between ENSO and rice produc- tion of Jiangxi province in order to identify the reason that ENSO might have little effect on Chinese rice production. Using a data set with measures of Jiangxi's climate and rice pro- duction, we find the reason that during 1985 and 2004 ENSO's well correlated with rainfall did not promote Chinese rice production. First, the largest effects of ENSO mostly occur in the months when there is no rice in the field. Second, there is almost no temperature effect. Fi- nally, the monthly distribution of rainfall is almost the same in ENSO and neutral years be- cause the largest effects are during months when there is the least rain. In addition, due to the high irrigation share and reliable and effective irrigation facilities of cultivated land, China's rice production is less climate-sensitive.

Rainfall trends in the KwaZulu‐Natal Drakensberg region of South Africa during the twentieth century

AbstractThis study assesses long‐term rainfall records in the KwaZulu‐Natal Drakensberg, South Africa's most valuable source of surface runoff. Records from 11 stations covering the Drakensberg region in South Africa indicate that no statistically significant trend in interannual variability existed during the last half of the twentieth century. Annual rainfall in the Drakensberg is highly seasonal, and analysis of monthly rainfall indicates an increase in the variability of the distribution of monthly rainfall and the strengthening of rainfall seasonality in the Drakensberg through a significant decrease in autumn rainfall. The El Niño/Southern Oscillation (ENSO) influences summer rainfall variability of the KwaZulu‐Natal Drakensberg, and a strong correlation also exists between summer rainfall and the Southern Oscillation Index (SOI) for preceding periods. This correlation between summer rainfall and ENSO events suggests that changes in the frequency and intensity of the ENSO should affect the rainfall in the Drakensberg. The lagged correlation between summer rainfall in the Drakensberg and the SOI could be used as an indicator for seasonal forecasting. Copyright © 2008 Royal Meteorological Society

THE POTENTIAL OF RAINFALL AND ITS IMPACT TO GROUNDWATER STORAGE IN JAVA ISLAND

The objectives of the study are to map the distribution of rainfall in Java, to analyze its potential and the impact to groundwater storage. To achieve those goals, rainfall distribution is mapped using isohyet method. From the average distribution of monthly rainfall, the annual potential of rainwater on every watershed was calculated. Afterwards, the groundwater storage was analyzed and counted by applying the water balance concept. The results of the study show that the mean of the highest annual rainfall is 4082 mm which occurs on Cisadane- Ciliwung watershed and the lowest one is 1421 mm on Citarum Hilir watershed. From the rainfall potential, Cisadeg-Cikuningan watershed has the highest rainfall potential at the amount of 25342 million m31month and Grindulu Panggul watershed has the lowest potential at the amount of 3678 million m3lmonth. Meteorologically, Cisadeg-Cikuningan watershed has the highest groundwater storage at the amount of 6088 million m31yearand the lowest amount of it occurs on Madura watershed at 78 million m3lyear.

Long-term effect of nutrient management and cropping system on cotton yield and soil fertility in rainfed vertisols

The effect of different N, P and K combinations with and without FYM on cotton productivity and the changes in soil fertility of three rainfed cotton based cropping systems were analyzed through a field experiment, conducted for 11 yr. Monoculture of G. arboreum (Asiatic) cotton, out-yielded monoculture of G. hirsutum (upland) cotton in 9 out of 11 yr. except in years of heavy rainfall. G. hirsutum cotton in rotation with sorghum produced 8% more yield than monocultured G. hirsutum. Significant responses to N and P application were consistently observed, while the response to K was inconsistent. Substituting half the N dose with FYM, gave 162 kg/ha and 222 kg/ha more seed cotton at low (N60 P13 K25) and high (N90 P20 K38) doses respectively. Also substituting half the N dose with FYM built up soil organic C from 4.2 to 5.4 g/kg, and increased available P from 4.5 to 6.4 mg/kg. The variations in the performance of the cropping systems and the response to fertilizers could not be accounted for by total rainfall alone. However, there was significant positive correlation between cotton yield and post September rainfall. Multiple regression equations were fitted to estimate G. arboreum and G. hirsutum yields based on the monthly distribution of rainfall.

Effects of the southern oscillation on the probability for climatic categories of monthly rainfall, in a semi-arid region in the southern mid-latitudes

In many regions of the world, planning agricultural and water management activities is usually done based on probabilities for monthly rainfall, taking on values on specified intervals of values. These intervals of monthly rainfall amounts are commonly grouped into three categories: drought, normal rainfall, and abundant rainfall. Changes in the probabilities for occurrence of monthly rainfall amounts within these climatic rainfall categories will influence the decisions farmers and water managers will take (for example, crops to cultivate, flood preparedness, and operations of water reservoirs). This research explores the changes produced by the SO (Southern Oscillation) on the probability that the areal average of monthly rainfall (AAvMR) takes on values belonging to specified climatic rainfall categories. The semi-arid region under study is a major agricultural region in central Argentina; weather effects on agriculture in this region influence the world market of several crops. The evolution of the Southern Oscillation was divided into three phases: LSOI (low Southern Oscillation index phase, that includes ENSO events), NSOI (neutral SOI phase), and HSOI (high SOI phase that includes La Niña–SO events). The following are the criteria defining the three phases of the SO: (1) low SOI (ENSO), where the five-month moving average of the SO index, SOI, is less than −0.5 standard deviation during at least five consecutive months, and is equal to or less than −1 standard deviation during at least one month; (2) high SOI (La Niña–SO), where the SOI is greater than 0.5 standard deviation during at least five consecutive months, and is equal to or greater than 1 standard deviation during at least one month; and (3) neutral SOI (transition between extremes), where the SOI does not correspond to low SOI nor to high SOI. It was found that the Southern Oscillation influences the probability distribution of monthly rainfall only in four months of the year. Findings show that monthly rainfall has a complex response to the evolution of the SO. The response is not restricted to higher probability for occurrence of abundant rainfall or drought categories during low SOI (ENSO) or high SOI (La Niña–SO) episodes, respectively. The LSOI (ENSO) phase influences the AAvMR in several ways: depending on the month, it increases or decreases the probability of the abundant rainfall category. LSOI (ENSO) also increases or decreases, depending on the month, the probability of the normal rainfall category. It also decreases the probability that AAvMR takes on values in the drought category. A similar kind of complex response of monthly rainfall amounts occurs when the active phase is the HSOI (La Niña–SO). The responses are: (1) the probability of the category `drought' increases only in three months of the year, (2) increase or decrease of the probability of the normal rainfall category, depending on the month, and (3) decrease of the probability of the abundant rainfall category. Finally, the effects of NSOI (neutral phase of the SO) are not negligible. Depending on the month, NSOI episodes increase or decrease the probability of drought, or abundant rainfall, or normal rainfall categories.

Using the seasonal and temporal Precipitation concentration index for characterizing the monthly rainfall distribution in Spain

Summary The concentration of the rainfall in a year is an important aspect of the climate. An unbalanced distribution of rainfall evokes periods of rainfall excess and periods of drought which make plant and crop growth difficult. Rainfall concentration needs to be considered in the assessment and the prediction of soil losses by water erosion. A statistical derived index, known as the Precipitation Concentration Index is presented to be used in quantifying the relative distribution of the rainfall patterns. Based on the available data sets, two different calculation procedures were used for deriving the Precipitation Concentration Index (Seasonal and Temporal). The application of the two procedures on the rainfall data of two meteorological stations from different climatological regions revealed how the two methods can be used in quantifying the seasonal and temporal concentration of the rainfall. The rainfall data from meteorological stations situated in a central transect of Spain were used in this investigation. From the observed results, it can be concluded that in the Southern part of the transect, the concentration of the rainfall is not a seasonal effect (not strongly confined by a typical dry or wet period) but a temporal effect (bounded to the unreliable, unpredictable character of the rainfall).

Some hydrometeorological studies over Teesta basin in north Bengal

Based on data of 40 rainfall stations located within and in the neighbourhood of Teesta basin in north Bengal for period ranging between 7 & 23 years, hydrometeorological informations of the spatial distribution of monthly rainfall, umber of rainy days and extreme rainfall distribution over Teesta basin have been determined and presented on basin maps for the months of May to October.
 The average monthly areal precipitation depth as wi1l as extreme areal precipitation depth for a day have been discussed for 6 sectors of the basin. The pentads rainfall for 22 selected stations in the catchment during May to October have also been evaluated and discussed.

MONTHLY PRECIPITATION DISTRIBUTION: A COMPARATIVE INDEX

Modification of the Gibbs-Martin Index of Employment Diversification permits derivation of a precipitation concentration index (PCI) that characterizes the monthly concentration of precipitation on a scale that ranges from less than 10 for evenly distributed rainfall to 100 for extreme monthly rainfall distribution. The defined lower and upper limits of the index contrast to other statistical descriptions of precipitation distribution, which are open-ended. Mapped values of the PCI provide a good visual guide to relative monthly distribution of precipitation. Suggested applications of the index are related to both pedagogic and research applications.

Distribution of Monthly Rainfall in Northeast Thailand

Distribution of Monthly Rainfall in Northeast Thailand

Major climatological discontinuities in the monthly monsoon activity in the neightbourhood of theWestern Ghats

The major climatological discontinuities to the monsoon activity from July to August and from August to September in the neighbourhood of the Western Ghats have been studied in detail on the basis of a close network of raingauge stations and the role of the Western Ghats has been examined, The criterion used for defining the major climatological discontinuity is based on the quartiles of the monthly rainfall distribution, The Western Ghats appear to playa differential role. Since meteorological conditions are most favourable during July and become progressively less favourable with the advance of the summer monsoon season, the Western Ghats enhance rainfall substantially under favourable conditions, and decrease the rainfall substantially under relatively urifavourable conditions, and thus contribute to the major climatological discontinuities.

ON THE UTILITY OF MONTHLY DATA FOR THE DYNAMIC CLIMATOLOGY OF THE WORLD

Simple climatic data such as monthly atmospheric pressure, precipitation and temperature are found to be fairely effective to show the location of ITC, polar front and other important weather phenomena of dynamic nature. Figs. 3, 4, 5, and 6 are the examples of these data, while Figs. 1 and 2 show the daily location of all fronts and ITC extracted from IGY (1958) World Weather Maps. Low pressure axes drawn in Figs. 5 and 6 run along the borders of rainfall belts in the low latitude and therefore may be ragarded as NITC and SITC. IGY maps, however, reveal only one of them, mostly NITC. Even the temperature distribution reflects the seasonal shift of the rainfall belt, i.e. the zone of the equatorial westerlies. Areas where monthly temperature is higher than 30°C are shaded in Figs.3 and 4, which are seen to migrate with the ITC. Since small anticyclones are recongized in Fig.6 in the zone between two low pressure axes, east winds must also exist between the anticyclones and the SITC, besides the wellknown equatorial westerlies on the northern side of the anticyclones. Heavy rains are found only in the westerlies-zone. After checks with daily weather phenomena for one year (1950), monthly data are thus found out to be sometimes more eloquent than weather maps in expressing some global weather phenomena. They can be used for survey more extensive in time and space, in which we may to certain extent extrapolate our understanding from mere facts of distribution of monthly rainfall, temperature and pressure to the inferences of displacement of atmospheric structures such as ITC, polar front and others.

Gamma Distribution Probability Model for Asian Summer Monsoon Monthly Rainfall

Abstract Using data from 39 well-distributed and long-record stations over the area, we found gamma distribution to be the most suitable probability model from among the Pearsonian models that show good fit to monthly rainfall in the Asian summer monsoon. We show that the monthly rainfall distribution is not Gaussian and the simple square-root, cube-root, and logarithmic transformations are of limited utility for normalizing the rainfall distribution. A Craig type chart indicates that the rainfall distribution is a Type I distribution or a special or limiting case of this distribution; these distributions are fitted to monthly rainfall, and the goodness-of-fit is tested by the chi-square test. The gamma distribution (Pearson's Type III), which is a limiting case of Type I distribution and next, to the Gaussian distribution in simplicity, gives a good fit to monthly rainfall at all the stations in each of the summer monsoon months; the Kolmogorov-Smirnov test and the variance ratio test confirm this good f...

Ecology of Desert Plants. I. Observations on Germination in the Joshua Tree National Monument, California

Plant communities exist due to interaction between the individual members and between these and the environment. This introduces such a complexity, that a physiological analysis of the community as a whole seems impossible at present. But as the starting point of such an analysis the desert communities offer an unusually favorable opportunity. In the first place the vegetation cover is not closed, so that 'interactions between plants are greatly reduced, and their influence on each others' immediate surroundings is relatively small. Under such conditions direct correlations between plants (the influence of one plant on the other) are more easily found, as shown by Went ('42). This wide spacing of the plants is of special importance in germination, because that process tends to occur much more frequently in open areas than in a closed cover of existing vegetation. In still another respect, desert plants are particularly favorable experimental material. They are subjected to more extreme conditions than other plants, so that their responses can be expected to be geared to greater climatic differences. Therefore laboratory experiments are likely to show larger differences in response than when plants of more equitable climates are used. Finally, everything which happens in the desert vegetation can be rather easily attributed to distinct climatic occurrences such as a particular rain. With these considerations in mind a series of trips were made, during the years 1945-1947, to study the vegetation of the Joshua Tree National Monument, located 200 km. (130 miles) due east of Los Angeles. The altitude of the areas most commonly visited varies between 800 and 1500 m. (2500-5000 ft.). The San Bernardino and San Jacinto mountains shield the area from the climatic influence of the ocean. Along its west boundary the Little San Bernardino Mountains, reaching a height of 1700 m., separate the area from the Coachella Valley. From the west the altitude of the broad valleys of the National Monument falls gradually to 800 m. in the north and east, with intervening mountain ranges. The climate can best be described with the help of figures 1, 2 and 3. Climatic records are kept by the Cooperative Weather Station at Twentynine Palms, just north of the Monument at 650 m., and daily temperatures are recorded at Hidden Valley at 1400 m. by Mr. Randolph.' Annual rainfall at Twentynine Palms amounts to 136 mm. but at Hidden Valley and higher altitudes in general the rainfall is considerably greater, especially during July, August and September, when thunderstorms break over the mountains. Figure 1 shows the monthly distribution of rainfall, the number of cloudy days and the relative humidity in the afternoon at Twentynine Palms, with an indication of the seasonal differences in rainfall. The winter rains are fairly evenly distributed over the whole National Monument, but the summer rains are highly localized, as figure 2 shows. This figure gives the approximate location of rainbursts ac-

Centre of Gravity of Annual Rainfall

I AM glad to read Mr. Cook's reply to my remarks, but believe that my criticism cannot be dismissed as a mere a priori one, and that it goes to the root of the matter. It is true that Mr. Cook illustrated his proposal in a most exhaustive manner, and that he did not suggest that his method might be of service in comparing the rainfalls of places in quite different climatic regions. But the general reasoning in the first paragraph of my former letter cannot be both correct and incorrect. Assuming it to be correct, it follows directly that even if we confine our attention to the records for a single station we might have the same C.G. for two years which differed greatly from one another as regards the monthly distribution of rainfall. In such a case, what possible significance could attach to the position of the C.G.?