scholarly journals Variability and trend analysis of rainfall data of Jhalawar district of Rajasthan, India

2016 ◽  
Vol 8 (1) ◽  
pp. 116-121 ◽  
Author(s):  
Bhim Singh
Keyword(s):  
Standard Deviation ◽  
Trend Analysis ◽  
Coefficient Of Variation ◽  
Monsoon Rainfall ◽  
Annual Rainfall ◽  
Dry Period ◽  
South West ◽  
The Mean ◽  
Drought Occurrence ◽  
Sw Monsoon

An attempt has been made to study the variability and trends of annual and seasonal rainfall for the period of 38 years (1973-2010) for all seven tehsils of Jhalawar district of Rajasthan. The mean annual rainfall of the district was found to 910 mm with standard deviation 218 mm and coefficient of variation 24 per cent. Annual rainfall varied from about 831 mm in Khanpur to more than 1022 mm in the Pirawa tehsil of the district. The annual rainfall showed declined trend (-0.23 to -17.41 mm/year) in all seven tehsils of the district. The negative trends at Pirawa (17.407 mm/year), Manoharthana (11.595 mm/year) and Aklera (5.789 mm/year) are statistically significant at less than 0.001, 0.05 and 0.05 levels, respectively. During the study period maximum dry period was recorded during postmonsoon and winter. Also, for the entire 38 years period maximum dry months were recorded during December till April. August was normal month for about 87 per cent followed by July and June for about 84 per cent and 66 per cent respectively. It was evident that the onset of south-west (SW) monsoon took place in the month of June and chancesof drought occurrence during kharif season were very low. Hence, SW monsoon rainfall is found ideal for raising kharif crops like soybeans, urd, moong, jowar, maize, tomato, brinjal, chilli, okra, kharif onion, amaranth, rainfed green gram, red gram, castor, etc in the district.

scholarly journals Variability and Trend Analysis of Rainfall Data of Shillong and Agartala Stations of North East India

2020 ◽  
pp. 134-142
Author(s):  
Mirbana Lusick K. Sangma ◽  
Hamtoiti Reang ◽  
G. T. Patle ◽  
P. P. Dabral
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Winter Season ◽  
Summer Season ◽  
Annual Rainfall ◽  
Rainfall Time Series ◽  
North East ◽  
South West ◽  
Total Annual Rainfall ◽  
Sw Monsoon

This paper discusses the variability in rainfall and trend analysis of annual and seasonal rainfall time series of Shillong and Agartala stations located in the north-east region of India. Commonly used non-parametric statistical methods namely Mann-Kendall and Sen’s slope estimator was used to analyse the seasonal and annual rainfall time series. Statistical analysis showed less variation in annual and south-west monsoon rainfall for both Shillong and Agartala stations. In the total annual rainfall, the share of south-west (SW) monsoon, north-east (NE) monsoon, winter season and summer season rainfall was observed 64.60%, 13.22%, 1.40% and 20.80%, respectively for Shillong station of Meghalaya state. However, the contribution of SW monsoon, NE monsoon, winter season and summer season rainfall in the total annual rainfall was 59.59%, 9.55%, 1.14% and 29.72%, respectively for Agartala station of Tripura state. Non-significant increasing trends of rainfall was observed by 4.54 mm/year, 2.80 mm/year and 2.54 mm/year for annual, SW monsoon, and summer season, whereas, non-significant decreasing trends in rainfall for NE monsoon and winter season was observed with a magnitude of 1.83 mm/year and 1.63 mm/year for Shillong, Meghalaya during 1992 to 2017. Results also revealed that rainfall increased by 1.07 mm/year and 0.18 mm/year in SW monsoon and winter season whereas, rainfall decreased by 7.64 mm/year, 2.58 mm/year and 1.29 mm/year during annual, NE monsoon and summer season non-significantly during 1995 to 2019 in case of Agartala. The findings of present study will be useful for water management and crop planning in hill agriculture of Meghalaya and Tripura state of India.

scholarly journals Classification and Statistical Trend Analysis in Detecting Glaucomatous Visual Field Progression

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Cristiana Valente ◽  
Elisa D’Alessandro ◽  
Michele Iester
Keyword(s):  
Statistical Analysis ◽  
Standard Deviation ◽  
Visual Field ◽  
Trend Analysis ◽  
Open Angle Glaucoma ◽  
Mean Deviation ◽  
Threshold Strategy ◽  
Visual Field Progression ◽  
The Mean

Aim. To evaluate the agreement between different methods in detection of glaucomatous visual field progression using two classification-based methods and four statistical approaches based on trend analysis. Methods. This is a retrospective and longitudinal study. Twenty Caucasian patients (mean age 73.8 ± 13.43 years) with open-angle glaucoma were recruited in the study. Each visual field was assessed by Humphrey Field Analyzer, program SITA standard 30-2 or 24-2 (Carl Zeiss Meditec, Inc., Dublin, CA). Full threshold strategy was also accepted for baseline tests. Progression was analyzed by using Hodapp–Parrish–Anderson classification and the Advanced Glaucoma Intervention Study visual field defect score. For the statistical analysis, linear regression (r2) was calculated for mean deviation (MD), pattern standard deviation (PSD), and visual field index (VFI), and when it was significant, each series of visual field was considered progressive. We also used Progressor to look for a significant progression of each visual field series. The agreement between methods, based on statistical analysis and classification, was evaluated using a weighted kappa statistic. Results. Thirty-eight visual field series were analyzed. The mean follow-up time was 6.2 ± 1.53 years (mean ± standard deviation). At baseline, the mean MD was −7.34 ± 7.18 dB; at the end of the follow-up, the mean MD was −9.25 ± 8.65 dB; this difference was statistically significant (p<0.001). The agreement to detect progression was fair between all methods based on statistical analysis and classification except for PSD r2. A substantial agreement (κ = 0.698 ± 0.126) was found between MD r2 and VFI r2. With the use of all the statistical analysis, there was a better time-saving. Conclusions. The best agreement to detect progression was found between MD r2 and VFI r2. VFI r2 showed the best agreement with all the other methods. GPA2 can help ophthalmologists to detect glaucoma progression and to help in treatment decisions. PSD r2 was the worse method to detect progression.

scholarly journals The importance of radiation fog in the tropical seasonal rain forest of Xishuangbanna, south-west China

2008 ◽  
Vol 39 (1) ◽  
pp. 79-87 ◽  
Author(s):  
Wen Jie Liu ◽  
Ping Yuan Wang ◽  
Jin Tao Li ◽  
Peng Ju Li ◽  
Wen Yao Liu
Keyword(s):  
Rain Forest ◽  
Tropical Rain Forest ◽  
Hydrological Cycle ◽  
Annual Rainfall ◽  
Rain Forests ◽  
Radiation Fog ◽  
West China ◽  
South West ◽  
The Mean ◽  
Effects Of Radiation

The tropical rain forest in Xishuangbanna, SW China has a high floristic diversity and is closely related to Malaysian rain forests in flora. This forest would not normally be established in such a climatic region as Xishuangbanna (less precipitation and lower air temperature) compared to those of the lowland moist tropics. The mean annual rainfall is 1487 mm, which is considerably lower than rain forests in other parts of the world. It is believed that the frequent occurrence of radiation fog might play an important role in the water relations of plants and in the hydrological cycle of this type of rain forest. However, the multiple hydrological and ecological effects of radiation fog are not well understood. In this paper, we describe and analyze the significance of radiation fog to this forest, and develop a hypothesis that fog plays an important role in the presence of the tropical rain forest in Xishuangbanna. Suggestions for further research on the significance of fog are offered.

A Proof for Rhiel's Range Estimator of the Coefficient of Variation for Skewed Distributions

2007 ◽  
Vol 100 (1) ◽  
pp. 208-210 ◽  
Author(s):  
G. Steven Rhiel
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Research Study ◽  
Skewed Distributions ◽  
The Mean ◽  
Standard Deviations

In this research study is proof that the coefficient of variation ( CVhigh-low) calculated from the highest and lowest values in a set of data is applicable to specific skewed distributions with varying means and standard deviations. Earlier Rhiel provided values for dn, the standardized mean range, and an, an adjustment for bias in the range estimator of μ. These values are used in estimating the coefficient of variation from the range for skewed distributions. The dn and an values were specified for specific skewed distributions with a fixed mean and standard deviation. In this proof it is shown that the dn and an values are applicable for the specific skewed distributions when the mean and standard deviation can take on differing values. This will give the researcher confidence in using this statistic for skewed distributions regardless of the mean and standard deviation.

scholarly journals Properties of the Standard Deviation that are Rarely Mentioned in Classrooms

2016 ◽  
Vol 38 (3) ◽  
Author(s):  
Mohammad Fraiwan Al-Saleh ◽  
Adil Eltayeb Yousif
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Sample Variance ◽  
Mean Absolute Deviation ◽  
Hidden Information ◽  
Absolute Deviation ◽  
Sample Mean ◽  
The Mean ◽  
Vague Concept ◽  
Chebyshev's Inequality

Unlike the mean, the standard deviation ¾ is a vague concept. In this paper, several properties of ¾ are highlighted. These properties include the minimum and the maximum of ¾, its relationship to the mean absolute deviation and the range of the data, its role in Chebyshev’s inequality and the coefficient of variation. The hidden information in the formula itself is extracted. The confusion about the denominator of the sample variance being n ¡ 1 is also addressed. Some properties of the sample mean and varianceof normal data are carefully explained. Pointing out these and other properties in classrooms may have significant effects on the understanding and the retention of the concept.

scholarly journals Annual and monthly rainfall trend in plantation and spice farming Western Ghats districts

1970 ◽  
pp. 45
Author(s):  
K Kandiannan, K S Krishnamurthy, C K Thankamani, S J Ankegowda
Keyword(s):  
Coefficient Of Variation ◽  
Western Ghats ◽  
Monsoon Rainfall ◽  
Southwest Monsoon ◽  
Monthly Rainfall ◽  
Negative Trend ◽  
Annual Rainfall ◽  
Post Monsoon ◽  
The Nilgiris ◽  
Southwest Monsoon Rainfall

Rainfall analysis of important plantation and spices producing districts such as The Nilgiris (Tamil Nadu), Kodagu (Karnataka) Idukki (Kerala) and Wayanad (Kerala) with 100 years data (1901 to 2000) obtained from the India Meteorological Department (IMD), Pune indicated that mean annual rainfall were 1839.7mm, 2715.7mm, 2979.4mm and 3381.0mm with a coefficient of variation (CV) of 16.0%, 17.0%, 25.8% and 19.6%, respectively. The contribution of southwest monsoon(June-September) to the annual rainfall in these districts were 80.3% (Wayanad), 78.9% (Kodagu),  65.2% (Idukki) and 56.3%  (The Nilgiris) with corresponding CV of 24.1%, 20.6%, 32.5%, and 24.6%, respectively. The declining trend in mean annual rainfall was noticed for Idukki, Wayanad and The Nilgiris, whereas, for Kodagu, it was stable. The change was significant in Wayanad and The Nilgiris. Similar trend was also observed for the southwest monsoon rainfall. The maximum decline in annual and southwest monsoon rainfall was noticed in The Nilgiris followed by Wayanad. Pre and post monsoon rainfall receipts were comparatively less with high inter-annual variations. The pre-monsoon (March-May) receipt and its coefficient of variation (CV) was 252.4mm & 20.6% (Kodagu), 360.9mm & 36.5% (Idukki), 251.7mm & 36.6% (The Nilgiris) and 274.2mm & 54.2% (Wayanad). The post monsoon (October-December) rain was maximum in Idukki 548.1mm (CV 27.9%) followed by The Nilgiris 503.4mm(CV 31.3%), Wayanad, 333.1mm(CV 37.8%) and Kodagu 310.5mm (CV 32.7%). In all these districts there was a declining trend in the pre-monsoon rain with maximum decline in The Nilgiris. Similar declining trend was also observed in post-monsoon rain except for The Nilgiris, where the trend has been increasing. Overall, the study gives an indication that there was a spatial and temporal variation in rainfall amounts.  The maximum decline in annual rainfall and the southwest monsoon was observed in The Nilgiris and Wayanad. July was the rainiest month in all the districts studied. Significant negative trend was asscoaited with The Nilgiris for January, May, June, July and August months. Whereas, in Kodagu, no significant trend was observed for mean monthly rainfall, except for August. In Idukki, significant negative changes were noticed for January, March, October and December rainfall. Monthly rainfall of January, March, April and July monthly rainfall were showed significant negative trend in Wayanad,. These negative trends across important plantation and spices producing districts of the Western Ghats would affect not only the agricultural economy of this sector but also water resources.

scholarly journals THE 500 HPA SUB-TROPICAL ANTICYCLONE DURING APRIL AND MAY 1988 AND THE WEATHER OVER INDIA

MAUSAM ◽  
2021 ◽  
Vol 44 (1) ◽  
pp. 23-28
Author(s):  
RANJIT SINGH
Keyword(s):  
Long Range ◽  
Monsoon Rainfall ◽  
Synoptic Scale ◽  
The South ◽  
Northern Latitudes ◽  
Dry Spell ◽  
Logical Parameter ◽  
Scale Fluctuation ◽  
The Mean ◽  
Sw Monsoon

The sub-tropical ridge at 500 hPa in April has a considerable synoptic scale fluctuation. In April 1988, it showed a steady southward displacement to the equator. In May 1988, a fresh sub-tropical anticyclone formed in northern latitudes by the anticyclonic recut-mg of the dry northwesterlies of extra-tro-pical origin. By extending southward the northerlies ushered a dry spell extensively to the south of the sub-tropical ridge (STR). This was an event contrary to the normal northward progress of equatorial weather belt and the STR. Thus the mean April 500 hPa ridge does not provide a logical parameter for long range forecast-ing of the southwest (SW) monsoon rainfall over India.

scholarly journals Long term rainfall variability and trend analysis in lower Shivaliks of Punjab, India

MAUSAM ◽  
2021 ◽  
Vol 72 (3) ◽  
pp. 571-582
Author(s):  
NAVNEET KAUR ◽  
ABRAR YOUSUF ◽  
M. J. SINGH
Keyword(s):  
Trend Analysis ◽  
Monsoon Rainfall ◽  
Rainfall Variability ◽  
Kendall Test ◽  
Annual Rainfall ◽  
Entire Study ◽  
Seasonal Basis ◽  
Normal Rainfall ◽  
Rainy Days

The trend analysis of historical rainfall data on monthly, annual and seasonal basis for three locations in lower Shivaliks of Punjab, viz., Patiala-ki-Rao (1982-2015), Ballowal Saunkhri (1987-2015) and Saleran (1984-2017) has been done in the present study using linear regression model, Mann Kendall test and Sen’s slope. Further, the data for annual and seasonal rainfall and rainy days has also been analyzed on quindecennial basis, i.e., for the period of 1986-2000 and 2001-2015. The analysis of data showed that annual rainfall in the region ranged from 1000 to 1150 mm. The trend analysis of the data shows that the monthly rainfall is decreasing at Patiala-ki-Rao and Saleran, however, the trend was significant for May at Patiala-ki-Rao; and in March and November at Saleran. At Ballowal Saunkhri, the decreasing trend is observed from May to October, however, the trend is significant only in August. The decrease in annual and monsoon rainfall is about 13 to 17 mm and 12 to 13 mm per year respectively at three locations in lower Shivaliks of Punjab. The highest annual (1600-2000 mm) and monsoon (1500-1800 mm) rainfall during the entire study period was recorded in the year 1988 at three locations. The decadal analysis of the data shows below normal rainfall during April to October. The analysis of the rainfall and rainy days on monthly, annual and seasonal averages of 15 year basis showed that both rainfall and rainy days have decreased during the 2001-2015 as compared to 1986-2000 during all the seasons of the year.

Correction for Rhiel's Theory for the Range Estimator of the Coefficient of Variation for Skewed Distributions

2010 ◽  
Vol 106 (1) ◽  
pp. 93-94
Author(s):  
G. Steven Rhiel
Keyword(s):  
Standard Deviation ◽  
Correction Factor ◽  
Coefficient Of Variation ◽  
Unbiased Estimate ◽  
Correction Factors ◽  
Skewed Distributions ◽  
The Mean

In 2007, Rhiel presented a technique to estimate the coefficient of variation from the range when sampling from skewed distributions. To provide an unbiased estimate, a correction factor ( an) for the mean was included. Numerical correction factors for a number of skewed distributions were provided. In a follow-up paper, he provided a proof he claimed showed the correction factor was independent of the mean and standard deviation, making the factors useful as these parameters vary; however, that proof did not establish independence. Herein is a proof which establishes the independence.

scholarly journals The precision of temporal judgement: milliseconds, many minutes, and beyond

2009 ◽  
Vol 364 (1525) ◽  
pp. 1897-1905 ◽  
Author(s):  
P.A. Lewis ◽  
R.C. Miall
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Human Subjects ◽  
Short Interval ◽  
Time Measurement ◽  
Scalar Property ◽  
Timing Mechanisms ◽  
Timing Data ◽  
The Mean ◽  
Different Levels

The principle that the standard deviation of estimates scales with the mean estimate, commonly known as the scalar property, is one of the most broadly accepted fundamentals of interval timing. This property is measured using the coefficient of variation (CV) calculated as the ratio between the standard deviation and the mean. In 1997, John Gibbon suggested that different time measurement mechanisms may have different levels of absolute precision, and would therefore be associated with different CVs. Here, we test this proposal by examining the CVs produced by human subjects timing a broad range of intervals (68 ms to 16.7 min). Our data reveal no evidence for multiple mechanisms, but instead show a continuous logarithmic decrease in CV as timed intervals increase. This finding joins other recent reports in demonstrating a systematic violation of the scalar property in timing data. Interestingly, the estimated CV of circadian judgements fits onto the regression of decreasing CV, suggesting a link between short interval and circadian timing mechanisms.

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