DAKSHIN BHARTIYA PADHAR PAR HONE WALI MONSOON WARSHA KA PRADHAN AVYAV VISHLESHAN

The result of the Principal Component Analysis of southwest and northeast monsoon rainfall on the southern India plateau have been discussed. Monsoon rainfall data of five meteorological sub-divisions, i.e., Coastal Andhra Pradesh, Rayalseema, Tamilnadu, Interior parts of South Karnataka & Kerala, for a period of 33 years (1960-92), have been utilized. The results indicate that the rainfall of Coastal Andhra Pradesh and Rayalseema has maximum impact on first principal component of southwest monsoon rainfall of five meteorological sub-divisions. The study of only first principal component is sufficient in order to understand the 49% of total variability of southwest monsoon rainfall. Analysis of first three principal components is important to understand 85% of total variability of the rainfall of this season. On the first principal component of northeast monsoon rainfall of aforesaid five meteorological sub-divisions the impact of the rainfall of Kerala and south interior Karnataka has been found maximum. In order to understand the 56% of total variability the analysis of first principal component is sufficient. The special negative relation is found between northeast monsoon rainfall on the Coastal Andhra Pradesh and southwest monsoon rainfall of previous year on this very sub-division and Rayalseema. The principal components of southwest monsoon rainfall may prove useful for forecasting the northeast monsoon rainfall of southern Indian plateau.

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Southwest monsoon rainfall in Assam: An application of principal component analysis for understanding of variability

MAUSAM ◽

10.54302/mausam.v68i2.638 ◽

2021 ◽

Vol 68 (2) ◽

pp. 357-366

Author(s):

PIJUSH BASAK

Keyword(s):

Principal Component Analysis ◽

Principal Components ◽

Temporal Variability ◽

Monsoon Rainfall ◽

Principal Component ◽

Component Analysis ◽

Southwest Monsoon ◽

The State ◽

Spatial And Temporal Variability ◽

Southwest Monsoon Rainfall

The principal component analysis (PCA) is applied to understand the spatial and temporal variability of monsoonal rainfall in the state Assam in India. The Southwest Monsoon (SWM) rainfall data over 12 widely spread stations located over the state has been analyzed for a period of 60 years for understanding variability. A statistically significant trend and a above/below transition signal has been observed for a few stations and the corresponding principal components (PCs). Coherent regions of Northern and Southern Assam have been identified through PCA to bring out the possible significant signals. It is observed that some of PCs for state-wise and coherent regions have positive or negative trend and significant above/below transition.

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Northeast monsoon rainfall and agricultural production in Tamilnadu and Andhra PradeshI - Rainfall variability and its significance in agricultural production

MAUSAM ◽

10.54302/mausam.v64i2.687 ◽

2021 ◽

Vol 64 (2) ◽

pp. 309-316

Author(s):

R.P. SAMUI ◽

M.V. KAMBLE ◽

J.P. SABALE

Keyword(s):

Agricultural Production ◽

Andhra Pradesh ◽

Monsoon Rainfall ◽

Positive Impact ◽

Monsoon Season ◽

Rainfall Variability ◽

Southwest Monsoon ◽

Positive Trend ◽

Northeast Monsoon ◽

Northeast Monsoon Rainfall

ekWulwu Hkkjrh; vFkZO;oLFkk dk egRoiw.kZ ?kVd gS tks —f"k dks izR;{k% :i ls izHkkfor djrk gS D;ksafd ;g ,d pkSFkkbZ th-Mh-ih- vkSj —f"k ij fuHkZj 60 izfr’kr turk dh vkthfodk dks izHkkfor djrk gSA Hkkjr esa eq[;r% nf{k.k&if’peh ekWulwu +_rq ds nkSjku o"kkZ gksrh gSA Hkkjr esa vDrwcj ls fnlEcj ds nkSjku fo’ks"kdj iwohZ vkSj nf{k.kh jkT;ksa esa ekulwuksRrj vof/k] ftls mRrj iwohZ ekWulwu dgrs gS] esa Hkh dkQh o"kkZ gksrh gSA ;g o"kkZ —f"k ds fy, vkSj bu {ks=ksa ds lac) lsDVjksa ds fy, dkQh egRoiw.kZ gksrh gSA rfeyukMq ds iwohZ rVh; ftyksa esa nf{k.k ls mRrj rd o"kkZ esa o`f) dh izo`fRr dk irk pyk gSA blds foijhr vka/kz izns’k ds rVh; nf{k.k iwohZ ftyksa esa vf/kd vkSj mRrj iwohZ Hkkxksa esa o"kkZ esa deh dh izo`fRr dk irk pyk gSA vka/kz izns’k dh vis{kk rfeyukMq esa o"kkZ dh vf/kdrk ds dkj.k mRrj iwohZ ekulwu dk nf{k.k if’pe ekulwu o"kkZ dh rqyuk esa —f"k mRiknu ij vf/kd izHkko dk irk pyrk gSA —f"k mRiknu ij o"kkZ ds izHkko ds v/;;uksa ls vka/kz izns’k esa pkoy vkSj eDdk ds mRiknu esa mRrj iwohZ ekWulwu ds ldkjkRed izHkko dk irk pyk gSA eDdk dh mit esa yxkrkj ldkjkRed izo`fRr dk irk pyk gSA mRrj iwohZ ekulwu _rq ds nkSjku vka/kz izns’k ds rVh; ftyksa dh rqyuk esa rfeyukMq ds rVh; ftyksa esa pØokr ;k vonkc dh otg ls Hkkjh ls vf/kd Hkkjh o"kkZ vkSj ck<+ ds dkj.k mRiknu dh deh vkbZ gSA ifjofrZrk ds ckjs esa mfpr tkudkjh rFkk mRrj iwohZ ekulwu o"kkZ ds ekSleh iwokZuqeku ds lkFk&lkFk —f"k izpkyuksa ds fy, fofo/k uhfr;ksa dk fodkl djus ls bu {ks=ksa ds —f"k vkSj tylalk/ku lsDVjksa ds fy, fu.kZ; ysus esa egRoiw.kZ vuqiz;ksx Hkwfedk gksxhA Monsoon which directly impacts agriculture is an important component of Indian economy because it influences about a quarter of the GDP and livelihood of 60% of the population who depend on agriculture for their livelihood. India receives rainfall mainly during southwest monsoon season. A considerable rainfall also occurs in India during the post monsoon period called as northeast monsoon during October to December, particularly over eastern and southern states and this is of great significance in agriculture and allied sectors in these regions. Increasing trend of rainfall is noticed from south to north in eastern coastal districts of Tamilnadu. On the contrary, it is higher in coastal southeast districts with decreasing trend in northeast parts of Andhra Pradesh. NE monsoon shows greater impact on agricultural production due to its higher quantum of rainfall compared to that of southwest monsoon rain in Tamilnadu than that in Andhra Pradesh. Studies on impact of rainfall on agricultural production revealed positive impact of NE monsoon on rice and maize production in AP. Maize yield is found to exhibit a consistent positive trend. Loss in production due to heavy to very heavy rain and flooding associated with cyclone or depression was more prominent along the coastal districts of Tamilnadu than that in the coastal districts of Andhra Pradesh during northeast monsoon season. Proper understanding of the variability and developing diversified strategies for agricultural operations alongwith the seasonal prediction of northeast monsoon rainfall would have considerable application value for decision making in agriculture and water resource sectors of these regions.

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Southwest monsoon rainfall in India : Part II - Principal components in temporal domain

MAUSAM ◽

10.54302/mausam.v49i3.3635 ◽

2021 ◽

Vol 49 (3) ◽

pp. 301-308

Author(s):

A. B. MAZUMDAR

Keyword(s):

Principal Components ◽

Monsoon Rainfall ◽

Principal Component ◽

Southwest Monsoon ◽

Temporal Domain ◽

Synoptic Features ◽

Southwest Monsoon Rainfall ◽

Relationship Of ◽

The Relationship ◽

Low Pressure Systems

An attempt has been made towards objective identification of phases of the southwest monsoon by principal component analysis (PCA) in temporal domain (T-mode). The method utilizes the relationship of weekly rainfall activities with principal components (PCs) of southwest monsoon. Based on the relationships, subgroup of weeks with similar spatial patterns have been identified. Synoptic features of these subgroups have been brought out with the help of synoptic charts. The first four significant PCs are associated with four kinds of active phases of the southwest monsoon when the low pressure systems have typical characteristics corresponding to each PC. Thus, the study suggests a method of interpretation of PCs with the help of synoptic charts by objective identification of phases of southwest monsoon.

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Variability of south west monsoon rainfall in West Bengal : An application of principal component analysis

MAUSAM ◽

10.54302/mausam.v65i4.1201 ◽

2021 ◽

Vol 65 (4) ◽

Author(s):

PIJUSH BASAK

Keyword(s):

Principal Component Analysis ◽

West Bengal ◽

Monsoon Rainfall ◽

Principal Component ◽

Component Analysis ◽

Southwest Monsoon ◽

Spatial And Temporal Variability ◽

Annual Variations ◽

South West Monsoon ◽

Southwest Monsoon Rainfall

The principal component analysis is utilized to understand the spatial and temporal variability of monsoonal rainfall. The southwest monsoon rainfall data of West Bengal, situated over 21 stations widely spread over the state, has been analyzed for a period of 60 years for inter-annual variations. A coherent subset of 8 north and 13 south stations has been studied separately to produce statistically significant inter-annual signals. It is observed that the above/below transition is quite significant both for station rainfalls and principal components for state-wise and coherent zone analysis.

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Some characteristics of southwest monsoon rainfall over urban entres in Andhra Pradesh and Telangana

MAUSAM ◽

10.54302/mausam.v68i1.409 ◽

2021 ◽

Vol 68 (1) ◽

pp. 51-66

Author(s):

K. NAGA RATNA ◽

MANORAMA MOHANTY

Keyword(s):

Andhra Pradesh ◽

Monsoon Rainfall ◽

Daily Rainfall ◽

Significance Test ◽

Southwest Monsoon ◽

T Test ◽

Urban Centre ◽

Rainfall Events ◽

Southwest Monsoon Rainfall ◽

Heavy Rainfall Events

In the present study daily rainfall data for 46 years (1969-2014) was selected for the urban stations and surrounding stations for coastal areas of Coastal Andhra Pradesh (CAP) and inland areas of Telanagana (TEL) and Rayalaseema (RSM). The statistics such as regression, standard deviation and coefficient of variance, significance test using t-test, Mann-Kandell test were worked out for the entire period for the stations. The stations were selected on the basis where the period of data is same. The t-test thus performed for all stations showed significance (p < 0.001) in seasonal rainfall (JJAS) for all the stations. Further z-statistics using Mann-Kandell test was performed that showed significant increase at 95% confidence level for Gannavaram, Machilipatnam and Visakhapatnam along the coast of Andhra Pradesh state. Over Telengana, Hyderabad (Urban centre) an inland station, showed significant increase at 90% level of confidence for extreme heavy rainfall events. Henceforth, seperate studies for each urban centre (Visakhapatnam, Gannavaram, Machilipatnam and Hyderabad) were done and results showed significant increase in rainfall over urban centres compared to other surrounding stations and the significant increase in rainfall was observed for the coastal stations along Andhra Pradesh coast when compared to inland stations of Telanagana and Rayalaseema.

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Southwest monsoon rainfall in India: Part I-Spatial variability

MAUSAM ◽

10.54302/mausam.v49i1.3600 ◽

2021 ◽

Vol 49 (1) ◽

pp. 71-78

Author(s):

A. B. MAZUMDAR

Keyword(s):

Monsoon Rainfall ◽

Principal Component ◽

High Standard ◽

Southwest Monsoon ◽

Madden Julian Oscillation ◽

Data Set ◽

The Third ◽

Rainfall Anomalies ◽

The Mean ◽

Southwest Monsoon Rainfall

Results of Principal Component Analysis (PCA) in spatial mode (S-Mode) applied on a 10 years' (1977-86) data set of weekly rainfall anomalies are presented in this study. The rainfall activity has been below average in the period under study with high standard deviations mostly over low rainfall areas. Inter - subdivisional correlation values suggest predominance of broad- scale weather systems over most parts of the country .The first principal component (PC) resemblance with the mean pattern. The second PC has been associated with active monsoon condition. The third and fourth PCs have been related to the northward progression of the Madden-Julian oscillation and the weak monsoon condition respectively. Resemblance of spatial patterns of alternative PCs with typical strong and weak monsoon activities suggest significant contributions from certain parts of the country (northeast, southeast) towards overall rainfall activity during weak monsoon situation.

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On some aspects of southwest monsoon rainfall over Tamilnadu

MAUSAM ◽

10.54302/mausam.v46i4.3302 ◽

2022 ◽

Vol 46 (4) ◽

pp. 377-382

Author(s):

S. K. SUBRAMANIAN ◽

V. N. THANKAPPAN

Keyword(s):

Monsoon Rainfall ◽

Monsoon Season ◽

Southwest Monsoon ◽

Point Of View ◽

Annual Rainfall ◽

Northeast Monsoon ◽

The North ◽

Rainfall Occurrence ◽

Southwest Monsoon Rainfall ◽

Southwest Monsoon Season

The rainfall during southwest monsoon season over Tamilnadu is quite significant from the point of view of water storage in major reservoirs as northeast monsoon rainfall, which is about half of the annual rainfall, is not stable enough due to its large interannual variability. The southwest monsoon rainfall, on the other hand, is more stable. The north-south oriented trough over Tamilnadu and adjoining Bay togetherwith upper air cyclonic circulation/trough in lower tropospheric levels account for three fourths of significant rainfall occurrence during southwest monsoon season. Rainfall during southwest monsoon and northeast monsoon seasons was found to be independent with a small negative correlation of -0.18. This shows that the southwest monsoon rainfall may not be of much use to predict the pattern of northeast monoon rainfall over Tamilnadu.

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Precipitation regionalization of southwest monsoon by hierarchical cluster analysis

MAUSAM ◽

10.54302/mausam.v60i2.1069 ◽

2021 ◽

Vol 60 (2) ◽

pp. 185-196

Author(s):

A. B. MAZUMDAR

Keyword(s):

Cluster Analysis ◽

Hierarchical Cluster Analysis ◽

Monsoon Rainfall ◽

Principal Component ◽

Hierarchical Cluster ◽

Southwest Monsoon ◽

Different Types ◽

Synoptic Features ◽

Southwest Monsoon Rainfall ◽

Homogeneous Regions

An attempt has been made to identify coherent zones of southwest monsoon rainfall over the Indian region by employing hierarchical cluster analysis. Examination of dendrograms produced by different fusion strategies revealed the presence of 13 nuclei clusters of meteorological subdivisions. Formation of these nuclei clusters could be interpreted by their average principal component (PC) scores and associated synoptic features of PCs. Higher level inter-nuclei joinings have occurred in various fusion strategies to produce different types of clusters of subdivisions. A flexible strategy providing well separated groups of meteorological sub-divisions has been found to be suitable. The method has identified six homogeneous regions of rainfall over India. The meteorological subdivisions have been found to be evenly distributed in these coherent zones. The clustering obtained by this method has been reasonable and largely interpretable.

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