Analysis of Temporal and Spatial Variations in Extreme Precipitation over Kerala

This study focuses on the spatial and temporal variability of southwest monsoon (SWM) and northeast monsoon (NEM) rainfall over India, after the 1976–1977 regime shift. Through wavelet analysis the dominant mode of variability in the SWM and NEM rainfall is found to be in the 2–8-year scale (ENSO band). Therefore, scale-averaged wavelet power (SAP) of SWM (SAPSWM) and NEM (SAPNEM) rainfall obtained from a high-resolution dataset for the period 1977–2001 was subjected to empirical orthogonal function analysis, in order to understand the homogenous regions of rainfall variability. As the study utilizes SAP, the decadal variability is observed in the spatial and temporal patterns of rainfall. The maximum variability of SAPSWM rainfall is found to be in the 2–4-year period, whereas, for the SAPNEM rainfall, the biennial mode explains the variability over the core region of NEM rainfall. Significant power is also observed in the 4-year period. The evolution of the principal components (PCs) is consistent with the above/below normal rainfall received over the region. Similar analysis has been carried out also for the SAP of monthly sea surface temperature (SAPSST) over Indian Ocean for the months from January to September. Compared with any other month, the decadal changes of the PCs of SAPSWM and SAPNEM rainfall are highly correlated with the decadal variations of PC1 of SAPSST for the month of March. Therefore, the relation between the rainfall and SST was explained using SAPSST for the month of March. Significant biennial power is also observed in March SST over southeast Indian Ocean (85–110°E and 5–40°S) after the climate shift of 1976. In order to identify any change in the relation between NEM rainfall and SAPSST (March) before and after 1976, a correlation between NEM rainfall and PC1 of SAPSST (March) was found for the period 1951–1975 and 1977–2001. Results show that correlation has increased after 1976. Therefore, this PC can be made use of in the prediction of NEM rainfall. Copyright © 2012 Royal Meteorological Society

The association between the southwest and northeast monsoon (October-December) rainfall over Tamil Nadu has been examined for the 100-year period from 1877 to 1976. A correlation analysis between the two rainfall series revealed that the southwest monsoon (June-September) rainfall is negatively correlated with that of the northeast monsoon rainfall. That is, an excess or deficit of southwest monsoon rainfall over this region is generally followed by an opposite tendency in the northeast monsoon rainfall. A χ2 test of dependence further indicated that the rainfalls in the two monsoons are not independent of each other. The negative rainfall relationship can be a useful tool in foreshadowing the northeast monsoon rainfall over Tamil Nadu, which is of considerable economic importance for this region.

The spatial variability of northeast monsoon (NEM) rainfall of peninsular India and Sri Lanka is studied using Empirical Orthogonal Function (EOF) analysis based on monthly / seasonal rainfall data for the months of October, November, December, January and for the season October-December (OND) for the 107 year period of 1900-2006 over nine sub-regions defined for the study based on climatology and geography. Monthly / seasonal rainfall series over these nine sub-regions are subjected to EOF analysis and 2-3 significant Principal Components (PCs) are identified for each case. Each PC is then linked to physical modes known to be associated with NEM using correlation and compositing techniques. For the OND season and for all the four individual months, the first PC explaining maximum variance of 49-64% in the spatial rainfall distribution is identified with the overall NEM strength. The second and the third PCs are identified with rainfall due to passage of synoptic scale systems such as cyclones and depressions (explaining 11-20% variation) and southwest monsoon (SWM) rainfall prior to onset of NEM in October (15% variance explained). PCs representing NEM strength and SWM contribution exhibit contrasting nature of relation with the major climate index Southern Oscillation Index. Relation between the PCs and important regional circulation features, viz., the subtropical ridge at 200 hPa level and the equatorial trough at 850 hPa are used to delineate the PCs associated with SWM and NEM rainfall during October. The study also reveals that the sub-region of north coastal Andhra Pradesh is not benefitted by the over NEM strength but, receives rainfall due to passage of cyclonic disturbances and SWM prior to NEM onset.

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.

North-East monsoon rainfall extremes over the southern peninsular India and their association with El Niño

Climate being a significant driver for best selection of crops in a region, allocation of similar climatic zones has always received plunge.Twenty per cent or more precipitation decrease is anticipated for many parts of the arid regions in the next century. Rainfall is a crucial agro-climatological factor in the seasonally arid parts of the world and its analysis is an essential prerequisite for agricultural planning in India. Ninety years (1911-2000) of both South West Monsoon (SWM) and North East Monsoon (NEM) rainfall data of Tamil Nadu (excluding urbanite Chennai)and potential evapotranspiration data were collected and analysed. The moisture index (Im) was computed based on Thornthwaite and Mather model. Based on the moisture index value of the SWM and NEM, the districts were classified under different climate groups.Over 90 years study, seven districts comes under arid (E), 17 under semi-arid(D), five under dry sub humid(C1) and one each in moist sub humid(C2) and per humid (A) class respectively(SWM period). During NEM no districts registered under (E) or (D) climate class. Further seven districts fell each in (C1) and (C2) class respectively and12 districts comes under Humid(B) and five districts under (A) climate class for Tamil Nadu.During SWM, both the data slice (30 years) and decadal (10 years) analysis explored Trichy district might experience severe moisture stress compared to the past. Madurai, Perambalur and Virudhunagar showed a change from (B1) to (C2) during NEM which showed there might be a change in reduction in soil moisture status among the data slice period. Remaining districts fell within the same climate group.

The relation between 200 hPa upper tropospheric parameters such as temperature, zonal and meridional winds over India with the Indian southwest and northeast monsoons has been studied, based on monthly and seasonal upper air data of 14 well-distributed Indian radiosonde stations for the 36 year period 1963-98. It has been found that by and large, positive temperature/height anomalies, negative zonal wind anomalies and northerly position of the sub-tropical ridge during the preceding months/seasons are associated with good southwest/poor northeast monsoons and that complement of the above with poor southwest/good northeast monsoons. The profiles of the above relationship display a double peak in May and September/October. A multiple regression forecast scheme for seasonal forecasting of northeast monsoon rainfall, based on October data has been derived which when tested in an independent sample of 5 years yielded nearly 50% correct forecasts. The southwest monsoon rainfall of India and the northeast monsoon rainfall of Tamil Nadu/Southern parts of India have been shown to share a negative relationship, though the relationship is discordant rather than decisive, which gets defined better when years of deficient southwest monsoon rainfall get excluded. The feature of good Indian northeast monsoon getting preceded by colder upper tropospheric temperatures as shown in the study tie in well with the accepted mechanism of Asian winter monsoon getting intensified due to cold surges from the Siberian High.

This study investigates the variation of seasonal streamflow and streamflow extremes in five catchments of the Mahaweli River Basin (MRB) Sri Lanka from 1990 to 2014, and the relationship between streamflow and seasonal rainfall in each catchment is then examined. Furthermore, the influence of Indian Ocean Dipole (IOD) and El Nino and Southern Oscillation (ENSO) on the seasonal rainfall and streamflow in the upper (UMRB) and lower reaches (LMRB) of MRB are explored. It’s found that the rainfall amount in southwest monsoon (SWM) season contributes 29.7% out of annual total rainfall in the UMRB, while the LMRB records 41% of the total rainfall during the northeast monsoon (NEM) season. The maximum streamflow of upper (lower) Mahaweli catchments is observed in the SWM (NEM) season. Catchments in the UMRB (LMRB) recorded strong interannual variability of seasonal overall flow (Q50), Maximum 10-day, and 30-day flows during the SWM (NEM) season. It’s further revealed that the catchment streamflow in the UMRB is closely correlated with the SWM rainfall in the interannual time scale, while streamflow of catchments in the LMRB is closely associated with the NEM rainfall. The effects of ENSO and IOD on streamflow are consistent with their impacts on rainfall for all catchments in MRB, with strong seasonal dependent. These suggested that the sea surface temperature anomalies in the both Indian Ocean and tropical Pacific Ocean are important factors affecting the streamflow variability in the MRB, especially during the SWM 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.

Long-term (1901–2010) district data have been used to examine the observed variability and trends in rainfall during the south-west monsoon season (June–September) and north-east monsoon season (October–December) over India. South-west monsoon rainfall averaged over the country as a whole does not show any significant long-term trend during the period 1901–2010, suggesting that south-west monsoon system is stable. However, there is a significant multi-decadal epochal variability over the country and the four homogenous regions over India. The recent decades from 1971 onwards are found to be drier than normal with the recent decade 2001–2010 being the driest. Rainfall during the month of July shows a decreasing trend over most parts of the central India. However, rainfall during June and August shows increasing trend over the central and south-western parts of the country. Significant decreasing trends are observed in the seasonal rainfall over three subdivisions, and significant increasing trends are observed over eight other subdivisions. The analysis of the north-east monsoon (October–December) rainfall over the five met-subdivisions of Peninsular India reveals no significant long-term trend. However, the presence of decadal variability in north-east monsoon rainfall is clearly observed.

The northeast (NE) monsoon contributes considerable annual rainfall over southern peninsular India. Here, an attempt has been made to evaluate the role of convectively coupled mixed Rossby-Gravity (MRG) waves on the variabilities of NE monsoon rainfall. The gridded rainfall data from 1980 to 2021 from the India Meteorological Department shows large interannual variability in NE monsoon rainfall over southern peninsular India. Wavelet analysis of outgoing longwave radiation (OLR) data shows the dominance of short-period waves over the equatorial Indian Ocean during the above-normal NE monsoon rainfall years compared to below-normal rainfall years. The space-time spectral analysis further confirms the dominance of the short-period westward propagating convectively coupled equatorial waves (CCEW) during above-normal excess NE monsoon rainfall years. In contrast, the eastward component of CCEWs dominates the deficit rainfall years. Further, the empirical orthogonal function (EOF) analysis of OLR filtered for MRG wave shows that the first two leading modes explain more than 14% of variability over the Indian Ocean domain. Moreover, the vertically integrated moisture flux convergence indicates the role of MRG wave in triggering the extreme rainfall over southern peninsular India and also offer favourable condition for the formation of cyclogenesis and, thereby, inducing heavy rainfall over the South Indian domain. Thus, the results suggest that the westward propagating MRG waves play a seminal role in modulating the NE monsoon rainfall over southern peninsular India. Keywords: mixed Rossby-Gravity wave, north-east monsoon, extreme precipitation

Compared with the southwest monsoon, the mechanisms and history of northeast monsoon (NEM) variability over South Asia are poorly known. The NEM nevertheless contributes >50% of rainfall to semi-arid southeast India, and has underpinned the success, over the last 2000 years, of a widespread indigenous water resource management system based on rainwater harvesting and storage in man-made lakes. Based on a power spectrum analysis of 60- to 100-yr instrumental rainfall records, we show that NEM rainfall is both chaotic in the high-frequency time domain and spatially unpredictable, but that the sustainability of the agricultural water-harvesting infrastructure is tied to excess rain from NEM cyclones. Cyclonic activity has declined sharply since 1977. Based on twentieth-century analogues, we propose a qualitative model in which storminess decreases when NEM wind intensities increase and Eurasian winter temperatures are anomalously low. Extrapolating to the Holocene time frame, model expectations for the palaeorainfall record correlate with the independently established chronologies of Indian runoff-irrigation development and the ‘Mediaeval Warm Period’–‘Little Ice Age’ oscillations, and further suggest that NEM and SWM rainfall anomalies have covaried with the same sign from seasonal to millennial timescales. The fortunes of the reservoir system are therefore tangibly climate-driven.

The five meteorological sub-divisions of India viz. Tamil Nadu, Coastal Andhra Pradesh, Rayalaseema, South Interior Karnataka and Kerala which together are referred here as the Southern Peninsular Region (SPR), are the major beneficiaries of Indian northeast monsoon which prevails over SPR during Oct-Dec. In this article how the knowledge base on Indian northeast monsoon evolved in the 19th, 20th and 21st centuries is presented. The article describes the transition from the southwest monsoon season to northeast monsoon season. The northeast monsoon rainfall (NMR) climatology of SPR based on 150 year data of 1871-2020 is presented and discussed. How the onset and withdrawal dates of northeast monsoon for 1871-2020 have been determined in various studies is set out. The inter-annual, intra-seasonal and diurnal variation features of NMR, components and weather systems of northeast monsoon are described. Short, medium range and seasonal forecasting of NMR, global teleconnections, relation between NMR and Indian southwest monsoon rainfall are elaborated. The climatic classification of SPR, research on northeast monsoon and a brief reference to the northeast monsoon of Sri Lanka are included.

The coupling of temporal and spatial variations of chlorophyll a concentration and the East Asian monsoons in the southern Taiwan Strait

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.