Relationship between all-India summer monsoon rainfall and southern oscillation/eastern equatorial Pacific sea surface temperature

The interannual variability of all-India summer monsoon (June to September) rainfall and its teleconnections with the southern oscillation index (SOI) and sea surface temperature (SST) anomaly of the eastern equatorial Pacific ocean have been examined for the period 1871–1978 for different seasons (i.e., winter, spring, summer and autumn). The relationship (correlation coefficient) between all-India summer monsoon rainfall andSOI for different seasons is positive and highly significant. Further examination of 10-, 20- and 30-year sliding window lengths’ correlations, brings out the highly consistent and significant character of the relationships. The relationship between all-India monsoon rainfall andSST for different seasons is negative and is significant at 1 % level or above. Drought years are characterised by negative anomalies ofSOI and positive anomalies ofSST and vice versa with flood years. The relationship betweenSOI andSST is negative and significant at 0.1 % level. The relationships between all-India summer monsoon rainfall,SOI and sst are expected to improve our understanding of the interannual variability of the summer monsoon.     

Global surface temperature in relation to northeast monsoon rainfall over Tamil Nadu

The local and teleconnective association between Northeast Monsoon Rainfall (NEMR) over Tamil Nadu and global Surface Temperature Anomalies (STA) is examined using the monthly gridded STA data for the period 1901–2004. Various geographical regions which have significant teleconnective signals associated with NEMR are identified. During excess (deficient) NEMR years, it is observed that the meridional gradient in surface air temperature anomalies between Europe and north Africa, in the month of September is directed from the subtropics (higher latitudes) to higher latitudes (subtropics). It is also observed that North Atlantic Oscillation (NAO) during September influences the surface air temperature distribution over north Africa and Europe. Also, the NAO index in January shows significant inverse relationship with NEMR since recent times. The central and eastern equatorial Pacific oceanic regions have significant and consistent positive correlation with NEMR while the western equatorial region has significant negative correlation with NEMR. A zonal temperature anomaly gradient index (ZTAGI) defined between eastern equatorial Pacific and western equatorial Pacific shows stable significant inverse relationship with NEMR     

Spatial monsoon variability with respect to NAO and SO

In this paper, the simultaneous effect of North Atlantic Oscillation (NAO) and Southern Oscillation (SO) on monsoon rainfall over different homogeneous regions/subdivisions of India is studied. The simultaneous effect of both NAO and SO on Indian summer monsoon rainfall (ISMR) is more important than their individual impact because both the oscillations exist simultaneously throughout the year. To represent the simultaneous impact of NAO and SO, an index called effective strength index (ESI) has been defined on the basis of monthly NAO and SO indices. The variation in the tendency of ESI from January through April has been analyzed and reveals that when this tendency is decreasing, then the ESI value throughout the monsoon season (June–September) of the year remains negative andvice versa. This study further suggests that during the negative phase of ESI tendency, almost all subdivisions of India show above-normal rainfall andvice versa. The correlation analysis indicates that the ESI-tendency is showing an inverse and statistically significant relationship with rainfall over 14 subdivisions of India. Area wise, about 50% of the total area of India shows statistically significant association. Moreover, the ESI-tendency shows a significant relationship with rainfall over north west India, west central India, central north east India, peninsular India and India as a whole. Thus, ESI-tendency can be used as a precursor for the prediction of Indian summer monsoon rainfall on a smaller spatial scale.     

Relationship between the southern oscillation/El Nino and rainfall in some tropical and midlatitude regions

Association of ENSO (El Nino/southern oscillation) events with annual rainfalls in S. America, Africa, India, Australia and New Zealand was found to be poor except for India and Victoria. For these two regions the relationships were one-sided i.e. most of the ENSO were associated with droughts; but many droughts were not associated with ENSO. for some rainfall series, the relationships are significant and prominent periodicities existed in the long periodicity region.     

Variation in the relationship of the Indian summer monsoon with global factors

Utilizing data for the long period 1871–1990, variation in the relationships between Indian monsoon rainfall (IMR) and tendencies of the global factors. Southern Oscillation Index (SOI) and the sea surface temperature (SST) over eastern equatorial Pacific Ocean has been explored. The periods for which relationships exist have been identified. Tendencies from the season SON (Sept-Oct-Nov) to season DJF (Dec-Jan-Feb) and from DJF to MAM (Mar-Apr-May) before the Indian summer monsoon are indicated respectively by SOIT-2/SSTT-2 and SOIT-l/SSTT-1, current tendency from JJA (June-July-Aug) to SON, by SOIT0/SSTT0, tendencies from SON to DJF and DJF to MAM following monsoon, by SOIT1/SSTT1 and SOIT2/SSTT2 respectively. It is observed that while the relationships of IMR with SSTT-1, SSTT0 and SSTT2 exist almost throughout the whole period, that with SOIT-1 exists for 1942–1990, with SOIT0 for 1871–1921 and 1957–1990 and with SOIT2, for 1871–1921 only. The relationships that exist with SOIT-1, SOIT2, SSTT-1, SSTT2 and with SSTT0 (for period 1931–1990) are found to be very good and those that exist with SOIT0 for periods 1871–1921 and 1957–90 and for SSTT0 for the period 1871–1930 are good. It is thus seen that the relationships of SOIT-1, SOIT0 and SOIT2 with IMR do not correspond well with those of SSTT-1, SSTT0 and SSTT2 with IMR respectively, even though SOI and SST are closely related to each other for all the seasons. SOIT-1 and SSTT-1 can continue to be used as predictors for IMRDuring the whole period, IMR is found to play a passive, i.e. of being influenced or anticipated by SSTT-1 as well as an active role, i.e. of influencing or anticipating SSTT2. This implies a complex and perhaps non-linear interaction between IMR and SST tendency from DJF to MAM. Possibly, this is a part of the larger interaction between Asian monsoon rainfall and the tropical Pacific. A possible physical mechanism for the interaction is indicated.     

Some characteristics of very heavy rainfall over Orissa during summer monsoon season

Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥125 mm) over Orissa during summer monsoon season (June–September) by analysing 20 years (1980–1999) daily rainfall data of different stations in Orissa. The principal objective of this study is to find out the role of synoptic scale monsoon disturbances in spatial and temporal variability of very heavy rainfall over Orissa. Most of the very heavy rainfall events occur in July and August. The region, extending from central part of coastal Orissa in the southeast towards Sambalpur district in the northwest, experiences higher frequency and higher intensity of very heavy rainfall with less interannual variability. It is due to the fact that most of the causative synoptic disturbances like low pressure systems (LPS) develop over northwest (NW) Bay of Bengal with minimum interannual variation and the monsoon trough extends in west-northwesterly direction from the centre of the system. The very heavy rainfall occurs more frequently with less interannual variability on the western side of Eastern Ghat during all the months and the season except September. It occurs more frequently with less interannual variability on the eastern side of Eastern Ghat during September. The NW Bay followed by Gangetic West Bengal/Orissa is the most favourable region of LPS to cause very heavy rainfall over different parts of Orissa except eastern side of Eastern Ghat. The NW Bay and west central (WC) Bay are equally favourable regions of LPS to cause very heavy rainfall over eastern side of Eastern Ghat. The frequency of very heavy rainfall does not show any significant trend in recent years over Orissa except some places in north-east Orissa which exhibit significant rising trend in all the monsoon months and the season as a whole.     

The chaotic time series of Indian monsoon rainfall and its prediction

The time series of Indian summer monsoon rainfall for the period 1871–1989 has been analysed using the method of deterministic chaos. It is found that a strange attractor underlies the time series implying the existence of a prediction function. This function has been approximated by a second-degree polynomial, involving the rainfalls of the past seven years and the coefficients have been estimated by least squares fit. The interannual variations of actual and computed rainfalls have been presented for a comparative study.     

上新世暖期和未来增暖背景下亚非夏季风降水变化的模拟对比研究

亚非夏季风降水对当地农业、水资源管理、粮食安全以及生态系统等均有广泛影响, 其对全球变暖的响应特征是一个重要的科学问题。本研究基于上新世模式比较计划(PlioMIP2)的15个上新世暖期模式模拟数据和第六次国际耦合模式比较计划(CMIP6)的31个高排放情景SSP5-8.5模式模拟数据, 对比分析了上新世暖期和未来增暖背景下亚非夏季风降水变化特征的差异及其成因机制。结果表明: 在这两类气候增暖背景下, 亚非夏季风降水都呈增加的趋势, 然而对应于全球平均1 ℃升温, 季风降水在上新世暖期的强度增幅(0.24 mm/day/℃)明显大于其在未来增暖情景的强度增幅(0.17 mm/day/℃), 前者降水异常值约为后者的1.4倍。这种差异主要源于, 对应于全球平均1 ℃升温, 上新世暖期中高纬增温幅度显著强于未来增暖情景, 而低纬度较小。上新世暖期低纬和北半球中高纬度之间的经向温度梯度减弱幅度更大, 有利于亚非夏季风环流显著增强, 从而导致亚非夏季风降水强度显著强于未来增暖时期。本研究表明, 气候增暖背景下低纬与中高纬度之间的经向温度梯度变化对亚非夏季风具有显著影响, 准确衡量暖期南-北半球间经向温度梯度的变化对预估区域季风和水循环变化至关重要。

     

Multivariate forecast of winter monsoon rainfall in India using SST anomaly as a predictor: Neurocomputing and statistical approaches

In this article, the complexities in the relationship between rainfall and sea surface temperature (SST) anomalies during the winter monsoon over India were evaluated statistically using scatter plot matrices and autocorrelation functions. Linear, as well as polynomial trend equations were obtained, and it was observed that the coefficient of determination for the linear trend was very low and it remained low even when polynomial trend of degree six was used. An exponential regression equation and an artificial neural network with extensive variable selection were generated to forecast the average winter monsoon rainfall of a given year using the rainfall amounts and the SST anomalies in the winter monsoon months of the previous year as predictors. The regression coefficients for the multiple exponential regression equation were generated using Levenberg-Marquardt algorithm. The artificial neural network was generated in the form of a multilayer perceptron with sigmoid non-linearity and genetic-algorithm based variable selection. Both of the predictive models were judged statistically using the Willmott's index, percentage error of prediction, and prediction yields. The statistical assessment revealed the potential of artificial neural network over exponential regression.     

Rainfall analysis for Indian monsoon region using the merged rain gauge observations and satellite estimates: Evaluation of monsoon rainfall features

Objective analysis of daily rainfall at the resolution of 1° grid for the Indian monsoon region has been carried out merging dense land rainfall observations and INSAT derived precipitation estimates. This daily analysis, being based on high dense rain gauge observations was found to be very realistic and able to reproduce detailed features of Indian summer monsoon. The inter-comparison with the observations suggests that the new analysis could distinctly capture characteristic features of the summer monsoon such as north-south oriented belt of heavy rainfall along the Western Ghats with sharp gradient of rainfall between the west coast heavy rain region and the rain shadow region to the east, pockets of heavy rainfall along the location of monsoon trough/low, over the east central parts of the country, over north-east India, along the foothills of Himalayas and over the north Bay of Bengal. When this product was used to assess the quality of other available standard climate products (CMAP and ECMWF reanalysis) at the gird resolution of 2.5°, it was found that the orographic heavy rainfall along Western Ghats of India was poorly identified by them. However, the GPCC analysis (gauge only) at the resolution of 1° grid closely discerns the new analysis. This suggests that there is a need for a higher resolution analysis with adequate rain gauge observations to retain important aspects of the summer monsoon over India. The case studies illustrated show that the daily analysis is able to capture large-scale as well as mesoscale features of monsoon precipitation systems. This study with data of two seasons (2001 and 2003) has shown sufficiently promising results for operational application, particularly for the validation of NWP models.     

Millennial-scale dynamics of the winter cold tongue in the southern South China Sea over the past 26 ka and the East Asian winter monsoon

Millennial-scale variations of the East Asian winter monsoon (EAWM) remain elusive due to sparse and controversial reconstructions. By compiling a variety of alkenone-based sea surface temperature (SST) estimates, we find that the west-east SST gradient in the southern South China Sea (SCS) well documents the temporal dynamics of the winter “cold tongue” off the southern Vietnam and by inference, variations in the EAWM intensity over the past 26 ka. Our results reveal that the winter “cold tongue” SSTs were significantly colder during Heinrich event 1 and the Younger Dryas event, resulting in an increased west-east SST gradient in the southern SCS due to a strengthened EAWM. Within dating uncertainties, an intensified EAWM during cold stadials was coeval with the shutdown or a reduction in strength of the Atlantic meridional overturning circulation (AMOC), exhibiting a strong linkage between the AMOC and the EAWM system. The west-east SST gradient also indicates an enhanced EAWM during the early Holocene, which may be induced by postglacial ice-sheet dynamics and a strong seasonal contrast in solar insolation. Our findings suggest that the EAWM was probably modulated by a complex interplay between the AMOC, solar insolation and ice-sheet dynamics on sub-orbital time scales.     

The role of low-frequency intraseasonal oscillations in the anomalous Indian summer monsoon rainfall of 2002

We analyze the dynamical features and responsible factors of the low-frequency intraseasonal time scales which influenced the nature of onset, intensity and duration of active/break phases and withdrawal of the monsoon during the anomalous Indian summer monsoon of 2002 — the most severe drought recorded in recent times. During that season, persistent warm sea surface temperature anomalies over the equatorial Indian Ocean played a significant role in modulating the strength of the monsoon Hadley circulation. This in turn affected the onset and intense break spells especially the long break during the peak monsoon month of July. Strong low-frequency intraseasonal modulations with significant impact on the onset and active/break phases occurred in 2002 which were manifested as a good association between low-frequency intraseasonal oscillations and the onset and active/break spells. Further, SST anomalies over the equatorial Indo-Pacific region on low-frequency intraseasonal time scales were found to affect the equatorial eastward and thereby off-equatorial northward propagations of enhanced convection over the Indian region. These propagations in turn modulated the active/break cycle deciding the consequent severity of the 2002 drought.     

Probabilities of excess and deficient southwest monsoon rainfall over different meteorological sub-divisions of India

Temporal distribution of southwest monsoon (June –September) rainfall is very useful for the country’s agriculture and food grain production. It contributes more than 75% of India’s annual rainfall. In view of this, an attempt has been made here to understand the performance of the monthly rainfall for June, July, August and September when the seasonal rainfall is reported as excess, deficient or normal. To know the dependence of seasonal rainfall on monthly rainfall, the probabilities of occurrence of excess, deficient and normal monsoon when June, July, August and also June + July and August + September rainfall is reported to be excess or deficient, are worked out using the long homogenous series of 124 years (1871-–1994) data of monthly and seasonal rainfall of 29 meteorological sub-divisions of the plain regions of India. In excess monsoon years, the average percentage contribution of each monsoon month to the long term mean (1871–1994) seasonal rainfall (June –September) is more than that of the normal while in the deficient years it is less than normal. This is noticed in all 29 meteorological sub-divisions. From the probability analysis, it is seen that there is a rare possibility of occurrence of seasonal rainfall to be excess/deficient when the monthly rainfall of any month is deficient/excess.     

过去千年3个特征时期东亚冬夏季风关系的模拟研究

使用美国大气研究中心开展的过去千年集合模拟试验（Community Earth System Model-Last Millennium Ensemble,简称CESM-LME）数据,对过去千年（公元850~2005年）3个重要的特征时期——中世纪气候异常期、小冰期和现代暖期的东亚冬、夏季风关系,尤其是年代-多年代尺度上的关系进行了对比研究。结果表明：在年代和多年代尺度上,由自然外强迫主导的中世纪气候异常期和小冰期及人类活动主导的现代暖期,东亚冬、夏季风均呈负位相变化形势,但影响二者关系的机制在3个时期并不相同。研究发现,太平洋年代际振荡（Pacific Decadal Oscillation,简称PDO）可能是造成前两个特征时期东亚冬、夏季风反位相变化的主要原因,大西洋多年代际振荡（Atlantic Multidecadal Oscillation,简称AMO）的作用相对较小。现代暖期AMO的作用有所加强,与PDO的作用相当,同时夏季风环流对PDO和AMO的响应较前两个时期强,且响应特征有所不同,这可能与人类活动有较大关系。另外在人类活动作用下,季风指数的定义方法可能会对季风关系的研究结果产生影响,这是未来预估研究中需要留意的地方。

     

东亚和南亚夏季风对中国季风区径流深影响

为揭示中国东部季风区径流深对东亚和南亚夏季风变化的响应规律,建立了八大流域VIC(Variable Infiltration Capacity)水文模型以及应用了Mann-Kendall和局部加权回归分析(Locally Weighted Scatter Plot Smoothing, LOWESS)相关性检验方法,并分析了径流深系数空间变化情况。结果表明:东亚夏季风与径流深显著性相关范围要明显大于南亚夏季风,主要位于长江流域以北和松花江流域以南的广大地区以及华南部分地区,并分别成正相关和负相关;而南亚夏季风与径流深显著性正负相关的区域则分别位于华南地区及长江流域上游部分地区。此外,季风区径流深系数空间差异明显,易产流区主要位于长江流域及东南沿海地区,而黄河及海河流域则产流较难。因此,对东亚及南亚夏季风的研究可为预测中国东部不同地区的水文过程及水资源变化提供重要的科学参考。     

Large-scale interannual variation of the summer monsoon over India and its empirical prediction

Large-scale interannual variability of the northern summer southwest monsoon over India is studied by examining its variation in the dry area during the period 1871–1984. On the mean summer monsoon rainfall (June to September total) chart the 800 mm isohyet divides the country into two nearly equal halves, named as dry area (monsoon rainfall less than 800 mm) and wet area (monsoon rainfall greater than 800 mm). The dry area/wet area shows large variations from one year to another, and is considered as an index for assessing the large-scale performance of the Indian summer monsoon. Statistical and fluctuation characteristics of the summer monsoon dry area (SMDA) are reported. To identify possible causes of variation in the Indian summer monsoon, the correlation between the summer monsoon dry area and eleven regional/global circulation parameters is examined. The northern hemisphere surface air temperature, zonal/hemispheric/global surface air and upper air temperatures, Southern Oscillation, Quasi-biennial oscillation of the equatorial lower stratosphere, April 500-mb ridge along 75°E over India, the Indian surface air temperature and the Bombay sea level pressure showed significant correlation. A new predictor parameter that is preceding year mean monsoon rainfall of a few selected stations over India has been suggested in the present study. The stations have been selected by applying the objective technique ‘selecting a subset of few gauges whose mean monsoon rainfall of the preceding year has shown the highest correlation coefficient (CC) with the SMDA’. Bankura (Gangetic West Bengal), Cuddalore (Tamil Nadu) and Anupgarh (West Rajasthan) entered the selection showing a CC of 0.724. Using a dependent sample of 1951–1980 a predictive model (multiple CC = 0.745) has also been developed for the SMDA with preceding year mean monsoon rainfall of the three selected stations and the sea level pressure tendency at Darwin from Jan–Feb to Mar–May as independent parameters.     

A study of the empirical functions of the height fields over India and their relation with the rainfall

The empirical orthogonal functions have been obtained for the individual summer monsoon (June through September) months using the grid point values of monthly 700 mb geopotential heights over Indian region. The data for 21 summer monsoon months for the years 1958 to 1978 have been used in the present computation. The major variance reduction is due to the first three dominant functions accounting over 80% of the total variance in each month. The variance reduction only due to the first function ranges from 45 to 65%. The first function has in-pbase oscillation throughout the area indicating that the area under study is homogeneous and the centre of the oscillation lies over northwest India. The amplitudes of the first function also show generally quasipers stence in their sign within a season. The second function has two centres of action over the region of monsoon trough which are in phase. The third function has also two centres oriented in the east-west direction but they are in the opposite phase. Fairly large values of correlation coefficients between the patterns of the different monsoon months suggest that the patterns for these months corresponding to the first and the second functions respectively are quite similar. The patterns for these months also evolve with time in a related way. The spectrum analysis to the time series of amplitudes indicates the presence of the quasi-periodicity of 3 years during these monsoon months. The amplitudes corresponding to the dominant functions are found to be significantly related with the rainfall of central and western parts of India     

Coral δO records as an indicator of winter monsoon intensity in the South China Sea

We have used correlative analysis between mean December-January-February winter wind velocities, measured at the Xisha Meteorological Observatory (16°50′N, 112°20′E) in the middle of the South China Sea, and mean δ¹⁸O data for the corresponding month from Porites lutea coral, collected in Longwan waters (19°20′N, 110°39′E), to obtain a linear equation relating the two datasets. This winter wind velocity for the South China Sea (WMII_scs) can then be correlated to the coral δ¹⁸O by the equation WMII_scs = −1.213-1.351 δ¹⁸O (‰ PDB), r = −0.60, n = 40, P = 0.01. From this, the calculated WMII_scs-δ18O series from 1944 to 1997 tends to decrease during the 1940s to the 1960s; it increases slightly during the 1970s and then decreases again in the 1980s and 1990s. The calculated decadal mean WMII_scs-δ18O series had a obvious decrease from 5.92 to 4.63 m/s during the period of 1944-1997. The calculated yearly mean WMII_scs-δ18O value is 5.58 m/s from 1944 to 1976 and this decreases to 4.85 m/s from 1977 to 1998. That is the opposite trend to the observed yearly mean SST variation. The yearly mean SST anomaly is −0.27° from 1943 to 1976 and this increases to +0.16° from 1977 to 1998. Spectral analysis used on a 54-year-long calculated WMII_scs-δ18O series produces spectral peaks at 2.4-7 yr, which can be closely correlated with the quasibiennial oscillation band (QBO band, 2-2.4 yr) and the El Ñino southern oscillation band (ENSO band, 3-8 yr). Hence most of the variability of the winter monsoon intensity in the middle of the South China Sea is mainly constrained by changes in the thermal difference between the land and the adjoining sea area, perhaps due to global warming.     

On the impacts of ENSO and Indian Ocean dipole events on sub-regional Indian summer monsoon rainfall

The relative impacts of the ENSO and Indian Ocean dipole (IOD) events on Indian summer (June–September) monsoon rainfall at sub-regional scales have been examined in this study. GISST datasets from 1958 to 1998, along with Willmott and Matsuura gridded rainfall data, all India summer monsoon rainfall data, and homogeneous and sub-regional Indian rainfall datasets were used. The spatial distribution of partial correlations between the IOD and summer rainfall over India indicates a significant impact on rainfall along the monsoon trough regions, parts of the southwest coastal regions of India, and also over Pakistan, Afghanistan, and Iran. ENSO events have a wider impact, although opposite in nature over the monsoon trough region to that of IOD events. The ENSO (IOD) index is negatively (positively) correlated (significant at the 95% confidence level from a two-tailed Student t-test) with summer monsoon rainfall over seven (four) of the eight homogeneous rainfall zones of India. During summer, ENSO events also cause drought over northern Sri Lanka, whereas the IOD events cause surplus rainfall in its south. On monthly scales, the ENSO and IOD events have significant impacts on many parts of India. In general, the magnitude of ENSO-related correlations is greater than those related to the IOD. The monthly-stratified IOD variability during each of the months from July to September has a significant impact on Indian summer monsoon rainfall variability over different parts of India, confirming that strong IOD events indeed affect the Indian summer monsoon.

Improving the performance of precipitation outputs from Global Climate Models to predict monthly and seasonal rainfall over the Indian subcontinent

Skilful prediction of the monthly and seasonal summer monsoon rainfall over India at a smaller spatial scale is a major challenge for the scientific community. The present study is aimed at achieving this objective by hybridising two mathematical techniques, namely synthetic superensemble (SSE) and supervised principal component regression (SPCR) on six state-of-the art Global Climate Models (GCMs). The performance of the mathematical model is evaluated using correlation analysis, the root mean square error, and the Nash–Sutcliffe efficiency index. Results feature reasonable improvement over central India, which is a zone of maximum rainfall activity in the summer monsoon season. The study also highlights improvement in the monthly prediction of rainfall over raw GCMs (15–20% improvement) with exceptional improvement in July. The developed model is also examined for anomalous years of monsoon and it is found that the model is able to capture the signs of anomalies over different gridpoints of the Indian domain.