Homogeneous Indian Monsoon rainfall: Variability and prediction

The Indian summer monsoon rainfall is known to have considerable spatial variability, which imposes some limitations on the all-India mean widely used at present. To prepare a spatially coherent monsoon rainfall series for the largest possible area, fourteen subdivisions covering the northwestern and central parts of India (about 55% of the total area of the country), having similar rainfall characteristics and associations with regional/global circulation parameters are merged and their area-weighted means computed, to form monthly and seasonal Homogeneous Indian Monsoon (HIM) rainfall series for the period 1871–1990. This paper includes a listing of monthly and seasonal rainfall of HIM region. HIM rainfall series has been statistically analysed to understand its characteristics, variability and teleconnections for long-range prediction. HIM rainfall series isfound to be homogeneous, Gaussian distributed and free from persistence. The mean (R) rainfall is 757 mm (87% of annual) and standard deviation (S) 119 mm, with a Coefficient of Variation (CV) of 16%. There were 21 dry (K, -<R S) and 19 wet (R _i R + S) years during 1871–1990. There were clusters of frequent negative departures during 1899–1920 and 1965–1987 and positive departures during 1942–1961. The recent three decades show very high rainfall variability with 10 dry and 6 wet years. The decadal averages were alternatively positive and negative for three consecutive decades, viz., 1871–1900 (positive); 1901–1930 (negative); 1931–1960 (positive) and 1961–1990 (negative) respectively. Significant QBO and autocorrelation at 14th lag have been found in HIM rainfall series. To delineate the changes in the climatic regime of the Indian summer monsoon, sliding correlation coefficients (CCs) between HIM rainfall series and (i) Bombay msl pressure, (ii) Darwin msl pressure and (iii) Northern Hemisphere surface air temperature over the period 1871–1990 have been examined. The 31-year sliding CCs showed the systematic turning points of positive and negative CCs around the years, 1900 and 1940. In the light of other corroborative evidences, these turning points seem to delineate ‘meridional’ monsoon regime during 1871–1900 and 1940–1990 and ‘zonal’ monsoon regime during 1901–1940. The monsoon signal is particularly dominant in many regional and global circulation parameters, during 1951–1990. Using the teleconnections ofHIM series with 12 regional/global circulation parameters during the recent 36-year period 1951–86 regression models have been developed for long-range prediction. In the regression equations 3 to 4 parameters were entered, explaining upto 80% of the variance, depending upon the data period. The parameters that prominently enter the multiple regression equations are (i) Bombay msl pressure, (ii) April 500 mb Ridge at 75°E, (iii) NH temperature, (iv) Nouvelle minus Agalega msl pressure and (v) South American msl pressure. Eleven circulation parameters for the period 1951–80 were subjected to Principal Component Analysis (PCA) and the PC’s were used in the regression model to estimate HIM rainfall. The multiple regression with three PCs explain 72% of variance in HIM rainfall.     

Interannual and long-term variability of the summer monsoon and its possible link with northern hemispheric surface air temperature

Some statistical properties of the summer monsoon seasonal rainfall for India during the last 100 years (1881–1980) are presented. The most recent decade of 1971–1980 shows the lowest value of standard-decadal average monsoon rainfall (86.40 cm) and is also characterised by the second highest value of coefficient of variation in monsoon rainfall (12.4 %). The combined last two standard-decadal period of 1961–1980 was the period of the largest coefficient of variation and the lowest average monsoon rainfall for India. The possible influence of global climatic variability on the performance of the monsoon is also examined. Analyses of correlation coefficient show that a statistically significant positive relationship with a time-lag of about six months exists between monsoon rainfall and northern hemispheric surface air temperature. A cooler northern hemisphere during January/February leads to a poor monsoon. All the major drought years during the last 3 decades had much cooler January/February periods over the northern hemisphere—1972 having the coldest January/February with a temperature departure of −0.94°C and the most disastrous monsoon failure.     

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.     

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.

Anomalous behaviour of the Indian summer monsoon 2009

The Indian subcontinent witnessed a severe monsoon drought in the year 2009. India as a whole received 77% of its long period average during summer monsoon season (1 June to 30 September) of 2009, which is the third highest deficient all India monsoon season rainfall year during the period 1901–2009. Therefore, an attempt is made in this paper to study the characteristic features of summer monsoon rainfall of 2009 over the country and to investigate some of the possible causes behind the anomalous behaviour of the monsoon.     

Summer monsoon intraseasonal oscillation over eastern Arabian sea — As revealed by TRMM microwave imager products

The time evolution of atmospheric parameters on intraseasonal time scale in the eastern Arabian Sea (EAS) is studied during the summer monsoon seasons of 1998–2003 using Tropical Rainfall Measuring Mission Microwave Imager (TMI) data. This is done using the spectral and wavelet analysis. Analysis shows that over EAS, total precipitable water vapour (TWV) and sea surface wind speed (SWS) have a periodicity of 8–15 days, 15–30 days and 30–60 days during the monsoon season. Significant power is seen in the 8–15-day time scale in TWV during onset and retreat of the summer monsoon. Analysis indicates that the timings of the intensification of 8–15, 15–30, and 30–60 days oscillations have a profound effect on the evolution of the daily rainfall over west coast of India. The positive and negative phases of these oscillations are directly related to the active and dry spells of rainfall along the west coast of India. The spectral analysis shows interannual variation of TWV and SWS. Heavy rainfall events generally occur over the west coast of India when positive phases of both 30–60 days and 15–30 days modes of TWV and SWS are simultaneously present.     

Interannual and long-term variability of Indian summer monsoon rainfall

Analysis of summer monsoon (June to September) rainfall series of 29 subdivisions based on a fixed number of raingauges (306 stations) has been made for the 108-year period 1871–1978 for interannual and long-term variability of the rainfall. Statistical tests show that the rainfall series of 29 sub-divisions are homogeneous, Gaussian-distributed and do not contain any persistence. The highest and the lowest normal rainfall of 284 and 26 cm are observed over coastal Karnataka and west Rajasthan sub-divisions respectively. The interannual variability (range) varies over different sub-divisions, the lowest being 55 and the highest 231% of the normal rainfall, for south Assam and Saurashtra and Kutch sub-divisions respectively. High spatial coherency is observed between neighbouring sub-divisions; northeast region and northern west and peninsular Indian sub-divisions show oppositic correlation tendency. Significant change in mean rainfall of six sub-divisions is noticed. Correlogram and spectrum analysis show the presence of 14-year and QBO cycles in a few sub-divisional rainfall series.     

Global temperature and monsoon activity

In this paper an attempt has been made to search a new parameter for the prediction of the Indian summer monsoon rainfall. For this purpose the relationship of the global surface-air temperature of four standard seasons viz., Winter (December-January-February), Spring (March-April-May), Summer (June-July-August), Autumn (September-October-November) with the Indian summer monsoon rainfall has been carried out. The same analysis is also carried out with surface-air temperature anomalies within the tropical belt (30°S to 30°N) and Indian summer monsoon rainfall. For the present study data for 30 years period from 1958 to 1988 have been used. The analysis reveals that there is a strong inverse relationship between the monsoon activity and the tropical belt temperature.     

Changing predictability of Indian monsoon rainfall anomalies?

The predictability of Indian summer monsoon rainfall from pre-season circulation indices is explored from observations during 1939–91. The predictand is the all-India average of June–September precipitation NIR, and the precursors examined are the latitude position of the 500 mb ridge along 75°E in April (L), the pressure tendency April minus January at Darwin (DPT), March-April-May temperature at six stations in west central India (T6), the sea surface temperature (SST) anomaly in the northeastern Arabian Sea in May (ASM), SST anomaly in the Arabian Sea in January (ANJ), northern hemisphere temperature anomaly in January–February (NHT), and Eurasian snow cover in January (SNOW). Monsoon rainfall tends to be enhanced with a more northerly ridge position, small Darwin pressure tendency, warmer pre-season conditions, and reduced winter snow cover. However, relationships have varied considerably over the past half-century, with the strongest associations during 1950–80, and a drastic weakening in the 1980s. Four prediction models were constructed based on stepwise multiple regression, using as predictors combinations of L, DPT, T6, ASM, and NHT, with 1939–68 as “dependent” dataset, or training period, and 1969–91 as “independent” dataset or verification period. For the 1969–80 portion of the verification period calculated and observed NIR values agreed closely, with the models explaining 74–79% of the variance. By contrast, after 1980 predictions deteriorated drastically, with the explained variance for the 1969–89 time span dropping to 25–31%. The monsoon rainfall of 1990 and 1991 turned out to be again highly predictable from models based on stepwise multiple regression and linear discriminant analysis and using as input L + DPT or L + DPT + NHT, and with this encouragement an experimental real-time forecast was issued of the 1992 monsoon rainfall. These results underline the need for investigations into decadal-scale changes in the general circulation setting and raise concern for the continued success of seasonal forecasting.     

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.     

Active and break spells of the Indian summer monsoon

In this paper, we suggest criteria for the identification of active and break events of the Indian summer monsoon on the basis of recently derived high resolution daily gridded rainfall dataset over India (1951–2007). Active and break events are defined as periods during the peak monsoon months of July and August, in which the normalized anomaly of the rainfall over a critical area, called the monsoon core zone exceeds 1 or is less than −1.0 respectively, provided the criterion is satisfied for at least three consecutive days. We elucidate the major features of these events. We consider very briefly the relationship of the intraseasonal fluctuations between these events and the interannual variation of the summer monsoon rainfall.     

Momentum transport of wave zero during March: A possible predictor for the Indian summer monsoon

Analysis of monthly momentum transport of zonal waves at 850 hPa for the period 1979 to 1993, between ‡S and ‡N for January to April, using zonal (u) and meridional (v) components of wind taken from the ECMWF reanalysis field, shows a positive correlation (.1% level of significance) between the Indian summer monsoon rainfall (June through September) and the momentum transport of wave zero TM(0) over latitudinal belt between 25‡S and 5‡N (LB) during March. Northward (Southward) TM(0) observed in March over LB subsequently leads to a good (drought) monsoon season over India which is found to be true even when the year is marked with the El-Nino event. Similarly a strong westerly zone in the Indian Ocean during March, indicates a good monsoon season for the country, even if the year is marked with El-Nino. The study thus suggests two predictors, TM(0) over LB and the strength of westerly zone in the Indian Ocean during March.     

Sea-breeze-initiated rainfall over the east coast of India during the Indian southwest monsoon

Sea-breeze-initiated convection and precipitation have been investigated along the east coast of India during the Indian southwest monsoon season. Sea-breeze circulation was observed on approximately 70–80% of days during the summer months (June–August) along the Chennai coast. Average sea-breeze wind speeds are greater at rural locations than in the urban region of Chennai. Sea-breeze circulation was shown to be the dominant mechanism initiating rainfall during the Indian southwest monsoon season. Approximately 80% of the total rainfall observed during the southwest monsoon over Chennai is directly related to convection initiated by sea-breeze circulation.     

Meteorological fields variability over the Indian seas in pre and summer monsoon months during extreme monsoon seasons

In this study, the possible linkage between summer monsoon rainfall over India and surface meteorological fields (basic fields and heat budget components) over monsoon region (30‡E-120‡E, 30‡S30‡N) during the pre-monsoon month of May and summer monsoon season (June to September) are examined. For this purpose, monthly surface meteorological fields anomaly are analyzed for 42 years (1958-1999) using reanalysis data of NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research). The statistical significance of the anomaly (difference) between the surplus and deficient monsoon years in the surface meteorological fields are also examined by Student’s t-test at 95% confidence level. Significant negative anomalies of mean sea level pressure are observed over India, Arabian Sea and Arabian Peninsular in the pre-monsoon month of May and monsoon season. Significant positive anomalies in the zonal and meridional wind (at 2 m) in the month of May are observed in the west Arabian Sea off Somali coast and for monsoon season it is in the central Arabian Sea that extends up to Somalia. Significant positive anomalies of the surface temperature and air temperature (at 2 m) in the month of May are observed over north India and adjoining Pakistan and Afghanistan region. During monsoon season this region is replaced by significant negative anomalies. In the month of May, significant positive anomalies of cloud amount are observed over Somali coast, north Bay of Bengal and adjoining West Bengal and Bangladesh. During monsoon season, cloud amount shows positive anomalies over NW India and north Arabian Sea. There is overall reduction in the incoming shortwave radiation flux during surplus monsoon years. A higher magnitude of latent heat flux is also found in surplus monsoon years for the month of May as well as the monsoon season. The significant positive anomaly of latent heat flux in May, observed over southwest Arabian Sea, may be considered as an advance indicator of the possible behavior of the subsequent monsoon season. The distribution of net heat flux is predominantly negative over eastern Arabian Sea, Bay of Bengal and Indian Ocean. Anomaly between the two extreme monsoon years in post 1980 (i.e., 1988 and 1987) shows that shortwave flux, latent heat flux and net heat flux indicate reversal in sign, particularly in south Indian Ocean. Variations of the heat budget components over four smaller sectors of Indian seas, namely Arabian Sea, Bay of Bengal and west Indian Ocean and east Indian Ocean show that a small sector of Arabian Sea is most dominant during May and other sectors showing reversal in sign of latent heat flux during monsoon season.     

Impact of vegetation on the simulation of seasonal monsoon rainfall over the Indian subcontinent using a regional model

The change in the type of vegetation fraction can induce major changes in the local effects such as local evaporation, surface radiation, etc., that in turn induces changes in the model simulated outputs. The present study deals with the effects of vegetation in climate modeling over the Indian region using the MM5 mesoscale model. The main objective of the present study is to investigate the impact of vegetation dataset derived from SPOT satellite by ISRO (Indian Space Research Organization) versus that of USGS (United States Geological Survey) vegetation dataset on the simulation of the Indian summer monsoon. The present study has been conducted for five monsoon seasons (1998–2002), giving emphasis over the two contrasting southwest monsoon seasons of 1998 (normal) and 2002 (deficient). The study reveals mixed results on the impact of vegetation datasets generated by ISRO and USGS on the simulations of the monsoon. Results indicate that the ISRO data has a positive impact on the simulations of the monsoon over northeastern India and along the western coast. The MM5-USGS has greater tendency of overestimation of rainfall. It has higher standard deviation indicating that it induces a dispersive effect on the rainfall simulation. Among the five years of study, it is seen that the RMSE of July and JJAS (June–July–August–September) for All India Rainfall is mostly lower for MM5-ISRO. Also, the bias of July and JJAS rainfall is mostly closer to unity for MM5-ISRO. The wind fields at 850 hPa and 200 hPa are also better simulated by MM5 using ISRO vegetation. The synoptic features like Somali jet and Tibetan anticyclone are simulated closer to the verification analysis by ISRO vegetation. The 2 m air temperature is also better simulated by ISRO vegetation over the northeastern India, showing greater spatial variability over the region. However, the JJAS total rainfall over north India and Deccan coast is better simulated using the USGS vegetation. Sensible heat flux over north-west India is also better simulated by MM5-USGS.     

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.     

Influence of different land-surface processes on Indian summer monsoon circulation

The impact of different land-surface parameterisation schemes for the simulation of monsoon circulation during a normal monsoon year over India has been analysed. For this purpose, three land-surface parameterisation schemes, the NoaH, the Multi-layer soil model and the Pleim-Xiu were tested using the latest version of the regional model (MM5) of the Pennsylvania State University (PSU)/National Center for Atmospheric Research (NCAR) over the Indian summer monsoon region. With respect to different land-surface parameterisation schemes, latent and sensible heat fluxes and rainfall were estimated over the Indian region. The sensitivity of some monsoon features, such as Somali jet, tropical easterly jet and mean sea level pressure, is discussed. Although some features of the Indian summer monsoon, such as wind and mean sea level pressure, were fairly well-simulated by all three schemes, many differences were seen in the simulation of the typical characteristics of the Indian summer monsoon. It was noticed from the results that the features of the Indian summer monsoon, such as strength of the low-level westerly jet, the cross-equatorial flow and the tropical easterly jet were better simulated by NoaH compared with verification analysis than other land-surface schemes. It was also observed that the distribution of precipitation over India during the peak period of monsoon (July) was better represented with the use of the NoaH scheme than by other schemes.

Energetics of lower tropospheric ultra-long waves: A key to intra-seasonal variability of Indian monsoon

Analysis of fifty four (1951–2004) years of daily energetics of zonal waves derived from NCEP/NCAR wind (u and υ) data and daily rainfall received over the Indian landmass (real time data) during southwest monsoon season (1 June–30 September) indicate that energetics (momentum transport and kinetic energy) of lower tropospheric ultra-long waves (waves 1 and 2) of low latitudes hold a key to intra-seasonal variability of monsoon rainfall over India. Correlation coefficient between climatology of daily (122 days) energetics of ultra-long waves and climatology of daily rainfall over Indian landmass is 0.9. The relation is not only significant but also has a predictive potential. The normalised plot of both the series clearly indicates that the response period of rainfall to the energetics is of 5–10 days during the onset phase and 4–7 days during the withdrawal phase of monsoon over India. During the established phase of monsoon, both the series move hand-in-hand. Normalised plot of energetics of ultra-long waves and rainfall for individual year do not show marked deviation with respect to climatology. These results are first of its kind and are useful for the short range forecast of rainfall over India.     

东绒布冰芯净积累量与印度夏季风降水的关系

珠穆朗玛峰东侧东绒布冰川积累区的降水主要是由印度夏季风环流带来的.根据东绒布冰芯记录恢复的净积累量与印度中北部和印度半岛东部地区的夏季风降水量具有基本一致的周期, 三者有着较好的相关性, 因此可以通过冰芯净积累量来反映更长时间序列印度某些地区夏季风降水量的变化趋势.东绒布冰芯净积累量的相对变化幅度大于印度夏季风降水量的变化, 表明高海拔地区的降水比低海拔地区具有更高的敏感性.     

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.