Increasing trend of northeast monsoon rainfall over the equatorial Indian Ocean and peninsular India

Peninsular India and Sri Lanka receive major part of their annual rainfall during the northeast monsoon season (October–December). The long-term trend in the northeast monsoon rainfall over the Indian Ocean and peninsular India is examined in the vicinity of global warming scenario using the Global Precipitation Climatology Project (GPCP) dataset available for the period 1979–2010. The result shows a significant increasing trend in rainfall rate of about 0.5 mm day^?1 decade^?1 over a large region bounded by 10 °S–10 °N and 55 °E–100 °E. The interannual variability of seasonal rainfall rate over peninsular India using conventional rain gauge data is also investigated in conjunction to the Indian Ocean dipole. The homogeneous rain gauge data developed by Indian Institute of Tropical Meteorology over peninsular India also exhibit the considerable upward rainfall trend of about 0.4 mm day^?1 decade^?1 during this period. The associated outgoing longwave radiation shows coherent decrease in the order of 2 W?m^?2 decade^?1 over the rainfall increase region.     

A universal spectrum for interannual variability of monsoon rainfall over India

Continuous periodogram analyses of 115 years (1871-1985) summer monsoon rainfall over the Indian region show that the power spectra follow the universal and unique inverse power law form of the statistical normal distribution with the percentage contribution to total variance representing the eddy probability corresponding to the normalized standard deviation equal to [(log L/log T50) – 1] where L is the period length in years and T50 the period up to which the cumulative percentage contribution to total variance is equal to 50. The above results are con-sistent with a recently developed non-deterministic cell dynamical model for atmospheric flows. The implications of the above result for prediction of interannual variability of rainfall is discussed.     

Surface pressure and summer monsoon rainfall over India

The relationship between the all-India summer monsoon rainfall and surface pressure over the Indian region has been examined to obtain a useful predictor for the monsoon rainfall. The data series of all-India monsoon rainfall and the mean pressures of three seasons before and after the monsoon season as well as the winter-to-spring pressure tendency (MAM-DJF) at 100 stations for the period 1951-1980 have been used in the analysis. The all-India monsoon rainfall is negatively correlated with the pressure of the spring (MAM) season preceding the monsoon and winter-to-spring seasonal difference as pressure tendency (MAM-DJF), at almost all the stations in India, and significantly with the pressures over central and northwestern regions. The average mean sea level pressure of six stations (Jodhpur, Ahmedabed, Bombay, Indore, Sagar and Akola) in the Western Central Indian (WCI) region showed highly significant (at 1% level) and consistent CCs of -0.63 for MAM and -0.56 for MAM-DJF for the period 1951–1980. Thus, the pre-monsoon seasonal pressure anomalies over WCI could provide a useful parameter for the long-range forecasting scheme of the Indian monsoon rainfall.     

Pre-monsoon surface pressure and summer monsoon rainfall over India

Summary The relationship between the surface air pressure field during the pre-monsoon months and the Indian summer monsoon rainfall is analysed using climate data from 105 stations situated in Eurasia between 0°–60° N and 20°–100° E. Moreover, grid-point data for the whole northern hemisphere are used. Pressure during April over an area around 50° N and 35° E is found to show a significant negative correlation with the subsequent monsoon rainfall. During May the pressure over a large part of the study area south of 40° N shows a significant correlation with its highest value in the heat low region over Pakistan. It is assumed that monitoring of pressure variations over this region may be useful in predicting monsoon rainfall, particularly the rainfall during the first half of the season. Certain limitations of the climate data in this region are also discussed.With 5 Figures     

Development of an artificial neural network based multi-model ensemble to estimate the northeast monsoon rainfall over south peninsular India: an application of extreme learning machine

The south peninsular part of India gets maximum amount of rainfall during the northeast monsoon (NEM) season [October to November (OND)] which is the primary source of water for the agricultural activities in this region. A nonlinear method viz., Extreme learning machine (ELM) has been employed on general circulation model (GCM) products to make the multi-model ensemble (MME) based estimation of NEM rainfall (NEMR). The ELM is basically is an improved learning algorithm for the single feed-forward neural network (SLFN) architecture. The 27 year (1982–2008) lead-1 (using initial conditions of September for forecasting the mean rainfall of OND) hindcast runs (1982–2008) from seven GCM has been used to make MME. The improvement of the proposed method with respect to other regular MME (simple arithmetic mean of GCMs (EM) and singular value decomposition based multiple linear regressions based MME) has been assessed through several skill metrics like Spread distribution, multiplicative bias, prediction errors, the yield of prediction, Pearson’s and Kendal’s correlation coefficient and Wilmort’s index of agreement. The efficiency of ELM estimated rainfall is established by all the stated skill scores. The performance of ELM in extreme NEMR years, out of which 4 years are characterized by deficit rainfall and 5 years are identified as excess, is also examined. It is found that the ELM could expeditiously capture these extremes reasonably well as compared to the other MME approaches.     

Temperature variability over the Indian Ocean and its relationship with Indian summer monsoon rainfall

Summary The present study examines the long term trend in sea surface temperatures (SSTs) of the Arabian Sea, Bay of Bengal and Equatorial South India Ocean in the context of global warming for the period 1901–2002 and for a subset period 1971–2002. An attempt has also been made to identify the relationship between SST variations over three different ocean areas, and All-India and homogeneous region summer monsoon rainfall variability, including the role of El-Ni?o/Southern Oscillation (ENSO). Annual sea surface temperatures of the Arabian Sea, Bay of Bengal and Equatorial South India Ocean show a significant warming trend of 0.7 °C, 0.6 °C and 0.5 °C per hundred years, respectively, and a relatively accelerated warming of 0.16 °C, 0.14 °C and 0.14 °C per decade during the 1971–2002 period. There is a positive and statistically significant relationship between SSTs over the Arabian Sea from the preceding November to the current February, and Indian monsoon rainfall during the period 1901–2002. The correlation coefficient increases from October and peaks in December, decreasing from February to September. This significant relationship is also found in the recent period 1971–2002, whereas, during 1901–70, the relationship is not significant. On the seasonal scale, Arabian Sea winter SSTs are positively and significantly correlated with Indian monsoon rainfall, while spring SSTs have no significant positive relationship. Nino3 spring SSTs have a negative significant relationship with Indian monsoon rainfall and it is postulated that there is a combined effect of Nino3 and Arabian Sea SSTs on Indian monsoon. If the Nino3 SST effect is removed, the spring SSTs over the Arabian Sea also have a significant relationship with monsoon rainfall. Similarly, the Bay of Bengal and Equatorial South Indian Ocean spring SSTs are significantly and positively correlated with Indian monsoon rainfall after removing the Nino3 effect, and correlation values are more pronounced than for the Arabian Sea. Authors’ address: Dr. D. R. Kothawale, A. A. Munot, H. P. Borgaonkar, Climatology and Hydrometeorology divisions, Indian Institute of Tropical Meteorology, Pune 411008, India.     

Seasonal extreme rainfall variability over India and its association with surface air temperature

Theoretical and Applied Climatology - Spatial variability in catchment processes is crucial for hydrologic and water resources planning and management. The spatial density of ground-based rain...     

Changes in monsoon precipitation patterns over Bangladesh and its teleconnections with global climate

Theoretical and Applied Climatology - Understanding changes in monsoon precipitation patterns is crucial as it determines the occurrence, intensity, and duration of floods and droughts in...     

Surface and upper air temperatures over India in relation to monsoon rainfall

Summary The relationship between the all-India summer monsoon rainfall and surface/upper air (850, 700, 500 and 200 mb levels) temperatures over the Indian region and its spatial and temporal characteristics have been examined to obtain a useful predictor for the monsoon rainfall. The data series of all-India and subdivisional summer monsoon rainfall and various seasonal air temperatures at 73 surface observatories and 9 radiosonde stations (1951–1980) have been used in the analysis. The Correlation Coefficients (CCs) between all-India monsoon rainfall and seasonal surface air temperatures with different lags relative to the monsoon season indicate a systematic relationship.The CCs between the monsoon rainfall and surface-air temperature of the preceding MAM (pre-monsoon spring) season are positive over many parts of India and highly significant over central and northwestern regions. The average surface air temperature of six stations i.e., Jodhpur, Ahmedabad, Bombay, Indore, Sagar and Akola in this region (Western Central India, WCI) showed a highly significant CC of 0.60 during the period 1951–1980. This relationship is also found to be consistently significant for the period from 1950 to present, though decreasing in magnitude after 1975. WCI MAM surface air temperature has shown significant CCs with the monsoon rainfall over eleven sub-divisions mainly in northwestern India, i.e., north of 15 °N and west of 80 °E.Upper air temperatures of the MAM season at almost all the stations and all levels considered show positive CCs with the subsequent monsoon rainfall. These correlations are significant at some central and north Indian stations for the lower and middle tropospheric temperatures.The simple regression equation developed for the period 1951–1980 isy = – 183.20 + 8.83x, wherey is the all-India monsoon rainfall in cm andx is the WCI average surface air temperature of MAM season in °C. This equation is significant at 0.1% level. The suitability of this parameter for inclusion in a predictive regression model along with five other global and regional parameters has been discussed. Multiple regression analysis for the long-range prediction of monsoon rainfall, using several combinations of these parameters indicates that the improvement of predictive skill considerably depends upon the selection of the predictors.With 9 Figures     

Possible teleconnections of winter rainfall in southern Brazil with Indian monsoon activity

Summary Three homogeneous subregions of rainfall anomaly are identified in southern Brazil from the precipitation data for the months of June to September for the period 1960–1993. The area average monthly rainfall of these regions is correlated with the Indian monsoon rainfall index (MRI). The correlations are weak; however some significant negative correlation coefficients of the order of 0.3 or higher are found, indicating that more than normal monsoon activity in July has an effect of reducing the rainfall in southern Brazil in austral winter. The relevance of this result lies in the fact that any rainfall shortage in the midwinter and spring seasons can increase ambiental hazards such as forest fires.With 5 Figures     

Intra-seasonal and Inter-annual variability of Bowen Ratio over rain-shadow region of North peninsular India

Intra-seasonal and inter-annual variability of Bowen Ratio (BR) have been studied over the rain-shadow region of north peninsular India during summer monsoon season. Daily grid point data of latent heat flux (LHF), sensible heat flux (SHF) from NCEP/NCAR Reanalysis for the period 1970–2014 have been used to compute daily area-mean BR. Daily grid point rainfall data at a resolution of 0.25° × 0.25° from APHRODITE’s Water Resources for the available period 1970–2007 have been used to study the association between rainfall and BR. The study revealed that BR rapidly decreases from 4.1 to 0.29 in the month of June and then remains nearly constant at the same value (≤0.1) in the rest of the season. High values of BR in the first half of June are indicative of intense thermals and convective clouds with higher bases. Low values of BR from July to September period are indicative of weak thermals and convective clouds with lower bases. Intra-seasonal and inter-annual variability of BR is found to be inversely related to precipitation over the region. BR analysis indicates that the land surface characteristics of the study region during July–September are similar to that over oceanic regions as far as intensity of thermals and associated cloud microphysical properties are concerned. Similar variation of BR is found in El Nino and La Nina years. During June, an increasing trend is observed in SHF and BR and decreasing trend in LHF from 1976 to 2014. Increasing trend in the SHF is statistically significant.

     

The Interannual variability of rainfall over homogeneous regions of Indian summer monsoon

Theoretical and Applied Climatology - The Indian subcontinent, due to its enormous variety of geographical features, is associated with inhomogeneity. Hence, in the present study, we have...     

New statistical models for long-range forecasting of southwest monsoon rainfall over India

The India Meteorological Department (IMD) has been issuing long-range forecasts (LRF) based on statistical methods for the southwest monsoon rainfall over India (ISMR) for more than 100 years. Many statistical and dynamical models including the operational models of IMD failed to predict the recent deficient monsoon years of 2002 and 2004. In this paper, we report the improved results of new experimental statistical models developed for LRF of southwest monsoon seasonal (June–September) rainfall. These models were developed to facilitate the IMD’s present two-stage operational forecast strategy. Models based on the ensemble multiple linear regression (EMR) and projection pursuit regression (PPR) techniques were developed to forecast the ISMR. These models used new methods of predictor selection and model development. After carrying out a detailed analysis of various global climate data sets; two predictor sets, each consisting of six predictors were selected. Our model performance was evaluated for the period from 1981 to 2004 by sliding the model training period with a window length of 23 years. The new models showed better performance in their hindcast, compared to the model based on climatology. The Heidke scores for the three category forecasts during the verification period by the first stage models based on EMR and PPR methods were 0.5 and 0.44, respectively, and those of June models were 0.63 and 0.38, respectively. Root mean square error of these models during the verification period (1981–2004) varied between 4.56 and 6.75% from long period average (LPA) as against 10.0% from the LPA of the model based on climatology alone. These models were able to provide correct forecasts of the recent two deficient monsoon rainfall events (2002 and 2004). The experimental forecasts for the 2005 southwest monsoon season based on these models were also found to be accurate.     

Stratospheric zonal wind and temperature in relation to summer monsoon rainfall over India

Summary  The interannual variability of the Indian summer monsoon (June–September) rainfall is examined in relation to the stratospheric zonal wind and temperature fluctuations at three stations, widely spaced apart. The data analyzed are for Balboa, Ascension and Singapore, equatorial stations using recent period (1964–1994) data, at each of the 10, 30 and 50 hPa levels. The 10 hPa zonal wind for Balboa and Ascension during January and the 30 hPa zonal wind for Balboa during April are found to be positively correlated with the subsequent Indian summer monsoon rainfall, whereas the temperature at 10 hPa for Ascension during May is negatively correlated with Indian summer monsoon rainfall. The relationship with stratospheric temperatures appears to be the best, and is found to be stable over the period of analysis. Stratospheric temperature is also significantly correlated with the summer monsoon rainfall over a large and coherent region, in the north-west of India. Thus, the 10 hPa temperature for Ascension in May appears to be useful for forecasting summer monsoon rainfall for not only the whole of India, but also for a smaller region lying to the north-west of India. Received July 30, 1999 Revised March 17, 2000     

Long-term variability in the date of monsoon onset over western India

The date of onset of the southwest monsoon in western India is critical for farmers as it influences the timing of crop plantation and the duration of the summer rainy season. Identifying long-term variability in the date of monsoon onset is difficult, however, as onset dates derived from the reanalysis of instrumental rainfall data are only available for the region from 1879. This study uses documentary evidence and newly uncovered instrumental data to reconstruct annual monsoon onset dates for western India for the period 1781–1878, extending the existing record by 97 years. The mean date of monsoon onset over the Mumbai (Bombay) area during the reconstruction period was 10 June with a standard deviation of 6.9 days. This is similar to the mean and standard deviation of the date of monsoon onset derived from instrumental data for the twentieth century. The earliest identified onset date was 23 May (in 1802 and 1839) and the latest 22 June (in 1825). The longer-term perspective provided by this study suggests that the climatic regime that governs monsoon advance over western India did not change substantially from 1781 to 1955. Monsoon onset over Mumbai has occurred at a generally later date since this time. Our results indicate that this change is unprecedented during the last 230 years. Following a discussion of the results, the nature of the relationship between the date of monsoon onset and the El Niño-Southern Oscillation is discussed. This relationship is shown to have been stable since 1781.