Performance of general circulation models and their ensembles for the prediction of drought indices over India during summer monsoon

The drought during the months of June to September (JJAS) results in significant deficiency in the annual rainfall and affects the hydrological planning, disaster management, and the agriculture sector of India. Advance information on drought characteristics over the space may help in risk assessment over the country. This issue motivated the present study which deals with the prediction of drought during JJAS through standardized precipitation index (SPI) using nine general circulation models (GCM) product. Among these GCMs, three are the atmospheric and six are atmosphere–ocean coupled models. The performance of these GCM’s predicted SPI is examined against the observed SPI for the time period of 1982–2010. After a rigorous analysis, it can be concluded that the skill of prediction by GCM is not satisfactory, whereas the ability of the coupled models is better than the atmospheric models. An attempt has been made to improve the accuracy of predicted SPI using two different multi-model ensemble (MME) schemes, viz., arithmetic mean and weighted mean using singular value decomposition-based multiple linear regressions (SVD-MLR) of GCMs. It is found that among these MME techniques, SVD-MLR-based MME has more skill as compared to simple MME as well as individual GCMs.     

Performance of Multi Model Canonical Correlation Analysis (MMCCA) for prediction of Indian summer monsoon rainfall using GCMs output

The emerging advances in the field of dynamical prediction of monsoon using state-of-the-art General Circulation Models (GCMs) have led to the development of various multi model ensemble techniques (MMEs). In the present study, the concept of Canonical Correlation Analysis is used for making MME (referred as Multi Model Canonical Correlation Analysis or MMCCA) for the prediction of Indian summer monsoon rainfall (ISMR) during June-July-August-September (JJAS). This method has been employed on the rainfall outputs of six different GCMs for the period 1982 to 2008. The prediction skill of ISMR by MMCCA is compared with the simple composite method (SCM) (i.e. arithmetic mean of all GCMs), which is taken as a benchmark. After a rigorous analysis through different skill metrics such as correlation coefficient and index of agreement, the superiority of MMCCA over SCM is illustrated. Performance of both models is also evaluated during six typical monsoon years and the results indicate the potential of MMCCA over SCM in capturing the spatial pattern during extreme years.     

Experimental real-time multi-model ensemble (MME) prediction of rainfall during monsoon 2008: Large-scale medium-range aspects

Realistic simulation/prediction of the Asian summer monsoon rainfall on various space–time scales is a challenging scientific task. Compared to mid-latitudes, a proportional skill improvement in the prediction of monsoon rainfall in the medium range has not happened in recent years. Global models and data assimilation techniques are being improved for monsoon/tropics. However, multi-model ensemble (MME) forecasting is gaining popularity, as it has the potential to provide more information for practical forecasting in terms of making a consensus forecast and handling model uncertainties. As major centers are exchanging model output in near real-time, MME is a viable inexpensive way of enhancing the forecasting skill and information content. During monsoon 2008, on an experimental basis, an MME forecasting of large-scale monsoon precipitation in the medium range was carried out in real-time at National Centre for Medium Range Weather Forecasting (NCMRWF), India. Simple ensemble mean (EMN) giving equal weight to member models, bias-corrected ensemble mean (BCEMn) and MME forecast, where different weights are given to member models, are the products of the algorithm tested here. In general, the aforementioned products from the multi-model ensemble forecast system have a higher skill than individual model forecasts. The skill score for the Indian domain and other sub-regions indicates that the BCEMn produces the best result, compared to EMN and MME. Giving weights to different models to obtain an MME product helps to improve individual member models only marginally. It is noted that for higher rainfall values, the skill of the global model rainfall forecast decreases rapidly beyond day-3, and hence for day-4 and day-5, the MME products could not bring much improvement over member models. However, up to day-3, the MME products were always better than individual member models.     

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.     

Trends and variability of meteorological drought over the districts of India using standardized precipitation index

Meteorological drought during the southwest monsoon season and for the northeast monsoon season over five meteorological subdivisions of India for the period 1901–2015 has been examined using district and all India standardized precipitation index (SPI). Whenever all India southwest monsoon rainfall was less than ?10% or below normal, for those years all India SPI was found as ?1 or less. Composite analysis of SPI for the below normal years, viz., less than ?15% and ?20% of normal rainfall years indicate that during those years more than 30% of country’s area was under drought condition, whenever all India southwest monsoon rainfall was –15% or less than normal. Trend analysis of monthly SPI for the monsoon months identified the districts experiencing significant increase in drought occurrences. Significant positive correlation has been found with the meteorological drought over most of the districts of central, northern and peninsular India, while negative correlation was seen over the districts of eastern India with NINO 3.4 SST. For the first time, meteorological drought analysis over districts and its association with equatorial pacific SST and probability analysis has been done for the northeast monsoon over the affected regions of south peninsular India. Temporal correlation of all India southwest monsoon SPI and south peninsular India northeast monsoon SPI has been done with the global SST to identify the teleconnection of drought in India with global parameters.     

The WRF model performance for the simulation of heavy precipitating events over Ahmedabad during August 2006

The summer monsoon season of the year 2006 was highlighted by an unprecedented number of monsoon lows over the central and the western parts of India, particularly giving widespread rainfall over Gujarat and Rajasthan. Ahmedabad had received 540.2mm of rainfall in the month of August 2006 against the climatological mean of 219.8mm. The two spells of very heavy rainfall of 108.4mm and 97.7mm were recorded on 8 and 12 August 2006 respectively. Due to meteorological complexities involved in replicating the rainfall occurrences over a region, the Weather Research and Forecast (WRF-ARW version) modeling system with two different cumulus schemes in a nested configuration is chosen for simulating these events. The spatial distributions of large-scale circulation and moisture fields have been simulated reasonably well in this model, though there are some spatial biases in the simulated rainfall pattern. The rainfall amount over Ahmedabad has been underestimated by both the cumulus parameterization schemes. The quantitative validation of the simulated rainfall is done by calculating the categorical skill scores like frequency bias, threat scores (TS) and equitable threat scores (ETS). In this case the KF scheme has outperformed the GD scheme for the low precipitation threshold.     

The relationship between the isotopic content of precipitation and the precipitation amount in tropical regions

General circulation models (GCMs) fitted with stable isotope schemes are widely used to interpret the isotope–climate relationship. However, previous studies have found that the spatiotemporal isotope/precipitation correlation simulated by GCMs is stronger and more widespread than the observed value. To understand the reason for this failure, we investigated the factors influencing the empirically well-known isotope/precipitation relationship, or precipitation amount effect, in the tropics using newly obtained daily precipitation isotope monitoring data over Asia. As in previous studies, we found an apparent correlation between the long-term monthly mean isotopic content and the corresponding precipitation amount (local precipitation) observed at sub-tropical island stations. Furthermore, on a monthly timescale, the isotopic variability of precipitation for these stations was more clearly related to the regional precipitation amount than to local precipitation. This correlation of isotopic content with the regional precipitation amount was observed at the equatorial (Maritime Continent) stations. For these stations, isotope/local precipitation relationships only appeared over longer timescales, with different regression line slopes at each station. However, at the coastal stations, there was a strong linear relationship between the monthly mean isotopic content and corresponding regional precipitation, and regression line slopes were spatially uniform. For the two sub-tropical terrestrial (Indochina Peninsula) stations, the isotopic minimum appeared without any relationship to rainfall amount but usually occurred at the leeward station during the rainy season. These results suggest that the isotopic variations of precipitation did not depend on the ’local’ rain-out history but on the rain-out process in the surrounding region. However, local rainfall events were associated not only with large-scale disturbances but also with regional circulation. Thus, the scale difference of controlling factors between local rainfall amount and isotopic value results in the weakening of the rainfall amount effect at the observation site and in the discrepancy between GCM simulations and observations. This finding suggests that regional precipitation–isotope relationships should be compared with GCM results. Additionally, because the isotope signal reflects the rain-out history at a regional scale, evaluation of the isotopic field using isotopic GCMs will be useful not only to reconstruct paleoclimate conditions but also to examine how GCMs can reproduce real atmospheric circulation over the tropics.     

Interannual variability of summer monsoon rainfall over Myanmar

Observed summer (May–October) rainfall in Myanmar for the period 1981–2010 was used to investigate the interannual variability of summer monsoon rainfall over Myanmar. Empirical orthogonal function, the sequential Mann-Kendall test, power spectrum analysis, and singular value decomposition (SVD) were deployed in the study. Results from spectral analysis showed that the variability of rainfall over Myanmar exhibits a 2- to 6-year cycle. An abrupt change in rainfall over the country was noted in 1992. There was a notable increasing rainfall trend from 1989. After the sudden change, the mean rainfall increased by 36.1 mm, compared with the mean rainfall before the sudden change, and was associated with a rise in temperature of about 0.2 °C. An increase in heavy rainfall days was observed from the early 1990s to 2010. IOD and ENSO play an important role in the interannual variability of the summer rainfall over Myanmar. The covariability between rainfall over Myanmar and Indian Ocean SST generally suggests that a positive IOD mode is associated with suppressed rainfall in the central and northern parts of Myanmar. During a negative IOD mode, nearly the whole Myanmar experiences enhanced rainfall, which is associated with devastating socioeconomic impacts. The covariability between the rainfall over Myanmar and the sea surface temperature in the Pacific Ocean in the first and second SVD modes was dominated by warming in the east and central Pacific—an El Niño-like pattern—resulting in dry conditions in central Myanmar.     

Inter-annual variability of summer monsoon rainfall over Orissa (India) in relation to cyclonic disturbances

The summer monsoon rainfall over Orissa, a state on the eastern coast of India, is more significantly related than Indian summer monsoon rainfall (ISMR) to the cyclonic disturbances developing over the Bay of Bengal. Orissa experiences floods and droughts very often due to variation in the characteristics of these disturbances. Hence, an attempt was made to find out the inter-annual variability in the rainfall over Orissa and the frequencies of different categories of cyclonic disturbances affecting Orissa during monsoon season (June–September). For this purpose, different statistical characteristics, such as mean, coefficient of variation, trends and periodicities in the rainfall and the frequencies of different categories of cyclonic disturbances affecting Orissa, were analysed from 100 years (1901–2000) of data. The basic objective of the study was to find out the contribution of inter-annual variability in the frequency of cyclonic disturbances to the inter-annual variability of monsoon rainfall over Orissa. The relationship between summer monsoon rainfall over Orissa and the frequency of cyclonic disturbances affecting Orissa shows temporal variation. The correlation between them has significantly decreased since the 1950s. The variation in their relationship is mainly due to the variation in the frequency of cyclonic disturbances affecting Orissa. The variability of both rainfall and total cyclonic disturbances has been above normal since the 1960s, leading to more floods and droughts over Orissa during recent years. The inter-annual variability of seasonal rainfall over Orissa and the frequency of cyclonic disturbances affecting Orissa during monsoon season show a quasi-biennial oscillation period of 2–2.8 years. There is least impact of El Nino southern oscillation (ENSO) on inter-annual variability of both the seasonal rainfall over Orissa and the frequencies of monsoon depressions/total cyclonic disturbances affecting Orissa.     

Probabilistic multi-model ensemble prediction of Indian summer monsoon rainfall using general circulation models: A non-parametric approach

Probabilistic prediction has the ability to convey the intrinsic uncertainty of forecast that helps the decision makers to manage the climate risk more efficiently than deterministic forecasts. In recent times, probabilistic predictions obtained from the products from General Circulation Models (GCMs) have gained considerable attention. The probabilistic forecast can be generated in parametric (assuming Gaussian distribution) as well as non-parametric (counting method) ways. The present study deals with the non-parametric approach that requires no assumption about the form of the forecast distribution for the prediction of Indian summer monsoon rainfall (ISMR) based on the hindcast run of seven general circulation models from 1982 to 2008. Probabilistic prediction from each of the GCM products has been generated by non-parametric methods for tercile categories (viz. below normal (BN), near-normal (NN), and above normal (AN)) and evaluation of their skill is assessed against observed data. Five different types of PMME schemes have been used for combining probabilities from each GCM to improve the forecast skill as compared to the individual GCMs. These schemes are different in nature of assigning the weights for combining probabilities. After a rigorous analysis through Rank Probability Skill Score (RPSS) and relative operating characteristic (ROC) curve, the superiority of PMME has been established over climatological probability. It is also found that, the performances of PMME1 and PMME3 are better than all the other methods whereas PMME3 has showed more improvement over PMME1.     

Climate change impact projections at the catchment scale in Tunisia using the multi-model ensemble mean approach

In this work, we developed a mean projection for climate change and assessed its impact on some hydro-meteorological indicators relevant to climatic condition, precipitation extremes magnitude and frequency for the Siliana catchment in Tunisia based on an ensemble of seven combinations of global circulation models (GCMs) and regional climate models (RCMs) derived from the EU-FP6 ENSEMBLES project. We performed quantile-based mapping (QM) bias correction technique of climate model projection using local observations. Because there is no warranty that the best climate model based on its performances in reproducing historic climate will be superior to other models in simulating future climate, we used the multi-model ensemble (MME) mean approach to derive a mean projection as the best guess for climate change projection for the Siliana catchment. We also quantified the uncertainty of the MME in the projected change in the selected indicators by comparing their values in the reference period (1981–2010) to these in the future period (2041–2070). Results reveal that the Siliana catchment will be prone to drier and warmer climate in the future with less rainy days for each month. The uncertainty associated with the MME projection suggests that no clear general tendency for extreme rainy days in the future is expected. These findings highlight the need to consider an ensemble of multi-climate models with an uncertainty framework if reliable climate change impact study is sought at the catchment scale.     

Spatio-temporal variability of summer monsoon rainfall over Orissa in relation to low pressure systems

The summer monsoon rainfall over Orissa occurs mostly due to low pressure systems (LPS) developing over the Bay of Bengal and moving along the monsoon trough. A study is hence undertaken to find out characteristic features of the relationship between LPS over different regions and rain-fall over Orissa during the summer monsoon season (June-September). For this purpose, rainfall and rainy days over 31 selected stations in Orissa and LPS days over Orissa and adjoining land and sea regions during different monsoon months and the season as a whole over a period of 20 years (1980-1999) are analysed. The principal objective of this study is to find out the role of LPS on spatial and temporal variability of summer monsoon rainfall over Orissa. The rainfall has been significantly less than normal over most parts of Orissa except the eastern side of Eastern Ghats during July and hence during the season as a whole due to a significantly less number of LPS days over northwest Bay in July over the period of 1980-1999. The seasonal rainfall shows higher interannual variation (increase in coefficient of variation by about 5%) during 1980-1999 than that during 1901-1990 over most parts of Orissa except northeast Orissa. Most parts of Orissa, especially the region extending from central part of coastal Orissa to western Orissa (central zone) and western side of the Eastern Ghats get more seasonal monsoon rainfall with the development and persistence of LPS over northwest Bay and their subsequent movement and persistence over Orissa. The north Orissa adjoining central zone also gets more seasonal rainfall with development and persistence of LPS over northwest Bay. While the seasonal rainfall over the western side of the Eastern Ghats is adversely affected due to increase in LPS days over west central Bay, Jharkhand and Bangladesh, that over the eastern side of the Eastern Ghats is adversely affected due to increase in LPS days over all the regions to the north of Orissa. There are significant decreasing trends in rainfall and number of rainy days over some parts of southwest Orissa during June and decreasing trends in rainy days over some parts of north interior Orissa and central part of coastal Orissa during July over the period of 1980-1999     

On breaks of the Indian monsoon

For over a century, the term break has been used for spells in which the rainfall over the Indian monsoon zone is interrupted. The phenomenon of ’break monsoon’ is of great interest because long intense breaks are often associated with poor monsoon seasons. Such breaks have distinct circulation characteristics (heat trough type circulation) and have a large impact on rainfed agriculture. Although interruption of the monsoon rainfall is considered to be the most important feature of the break monsoon, traditionally breaks have been identified on the basis of the surface pressure and wind patterns over the Indian region. We have defined breaks (and active spells) on the basis of rainfall over the monsoon zone. The rainfall criteria are chosen so as to ensure a large overlap with the traditional breaks documented by Ramamurthy (1969) and Deet al (1998). We have identified these rainbreaks for 1901-89. We have also identified active spells on the basis of rainfall over the Indian monsoon zone. We have shown that the all-India summer monsoon rainfall is significantly negatively correlated with the number of rainbreak days (correlation coefficient -0.56) and significantly positively correlated with the number of active days (correlation coefficient 0.47). Thus the interannual variation of the all-India summer monsoon rainfall is shown to be related to the number of days of rainbreaks and active spells identified here. There have been several studies of breaks (and also active spells in several cases) identified on the basis of different criteria over regions differing in spatial scales (e.g., Websteret al 1998; Krishnanet al it 2000; Goswami and Mohan 2000; and Annamalai and Slingo 2001). We find that there is considerable overlap between the rainbreaks we have identified and breaks based on the traditional definition. There is some overlap with the breaks identified by Krishnanet al (2000) but little overlap with breaks identified by Websteret al (1998). Further, there are three or four active-break cycles in a season according to Websteret al (1998) which implies a time scale of about 40 days for which Goswami and Mohan (2000), and Annamalai and Slingo (2001) have studied breaks and active minus break fluctuations. On the other hand, neither the traditional breaks (Ramamurthy 1969; and Deet al 1998) nor the rainbreaks occur every year. This suggests that the `breaks’ in these studies are weak spells of the intraseasonal variation of the monsoon, which occur every year. We have derived the OLR and circulation patterns associated with rainbreaks and active spells and compared them with the patterns associated with breaks/active minus break spells from these studies. Inspite of differences in the patterns over the Indian region, there is one feature which is seen in the OLR anomaly patterns of breaks identified on the basis of different criteria as well as the rainbreaks identified in this paper viz., a quadrapole over the Asia-west Pacific region arising from anomalies opposite (same) in sign to those over the Indian region occurring over the equatorial Indian Ocean and northern tropical (equatorial) parts of the west Pacific. Thus it appears that this quadrapole is a basic feature of weak spells of the intraseasonal variation over the Asia-west Pacific region. Since the rainbreaks are intense weak spells, this basic feature is also seen in the composite patterns of these breaks. We find that rainbreaks (active spells) are also associated with negative     

Quantitative precipitation forecasting over Narmada Catchment

Quantitative precipitation forecasting (QPF) has been attempted over the Narmada Catchment following a statistical approach. The catchment has been divided into five sub-regions for the development of QPF models with a maximum lead-time of 24 hours. For this purpose the data of daily rainfall from 56 raingauge stations, twice daily observations on different surface meteorological parameters from 28 meteorological observatories and upper air data from 11 aerological stations for the nine monsoon seasons of 1972–1980 have been utilized. The horizontal divergence, relative vorticity, vertical velocity and moisture divergence are computed using the kinematic method at different pressure levels and used as independent variables along with the rainfall and surface meteorological parameters. Multiple linear regression equations have been developed using the stepwise procedure separately with actual and square root and log-transformed rainfall using 8-year data (1972–1979). When these equations were verified with an independent data for the monsoon season of 1980, it was found that the transformed rainfall equations fared much better compared to the actual rainfall equations. The performance of the forecasts of QPF model compared to the climatological and persistence forecasts has been assessed by computing the verification scores using the forecasts for the monsoon season of 1980.     

Impact of monsoon rainfall on the total foodgrain yield over India

The study focuses on understanding the variations of precipitation during summer monsoon season and its impact on Kharif and Rabi foodgrain yield over India. Total foodgrain yield over India during Kharif (summer) season is directly affected by variations in the summer monsoon precipitation (June–September). An increase (decrease) in rainfall is generally associated with an increase (decrease) in foodgrain yield. A similar correspondence during the Rabi (winter) foodgrain yield is not evident. The Rabi crop is not directly affected by variations in the post-monsoon precipitation (October–December) alone, also the summer season precipitation influences the Rabi crop through water and soil moisture availability over many parts of India. Though the reduction of rainfall activity during the entire summer monsoon season leads to reduction in crop yields, the occurrence of prolonged rainfall breaks also causes adverse effect on the crop growth resulting in reduced crop yields.     

Spatial variability of aridity oyer northern India

Spatial variability of aridity over northern India (north of 20°N) is studied by examining variations in the arid area. Area with an objectively determined summer monsoon rainfall (June to September total) of less than 500 mm is identified as arid area. The summer monsoon rainfall of 212 rain-gauges from 212 districts of the region for the period 1871–1984 are used in the analysis. An interesting feature of the arid area series is that it shows decreasing trend from beginning of the present century. The summer monsoon rainfall fluctuations over five subjectively divided zones over northern India are examined to understand the association between rainfall and the arid area variations. The rainfall series for northwest India shows a significant increasing trend and that for northeast India a significant decreasing trend from the beginning of this century. Rainfall fluctuations over the remaining zones can be considered intermediate stages of a systematic spatial change in the rainfall pattern. This suggested that the recent decreasing trend in the arid area is due to a westward shift in the monsoon rainfall activities. From correlation analyses it is inferred that perhaps the recent decreasing trend in the arid area and increasing trend in the monsoon rainfall over northwest India are associated with a warming trend of the northern hemisphere.     

District-wide drought climatology of the southwest monsoon season over India based on standardized precipitation index (SPI)

District-wide drought climatology over India for the southwest monsoon season (June–September) has been examined using two simple drought indices; Percent of Normal Precipitation (PNP) and Standardized Precipitation Index (SPI). The season drought indices were computed using long times series (1901–2003) of southwest monsoon season rainfall data of 458 districts over the country. Identification of all India (nation-wide) drought incidences using both PNP and SPI yielded nearly similar results. However, the district-wide climatology based on PNP was biased by the aridity of the region. Whereas district-wide drought climatology based on SPI was not biased by aridity. This study shows that SPI is a better drought index than PNP for the district-wide drought monitoring over the country. SPI is also suitable for examining break and active events in the southwest monsoon rainfall over the country. The trend analysis of district-wide season (June–September) SPI series showed significant negative trends over several districts from Chattisgarh, Bihar, Kerala, Jharkhand, Assam and Meghalaya, Uttaranchal, east Madhya Pradesh, Vidarbha etc., Whereas significant positive trends in the SPI series were observed over several districts from west Uttar Pradesh, west Madhya Pradesh, South & north Interior Karnataka, Konkan and Goa, Madhya Maharashtra, Tamil Nadu, East Uttar Pradesh, Punjab, Gujarat etc.     

Validating quantitative precipitation forecast for the Flood Meteorological Office,Patna region during 2011–2014

In order to issue an accurate warning for flood, a better or appropriate quantitative forecasting of precipitation is required. In view of this, the present study intends to validate the quantitative precipitation forecast (QPF) issued during southwest monsoon season for six river catchments (basin) under the flood meteorological office, Patna region. The forecast is analysed statistically by computing various skill scores of six different precipitation ranges during the years 2011–2014. The analysis of QPF validation indicates that the multi-model ensemble (MME) based forecasting is more reliable in the precipitation ranges of 1–10 and 11–25 mm. However, the reliability decreases for higher ranges of rainfall and also for the lowest range, i.e., below 1 mm. In order to testify synoptic analogue method based MME forecasting for QPF during an extreme weather event, a case study of tropical cyclone Phailin is performed. It is realized that in case of extreme events like cyclonic storms, the MME forecasting is qualitatively useful for issue of warning for the occurrence of floods, though it may not be reliable for the QPF. However, QPF may be improved using satellite and radar products.     

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.     

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.