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.     

New Models for Long Range Forecasts of Summer Monsoon Rainfall over North West and Peninsular India

Summary New models based on (a) Multivariate Principal Component Regression (PCR) (b) Neural Network (NN) and (c) Linear Discriminant Analysis (LDA) techniques were developed for long-range forecasts of summer monsoon (June–September) rainfall over two homogeneous regions of India, viz., North West India and Peninsular India. The PCR and NN models were developed with two different data sets. One set consisted 42 years (1958–1999) of data with 8 predictors and the other, 49 years (1951–1999) of data with 6 predictors. The predictors were subjected to the Principal Component Analysis (PCA) before model development. Two different neural networks were designed with 2 and 3 hidden neurons. To avoid the nonlinear instability, 20 ensemble runs were made while training the network and the ensemble mean results are discussed. The LDA model was developed with 42 years of data (1958–1999) for classifying three rainfall intervals with equal prior probability of 0.33. Both the PCR and NN models showed useful forecast skill for NW India and Peninsular India. Models with 8 predictors performed better than the models with only 6 predictors. The NN model with 3 hidden neurons performed better than model with 2 hidden neurons. For NW India, the NN model performed better than the PCR model. The RMSE of the NN model and PCR model with 8 predictors for NW India (Peninsular India) during the independent period 1984–99 was 12.5% (12.2%) and 12.6% (11.5%), respectively. Corresponding figures for the models with 6 predictors are 15.0% (13.0%) and 13.9% (11.4%) respectively. During the independent period, model errors were large in 1991, 1994, 1997 and 1999. However all the models showed deteriorating predictive skill after 1988, both for NW India and Peninsular India. The LDA model correctly classified 62% of grouped cases for NW India and Peninsular India. The LDA model showed better skill in classifying deficient rainfall (< − 8%) over NW India and excess rainfall (> 3%) over Peninsular India. Received October 2, 1999 Revised December 28, 1999     

Active, weak and break spells in the Indian summer monsoon

Summary Active weak and break phases of the Indian summer monsoon for the period 1958–2002 are studied using ERA-40 data. The criteria for identifying the break are proposed and tested using the 850 hPa level horizontal wind shear. Independent datasets such as All-India Rainfall, NOAA Outgoing Long-wave Radiation and CMAP rainfall datasets are used for the verification of the proposed criteria. On leave from the National Center for Medium Range Weather Forecasting, A-50 Institutional Area, Phase-II, Sector 62, Noida, U.P., India.     

Simulation of Indian summer monsoon circulation and rainfall using RegCM3

Summary The Regional Climate Model RegCM3 has been used to examine its suitability in simulating the Indian summer monsoon circulation features and associated rainfall. The model is integrated at 55 km horizontal resolution over a South Asia domain for the period April–September of the years 1993 to 1996. The characteristics of wind at 850 hPa and 200 hPa, temperature at 500 hPa, surface pressure and rainfall simulated by the model over the Indian region are examined for two convective schemes (a Kuo-type and a mass flux scheme). The monsoon circulation features simulated by RegCM3 are compared with those of the NCEP/NCAR reanalysis and the simulated rainfall is validated against observations from the Global Precipitation Climatology Centre (GPCC) and the India Meteorological Department (IMD). Validation of the wind and temperature fields shows that the use of the Grell convection scheme yields results close to the NCEP/NCAR reanalysis. Similarly, the Indian Summer Monsoon Rainfall (ISMR) simulated by the model with the Grell convection scheme is close to the corresponding observed values. In order to test the model response to land surface changes such as the Tibetan snow depth, a sensitivity study has also been conducted. For such sensitivity experiment, NIMBUS-7 SMMR snow depth data in spring are used as initial conditions in the RegCM3. Preliminary results indicate that RegCM3 is very much sensitive to Tibetan snow. The model simulated Indian summer monsoon circulation becomes weaker and the associated rainfall is reduced by about 30% with the introduction of 10 cm of snow over the Tibetan region in the month of April.     

Fluctuations of Tropical Easterly Jet during contrasting monsoons over India: A GCM study

Summary  The fluctuations of intensity of the Tropical Easterly Jet (TEJ) and its association with the Indian summer monsoon rainfall have been examined using the diagnostics from NCEP/NCAR (National Centre for Environmental Prediction/National Centre for Atmospheric Research) reanalyses project for the period 1986 to 1994. The intensity of TEJ is found to be well correlated with India summer monsoon rainfall. The TEJ is weaker/stronger during the El Ni?o/La Ni?a year of 1987/1988 and is associated with deficient (excess) summer monsoon rainfall over India. A numerical study was carried out for the same period using the Centre for Ocean-Land-Atmosphere studies General Circulation Model (COLA GCM, T30L18) with observed Sea-Surface Temperature (SST). The GCM simulates the TEJ with reasonable accuracy. The strong interannual variability of TEJ during the El Ni?o/La Ni?a years of 1987/1988 are well simulated in the GCM. Like observations, the intensity of the TEJ is positively correlated with the summer monsoon rainfall over India in the model simulation. The intensity of Tibetan anticyclone and diabatic heating over the Tibetan Plateau diminished during the El Ni?o-year of 1987. The divergence centre in the upper troposphere associated with Asian monsoon becomes weaker and shifts eastward during the weak monsoon season of 1987. However, the opposite happens for the strong monsoon season of 1988. Also the middle and upper tropospheric meridional temperature gradient between the Tibetan High and Indian Ocean region decreased (increased) during the weak(strong) monsoon season of 1987 (1988). Received May 27, 1999/Revised March 20, 2000     

Intense rainfall events over the west coast of India

Summary The west coast of the Indian peninsula receives very heavy rainfall during the summer Monsoon (June–September) season with average rainfall over some parts exceeding 250 cm. Heavy rainfall events with rainfall more than 15 cm day⁻¹ at one or more stations along the west coast of India occur frequently and cause considerable damage. A special observational programme, Arabian Sea Monsoon Experiment, was carried out during the monsoon season of 2002 to study these events. The spatial and temporal distributions of intense rainfall events, presented here, were used for the planning of this observational campaign. The present study using daily rainfall data for summer monsoon season of 37 years (1951–1987) shows that the probability of getting intense rainfall is the maximum between 14° N–16° N and near 19° N. The probability of occurrence of these intense rainfall events is high from mid June to mid August, with a dip in early July. It has been believed for a long time that offshore troughs and vortices are responsible for these intense rainfall events. However, analysis of the characteristics of cloud systems associated with the intense rainfall events during 1985–1988 using very high resolution brightness temperature data from INSAT-IB satellite shows that the cloud systems during these events are characterized by large spatial scales and high cloud tops. Further study using daily satellite derived outgoing longwave radiation (OLR) data over a longer period (1975–1998) shows that, most of these events (about 62%) are associated with systems organized on synoptic and larger scales. We find that most of the offshore convective systems responsible for intense rainfall along the west coast of India are linked to the atmospheric conditions over equatorial Indian Ocean.     

Prediction of summer monsoon rainfall over India using the NCEP climate forecast system

The performance of a dynamical seasonal forecast system is evaluated for the prediction of summer monsoon rainfall over the Indian region during June to September (JJAS). The evaluation is based on the National Centre for Environmental Prediction’s (NCEP) climate forecast system (CFS) initialized during March, April and May and integrated for a period of 9 months with a 15 ensemble members for 25 years period from 1981 to 2005. The CFS’s hindcast climatology during JJAS of March (lag-3), April (lag-2) and May (lag-1) initial conditions show mostly an identical pattern of rainfall similar to that of verification climatology with the rainfall maxima (one over the west-coast of India and the other over the head Bay of Bengal region) well simulated. The pattern correlation between verification and forecast climatology over the global tropics and Indian monsoon region (IMR) bounded by 50°E–110°E and 10°S–35°N shows significant correlation coefficient (CCs). The skill of simulation of broad scale monsoon circulation index (Webster and Yang; WY index) is quite good in the CFS with highly significant CC between the observed and predicted by the CFS from the March, April and May forecasts. High skill in forecasting El Nino event is also noted for the CFS March, April and May initial conditions, whereas, the skill of the simulation of Indian Ocean Dipole is poor and is basically due to the poor skill of prediction of sea surface temperature (SST) anomalies over the eastern equatorial Indian Ocean. Over the IMR the skill of monsoon rainfall forecast during JJAS as measured by the spatial Anomaly CC between forecast rainfall anomaly and the observed rainfall anomaly during 1991, 1994, 1997 and 1998 is high (almost of the order of 0.6), whereas, during the year 1982, 1984, 1985, 1987 and 1989 the ACC is only around 0.3. By using lower and upper tropospheric forecast winds during JJAS over the regions of significant CCs as predictors for the All India Summer Monsoon Rainfall (AISMR; only the land stations of India during JJAS), the predicted mean AISMR with March, April and May initial conditions is found to be well correlated with actual AISMR and is found to provide skillful prediction. Thus, the calibrated CFS forecast could be used as a better tool for the real time prediction of AISMR.     

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     

East Asian summer monsoon simulation by a 20-km mesh AGCM

East Asian summer monsoon climate simulated by a global 20-km mesh atmospheric general circulation model (AGCM) forced by the global sea surface temperature during the period 1979–1998 is investigated. In comparison with a lower resolution (180-km mesh) model experiment, it is revealed that the 20-km mesh AGCM shows the superiority in simulating orographic rainfall not only its location but also its amount. The Baiu frontal structure is also better simulated in the higher resolution model, which leads to stronger Baiu rainfall. The 20-km model also shows more intense extremes in precipitation. Interannual variability of June–August mean precipitation and seasonal march of the monsoon rain band are also investigated. This paper is a contribution to the AMIP-CMIP Diagnostic Sub-project on General Circulation Model Simulation of the East Asian Climate, coordinated by W.-C. Wang.     

A reconstructed dynamic Indian monsoon index extended back to 1880

The authors present a reconstruction of summer (June–July–August) mean dynamic Indian monsoon index (DIMI) back to 1880 based on a large number of historical surface observation data as well as information from the upper air data. The reconstruction shows a satisfying skill in terms of both the value of reduction of error and an evaluation against other independent monsoon indices. The skill of reconstruction increases over time with more predictor data (in particular upper-level data) becoming available. A comparison with the observed all Indian summer monsoon rainfall index (AIRI) shows a high consistence in both inter-decadal and inter-annual variability. The reconstruction shows stronger than normal monsoon during the 1880s, 1915–1925 (around 1920) and 1930–1945 (around 1940) as the AIRI. The El Nino/Southern Oscillation (ENSO)—monsoon relationship is reasonably captured in the reconstruction. Powers concentrating within quasi-biennial band stand out in the reconstruction as well as in the AIRI. A comparison of the reconstruction against an atmospheric general circulation model simulation with specified SST and external forcing agents spanning 1901–1999 indicates a slightly higher reproducibility of monsoon circulation than monsoon rainfall in terms of interannual variability. The relationship between the Asian continent warming and the ENSO–monsoon connection is also discussed by using the new dynamic index.     

Periodicity in intraseasonal variation of summer monsoon rainfall over Orissa, India in relation to synoptic disturbances

Summary The summer monsoon rainfall over Orissa, a state of eastern India, shows characteristic intraseasonal and interannual variability, due to interaction of basic westerly flow with orography and the synoptic scale monsoon disturbances including low-pressure systems and cyclonic circulations extending upto mid-tropospheric level (LPSC). These systems normally develop over the north Bay of Bengal and move west-northwestwards along the monsoon trough. The essence of this study is to find out the main features of the intraseasonal variability of daily monsoon rainfall over Orissa in relation to synoptic systems like LPSC and its implication on the interannual variation of rainfall. For this purpose, the actual and mean daily rainfall data of 31 uniformly distributed stations, six homogeneous regions and Orissa as a whole during monsoon season (June–September) over a period of 20 years (1980–1999) are subjected to auto-correlation and power spectrum analyses. The actual and average daily scores of significant EOFs and actual daily occurrence along with daily probability of occurrence of the LPSC influencing rainfall over Orissa during the same period are also subjected to auto-correlation and power spectrum analyses. The intraseasonal variation of monsoon rainfall over Orissa and different homogeneous regions is dominated by the synoptic mode (3–9 days) of variation due to the similar mode of variation in the occurrence of LPSC influencing the rainfall. The seasonal rainfall and hence the interannual variation depends on the intraseasonal variation of rainfall modulated with the synoptic mode of variation in the occurrence of the LPSC. The occurrence of LPSC over the northwest (NW) Bay/NW and adjoining northeast (NE) Bay and its subsequent movement and persistence over Orissa and east Madhya Pradesh & Chhattisgarh in synoptic mode (3–6 days) alongwith absence of similar mode in the occurrence of the LPSC over NE Bay, Gangetic West Bengal (GWB) in the north and west central (WC) Bay to the south leads to excess rainfall over different homogeneous regions and Orissa as a whole. The reverse is the case in deficient years over Orissa and all homogeneous regions except southwest Orissa. The occurrence of the LPSC over GWB in synoptic mode (about 5 days) alongwith absence of synoptic mode in the occurrence of the LPSC over NW Bay leads to deficient rainfall year over southwest Orissa. Correspondence: U. C. Mohanty, Centre for Atmospheric Sciences, Indian Institute of Technology, Delhi Hauz Khas, New Delhi 110016, India     

Skill, reproducibility and potential predictability of the West African monsoon in coupled GCMs

In the framework of the ENSEMBLES FP6 project, an ensemble prediction system based on five different state-of-the-art European coupled models has been developed. This study evaluates the performance of these models for forecasting the West African monsoon (WAM) at the monthly time scale. From simulations started the 1 May of each year and covering the period 1991–2001, the reproducibility and potential predictability (PP) of key parameters of the WAM—rainfall, zonal and meridional wind at four levels from the surface to 200 hPa, and specific humidity, from July to September—are assessed. The Sahelian rainfall mode of variability is not accurately reproduced contrary to the Guinean rainfall one: the correlation between observations (from CMAP) and the multi-model ensemble mean is 0.17 and 0.55, respectively. For the Sahelian mode, the correlation is consistent with a low PP of about ~6%. The PP of the Guinean mode is higher, ~44% suggesting a stronger forcing of the sea surface temperature on rainfall variability over this region. Parameters relative to the atmospheric dynamics are on average much more skillful and reproducible than rainfall. Among them, the first mode of variability of the zonal wind at 200 hPa that depicts the Tropical Easterly Jet, is correlated at 0.79 with its “observed” counterpart (from the NCEP/DOE2 reanalyses) and has a PP of 39%. Moreover, models reproduce the correlations between all the atmospheric dynamics parameters and the Sahelian rainfall in a satisfactory way. In that context, a statistical adaptation of the atmospheric dynamic forecasts, using a linear regression model with the leading principal components of the atmospheric dynamical parameters studied, leads to moderate receiver operating characteristic area under the curve and correlation skill scores for the Sahelian rainfall. These scores are however much higher than those obtained using the modelled rainfall.     

Assessment of Data Assimilation Approaches for the Simulation of a Monsoon Depression Over the Indian Monsoon Region

A low pressure system that formed on 21 September 2006 over eastern India/Bay of Bengal intensified into a monsoon depression resulting in copious rainfall over north-eastern and central parts of India. Four numerical experiments are performed to examine the performance of assimilation schemes in simulating this monsoon depression using the Fifth Generation Mesoscale Model (MM5). Forecasts from a base simulation (with no data assimilation), a four-dimensional data assimilation (FDDA) system, a simple surface data assimilation (SDA) system coupled with FDDA, and a flux-adjusting SDA system (FASDAS) coupled with FDDA are compared with each other and with observations. The model is initialized with Global Forecast System (GFS) forecast fields starting from 19 September 2006, with assimilation being done for the first 24 hours using conventional observations, sounding and surface data of temperature and moisture from Advanced TIROS Operational Vertical Sounder satellite and surface wind data over the ocean from QuikSCAT. Forecasts are then made from these assimilated states. In general, results indicate that the FASDAS forecast provides more realistic prognostic fields as compared to the other three forecasts. When compared with other forecasts, results indicate that the FASDAS forecast yielded lower root-mean-square (r.m.s.) errors for the pressure field and improved simulations of surface/near-surface temperature, moisture, sensible and latent heat fluxes, and potential vorticity. Heat and moisture budget analyses to assess the simulation of convection revealed that the two forecasts with the surface data assimilation (SDA and FASDAS) are superior to the base and FDDA forecasts. An important conclusion is that, even though monsoon depressions are large synoptic systems, mesoscale features including rainfall are affected by surface processes. Enhanced representation of land-surface processes provides a significant improvement in the model performance even under active monsoon conditions where the synoptic forcings are expected to be dominant.     

Simulation of West African monsoon using the RegCM3. Part I: Model validation and interannual variability

Summary The West African monsoon oscillates each year with remarkable regularity but the interannual variability associated with the monsoon is not fully understood although much progress has been made in recent years. This study examines and evaluates the mean state and the interannual variability of the West African climate as simulated by the International Centre for Theoretical Physics (ICTP) Regional Climate Model version 3 (RegCM3) over the period 1979 through 1990 using the National Center for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis data as lateral boundary conditions. Our analysis shows that the averaged rainfall over the region is well represented by the model and demonstrates considerable skill in reproducing the extreme rainfall regimes. There is however a tendency to overestimate rainfall amounts along the Guinean coast, particularly around mountainous areas, and to underestimate it over the Soudano-Sahel. The increased rainfall along the coast is due to an enhanced low-level convergence of the moist southwesterly winds along the coast leading to a reduction of the moisture content in the atmosphere. The decrease over the Soudano-Sahel could be associated with the weakening of the land–sea temperature gradient and hence the decrease in the low level southerly flows. The spatial and temporal variations in temperature are well captured by the model except for slightly cold bias over the coastal region due to an overestimation of precipitation.     

Evaluation of the NMC Regional Ensemble Prediction System During the Beijing 2008 Olympic Games

Based on the B08RDP (Beijing 2008 Olympic Games Mesoscale Ensemble Prediction Research and Development Project) that was launched by the World Weather Research Programme (WWRP) in 2004, a regional ensemble prediction system (REPS) at a 15-km horizontal resolution was developed at the National Meteorological Center (NMC) of the China Meteorological Administration (CMA). Supplementing to the forecasters’ subjective affirmation on the promising performance of the REPS during the 2008 Beijing Olympic Games (BOG), this paper focuses on the objective verification of the REPS for precipitation forecasts during the BOG period. By use of a set of advanced probabilistic verification scores, the value of the REPS compared to the quasi-operational global ensemble prediction system (GEPS) is assessed for a 36-day period (21 July–24 August 2008). The evaluation here involves different aspects of the REPS and GEPS, including their general forecast skills, specific attributes (reliability and resolution), and related economic values. The results indicate that the REPS generally performs significantly better for the short-range precipitation forecasts than the GEPS, and for light to heavy rainfall events, the REPS provides more skillful forecasts for accumulated 6- and 24-h precipitation. By further identifying the performance of the REPS through the attribute-focused measures, it is found that the advantages of the REPS over the GEPS come from better reliability (smaller biases and better dispersion) and increased resolution. Also, evaluation of a decision-making score reveals that a much larger group of users benefits from using the REPS forecasts than using the single model (the control run) forecasts, especially for the heavy rainfall events.     

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.     

Precipitation climatology over India: validation with observations and reanalysis datasets and spatial trends

Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial–temporal analyses of rainfall have been studied by using 107 (1901–2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.     

The Relationship Between some Large-scale Atmospheric Parameters and Rainfall over Southeast Asia: A Comparison with Features over India

Summary Monthly rainfall data for 135 stations for periods varying from 25 to 125 years are utilised to investigate the rainfall climatology over the southeast Asian monsoon regime. Monthly rainfall patterns for the regions north of equator show that maximum rainfall along the west coasts occurs during the summer monsoon period, while the maximum along the east coasts is observed during the northeast monsoon period. Over the Indonesian region (south of the equator) maximum rainfall is observed west of 125 °E during northern winter and east of 125 °E during northern summer. The spatial relationships of the seasonal rainfall (June to September) with the large scale parameters – the Subtropical Ridge (STR) position over the Indian and the west Pacific regions, the Darwin Pressure Tendency (DPT) and the Northern Hemisphere Surface Temperature (NHST) – reveal that within the Asian monsoon regime, not only are there any regions which are in-phase with Indian monsoon rainfall, but there are also regions which are out-of-phase. The spatial patterns of correlation coefficients with all the parameters are similar, with in-phase relationships occurring over the Indian region, some inland regions of Thailand, central parts of Brunei and the Indonesian region lying between 120° to 140 °E. However, northwest Philippines and some southern parts of Kampuchea and Vietnam show an out-of-phase relationship. Even the first Empirical Orthogonal Function of seasonal rainfall shows similar spatial configuration, suggesting that the spatial correlation patterns depict the most dominant mode of interannual rainfall variability. The influence of STR and DPT (NHST) penetrates (does not penetrate) upto the equatorial regions. Possible dynamic causes leading to the observed correlation structure are also discussed. Received October 10, 1996 Revised February 25, 1997     

Association between extreme monsoons and the dipole mode over the Indian subcontinent

Summary The relationship of summer monsoon over India with the Indian Ocean Dipole Mode has been investigated applying simple statistical techniques. While a long time series of 132 years based on 1871–2002 for both summer monsoon rainfall as well as dipole mode index has been used in this study, the NCEP–NCAR reanalysis data (1948–2002) are used to examine the circulation features associated with the extreme dipole and monsoon phases. These flow patterns bring out the dynamics of the dipole – monsoon relationship. Lead/lag correlations between the dipole mode index and the Indian monsoon rainfall are computed. Results reveal that numerically the relationship is stronger following the monsoon. The lower troposphere flow patterns at 850 hPa associated with the extreme phases of the dipole and monsoon are consistent with the correlation analysis. Further a strong (weak) summer monsoon favours the development of the negative (positive) dipole event in autumn. The sliding correlations between Indian monsoon rainfall and the dipole mode index suggest that the impact of monsoon over dipole is weakening after 1960s. This weakening relationship has been evidenced by the composites of sea-surface temperature anomalies and circulation patterns. All the above analysis suggests that the summer monsoon has more influence on the dipole mode than vice-a-versa.     

On the ability of the regional climate model RIEMS to simulate the present climate over Asia

A continuous 10-year simulation in Asia for the period of 1 July 1988 to 31 December 1998 was conducted using the Regional Integrated Environmental Model System (RIEMS) with NCEP Reanalysis II data as the driving fields. The model processes include surface physics state package (BATS 1e), a Holtslag explicit planetary boundary layer formulation, a Grell cumulus parameterization, and a modified radiation package (CCM3). Model-produced surface temperature and precipitation are compared with observations from 1001 meteorology stations distributed over Asia and with the 0.5 × 0.5 CRU gridded dataset. The analysis results show that: (1) RIEMS reproduces well the spatial pattern and the seasonal cycle of surface temperature and precipitation; (2) When regionally averaged, the seasonal mean temperature biases are within 1–2C. For precipitation, the model tends to give better simulation in winter than in summer, and seasonal precipitation biases are mostly in the range of ?12%–50%; (3) Spatial correlation coefficients between observed and simulated seasonal precipitation are higher in north of the Yangtze River than in the south and higher in winter than in summer; (4) RIEMS can well reproduce the spatial pattern of seasonal mean sea level pressure. In winter, the model-simulated Siberian high is stronger than the observed. In summer, the simulated subtropical high is shifted northwestwards; (5) The temporal evolution of the East Asia summer monsoon rain belt, with steady phases separated by more rapid transitions, is reproduced.