Prediction of Indian summer monsoon: Status, problems and prospects

In this article, we review the present status and problems and future prospects of long-range forecasts of Indian summer monsoon. Since 1988, the India Meteorological Department has been issuing forecasts based on 16-parameter power regression and parametric models. All these forecasts are proved to be reasonably correct. However, in some years, forecast error was larger than the model error of ± 4. In 2000, four new promising predictors were introduced in the operational models. Using an empirical model with 100 years of data (1901-2000), we show that Indian summer monsoon predictability exhibits epochal variations. During the recent years the model is showing poor forecast skill due to weakened coupling between the boundary forcing and Indian monsoon. In spite of serious efforts by the modelling groups, there are still problems in the dynamical predictions of Indian monsoon. Prediction of Indian monsoon variability is found to be sensitive to the initial conditions, suggesting that chaotic internal dynamics may ultimately limit the predictability of Indian summer monsoon

Inter-annual relationship between Atlantic sea surface temperature anomalies and Indian summer monsoon

In this study, the simultaneous inter-annual relationships between SST anomalies over the Northwest Atlantic Ocean and southwest monsoon rainfall over the monsoon core region have been examined using monthly SST and atmospheric data for the period 1951-2005. Statistical analyses reveal significant inter-annual simultaneous relationship between the SST anomalies over North Atlantic and rainfall over the monsoon core region, but with significant epochal variations. The relationship has become stronger after mid-1970s when the El Nino-Indian monsoon relationship has weakened. Positive SST anomalies over the North Atlantic Ocean shift the North Atlantic Jet northwards and the associated circulation changes in the upper troposphere influence Indian monsoon through the circumglobal teleconnection across central Asia. The present study, thus highlights the important role of North Atlantic Ocean as an important source of inter-annual variability of the Indian summer monsoon

A high resolution daily gridded rainfall dataset (1971-2005) for mesoscale meteorological studies

In this communication, we discuss the development of a very high resolution (0.5° 0.5°) daily rainfall dataset for mesoscale meteorological studies over the Indian region. The dataset was developed using quality-controlled rainfall data from more than 3000 rain gauge stations over India. The analysis consists of daily rainfall data for all the seasons for the period 1971-2005. A well-tested interpolation method (Shepard's method) was used to interpolate the station data into regular grids of 0.5° 0.5° lat. long. After proper validation, it has been found that the present dataset is better compared to other available datasets. A few case studies have been shown to demonstrate the utility of the dataset for different mesoscale meteorological analyses. However, since the data density is not kept uniform, there is a possibility of temporal inhomogeneity and therefore, the present dataset cannot be used for trend analysis. The dataset is freely available from the India Meteorological Department, Pune

On the variability and increasing trends of heat waves over India

Over India, heat waves occur during the summer months of April to June. A gridded daily temperature data set for the period, 1961–2013 has been analyzed to examine the variability and trends in heat waves over India. For identifying heat waves, the Excess Heat Factor (EHF) and 90th percentile of maximum temperatures were used. Over central and northwestern parts of the country, frequency, total duration and maximum duration of heat waves are increasing. Anomalous persistent high with anti-cyclonic flow, supplemented with clear skies and depleted soil moisture are primarily responsible for the occurrence of heat waves over India. Variability of heat waves over India is influenced by both the tropical Indian Ocean and central Pacific SST anomalies. The warming of the tropical Indian Ocean and more frequent El Nino events in future may further lead to more frequent and longer lasting heat waves over India

Development of a high resolution daily gridded temperature data set (1969-2005) for the Indian region

A high resolution daily gridded temperature data set for the Indian region was developed using temperature data of 395 quality controlled stations for the period 1969–2005. A modified version of the Shepard's angular distance weighting algorithm was used for interpolating the station temperature data into 1° latitude × 1° longitude grids. Using the cross validation, errors were estimated and found less than 0.5 °C. The data set was also compared with another high resolution data set and found comparable. Mean frequency of cold and heat waves, temperature anomalies associated with the monsoon breaks have been presented

Monsoon prediction - Why yet another failure?

The country experienced a deficit of 13 in the summer monsoon of 2004. As in 2002, this deficit was not predicted either by the operational empirical models at India Meteorological Department (IMD) or by the dynamical models at national and international centres. Our analysis of the predictions generated by the operational models at IMD from 1932 onwards suggests that the forecast skill has not improved over the seven decades despite continued changes in the operational models. Clearly, new approaches need to be explored with empirical models. The simulation of year-to-year variation of the monsoon is still a challenging problem for models of the atmosphere as well as the coupled ocean-atmosphere system. We expect dynamical models to generate better prediction only after this problem is successfully addressed

Characteristic features of winter precipitation and its variability over northwest India

Northwestern parts of India receive considerable amount of precipitation during the winter months of December-March. Although, it is only about 15 of the annual precipitation, the precipitation is very important for rabi crops and to maintain the glaciers extend in the Himalaya, which melt and supply water to the rivers during other seasons. The precipitation is mainly associated with the sequence of synoptic systems known as 'western disturbances'. The precipitation has considerable spatial and temporal variability, with maximum precipitation occurring particularly over northern hilly regions, with decreasing influence southwards. The spatially coherent winter precipitation series has been prepared for the largest possible area comprising nine meteorological subdivisions of northwest India, which constitute about 32 of the total area of the country, having similar precipitation characteristics. The precipitation series has been statistically analysed to understand its characteristics and variability. The seasonal precipitation series is found to be homogeneous, Gaussian (normal) distributed and free from persistence. The precipitation variability has increased during the most recent three decades with more excess and deficient years

Monsoon variability: Links to major oscillations over the equatorial Pacific and Indian oceans

In this article, we first discuss our perception of the factors which are critical for inter-annual variation of the Indian summer monsoon rainfall and the major milestones leading to this understanding. The nature of the two critical modes for monsoon variability, viz. El Nino Southern Oscillation and equatorial Indian Ocean Oscillation is considered and their links to the monsoon elucidated. We suggest possible reasons for the rather poor skill of simulation of the interannual variation of the Indian summer monsoon rainfall by atmospheric general circulation models, run with the observed sea surface temperature as boundary condition. We discuss implications of what we have learned for the monsoon of 2006, and possible use of information on the two important modes for prediction of the rainfall in all or part of the summer monsoon season. We conclude with our view of what the focus of research and development should be for achieving a substantial improvement in the skill of simulation and prediction of the Indian summer monsoon rainfall in the near future

Seasonal forecasts of Indian summer monsoon rainfall using local polynomial based non-parametric regression model

In this paper, details of new statistical models for forecasting southwest monsoon (June-September) rainfall over India (ISMR) and for northwest India summer monsoon rainfall (NWISMR) are discussed. These models are based on the local polynomial based non-parametric regression method. Two predictor sets (SET-I & SET-II consisting of 4 and 5 predictors respectively) were selected for developing two separate models for making predictions in April and late June respectively. Another predictor set (SET-III) was selected for developing model for monsoon rainfall over NW India (NWISMR). Principle Component Analysis (PCA) of predictor data set was done and the first two principal components were selected for model development. Data for the period 1977-2005 have been used for developing the model and the Jackknife method was used to assess the skill of the model. Both the models showed useful skill in predicting ISMR and showed better performance than the model based on pure climatology. The Hit scores for the three category forecasts during the verification period by April and June models are 0.65 and 0.66 respectively. Root Mean Square Error (RMSE) of these models during the verification period is 5.99 and 6.0 respectively from the Long Period Average (LPA) as against 10.0 from the LPA of the model based on climatology alone. RMSE of the Northwest India model during the independent period is 11.5 from LPA as against 18.5 from the LPA of the model based on the climatology alone. Hit score for the three category forecast for NW India during the verification period is 0.55

Prediction of Indian rainfall during the summer monsoon season on the basis of links with equatorial Pacific and Indian Ocean climate indices

Interannual variation of Indian summer monsoon rainfall (ISMR) is linked to El Niño-Southern oscillation (ENSO) as well as the Equatorial Indian Ocean oscillation (EQUINOO) with the link with the seasonal value of the ENSO index being stronger than that with the EQUINOO index. We show that the variation of a composite index determined through bivariate analysis, explains 54% of ISMR variance, suggesting a strong dependence of the skill of monsoon prediction on the skill of prediction of ENSO and EQUINOO. We explored the possibility of prediction of the Indian rainfall during the summer monsoon season on the basis of prior values of the indices. We find that such predictions are possible for July–September rainfall on the basis of June indices and for August–September rainfall based on the July indices. This will be a useful input for second and later stage forecasts made after the commencement of the monsoon seaso