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

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

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

The Indian monsoon: 5. Prediction of the monsoon

In this article we first consider the importance of prediction of the monsoon, and events such as the intense rainfall event over Mumbai in July 2005. We then discuss how meteorologists make short-, medium-, and long-range forecasts and the concept of the limit of predictability in a chaotic system such as the atmosphere. Problems and prospects of prediction on different time-scales are discussed by using one example of short-range forecasts and the prediction of the monsoon by dynamical and statistical methods. Finally we consider measures of the skill of a forecast and how high the skill has to be for it to be useful for applications

Sensitivity of surface radiation budget to clouds over the Asian monsoon region

Using the ISCCP-FD surface radiative flux data for the summer season (June to September) of the period 1992 to 1995, an analysis was done to understand the role of clouds on the surface radiation budget over the Asian monsoon region. At the top of atmosphere (TOA) of convective regions of the Asian monsoon region, the short wave radiative forcing (SWCRF) and long wave radiative forcing (LWCRF) do not cancel each other resulting in occurrence of the net cloud radiative forcing values exceeding −30 W/m2. This type of imbalance between SWCRF and LWCRF at TOA is reflected down on the earth surface-atmosphere system also as an imbalance between surface netcloud radiative forcing (NETCRF) and atmospheric NETCRF. Based on the regression analysis of the cloud effects on the surface radiation budget quantities, it has been observed that generally, the variance explained by multiple type cloud data is 50% more than that of total cloud cover alone. In case of SWCRF, the total cloud cover can explain about 3% (7%) of the variance whereas the three cloud type descriptions of clouds can explain about 44% (42%) of the variance over oceanic (land) regions. This highlights the importance of cloud type information in explaining the variations of surface radiation budget. It has been observed that the clouds produce more cooling effect in short-wave band than the warming effect in long-wave band resulting in a net cooling at the surface. Over the oceanic region, variations in high cloud amount contribute more to variations in SWCRF while over land regions both middle and high cloud variations make substantial contributions to the variations in both SWCRF and NETCRF

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

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

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