M. Rajeevan

Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data

In this study, using 104 years (1901-2004) of high resolution daily gridded rainfall data, variability and long-term trends of extreme rainfall events over central India have been examined. Frequency of extreme rainfall events shows significant inter-annual and inter-decadal variations in addition to a statistically significant long term trend of 6% per decade. Detailed analysis shows that inter-annual, inter-decadal and long-term trends of extreme rainfall events are modulated by the SST variations over the tropical Indian Ocean. The present study supports the hypothesis that the increasing trend of extreme rainfall events in the last five decades could be associated with the increasing trend of sea surface temperatures and surface latent heat flux over the tropical Indian Ocean. In the global warming scenario, the coherent relationship between Indian Ocean SST and extreme rainfall events suggests an increase in the risk of major floods over central India.

Evaluation of the ENSEMBLES multi-model seasonal forecasts of Indian summer monsoon variability

The performance of the new multi-model seasonal prediction system developed in the frame work of the ENSEMBLES EU project for the seasonal forecasts of India summer monsoon variability is compared with the results from the previous EU project, DEMETER. We have considered the results of six participating ocean-atmosphere coupled models with 9 ensemble members each for the common period of 1960–2005 with May initial conditions. The ENSEMBLES multi-model ensemble (MME) results show systematic biases in the representation of mean monsoon seasonal rainfall over the Indian region, which are similar to that of DEMETER. The ENSEMBLES coupled models are characterized by an excessive oceanic forcing on the atmosphere over the equatorial Indian Ocean. The skill of the seasonal forecasts of Indian summer monsoon rainfall by the ENSEMBLES MME has however improved significantly compared to the DEMETER MME. Its performance in the drought years like 1972, 1974, 1982 and the excess year of 1961 was in particular better than the DEMETER MME. The ENSEMBLES MME could not capture the recent weakening of the ENSO-Indian monsoon relationship resulting in a decrease in the prediction skill compared to the “perfect model” skill during the recent years. The ENSEMBLES MME however correctly captures the north Atlantic-Indian monsoon teleconnections, which are independent of ENSO.

Net Cloud Radiative Forcing at the Top of the Atmosphere in the Asian Monsoon Region

Based on the data from Earth Radiation Budget Experiment (ERBE), many investigators have concluded that the net cloud radiative forcing at the top of the atmosphere is small in the deep convective region of the Tropics. This conclusion has been shown to be invalid for the Asian monsoon region during the period June–September. The ERBE data have been used to show that in the Asian monsoon region the net cloud radiative forcing at the top of the atmosphere is negative and its magnitude exceeds

Gridded daily Indian monsoon rainfall for 14 seasons: Merged TRMM and IMD gauge analyzed values

30 W m^{-2}

On the Variability and Increasing Trends of Heat Waves over India

in 25% of the grids in this region. The large negative net cloud radiative forcing in the Asian monsoon region during June–September has been shown to be on account of the presence of large amount of high clouds and the large optical depth of these clouds. This combination of high cloud amount and high optical depth occurs in the Asian monsoon region only. In the other deep convective regions of the Tropics, high clouds with large optical depths are present, but they do not cover a large area.

Tropical Pacific upper ocean heat content variations and Indian summer monsoon rainfall

Indian monsoon is an important component of earth’s climate system. Daily rainfall data for longer period is vital to study components and processes related to Indian monsoon. Daily observed gridded rainfall data covering both land and adjoining oceanic regions are required for numerical model validation and model development for monsoon. In this study, a new gridded daily Indian rainfall dataset at 1°×1° latitude/longitude resolution covering 14 monsoon seasons (1998–2011) are described. This merged satellite gauge rainfall dataset (NMSG) combines TRMM TMPA rainfall estimates with gauge information from IMD gridded data. Compared to TRMM and GPCP daily rainfall data, the current NMSG daily data has more information due to inclusion of local gauge analysed values. In terms of bias and skill scores this dataset is superior to other daily rainfall datasets. In a mean climatological sense and also for anomalous monsoon seasons, this merged satellite gauge data brings out more detailed features of monsoon rainfall. The difference of NMSG and GPCP looks significant. This dataset will be useful to researchers for monsoon intraseasonal studies and monsoon model development research.

Spatial and temporal relationships between global land surface air temperature anomalies and indian summer monsoon rainfall

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.

Improving global model precipitation forecasts over India using downscaling and the FSU superensemble. Part I: 1-5-day forecasts

Indian southwest monsoon rainfall (ISMR) has strong links with El Nino/Southern Oscillation (ENSO). However, sea surface temperature (SST) anomalies during the pre-monsoon season do not have any predictive value for ensuing monsoon rainfalls. Recent studies have suggested that warm water volume (WWV) in the tropical Pacific Ocean in boreal winter is a good precursor of ENSO warm and cold events (El Nino and La Nina). In this study, we have analyzed inter-annual variations in the WWV in the tropical Pacific Ocean and Indian summer monsoon rainfall (ISMR) using upper ocean thermal field analyses spanning 54 years (1950-2003). Significant negative correlations have been observed between WWV anomalies in the boreal winter and spring seasons and ISMR, with deficient (excess) monsoon years corresponding to positive (negative) WWV anomalies. This relationship provides a much longer lead time than ENSO SST indicators for prediction of ensuing monsoon rainfall. Twenty-one year moving correlations show that the correlation between WWV anomalies in boreal winter and spring and subsequent ISMR anomalies has strengthened since the mid-1980s.

Characteristic features of winter precipitation and its variability over northwest India

SummaryUsing the 60 year period (1931–1990) gridded land surface air temperature anomalies data, the spatial and temporal relationships between Indian summer monsoon rainfall and temperature anomalies were examined. Composite temperature anomalies were prepared in respect of 11 deficient monsoon years and 9 excess monsoon years. Statistical tests were carried out to examine the significance of the composites. In addition, correlation coefficients between the temperature anomalies and Indian summer monsoon rainfall were also calculated to examine the teleconnection patterns.There were statistically significant differences in the composite of temperature anomaly patterns between excess and deficient monsoon years over north Europe, central Asia and north America during January and May, over NW India during May, over central parts of Africa during May and July and over Indian sub-continent and eastern parts of Asia during July. It has been also found that temperature anomalies over NW Europe, central parts of Africa and NW India during January and May were positively correlated with Indian summer monsoon rainfall. Similarly temperature anomalies over central Asia during January and temperature anomalies over central Africa and Indian region during July were negatively correlated. There were secular variations in the strength of relationships between temperature anomalies and Indian summer monsoon rainfall. In general, temperature anomalies over NW Europe and NW India showed stronger correlations during the recent years. It has been also found that during excess (deficient) monsoon years temperature gradient over Eurasian land mass from sub-tropics to higher latitudes was directed equatowards (polewards) indicating strong (weak) zonal flow. This temperature anomaly gradient index was found to be a useful predictor for long range forecasting of Indian summer monsoon rainfall.

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

Abstract The availability of daily observed rainfall estimates at a resolution of 0.5° × 0.5° latitude–longitude from a collection of over 2100 rain gauge sites over India provided the possibility for carrying out 5-day precipitation forecasts using a downscaling and a multimodel superensemble methodology. This paper addresses the forecast performances and regional distribution of predicted monsoon rains from the downscaling and from the addition of a multimodel superensemble. The extent of rainfall prediction improvements that arise above those of a current suite of operational models are discussed. The design of two algorithms one for downscaling and the other for the construction of multimodel superensembles are both based on the principle of least squares minimization of errors. That combination is shown to provide a robust forecast product through day 5 of the forecast for regional rains over the Indian monsoon region. The equitable threat scores from the downscaled superensemble over India well exce...