Modeling non-stationarity in intensity, duration and frequency of extreme rainfall over India

Significant changes are reported in extreme rainfall characteristics over India in recent studies though there are disagreements on the spatial uniformity and causes of trends. Based on recent theoretical advancements in the Extreme Value Theory (EVT), we analyze changes in extreme rainfall characteristics over India using a high-resolution daily gridded (1 degrees latitude x 1 degrees longitude) dataset. Intensity, duration and frequency of excess rain over a high threshold in the summer monsoon season are modeled by non-stationary distributions whose parameters vary with physical covariates like the El-Nino Southern Oscillation index (ENSO-index) which is an indicator of large-scale natural variability, global average temperature which is an indicator of human-induced global warming and local mean temperatures which possibly indicate more localized changes. Each non-stationary model considers one physical covariate and the best chosen statistical model at each rainfall grid gives the most significant physical driver for each extreme rainfall characteristic at that grid. Intensity, duration and frequency of extreme rainfall exhibit non-stationarity due to different drivers and no spatially uniform pattern is observed in the changes in them across the country. At most of the locations, duration of extreme rainfall spells is found to be stationary, while non-stationary associations between intensity and frequency and local changes in temperature are detected at a large number of locations. This study presents the first application of nonstationary statistical modeling of intensity, duration and frequency of extreme rainfall over India. The developed models are further used for rainfall frequency analysis to show changes in the 100-year extreme rainfall event. Our findings indicate the varying nature of each extreme rainfall characteristic and their drivers and emphasize the necessity of a comprehensive framework to assess resulting risks of precipitation induced flooding. (C) 2014 Elsevier B.V. All rights reserved.

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 Nino-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 season.

Waxing and waning of observed extreme annual tropical rainfall

We begin by providing observational evidence that the probability of encountering very high and very low annual tropical rainfall has increased significantly in the most recent decade (1998-present) compared with the preceding warming era (1979-1997). These changes over land and ocean are spatially coherent and comprise a rearrangement of very wet regions and a systematic expansion of dry zones. While the increased likelihood of extremes is consistent with a higher average temperature during the pause (compared with 1979-1997), it is important to note that the periods considered are also characterized by a transition from a relatively warm to a cold phase of the El Nino Southern Oscillation (ENSO). To probe the relation between contrasting phases of ENSO and extremes in accumulation further, a similar comparison is performed between 1960 and 1978 (another extended cold phase of ENSO) and the aforementioned warming era. Though limited by land-only observations, in this cold-to-warm transition, remarkably, a near-exact reversal of extremes is noted both statistically and geographically. This is despite the average temperature being higher in 1979-1997 compared with 1960-1978. Taking this evidence together, we propose that there is a fundamental mode of natural variability, involving the waxing and waning of extremes in accumulation of global tropical rainfall with different phases of ENSO.