[1] Monsoon droughts over the Indian subcontinent emanate from failures in the seasonal (June -September) monsoon rains. While prolonged dry-spells (''monsoonbreaks'') pervade on sub-seasonal/intra-seasonal time-scales, the underlying causes for these long-lasting anomalies remain elusive. Based on analyses of a suite of observed data sets, we report an ocean-atmosphere dynamical coupling on intra-seasonal time-scales, in the tropical Indian Ocean, which is pivotal in forcing extended monsoon-breaks and causing droughts over the subcontinent. This coupling involves a feedback between the monsoonal flow and thermocline depth in the Equatorial Eastern Indian Ocean (EEIO), in which an anomaly of the summer monsoon circulation induces downwelling and maintains a higherthan-normal heat-content. The near-equatorial anomalies induce strong and sustained suppression of monsoon rainfall over the subcontinent. It is concluded that the intraseasonal evolution of the ocean-monsoon coupled system is a vital key to unlocking the dynamics of monsoon droughts.

Projections of climate change are emerging to play major roles in many applications. However, assessing reliability of climate change projections, especially at regional scales, remains a major challenge. An important question is the degree of progress made since the earlier IPCC simulations (CMIP3) to the latest, recently completed CMIP5. We consider the continental Indian monsoon as an example and apply a hierarchical approach for assessing reliability, using the accuracy in simulating the historical trend as the primary criterion. While the scope has increased in CMIP5, there is essentially no improvement in skill in projections since CMIP3 in terms of reliability (confidence). Thus, it may be necessary to consider acceptable models for specific assessment rather than simple ensemble. Analysis of climate indices shows that in both CMIP5 and CMIP3 certain common processes at large and regional scales as well as slow timescales are associated with successful simulation of trend and mean.

[1] In the backdrop of a changing climate, we investigate whether the Indian summer monsoon is changing either in terms of duration or spatial coverage. Such an analysis specifically for the continental Indian region has both conceptual and societal implications, and has been lacking. We show here, based on an analysis of daily gridded observed rainfall data for the period 1951 -2003, that there are decreasing trends in both early and late monsoon rainfall and number of rainy days, implying a shorter monsoon over India. Similarly, there is a sharp decrease in the area that receives a certain amount of rainfall and number of rainy days during the season. These trends are consistent with other variables like OLR and rainfall from independent datasets; in particular, the land-ocean temperature contrast has a decreasing trend, consistent with a weakening monsoon. The results emphasize need for careful regional analysis in drawing conclusions regarding agro-ecological sustainability in a changing climate. Citation: Ramesh, K. V., and P. Goswami (2007), Reduction in temporal and spatial extent of the Indian summer monsoon, Geophys. Res. Lett., 34, L23704,

Diagnostic analysis of observations and a series of ensemble simulations using an atmospheric general circulation model (GCM) have been carried out with a view to understanding the processes responsible for the widespread suppression of the seasonal summer monsoon rainfall over the Indian subcontinent in 2000. During this period, the equatorial and southern tropical Indian Ocean (EQSIO) was characterized by persistent warmer than normal sea surface temperature (SST), increased atmospheric moisture convergence, and enhanced precipitation. These abnormal conditions not only offered an ideal prototype of the regional convective anomalies over the subcontinent and Indian Ocean, but also provided a basis for investigating the causes for the intensification and maintenance of the seasonal anomaly patterns. The findings of this study reveal that the strengthening of the convective activity over the region of the southern equatorial trough played a key role in inducing anomalous subsidence over the subcontinent and thereby weakened the monsoon Hadley cell. The leading empirical orthogonal function (EOF) of the intraseasonal variability of observed rainfall was characterized by a north-south asymmetric pattern of negative anomaly over India and positive anomaly over the region of the EQSIO and accounted for about 21% of the total rainfall variance during 2000. The GCM-simulated response to forcing by SST anomalies during 2000 is found to be consistent with observations in reasonably capturing the seasonal monsoon anomalies and the intraseasonal variability. Further, it is shown from the GCM experiments that the warm Indian Ocean (IO) SST anomalies influenced the regional intraseasonal variability in a significant manner by favoring higher probability of occurrence of enhanced rainfall activity over the EQSIO region and, in turn, led to higher probability of occurrence of dry spells and prolonged break-monsoon conditions over the subcontinent. In particular, the simulated breakmonsoon anomaly pattern of decreased rainfall over the subcontinent and increased rainfall over the EQSIO is shown to intensify and persist in response to the IO SST anomalies during 2000. These results clearly bring out the significance of the IO SST anomalies in altering the regional intraseasonal variability and thereby affecting the seasonal mean monsoon. Further studies will be required in order to investigate the detailed physical mechanisms that couple the variability of convection over the IO region with the local SST boundary forcing and the large-scale monsoon dynamics.

An objective method is used for determining the rainfall threshold for identifying extreme rainfall events (EREs) over the urban city, Bangalore, using observed rainfall data for a period of 35 years (1971–2005). Using this threshold, 52 EREs were identified during the period 2010–2014 using high‐resolution rain‐gauge observations. From these EREs, 15 localized and non‐localized events were chosen based on spatial distribution to examine the forecast skill of the Weather Research and Forecasting (WRF) model. Apart from the conventional verification methods, a number of skill scores and indices were defined for a comprehensive evaluation of rainfall model skill. In general, the forecast underpredicted the magnitude of localized and non‐localized EREs for the majority of cases; however, the model overpredicted light rainfall (≤10 mm day−1). The model showed a success rate of 59% in simulating light rainfall for localized EREs while 12% of events were missed and 29% were wrongly predicted. The success rate was significantly reduced at higher rainfall categories for localized and non‐localized EREs, where the forecast missed the majority of rainfall events. The Reliability Index (RI) computed clearly showed that model skill is relatively higher for non‐localized EREs compared to localized EREs. The average forecast reliability for non‐localized and localized EREs were 74 and 51%, respectively. For localized EREs, model skill is relatively higher in rainfall location prediction (61%) compared to area (44%) and intensity (46%) prediction; while in the case of non‐localized EREs, model skill is similar for location, intensity and area prediction. It is found that coupling an urban canopy model with WRF reduces the model errors particularly for lower rainfall thresholds.