[1] An interesting feature during El Niño Modoki summers (June-August) is the occurrence of surplus rainfall anomalies over the South China Sea (SCS) and off-equatorial tropical Northwest Pacific. Based on analyses of observed and reanalyzed data, it is noted that anomalous warming in central tropical Pacific during an El Niño Modoki induces a quasi-stationary Rossby wave response in the form of a low-level cyclonic flow over the northern SCS. This anomalous response favors rainfall enhancement over the SCS and also promotes the seasonal typhoon activity. We find that this scenario over SCS and sub-tropical NW Pacific is further amplified when an El Niño Modoki co-occurs with a positive Indian Ocean Dipole (IOD) as in 1994. The combination is apparently more conducive for extreme convection events over the region as compared to a pure El Niño Modoki case. The respective impacts of positive IOD and El Niño, on the other hand, are opposite to one another. The modulation of the typhoon activity by IOD events, however, is prominent only since late 1970s.

The present study examines the Kerala Flood Event (KFE, 15–16 August 2018, in India) that occurred along the west coast of India and resulted in ~400 mm of rainfall in one day. The KFE was unique in comparison to previous floods in India, not only due to the rainfall duration and amount, but also due to the fact that the dams failed to mitigate the flood, which made it the worst in history. The main goal of this study is to analyze and elucidate the KFE based on meteorological and hydrological parameters. A propagating low-pressure system (LPS) from the Bay of Bengal (BoB) caused the streak of plenty of rainfall over Kerala, the west coast, central India, and the BoB. Additionally, the upper-tropospheric anti-cyclonic system over the Middle East region inhibited a northward advancement of LPS. On the western coast of India, a non-propagating (with diurnal fluctuations) offshore trough was observed over the west coast (from Kerala to Gujarat state). Therefore, a synergic interaction between LPS, an intrusion of dry air in the middle-troposphere, and the offshore trough was the main reason for KFE. However, after around ten days, rainfall saturated the dam capacities; thus, the released water, along with the amount of precipitation on the day of the event, was one of the other possible reasons which worsened the flood over Kerala.

Spatial and temporal variability in precipitation has been dramatically changed due to climate variability and climate change over the global domain. Increasing in extreme precipitation events are pronounced in various regions, including monsoon Asia (MA) in recent decades. The present study evaluated precipitation variability in light of intensity, duration, and frequency with several extreme precipitation climate change indices developed by the Expert Team on Climate Change Detection Indices (ETCCDI) over the MA region. This study uses an improved version (APHRO_V1901) of the Asian Precipitation Highly Resolved Observation Data Integration Towards Evaluation of extreme events (APHRODITE-2) gridded rainfall product. Results showed that the spatial variability of the extreme precipitation climate change indices is reflected in the annual mean rainfall distribution in MA. Maximum one-day precipitation (R × 1) and precipitation contributed from extremes (R95) depict a peak in decadal mean rainfall values over topography regions. A significant positive trend in R × 1 (with a slope of 0.3 mm/yr) and precipitation greater than the 95th percentile (R95: with a slope of 0.5 mm/yr) are predominantly observed in decadal trends in regional average extreme precipitation climate change indices over MA. Maritime continental countries exhibit an inclined trend in R10, whereas central Asian arid regions show a decreasing tendency in continuous dry days (CDD). The positive trend in R95 is observed over central India, the monsoon region in China, countries that reside over the equator and some parts of Japan, and the Philippines. When comparing the influence of surface temperature (T) and total column water vapor (TCW) on precipitation climate change indices, TCW seems to be a crucial attributor to climate change indices meridional variability. The mutual correlation analysis depicts that precipitation contributed from extremes (R95) strongly correlates in terms of temporal variability with all extreme precipitation indices. Among various global circulation patterns, the prevalent conditions of sea surface temperature (SST) over the equatorial Pacific Ocean have a significant influence on decadal variability in extreme precipitation climate change indices. R10 and R95 possess a relatively significant correlation (0.86 and 0.91) with the Southern Oscillation Index. The maximum number of consecutive dry days (CDD) shows an increasing trend with a positive phase of the North Atlantic Oscillation Index.

Background: This study is based on datasets acquired from multi sources e.g. rain-gauges, satellite, reanalysis and coupled model for the region of Northwestern India. The influence of rainfall on crop production is obvious and direct. With the climate change and global warming, greenhouse gases are also showing an adverse impact on crop production. Greenhouse gases (e.g. CO2, NO2 and CH4) have shown an increasing trend over Northwestern Indian region. In recent years, rainfall has also shown an increasing trend over Northwestern India, while the production of rice and maize are reducing over the region. From eight selected sites, over Northwestern India, where rice and maize productions have reduced by 40%, with an increase in CO2, NO2 and CH4 gas emission by 5% from 1998 to 2011. Results: The correlation from one year to another between rainfall, gas emission and crop production was not very robust throughout the study period, but seemed to be stronger for some years than others. Conclusion: Such trends and crop yield are attributed to rainfall, greenhouse gas emissions and to the climate variability.

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