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Abstract Atmospheric convectively coupled equatorial Kelvin waves (CCKWs) are a major tropical weather feature strongly influenced by ocean–atmosphere interactions. However, prediction of the development and propagation of CCKWs remains a challenge for models. The physical processes involved in these interactions are assessed by investigating the oceanic response to the passage of CCKWs across the eastern Indian Ocean and Maritime Continent using the NEMO ocean model analysis with data assimilation. Three‐dimensional life cycles are constructed for “solitary” CCKW events. As a CCKW propagates over the eastern Indian Ocean, the immediate thermodynamic ocean response includes cooling of the ocean surface and subsurface, deepening of the mixed layer depth, and an increase in the mixed layer heat content. Additionally, a dynamical downwelling signal is observed two days after the peak in the CCKW westerly wind burst, which propagates eastward along the Equator and then follows the Sumatra and Java coasts, consistent with a downwelling oceanic Kelvin wave with an average phase speed of 2.3 m s⁻¹. Meridional and vertical structures of zonal velocity anomalies are consistent with this framework. This dynamical feature is consistent across distinct CCKW populations, indicating the importance of CCKWs as a source of oceanic Kelvin waves in the eastern Indian Ocean. The subsurface dynamical response to the CCKWs is identifiable up to 11 days after the forcing. These ocean feedbacks on time scales longer than the CCKW life cycle help elucidate how locally driven processes can rectify onto longer time‐scale processes in the coupled ocean–atmosphere system. 

In this study, tweets related to fires in Riau, Sumatra, were identified using carefully selected keywords for the 2014–2019 timeframe. The TAGGS algorithm was applied, which allows for geoparsing based on the user’s nationality and hometown and on direct referrals to specific locations such as name of province or name of city in the message itself. Online newspapers covering Riau were analyzed for the year 2019 to provide additional information about the reasons why fires occurred and other factors, such as impact on people’s health, animal mortality related to ecosystem disruption, visibility, decrease in air quality and limitations in the government firefighting response. Correlation analysis between meteorological information, Twitter activity and satellite-derived hotspots was conducted. The existing approaches that BMKG and other Indonesian agencies use to detect fire activity are reviewed and a novel approach for early fire detection is proposed based on the crowdsourcing of tweets. The policy implications of these results suggest that crowdsourced data can be included in the fire management system in Indonesia to support early fire detection and fire disaster mitigation efforts. 

Floods are a major contributor to natural disasters in Sumatra. However, atmospheric conditions leading to floods are not well understood due, among other factors, to the lack of a complete record of floods. Here, the 5 year flood record for Sumatra derived from governmental reports, as well as from crowd-sourcing data, based on Twitter messages and local newspapers’ reports, is created and used to analyze atmospheric phenomena responsible for floods. It is shown, that for the majority of analyzed floods, convectively coupled Kelvin waves, large scale precipitation systems propagating at ∼12 m/s along the equator, play the critical role. While seasonal and intraseasonal variability can also create conditions favorable for flooding, the enhanced precipitation related to Kelvin waves was found in over 90% of flood events. In 30% of these events precipitation anomalies were attributed to Kelvin waves only. These results indicate the potential for increased predictability of flood risk.