Spatial and temporal variability of floods in Indonesia based on governmental data, Twitter messages and paper reports 

<p>Indonesia, with its tropical and monsoonal climate, is exposed to heavy precipitation and enormous rainfall accumulation which results in weather-driven hazards, including extreme rainfall events and floods.&#160;There are several conventional sources of data to estimate potential of anomalously high precipitation in Indonesia, including&#160;rain gauge data, satellite data and meteorological reanalysis.&#160;Even though they allow assessment of precipitation variability, their usefulness is limited by biases and data gaps.&#160;Furthermore, assessment of a variability in precipitation patterns is not the same as identification of their adverse societal effects, such as floods.&#160;&#160;</p> <p>Due to the proliferation of social media, these conventional data sets can be supplemented with crowd-sourced information that can potentially provide longer-term, accurate records and cover a larger area.&#160;In this study, we&#160;demonstrated that Twitter is a useful source for flood detection and created a flood database. Twitter-based flood database is derived for subregions of major islands within Indonesia: Java, Sumatra, Borneo and Sulawesi, and validated against data from governmental reports and local paper articles. Results show that Twitter-based retrieval performs well in comparison with other sources, but only in regions characterized by sufficiently large pool of active users.&#160;</p> <p>Flood events and extreme rainfall events (defined using in-situ and satellite data) were compared in terms of their spatial and temporal distribution, as well as their meteorological drivers.&#160;In general, on each of the island, there is a seasonal cycle: a wet season during boreal winter, when the Southeast Asian monsoon provides an environment supportive of rain events, and a dry season during boreal summer. On intraseasonal scale, Madden-Julian Oscillation (MJO) creates the conditions favorable for weather extremes. MJO activity causes an increase in the local rainfall rate, with a significant increase in a chance of observing extreme precipitation during favorable MJO phase.&#160;&#160;</p>