Tropical ecosystems are characterized by high annual rainfall associated with weather-driven natural hazards. Indonesia, which constitutes the largest part of the Maritime Continent, is exposed to extreme rain accumulation (Chang et al. 2005) and thus, landslides and floods (e.g. Sekaranom and Masunaga 2017; Baranowski et al. 2020). Population growth, deforestation, significant changes in land use resulting in shrinking retention areas along with climate change make the country vulnerable for such hazardous events.
Chang, C. P., Z. Wang, J. McBride, and C. H. Liu, 2005: Annual cycle of Southeast Asia - Maritime continent rainfall and the asymmetric monsoon transition. J. Clim., https://doi.org/10.1175/JCLI-3257.1.
Sekaranom, A. B., and H. Masunaga, 2017: Comparison of TRMM-derived rainfall products for general and extreme rains over the maritime continent. J. Appl. Meteorol. Climatol., https://doi.org/10.1175/JAMCD-16-0272.1.
Baranowski, D. B., and Coauthors, 2020: Social-media and newspaper reports reveal large-scale meteorological drivers of floods on Sumatra. Nat. Commun., 1–10, https://doi.org/10.1038/s41467-020-16171-2.
In the literature, a variety of extreme precipitation definitions are in use. A definition of "extreme" precipitation event generally has 3 distinct aspects:
a metric (e.g. percentile values)
a timescale (e.g. accumulation over days)
a spatial scale (e.g. station-based approach)
Different definitions which were applied to the data are described below.
BMKG's definition
Following the definition adopted by the Agency for Meteorology, Climatology and Geophysics of the Republic of Indonesia (BMKG), at each station, days with in-situ measured rain accumulation exceeding 100 mm are classified as "extreme rainfall days". This absolute threshold corresponds to various percentile of daily rainfall total (depending on the station). The timespan is set for all available days between 1 January 2000 - 31 December 2020.
Raw data
All available data without any further processing
80 percentile_1
"Extreme rainfall days" are defined as exceeding the 80th percentile of daily precipitation (all days are considered)
80 percentile_2
"Extreme rainfall days" are defined as exceeding the 80th percentile of daily precipitation (only days with precipitation > 1 mm/day are considered)
85 percentile_1
"Extreme rainfall days" are defined as exceeding the 85th percentile of daily precipitation (all days are considered)
85 percentile_2
"Extreme rainfall days" are defined as exceeding the 85th percentile of daily precipitation (only days with precipitation > 1 mm/day are considered)
90 percentile_1
"Extreme rainfall days" are defined as exceeding the 90th percentile of daily precipitation (all days are considered)
90 percentile_2
"Extreme rainfall days" are defined as exceeding the 90th percentile of daily precipitation (only days with precipitation > 1 mm/day are considered)
95 percentile_1
"Extreme rainfall days" are defined as exceeding the 95th percentile of daily precipitation (all days are considered)
95 percentile_2
"Extreme rainfall days" are defined as exceeding the 95th percentile of daily precipitation (only days with precipitation > 1 mm/day are considered)
98 percentile_1
"Extreme rainfall days" are defined as exceeding the 98th percentile of daily precipitation (all days are considered)
98 percentile_2
"Extreme rainfall days" are defined as exceeding the 98th percentile of daily precipitation (only days with precipitation > 1 mm/day are considered)
NOTES
# filenames
Each filename is composed of WMO number, definition used, type of data, and info if these are values or a time series vector related to values.
e.g. "WMO_96529_60_percentile_1_Rainfall_Rate_values.txt"
# missing data
If you see 8888 in the values, it means "Unmeasured Data"
9999 refer to "No Data"
In raw data, time series vector is continous even if there is missing data.
# data availability
Whenever possible, timespan was set for all available days between 1 January 2000 - 31 December 2020.
# units
All data in mm/day.