1. Why the objects are cut differently here
Connected-component labelling, the step that turns a rainfall field into objects in the source method, is well matched to a catchment. The Lower Mekong work applied it over about 150,000 km² for a monsoon season and produced a clean population of around 1,700 storms.
Indonesia is a different regime. Convection here is close to continuous across 5,200 km of ocean and islands, so at the same 1 mm/h threshold the wet cells form one connected mass: a single object holds 90% of all wet voxels across the whole domain and the whole window. That object is not a storm, it is the intertropical convergence zone. Sub-dividing the domain does not help; at 5x5 degrees the largest object still holds 70%.
This is a property of the domain, not a defect in the published work. It does mean the object-cutting step had to be replaced before anything downstream could be trusted, and the rest of this section is what replaced it.
2. The flood night over the whole country
31 December 2019 to 1 January 2020, across the full area of interest. Every storm alive in those two days, drawn as the track of its volume‑weighted centre. Section 3 zooms into the same two days over Jakarta, under the same rule, so the two maps can be compared directly.
How each of these is measured
3. Jakarta, 31 December 2019 to 1 January 2020
The New Year flood that put much of the capital under water and killed at least 60 people. Every storm whose track starts or ends over Jakarta, Banten or West Java during those two days. Click any track to see what that storm was doing hour by hour.
Life cycle of one storm
No storm selected. Click a track on the map above, and its half‑hourly history appears here: how much rain it was delivering, how large it was, and how hard it was raining at its core.
Storms per 3 hours
Storm starts, binned. Times are UTC; local is UTC+7.
Volume against peak intensity
4. What the storm objects do not capture
A flood answers to accumulated depth over a catchment, and no single storm object represents that. The panel below reads the IMERG grid directly rather than the catalogue, and widens to 30 December to 2 January: a catchment responds to the build-up as well as to the peak, and section 12 shows that the window length changes the answer more than almost anything else.
Rain over Jakarta, hour by hour
Total over the four days
Where these storms sit in 28 years
5. The seasonal cycle
Share of the year's rainfall falling in each calendar month, over the full record. The band is the 10th to 90th percentile across individual years, which is wide: a single year cannot rank the months.
6. Year to year
Rainfall volume
Storm count
7. The domain average hides the strongest signal
Three regions, derived from the catalogue's own seasonality rather than drawn by hand. Each line is a region's rainfall shape through the year.
8. The day and night cycle, which nobody asked the method to find
Where storms are born, by hour. Land and sea separate cleanly and in opposite phase. This was never a target of the method, which makes it the strongest available evidence that the objects are physically real rather than artefacts of the segmentation.
9. A few storms carry most of the rain
10. Warning time comes from coastal geometry, not climate
A storm that forms at sea and then makes landfall has spent time over water where it could in principle have been watched. How much time depends on how far offshore storms form, which is a property of the coast, not of the climate region.
Offshore distance against lead time
Hours at sea before landfall
Bigger storms give more warning
11. The one parameter, and its honest sensitivity
Segmentation takes a single scale parameter: the intensity prominence
h, in mm/hr, that a peak must clear to count as its own storm. There is
no optimum. h chooses the size of weather system counted, so it has to
be quoted with every number taken from the catalogue.
Storm count against h
Rain captured against h
12. Severity: ranking cells, and ranking events
Section 4 ended on a problem. A severity class built from individual convective cells said nothing useful about a flood, because a cell is not the thing a flood responds to. This section has both scales, so the difference is visible.
Per storm: one convective cell
Per family: one linked event
What does work: rank the rainfall, not the object
Neither object layer identifies this flood, so the object is the wrong thing to rank. A flood responds to how much rain fell over a catchment in a window, which is a quantity no single object carries. Ranked that way, against the annual maximum for the same area and window length in each of the 27 complete years:
The answer depends on the area and the window
Choosing the band rates by measurement
The largest events in the record
Storm families by age
What this is not
- Not validated. No gauge or radar comparison has been made. This is a catalogue, not a measurement of skill. Any statement of accuracy on this page would be unsupported, and none is made.
- Not an impact product. Detecting rain over a place is not evidence of flooding. Section 3 shows this directly: the storms over Jakarta during a major flood are unremarkable on a domain-wide object scale.
- Not free of one arbitrary choice.
h= 4.0 is a declared scale, not an optimum, because no optimum exists. - Not a reproduction of the source method. The segmentation is different, and section 1 is why.