YearLocationdex framework (5th dex family)

Mike, 2026-06-26. Both the concept and the name are his: he described the shape as "a Yeardex of Locationdexes" and named the family YearLocationdex — the name says its two axes outright (year × location), so one broad family covers the whole space instead of splitting into week/month/year variants (Mike: "I want as few dex categories as possible, so the name describes what I am looking for"). The fifth dex family, after Eventdex (slot = event), Yeardex (slot = year), Locationdex (slot = place), and CelestialObjectDex (slot = object).

A YearLocationdex tracks each place across the years — a Yeardex crossed with a Locationdex. The slot is a (place, period) cell. Year is the top time unit, and a year holds its finer periods inside it (a year is ~52–54 weeks; drought is one cell per county per USDM week, those weeks rolling up under each year). So the family name commits to "year × location" while the source's native cadence (weekly here, monthly or annual elsewhere) nests within the year.

When a source is a YearLocationdex, not a single-axis dex

Ask: does the measurement exist for every (place, period) pair on a regular grid?

• A drought map redraws every US county every week → county × (year→week) grid.
• A station network's annual value per station → station × year grid.
• A county climate normal per month → county × (year→month) grid.

If instead each record is a one-off happening (slot = event), a fixed sensor's running series (slot = place, time is just a column), or a per-year subject with no place axis (slot = year), it is one of the four single-axis families. The test is regular coverage on both axes — a full place × time grid, not a sparse log.

Storage — one flat place-sorted spine, plus a by-year index

Decided for drought (Mike, 2026-06-26: "which one combines the most simplicity with the fastest access to data"). Do not physically nest two families or keep two sorted copies. Store the grid as ONE flat spine-parquet:

• rows = place × period, one row per cell, columns = the cell's measured value(s).
• Sorted by place (then period) so one place's whole history reads contiguously — the dominant read ("show me this county's drought history").
• A small by-year index JSON alongside gives the time cross-section directly (per-year counts + span) without a second 4M-row sorted copy. Year is the natural top key precisely because the finer periods nest under it.
• Spine-parquet, never file-per-slot: the grid is millions of cells (drought = 4.2M); file-per-slot would bloat the shared storehouse_index. Each YearLocationdex kind gets its own base dir (data/yearlocation_storehouse/<kind>/), kept out of the event index.

This is "both axes first-class" done cheaply: place axis is the physical sort, year axis is the index. A derived single-axis read (e.g. a drought-episode Eventdex, one slot per continuous spell) can be built on top later; it is not the primary store.

Multi-value cells ("data is data")

A cell may carry more than one measured value at different coverage spans. Carry them all; null where a value's span does not reach (feedback_data_is_data_partial_coverage). Do not drop a richer value because it covers fewer years than another.

Bright line

Same as every family: measured reality only (feedback_measured_reality_only). A grid of assessed/observed conditions is IN (USDM, on the FEMA administrative-record precedent); a grid of modeled values (SPEI's modeled PET, any reanalysis grid) is OUT.

Kinds

Kind	Slot	Source	Cells	Storage	Commit
drought	county × week	USDM (NCEI/NIDIS CDC archive)	4,198,880 (3,220 counties × 2000–2024 weeks)	data/yearlocation_storehouse/drought/drought_spine.parquet + by-year index	<pending>

Cell values for drought: in_drought_d1 (binary D1+ flag, 2000–2024) and area_pct_d1 (percent of county area in D1+, 2000–2021; null 2022–2024 until backfill). Scope freeze: docs/scope-drought-yearlocationdex.md.

Deferred

• Live edge for drought. No current-year county file exists (NCEI posts the annual file after the fact); the live usdm_drought PG feed is state-level (coarser). The live edge is a separate decision — likely a county-AOI pull from the USDM data services API.
• County centroids for mapping (a county is a polygon; v1 keys on FIPS + name + state).
• Per-week D0–D4 split (the historical archive carries only the D1+ threshold).