The Problem With Getting Sheet Data In and Out of Stormglass.io
You have a sheet of coordinates — port locations, dive sites, solar farm candidates, survey points — and you need weather forecasts, tide tables, or elevation values written back into adjacent columns. You need it for twenty rows, or fifty, and you need it updated next week too.
Stormglass.io aggregates high-resolution marine and land weather data from trusted meteorological institutions. But the path from your list of coordinates to a filled-in spreadsheet runs entirely through API calls you have to build yourself. The default flow is: find the right endpoint in the Stormglass docs, write or adapt a script, run it, paste the outputs row by row, and figure out what broke when the tenth request returns something unexpected.
Below are the four ways teams handle this. Only the last one doesn't require a second tool, a script, or an afternoon.
Method 1: Manual Copy-Paste
The default approach is to open the Stormglass dashboard or run API calls one at a time, copy the returned values, and paste them into the sheet by hand. For a single coordinate, it takes a few minutes. You pull the forecast, grab wave height, wind speed, and air temperature from the JSON, paste each value into the right cell, move to the next row.
Then row two. Then row three.
By the tenth coordinate you're deciding which column was C again. By the twentieth you're not confident the timestamp you grabbed corresponds to the right forecast window. And if someone changes the list — swaps a port, adds three new sites — you do it again from the top.
Method 2: Zapier or Make
Both platforms offer ways to hit the Stormglass API. You can set up a trigger on a sheet row update or run the flow on a schedule, pass the coordinates to Stormglass, receive the response, and write individual field values back into specified cells.
Before going further — do you know what a webhook trigger is? How to parse a JSON response and map individual keys to sheet columns? How to authenticate against an API using a key header? If those steps feel like a foreign language, this path isn't for you. Skip to Method 3 or 4 — you'll get there faster.
If you're still here: yes, it works. The configuration involves picking the right Stormglass endpoint for your data type (weather point, tide extremes, solar, elevation), passing lat and lng as parameters, handling the returned array of hourly or daily values, and mapping each field to the correct column. It's real automation once it's done.
But a row-per-trigger automation is not the same as a batch run.
Sending twenty coordinates through a Zap means twenty separate API calls, twenty trigger fires, and a task log that becomes impossible to audit when coordinate seven returns an unexpected null and the rest silently skip.
You probably just need the wave heights. You probably have no idea how to wire a Make module that parses nested JSON arrays — and you shouldn't have to. So you ask whoever on your team builds these things, and now you're waiting on a Slack thread while the tide window you were trying to plan around closes.
And the moment you need to filter rows conditionally — only coordinates with a "planned departure" flag, say — you've left the automation's native logic far behind.
Method 3: The Previous Generation — Connector Add-Ons
Until recently, the closest thing to a repeatable solution was a category of add-ons that let you configure API calls through a form-based interface. You picked your endpoint, mapped your input columns, set your output columns, saved the config, and ran it.
That was a real improvement over row-by-row copying. The output was consistent across runs, the team didn't have to redo the field mapping each time, and configs could be shared.
But you still had to know the Stormglass endpoint structure. You still mapped every field by hand. You still handled the conditional logic yourself — which rows to include, how to expand multi-event tide responses across rows, what to do when a coordinate returns no data. The add-on got the data through the pipe, but all the thinking was still yours to do. And when Stormglass changed a field name, or you added a new column to your sheet, the config broke until someone fixed it.
That was the previous generation. It shipped data. It didn't understand what you were trying to accomplish.
The Easy Way: Using SheetXAI in Google Sheets
There's a different way entirely. SheetXAI is an AI agent that lives inside your Google Sheet. It reads your coordinate data, understands what each column represents, and through its built-in Stormglass.io integration it can query forecasts, tides, solar data, elevation, or station lists for you — across every row, in one shot. No endpoint configuration, no field mapping, no script debugging. You just ask.
Example 1: Bulk weather forecast across a list of port coordinates
For each latitude/longitude pair in columns A and B, fetch the next 48-hour Stormglass weather forecast and write wave height, wind speed, and air temperature into columns C, D, and E.
SheetXAI iterates every row, queries Stormglass with the correct parameters, and writes the forecast values directly into the adjacent cells. Rows with invalid coordinates get a note in column F instead of a blank.
Example 2: Tide extremes written as expanded rows for dive site planning
For each coordinate in my "Dive Sites" tab, pull the next 14 days of Stormglass tide extremes and write each high/low event — with date, time, type, and height — as a separate row in the Tide Schedule tab.
The pattern: instead of getting one row of summary values back, you get the full event series expanded. SheetXAI handles the one-to-many expansion and routes the output to the right tab without needing a second configuration step.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with geographic coordinates — port locations, survey points, field sites — then ask it to pull Stormglass data for your list. The Stormglass.io integration is included in every SheetXAI plan.
More Stormglass.io + Google Sheets guides
Fetch a 48-Hour Weather Forecast for Every Coordinate in a Google Sheet
Pull wave height, wind speed, and air temperature from Stormglass for each lat/lng row and write the forecast values directly into adjacent columns.
Pull Tide Extremes Into a Google Sheet From Stormglass
Fetch high and low tide events — with timestamps and sea heights — for each coastal coordinate in your sheet and expand them into dated rows.
Fetch Solar Irradiance Data From Stormglass Into a Google Sheet
Pull daily GHI and UV index values from Stormglass for each site coordinate in your sheet to model energy yield across multiple locations.
Look Up Elevation and Bathymetry for Survey Points in a Google Sheet
Query Stormglass elevation values — including negative depths for offshore points — for every lat/lng pair in your spreadsheet.
Find Stormglass Tide Stations Within a Bounding Box in a Google Sheet
Use bounding-box corner coordinates stored in your sheet to query Stormglass for all tide stations inside that region and export their IDs and positions.
Export the Full Stormglass Tide Station Catalog Into a Google Sheet
Pull the complete list of Stormglass tide stations — with IDs, names, and coordinates — into your spreadsheet for filtering and regional analysis.