# NOAA Daily Weather — Global Station History (`sourcerow/noaa-daily-weather`) Actor

Daily weather from 132,501 stations worldwide, some going back to the 1800s — temperature, rainfall and snow, one row per station per day, with the quality flags NOAA leaves in the file.

- **URL**: https://apify.com/sourcerow/noaa-daily-weather.md
- **Developed by:** [SourceRow](https://apify.com/sourcerow) (community)
- **Categories:**
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.20 / 1,000 observations

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

Daily weather from 132,501 stations worldwide, some going back to the 1800s.
Temperature, rainfall and snow, one row per station per day, with the quality
flags NOAA publishes and most readers discard.

### What it does

GHCN-Daily is NOAA's global archive of daily land surface observations. It is
published as fixed-width text, one file per station, with each month on a single
line and quality flags interleaved with the values.

This Actor reads that format and returns one row per station per day with 29
fields, in metric units, with the flags kept.

Stations can be given by ID or found by name.

### What you get

29 fields per row, including `date`, `station_id`, `station_name`,
`country_code`, `latitude`, `longitude`, `elevation_m`, `tmax_c`, `tmin_c`,
`prcp_mm`, `snow_mm`, `snow_depth_mm`, `quality_ok`, `values_flagged` and
`other_elements`.

The table view shows 12 of them; all 29 are in the JSON, CSV and Excel
downloads.

### Input

| Field | Meaning |
|---|---|
| `stations` | GHCN station IDs, for example `USW00094728`. |
| `stationSearch` | Find stations by name instead. |
| `fromYear` / `toYear` | Restrict the period. |
| `maxObservations` | Stop after this many. `0` removes the cap. |

```json
{
  "stations": ["USW00094728"],
  "fromYear": 2020,
  "maxObservations": 1000
}
```

### Sample output

One complete record:

```json
{
  "date": "2020-01-03",
  "station_id": "USW00094728",
  "station_name": "NY CITY CNTRL PARK",
  "country_code": "US",
  "tmax_c": 9.4,
  "tmin_c": 6.7,
  "prcp_mm": 3.8,
  "snow_mm": 0,
  "snow_depth_mm": 0,
  "quality_ok": true,
  "values_flagged": 0,
  "issues": ""
}
```

### Pricing

| Event | Per 1,000 | Notes |
|---|---|---|
| Observation | $0.20 | One charge per station-day returned |

A station's full history is about $11.40. There is no start fee and no per-row
dataset fee.

### What it does not do

**Nothing is corrected or interpolated.** The data is reproduced as published.
Quality flags are surfaced, not acted on. A value NOAA flagged is returned with
`quality_ok` false rather than being removed or replaced.

**Five elements, not everything.** Temperature, precipitation, snowfall and snow
depth are extracted into their own fields. Stations record more —
`other_elements` lists what else was present that day — but those values are not
parsed into columns.

**Gaps are gaps.** A station that did not report has no row for that day. The
series is not filled in.

**No forecasts.** This is a historical archive. For current conditions or
forecasts, use a weather service.

### Notes

Filter on `quality_ok` before modelling. Everything else is a preference; this
one is the difference between a clean series and one containing outliers NOAA
already flagged.

Set `fromYear`. Requesting a full record without it is tens of thousands of rows
per station.

Station IDs begin with a two-letter country code, so `US`, `IT` and `FR`
prefixes allow geographic filtering after the fact.

`other_elements` shows what else a station recorded that day, which indicates
which stations are worth asking about for wind or humidity.

### Support

Open the **Issues** tab with the station ID and the date of the row in question.

### Licence and attribution

Daily observations from the Global Historical Climatology Network (GHCN-Daily),
published by NOAA's National Centers for Environmental Information. As a work of
the US federal government it carries no copyright under 17 U.S.C. 105. NOAA does
not endorse this Actor.

# Actor input Schema

## `stations` (type: `array`):

GHCN station identifiers, e.g. USW00094728 for New York Central Park.

## `stationSearch` (type: `array`):

Find stations whose name contains this text. Makes the run fetch an 11 MB station list once.

## `fromYear` (type: `integer`):

First year to include. Some stations reach back to the 1800s.

## `toYear` (type: `integer`):

Last year to include.

## `maxObservations` (type: `integer`):

Stop after this many daily records. **0 removes the cap.** One station can hold 57,000 days.

## Actor input object example

```json
{
  "stations": [
    "USW00094728"
  ],
  "stationSearch": [],
  "fromYear": 2020,
  "maxObservations": 1000
}
```

# Actor output Schema

## `observations` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "stations": [
        "USW00094728"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("sourcerow/noaa-daily-weather").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "stations": ["USW00094728"] }

# Run the Actor and wait for it to finish
run = client.actor("sourcerow/noaa-daily-weather").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "stations": [
    "USW00094728"
  ]
}' |
apify call sourcerow/noaa-daily-weather --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,sourcerow/noaa-daily-weather"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/nNRbrbmlflLjPuZRw/builds/uY3cQ3UsHhPjP0uUp/openapi.json