# US Hail History by Location (NOAA NEXRAD Radar) (`japan-open-data/us-hail-history`) Actor

Hail history for any U.S. latitude/longitude from NOAA NEXRAD radar hail signatures (NCEI SWDI): one row per hail day with max estimated hail size in inches, probability, detections and distance. For roofers, insurance adjusters and AI agents.

- **URL**: https://apify.com/japan-open-data/us-hail-history.md
- **Developed by:** [Japan Open Data](https://apify.com/japan-open-data) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 hail day rows

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## US Hail History by Location — Hail Reports from NOAA NEXRAD Radar

**Check the hail history of any U.S. location: enter a latitude/longitude and get every date on which NOAA's NEXRAD weather radars detected hail nearby — with the maximum estimated hail size in inches, hail probability, number of detections, and distance from your point.** One flat JSON row per location and hail day, back to 1995, usually up to 2 days ago.

- **Hail history by location:** one row per hail day, with max hail size, probability of hail and of severe hail, number of radar detections and storm cells, closest distance and exact detection times (UTC).
- **Hail map data for many points:** up to 100 locations per run (homes, roofs, branches, car lots, insured properties), each with its own label.
- **Official source:** NOAA National Centers for Environmental Information (NCEI), Severe Weather Data Inventory (SWDI), NEXRAD Level-III hail signatures. No API key, no login.
- **Cheap per-location hail reports:** pay only for hail-day rows found; "no hail found" and errors are free.

### What can it be used for?

1. **Roofing and exterior contractors — storm leads and hail verification.** Check which neighborhoods, streets or customer addresses were hit by 1"+ hail after a storm, or confirm the hail history of a property before you quote a roof replacement.
2. **Insurance claims and adjusters.** Get a date-of-loss candidate list for a property: every day with radar-detected hail within a few miles, the largest estimated hail size and how close it came. Useful for claim triage, fraud checks and supporting documentation (see the caveat below — this is not an insurance determination).
3. **Auto dealers, real estate and risk analysis.** Screen car lots for hail damage risk, add "hail days in the last 3 years" to property reports, or compare hail exposure across sites and portfolios. AI agents can answer "Did it hail at this address last month, and how big?" in one call.

### How to use it

Only `locations` is required. Run it with the default input to get the last 12 months of hail history for Dallas, TX.

| Input | Type | Default | What it does |
|---|---|---|---|
| `locations` | list | `["32.7767,-96.7970"]` | Points to check as `"latitude,longitude"` strings, or objects `{"latitude": 32.7767, "longitude": -96.797, "label": "Dallas office"}`. Up to 100 per run. |
| `radiusMiles` | number | `10` | Count radar hail detections within this distance of each point (0.1–50 miles). |
| `daysBack` | integer | `365` | Search the last N days when `startDate` is empty (1–1098). |
| `startDate` / `endDate` | `YYYY-MM-DD` | empty | Exact period (1995-01-01 or later, max 3 years per run). `endDate` empty = today. |
| `minHailSizeInches` | number | `0` | Ignore detections smaller than this, e.g. `1` for quarter-size hail or larger. |
| `timeZone` | IANA name | `America/Chicago` | Time zone used to assign detections to calendar dates (evening storms can fall on the next day in UTC). |
| `maxResults` | integer | `1000` | Maximum number of hail-day rows to return. |

This Actor takes **coordinates, not street addresses**. To get a hail report by address, geocode the address first (for example with the free U.S. Census Bureau geocoder or your CRM's coordinates) and pass the latitude/longitude.

#### Input example

Two locations, May–June 2026, 10-mile radius:

```json
{
  "locations": [
    { "latitude": 32.7767, "longitude": -96.797, "label": "Dallas office" },
    "39.7392,-104.9903"
  ],
  "startDate": "2026-05-01",
  "endDate": "2026-06-30",
  "radiusMiles": 10,
  "timeZone": "America/Chicago"
}
```

#### Output example

Real output from the input above (run on 2026-09-19): 12 hail-day rows — 7 for Dallas, TX and 5 for Denver, CO. The first row:

```json
{
  "status": "ok",
  "location": "32.7767,-96.797",
  "label": "Dallas office",
  "latitude": 32.7767,
  "longitude": -96.797,
  "radiusMiles": 10.0,
  "date": "2026-06-19",
  "timeZone": "America/Chicago",
  "maxHailSizeInches": 1.25,
  "maxHailProbabilityPct": 100,
  "maxSevereHailProbabilityPct": 60,
  "signatureCount": 23,
  "stormCellCount": 6,
  "closestDistanceMiles": 1.1,
  "closestHailSizeInches": 0.5,
  "closestRadar": "KFWS",
  "largestHailDistanceMiles": 7.11,
  "largestHailLatitude": 32.874,
  "largestHailLongitude": -96.837,
  "largestHailTimeUtc": "2026-06-19T11:28:38Z",
  "radars": "KDYX,KFWS,KGRK",
  "firstDetectionUtc": "2026-06-19T11:22:32Z",
  "lastDetectionUtc": "2026-06-19T13:16:01Z",
  "source": "NOAA NCEI Severe Weather Data Inventory (SWDI), NEXRAD Level-III hail signatures (nx3hail)",
  "sourceUrl": "https://www.ncei.noaa.gov/swdiws/csv/nx3hail/2026060105:2026070105?bbox=-96.9875,32.6145,-96.6065,32.9389"
}
```

Summary of all 12 rows from the same run:

| Location | Date | Max hail size (in) | Detections | Closest (mi) |
|---|---|---|---|---|
| Dallas office | 2026-06-19 | 1.25 | 23 | 1.1 |
| Dallas office | 2026-06-06 | 1.25 | 1 | 9.93 |
| Dallas office | 2026-06-02 | 1.75 | 5 | 8.42 |
| Dallas office | 2026-05-26 | 0.75 | 3 | 3.28 |
| Dallas office | 2026-05-24 | 1.25 | 9 | 6.15 |
| Dallas office | 2026-05-23 | 1.5 | 6 | 3.76 |
| Dallas office | 2026-05-19 | 1.25 | 11 | 7.33 |
| 39.7392,-104.9903 (Denver) | 2026-06-26 | 1.25 | 4 | 9.79 |
| 39.7392,-104.9903 (Denver) | 2026-06-24 | 1.75 | 24 | 3.18 |
| 39.7392,-104.9903 (Denver) | 2026-06-08 | 1.75 | 37 | 1.73 |
| 39.7392,-104.9903 (Denver) | 2026-06-01 | 2.25 | 24 | 0.36 |
| 39.7392,-104.9903 (Denver) | 2026-05-28 | 0.75 | 25 | 6.49 |

Locations with no hail detections, and invalid input, return one **free** row that says what to change (real output):

```json
{"status": "not_found", "location": "32.7767,-96.797", "label": null, "latitude": 32.7767, "longitude": -96.797, "radiusMiles": 1.0, "startDate": "2026-01-01", "endDate": "2026-01-31", "error": "No NEXRAD hail signatures within 1 miles between 2026-01-01 and 2026-01-31; widen \"radiusMiles\" or the dates (radar data usually lags about 2 days, and no detection does not guarantee there was no hail)."}
{"status": "error", "error": "Location #1 ('Dallas, TX') must be \"latitude,longitude\" in decimal degrees (e.g. \"32.7767,-96.7970\") or an object like {\"latitude\": 32.7767, \"longitude\": -96.797, \"label\": \"Dallas\"}."}
```

#### Output fields

| Field | Meaning |
|---|---|
| `status` | `ok`, `not_found` or `error` |
| `location`, `label`, `latitude`, `longitude`, `radiusMiles` | The point you asked about, your label, and the search radius |
| `date`, `timeZone` | Local calendar date of the hail day, and the time zone used |
| `maxHailSizeInches` | Largest radar-estimated hail size within the radius that day (inches) |
| `maxHailProbabilityPct`, `maxSevereHailProbabilityPct` | Highest radar probability of any hail / of severe hail that day |
| `signatureCount`, `stormCellCount` | Number of radar hail detections and distinct storm cells within the radius |
| `closestDistanceMiles`, `closestHailSizeInches`, `closestRadar` | Nearest detection to your point, its estimated size and the radar that saw it |
| `largestHailDistanceMiles`, `largestHailLatitude`, `largestHailLongitude`, `largestHailTimeUtc` | Where and when the largest hail estimate was detected |
| `radars` | NEXRAD radar stations that detected hail (comma-separated) |
| `firstDetectionUtc`, `lastDetectionUtc` | First and last detection time (UTC) |
| `source`, `sourceUrl` | Dataset name and the exact NOAA request the row was built from |
| `startDate`, `endDate`, `error` | On `not_found` / `error` rows: the period searched and one sentence explaining what to change |

### Pricing

This Actor uses **Pay per event** pricing — you pay for hail-day rows found, not for compute time:

| Event | Price | When |
|---|---|---|
| Result row (`result-row`) | **$0.005** per row ($5 per 1,000) | Each `ok` row = one location × one hail day |
| Actor start (`apify-actor-start`) | **$0.005** per run | Once at the start of each run |

- `not_found` and `error` rows are **free**.
- Example: the default run (Dallas, TX, last 12 months, 14 hail days) costs about **$0.075**.
- A 3-year hail history for one location (about 50–60 hail days in hail-prone Texas) costs about **$0.30** — a fraction of a typical paid per-address hail report.
- 100 customer locations, last 12 months: about $7 in a hail-prone area like Dallas (about 14 hail days per location), less elsewhere.
- Use the **maximum cost per run** option when you start the Actor to cap spending. If the limit is reached, the Actor stops cleanly and says so in the status message.

### Use via API & MCP (AI agents)

**Apify API (HTTP).** Run the Actor and get the rows in one call:

```bash
curl -X POST "https://api.apify.com/v2/acts/japan-open-data~us-hail-history/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"locations": ["32.7767,-96.7970"], "daysBack": 90, "minHailSizeInches": 1}'
```

**Python (apify-client):**

```python
from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("japan-open-data/us-hail-history").call(run_input={
    "locations": [{"latitude": 32.7767, "longitude": -96.797, "label": "Customer 1042"}],
    "startDate": "2026-05-01",
    "endDate": "2026-06-30",
})
for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(row["status"], row.get("date"), row.get("maxHailSizeInches"), row.get("closestDistanceMiles"))
```

**MCP (Claude, ChatGPT, Cursor and other AI agents).** Add this Actor as a tool through the Apify MCP server (https://mcp.apify.com), for example with `?tools=japan-open-data/us-hail-history`. Only `locations` is required, so an agent can call it with `{"locations": ["<lat>,<lon>"]}`.

Recommended agent settings:

- "Did it hail at X on date D?" → `{"locations": ["<lat>,<lon>"], "startDate": "D", "endDate": "D", "radiusMiles": 3}`.
- "Hail history of this property" → `daysBack: 1095` (3 years), `radiusMiles: 1`–`3`, `minHailSizeInches: 1` to keep only damaging-size hail.
- Pass the local `timeZone` of the property (e.g. `America/Denver`) so evening storms get the right date.
- Always check `status`; on `not_found`/`error` show the `error` sentence to the user. Remind users that results are radar estimates, not confirmed hail on the ground.

### Data source, attribution and caveats

- **Source:** NOAA National Centers for Environmental Information, Severe Weather Data Inventory (SWDI) — dataset `nx3hail` (NEXRAD Level-III hail signatures). https://www.ncei.noaa.gov/products/severe-weather-data-inventory
- **License:** public domain (CC0 1.0, U.S. federal government data, per the data.gov catalog). NOAA asks that the dataset be cited when used as a source — every row includes `source` and `sourceUrl`.
- **Radar-derived estimate, not ground truth.** Hail signatures are computed automatically from radar data and describe conditions that were *likely*; they are not observations of hail on the ground. Actual hail size at a specific address may be smaller, larger, or absent.
- **Absence of data does not mean no hail.** Radar coverage gaps, beam height, outages and algorithm limits mean hail can fall without a detection.
- **Not an insurance or legal determination.** Use this data as supporting information for inspections and claims, not as proof of damage or a claim decision.
- **Not affiliated:** this Actor is an independent project and is **not affiliated with, endorsed by or sponsored by NOAA, NCEI or the National Weather Service**. It does not use NOAA logos.
- **Access:** the Actor calls only NOAA's public SWDI web service, sequentially and politely (at most 300 requests per run), and identifies itself in the User-Agent.
- **No personal data:** only radar station IDs, detection coordinates, times, hail estimates and the points you provide.

### Known limitations

- **Coordinates only.** No built-in address geocoding (see "How to use it").
- **Coverage.** The continental U.S. and other areas covered by NEXRAD radars. Data from 1995; usually up to about 2 days ago.
- **Period.** At most 3 years per run; longer periods need several runs. Periods are fetched in 31-day blocks (the NOAA limit).
- **Many far-apart locations.** Nearby locations are fetched together; if the list spans a very large area, each location is fetched separately, which is slower. A run makes at most 300 NOAA requests — if more would be needed, the Actor returns one free `error` row asking you to shorten the period or split the list.
- **Row cap.** When `maxResults` is reached, remaining locations are skipped (the status message says "capped").
- **Cost limit.** If your maximum cost per run is lower than the price of one row, the dataset stays empty and the status message explains why.

### More from Japan Open Data

- [Japan Postal Code & Address in English](https://apify.com/japan-open-data/japan-postal-code-english) — look up Japanese postal codes (zip codes) and addresses in English/romaji, kanji and kana, from Japan Post's official data.
- [TSA Checkpoint Travel Numbers (Daily, Weekly & YoY)](https://apify.com/japan-open-data/tsa-checkpoint-throughput) — daily U.S. TSA airport checkpoint traveler counts as clean JSON, with Monday-Sunday weekly averages (calculated like Kalshi's TSA market) and year-over-year change.
- [Mexico Gas Prices API by Station (Official CNE)](https://apify.com/japan-open-data/mexico-fuel-station-prices) — today's regular, premium and diesel prices at every Mexican gas station from the official CNE feed, with coordinates and distance.
- [US Storm Reports API: Hail, Wind & Tornado (NWS)](https://apify.com/japan-open-data/us-storm-reports-live) — U.S. hail, wind, tornado and flood reports from official NWS Local Storm Reports within hours (last 7 days), filterable by state or radius.

### Feedback

Found a wrong value or need another field (e.g. address geocoding, grid-based hail maps)? Open an issue on the Actor's **Issues** tab with your input and what you expected.

# Actor input Schema

## `locations` (type: `array`):

Points to check, one per line as "latitude,longitude" in decimal degrees (e.g. "32.7767,-96.7970" for Dallas, TX). Via the API you can also pass objects like {"latitude": 32.7767, "longitude": -96.797, "label": "Dallas office"}. Up to 100 locations per run. Coverage: the continental U.S. and other areas covered by NEXRAD radars.

## `radiusMiles` (type: `number`):

Radar hail detections within this distance of each location are counted (0.1 to 50 miles).

## `daysBack` (type: `integer`):

How many days back from today to search when "startDate" is empty (1 to 1098; default 365 = the last 12 months). Radar data usually lags about 2 days.

## `startDate` (type: `string`):

First date to search, YYYY-MM-DD (1995-01-01 or later). Overrides "daysBack". Periods longer than 31 days are split into several NOAA requests automatically (maximum 3 years per run).

## `endDate` (type: `string`):

Last date to search, YYYY-MM-DD. Leave empty for today.

## `minHailSizeInches` (type: `number`):

Ignore radar detections with an estimated maximum hail size below this value, e.g. 1 for quarter-size hail or larger (0 = keep all).

## `timeZone` (type: `string`):

IANA time zone used to assign each detection to a calendar date, e.g. "America/Chicago", "America/New\_York", "America/Denver" or "UTC". Evening storms can fall on the next day in UTC.

## `maxResults` (type: `integer`):

Maximum number of hail-day rows to return (one row per location and date).

## Actor input object example

```json
{
  "locations": [
    "32.7767,-96.7970"
  ],
  "radiusMiles": 10,
  "daysBack": 365,
  "minHailSizeInches": 0,
  "timeZone": "America/Chicago",
  "maxResults": 1000
}
```

# Actor output Schema

## `results` (type: `string`):

Max estimated hail size, probabilities, number of detections and distance per location and date. Table view: overview.

# 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 = {
    "locations": [
        "32.7767,-96.7970"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("japan-open-data/us-hail-history").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 = { "locations": ["32.7767,-96.7970"] }

# Run the Actor and wait for it to finish
run = client.actor("japan-open-data/us-hail-history").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 '{
  "locations": [
    "32.7767,-96.7970"
  ]
}' |
apify call japan-open-data/us-hail-history --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,japan-open-data/us-hail-history"
        }
    }
}
```

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/DWnFllYHEU29lA2ax/builds/rKHZTOorCYeRs5j5i/openapi.json