# Multi-City Weather Comparison — 6 Global Cities Side by Side

**Use case:** 

Pulls 84 rows: 14 days (1–14 Aug 2026) of daily weather for New York, London, Tokyo, Sydney, Dubai and São Paulo in a single run. Every row carries the coordinate it belongs to plus temperature_2m_max, temperature_2m_min, temperature_2m_mean and precipitation_sum, so you can pivot or chart cities against each other straight from the CSV. Covers both hemispheres, so summer and winter appear in the 

## Input

```json
{
  "coordinates": [
    "40.71,-74.01",
    "51.51,-0.13",
    "35.68,139.69",
    "-33.87,151.21",
    "25.20,55.27",
    "-23.55,-46.63"
  ],
  "fromDate": "2026-08-01",
  "toDate": "2026-08-14",
  "dailyVars": [
    "temperature_2m_max",
    "temperature_2m_min",
    "temperature_2m_mean",
    "precipitation_sum"
  ],
  "maxItems": 84
}
```

## Output

```json
{
  "coordinate": {
    "label": "Coordinate"
  },
  "date": {
    "label": "Date"
  },
  "temperature_2m_max": {
    "label": "Temperature 2m max"
  },
  "temperature_2m_min": {
    "label": "Temperature 2m min"
  },
  "precipitation_sum": {
    "label": "Precipitation sum"
  }
}
```

## About this Actor

This example demonstrates how to use [Weather API — Historical & Forecast](https://apify.com/pepeschuster/open-meteo-weather-api.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/pepeschuster/open-meteo-weather-api.md) to learn more, explore other use cases, and run it yourself.


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For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/pepeschuster/open-meteo-weather-api.md

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).