Japan City Weather Dashboard

Real-Time Weather Data for Japan's Major Cities

JP Weather Pro is a hyperlocal weather intelligence dashboard built for people who live in, commute through, or do business in Japan's largest cities. We don't do travel blogging. We don't publish cherry blossom forecasts. We deliver current temperature, humidity, wind speed, precipitation, and a 24-hour temperature trajectory so you can make practical decisions about what to wear, whether to carry an umbrella, and how to plan your day.

The dashboard above fetches live meteorological data every time you load the page. Each city card displays the current temperature, weather condition, and a direct link to detailed hourly information. The data comes from the Open-Meteo API, an open-source weather data service that aggregates global meteorological models including the Japan Meteorological Agency's MSM (Meso-Scale Model) and GSM (Global Spectral Model) outputs. We don't manipulate, smooth, or "enhance" the data. What you see is what the models output.

Why We Built This

Most weather apps are built for casual users. They're ad-supported, cluttered with lifestyle content, and optimized for engagement rather than utility. If you commute from Yokohama to Tokyo every morning, you don't need a 14-day forecast with inspirational photography. You need to know if it's going to rain in the next 3 hours, whether the humidity will make a suit uncomfortable, and how the temperature will shift between your morning train and evening return.

That's why we built JP Weather Pro. Alex Park, our founder, spent three years dealing with Tokyo's summer humidity while commuting in business attire. Existing weather apps showed a daily high of 32°C but didn't communicate that the "feels like" temperature at 8 AM was already 38°C with 85% humidity. The experience of stepping out of an air-conditioned train into a wall of wet heat, wearing the wrong jacket, was the direct motivation for creating a tool that puts practical weather intelligence first.

Mei Tanaka, our data verification lead, checks API outputs against JMA published observations daily. If Open-Meteo reports 28°C for Shinjuku but JMA's AMeDAS station at the Tokyo Observatory recorded 30.2°C, we log the discrepancy. Over time, this builds a calibration understanding that helps us communicate data limitations honestly. Temperature readings can vary by 2-3°C within a single city depending on station location, elevation, and urban heat island intensity. We don't hide this.

Data Sources and Methodology

We use the Open-Meteo Forecast API, which provides global weather data from multiple numerical weather prediction models. For Japanese cities, the most relevant input is the JMA MSM model, which runs at a 5km horizontal resolution and updates every 3 hours. The GSM model provides broader coverage at lower resolution. Open-Meteo blends these with ECMWF (European Centre for Medium-Range Weather Forecasts) IFS model data to produce ensemble forecasts.

The API endpoint we query returns: current temperature at 2 meters above ground, apparent temperature (heat index / wind chill adjusted), relative humidity, weather condition code, precipitation amount, and wind speed at 10 meters. For hourly data, we get temperature, precipitation probability, and weather code for the next 24 hours. Daily data includes maximum and minimum temperature, total precipitation, and maximum UV index.

All data is requested with Asia/Tokyo timezone to ensure local-time alignment. The forecast covers 3 days, which is the practical limit for reliable city-scale temperature and precipitation prediction. Beyond 3 days, model skill degrades significantly for local conditions, and we'd rather show nothing than misleading long-range numbers.

Understanding Urban Weather Variations

A single temperature reading for "Tokyo" is inherently incomplete. Tokyo covers 2,194 square kilometers. The temperature at Tokyo Station at 2 PM in August can be 4°C higher than the temperature on the Olympic Peninsula 15 kilometers away. Our data uses coordinates for the city center (for Tokyo, that's approximately the Imperial Palace district at 35.6762°N, 139.6503°E), but you should understand that your actual experience depends on your micro-location.

Osaka sits in a basin surrounded by mountains on three sides. Heat accumulates. In summer, Osaka consistently records higher temperatures than Kyoto just 40 kilometers northeast, because Kyoto's basin is higher in elevation and has better nocturnal ventilation. Yokohama benefits from Tokyo Bay breezes that can drop temperatures by 2-3°C compared to central Tokyo on summer afternoons. Sapporo's continental climate produces temperature swings of 15°C within a single day in spring and autumn.

These geographic factors matter for practical decision-making. If our dashboard shows 26°C for Tokyo and you live in Nerima, add 1-2°C. If you work in Minato Mirai, subtract 1-2°C from the Yokohama reading. We're working on neighborhood-level resolution but current free API limits make this a future enhancement.

How to Use This Dashboard

Start with the city cards above. Click through to any city for detailed current conditions, a 24-hour SVG temperature chart, and a 3-day forecast table. The temperature chart is rendered directly from API hourly data using SVG path elements — no canvas, no charting libraries, just raw data drawn as a line. You can read the trajectory visually: a flat line means stable temperatures, a steep slope means rapid change.

Check the "What to Wear" page for temperature-based clothing recommendations calibrated to Japanese humidity levels. Our breakpoints account for the fact that 25°C in Tokyo (80% humidity) feels completely different from 25°C in Sapporo (50% humidity). The "Umbrella Check" page provides seasonal rain pattern data and month-by-month precipitation probability tables for each city.

Update Frequency and Reliability

Weather data updates every time you load or refresh the page. The Open-Meteo API itself refreshes model outputs every 1-3 hours depending on the model. JMA MSM updates every 3 hours (00, 03, 06, 09, 12, 15, 18, 21 JST). ECMWF IFS updates twice daily. This means the "current" conditions you see are interpolated from the most recent model run, not live station observations. They're accurate within 1-2°C for temperature and within 10% for humidity in our experience.

If the API fails to respond, city cards show "Updating..." and city pages display a refresh prompt. We never show fake static numbers. The timestamp at the bottom of each page shows when the data was fetched in Japan Standard Time (JST, UTC+9).

Coverage Cities

We track eight cities: Tokyo (population ~14 million, capital region), Osaka (2.7 million, Kansai economic hub), Yokohama (3.7 million, port city and Tokyo commuter zone), Nagoya (2.3 million, manufacturing center), Sapporo (1.9 million, Hokkaido capital), Fukuoka (1.6 million, Kyushu gateway), and Kobe (1.5 million, port and mountain climate). These represent Japan's largest urban areas and cover the country's major climatic zones: Pacific coastal, Seto Inland Sea, Japan Sea coastal, and continental Hokkaido.

City selection was based on population (all are among Japan's 10 largest cities) and climatic diversity. We didn't include Kyoto because it's climatically similar to Osaka and our Osaka page covers the Kansai basin. We didn't include Hiroshima because it falls between Osaka and Fukuoka climatically and receives similar Seto Inland Sea weather patterns.

Technical Notes

This site is built with pure HTML, CSS, and vanilla JavaScript. No frameworks. No build tools. No tracking scripts. We don't use Google Fonts (system fonts only). We don't load external JavaScript libraries. Weather icons are inline SVG. The temperature charts are SVG polyline elements computed directly from API data. The entire site loads in under 100KB excluding API calls.

We chose this approach because weather information should load fast, work on slow mobile connections, and not drain battery with unnecessary JavaScript execution. If you're checking the weather before leaving your apartment, you need the data in under 2 seconds. Our average page load time from a Tokyo connection is 800ms for the initial render, with API data filling in within 1.5 seconds total.

For questions, data issues, or city requests, use our contact form. For information about how we handle data, see our data methodology and accuracy log pages.