About Fuji Skyline
Ward-level weather observers. We ride bikes, take notes, and care about 2-degree differences between neighborhoods.
Fuji Skyline started with a bicycle and a thermometer. Yuki Matsuda, our founder, was commuting from his apartment in Setagaya to a job in Shinjuku and noticed something that weather apps never mentioned: the temperature difference between his home neighborhood and his office was consistently 3-5°C. On the hottest summer days, that gap meant leaving a tolerable morning and arriving drenched in sweat. On the coldest winter mornings, it meant underdressing for the wind tunnels around Shinjuku Station's south exit.
He started carrying a small digital thermometer on his rides. He logged temperatures at the same time each day, at the same points along his route. After six months, he had a dataset that showed clear patterns — not just the obvious ones like "parks are cooler," but subtle gradients along streets, wind effects around buildings, and humidity pockets near canals. The data matched his subjective experience. The weather forecast didn't.
What We Do
Fuji Skyline maps Tokyo's microclimates at the ward level. We combine live weather data from the Open-Meteo API with local knowledge of each ward's geography, building patterns, and wind behavior. The result isn't just a temperature reading. It's a context for understanding why that temperature exists and how it varies across the neighborhood.
We don't use proprietary models or secret algorithms. We use publicly available data and observable geography. The Open-Meteo API gives us temperature, humidity, and wind for specific coordinates. Our essays explain what those numbers mean on the ground — which streets catch the breeze, which plazas trap heat, where the humidity pools, and where the wind tunnels form.
Our Team
Yuki Matsuda — Founder
Yuki grew up in Saitama and moved to Tokyo for university. He's been cycling in the city for fifteen years, commuting through all 23 wards at various times. Before starting Fuji Skyline, he worked in logistics — planning delivery routes for a food distribution company. The route planning taught him to pay attention to terrain, wind, and traffic patterns. The cycling taught him that Tokyo's weather varies block by block.
He started Fuji Skyline in 2022 as a personal blog — temperature logs and route notes. The blog attracted a small following of cyclists, runners, and outdoor workers who shared his frustration with city-wide forecasts. By 2023, the project had outgrown a personal blog, and Yuki brought in collaborators to expand the coverage to all 23 wards.
Rachel Kim — Co-Founder
Rachel is an urban planner with a background in heat island mitigation research. She studied at the University of Tokyo's Department of Urban Engineering and worked for two years at the Tokyo Metropolitan Research Institute for Environmental Protection. Her research focused on cool pavement trials in Chiyoda Ward and the effectiveness of green roofs on mid-rise buildings.
She joined Fuji Skyline in 2023, bringing scientific rigor to the project's essays and data analysis. She wrote the heat island article that remains one of our most-read pages. She also manages our relationships with ward offices and environmental research groups. Her urban planning perspective keeps us focused on the physical reality of the city — the buildings, streets, and parks that create the microclimates we describe.
Tomoaki Sato — Contributor
Tomoaki installs and maintains IoT temperature sensors in ward offices across the 23 wards. These sensors provide ground-truth validation for the Open-Meteo API data. If the API says 30°C and Tomoaki's sensor says 32°C, we note the discrepancy and investigate. Over time, this validation work has given us confidence in the API's accuracy — and identified the specific wards and conditions where it diverges most.
Tomoaki's background is in electrical engineering. He builds the sensor units himself, using off-the-shelf components: ESP32 microcontrollers, SHT40 temperature-humidity sensors, and LoRaWAN radios for data transmission. The units are solar-powered and designed to run for months without maintenance. Each sensor costs approximately 8,000 yen to build and install — a fraction of the cost of commercial weather stations.
Our Data Sources
We use the Open-Meteo API for live weather data. Open-Meteo provides free access to global weather forecasts based on the Japan Meteorological Agency's GSM model and other numerical weather prediction systems. The data is available for any latitude and longitude, which means we can get ward-specific readings rather than city-wide averages.
We verify these readings against Tomoaki's IoT sensor network and against published data from the JMA's official observation stations. The JMA operates 17 stations within the 23 wards, but their coverage is uneven. Some wards have no station at all. Our approach — API data validated by distributed sensors — fills the gaps without requiring a multi-million-yen meteorological infrastructure.
Why We Do This
Tokyo's weather services are excellent at the macro scale. The JMA's forecasts are accurate, timely, and scientifically rigorous. But they're designed for a city-scale audience. When the forecast says "Tokyo: 33°C, sunny," it's averaging across a 627-square-kilometer area with enormous internal variation. That average is correct. It's also useless for someone deciding which route to cycle, where to take a walk, or whether their elderly parent in a different ward needs a check-in during a heat wave.
We built Fuji Skyline because we couldn't find a service that treated Tokyo's neighborhood-level weather variation seriously. We wanted something between "Tokyo: 33°C" and "the temperature outside your specific window right now." Ward-level data, explained with local context, is that middle ground. It's precise enough to matter. It's general enough to be useful.
We're not a meteorological agency. We don't issue warnings or produce our own forecasts. We're mappers and explainers. We take existing data and put it in context. If you're a cyclist planning a route, a runner choosing a morning loop, a construction worker scheduling outdoor tasks, or a resident wondering why your neighborhood feels different from the forecast — we're building this for you.
Contact
We welcome tips, corrections, and collaboration inquiries. If you know a neighborhood wind pattern we haven't described, if you've noticed a temperature gradient we should document, or if you're a researcher working on urban microclimates, we'd like to hear from you.
Email: maps@fujiskyline.com
Or use our contact form.