Longtime lurker, first-time poster. Nor am I a HA expert. Please be gentle if I mess this up, or at least make the roast entertaining!
I got a new Tempest Weather Station (highly recommend it!), but I noticed a few issues right away. The wind speeds it reported were much too low, the “feels-like” apparent temperature didn’t seem accurate (probably due to the too low wind speeds), and it only provided station pressure without an option to compute sea-level pressure. Living at a higher elevation with occasional spectacular winds I wanted high-frequency and representative observations from my backyard. I knew that placing the sensor at the ideal height for accurate wind readings wasn’t practical. So, I drew on my meteorology background, and some help from ChatGPT, to make corrections within Home Assistant. The results were great, so I thought I’d share what I learned to help you make similar improvements. I also highly recommend Home Assistant, though my wife might disagree!
Getting reliable weather data from a home weather station can be tricky due to placement challenges and local environmental factors. Ideally, a wind sensor should be mounted 10 meters above the ground to avoid interference from buildings, trees, or nearby structures, but that’s not exactly practical for most backyards. Fortunately, Home Assistant makes it possible to compensate for these limitations by applying calibration methods, like scaling factors and offsets, to account for your specific setup.
In my case, my Tempest station is mounted just 5.75 feet above the ground on a fence post in a suburban backyard at 6,000 feet elevation. It’s surrounded by shrubs and neighboring homes, which obstruct the wind to some degree. Additionally, the Rocky Mountain foothills to the west create dramatic weather effects, including Chinook winds that can send temperatures soaring and bring gusts exceeding 80 mph. These conditions meant that raw sensor data alone wouldn’t provide an accurate picture without some adjustments.
To fine-tune my setup, I incorporated data from two reliable nearby weather stations. The CO109 station, located 1.5 miles west in an open landscape, provides precise wind speed and temperature readings. The KBJC station at Rocky Mountain Metropolitan Airport offers aviation-grade data, including sea-level pressure, sky conditions, and visibility. By comparing my home station’s readings to these reference points, I was able to make corrections that significantly improved accuracy.
To achieve this, I used Home Assistant’s templating tools to create custom sensors that apply correction factors in real time. For example, I applied a scaling factor to adjust wind speed for the lower sensor height and a calculated offset to account for systematic differences between readings. Additionally, I implemented an average sensor to smooth out fluctuations and provide more stable wind speed data during rapidly changing conditions.
This setup also included key Home Assistant integrations. The National Weather Service (NWS) integration provides official U.S. forecasts and observations as a baseline, while the WeatherFlow integration pulls real-time data from the Tempest station. I also used the HA-Average integration (available through HACS) to compute rolling average of my Tempest wind speed, ensuring consistent offsets for corrections.
The end result was a set of refined sensor entities—like sensor.home_wind_speed, sensor.home_wind_gust, sensor.home_apparent_temperature, and sensor.home_sea_level_pressure that reflect local conditions more representative - at least they compare much better with nearby weather stations. These improved entities not only provide better insights for daily weather tracking but also enhance automations triggered by specific weather events.
With a bit of calibration and customization, your home weather station can provide data that’s not only informative but also comparable to professional-grade measurements without needing a 30-foot tower in your yard. I hope this guide effectively walks you through the process, assuming you’re comfortable with loading integrations and creating template sensors and automations in Home Assistant. Once set up, you’ll have a weather monitoring system that’s as impressive as the Tempest itself!
I’m just going to link the Google Doc I prepared on what I did: Weather Station Corrections in Home Assistant. Please let me know if there is a better way to share this information. I’d love ideas for making improvements to both the templates, automations, and documentation. I truly hope this is beneficial to some as I’ve gotten so much from this forum.