Rain calibration corrections

My rain and wind readings are off. It is showing way more rainfall than what is taking place. Last major rain recorded 88mm but we received way less than that maybe 20mm if lucky. And the wind readings are always less than Environment Canada states.

Hello mister insurance.

Can you tell us more about your setup, your station’s page, to what you compare etc.
A weather station is a measuring of a very local situation and many factors can influence it easily.

It is known that rain can be off and WF is working on calibration to make it better over time. Wind calibration kicks rather quickly in once it gets several windy moments coming from all sides.

Again share some more details so we can try to help you.


Morning - just adding to the observations. Last week our Sky reported almost 200% over the rainfall. This week its notably under reported (comparing to a Vue - side by side - so should be similar enough to compare).

Vue - 16mm
Sky - 6.4mm

The 16mm figure is much closer to the actual rainfall…

As a side note - i have two cloned sites to monitor - one with a

Vue - http://www.finchamweather.co.uk/vue/

Sky -http://www.finchamweather.co.uk/


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Hi Eric


The unit is mounted in my backyard on a pole about 6 feet above a shed. It regularly shows more rain than we get and way less wind than we normally get. This

is in comparison to Environment Canada’s local weather monitoring station.



Regarding rain, I won’t say much as indeed it is still not ok. In heavy rain conditions it goes way of for now and WF is as quickly as they can analyse the data make it better.

Wind is normally ok for most. I have no clue how much distance there is between your Sky and th reference you give but know I have 2 sky units 70 cm apart and even that is enough to give different readings. Every single obstacle,hieght of the device can really change a lot the result.

Other testers have several different stations (like VP2 etc mounted on the same pole etc) and will tell you that instant readings differ though slightly … but there is no way to read exactly the same. It is more on average that 2 units set very close will be equal.

here is a page from WF explaining in depth wind


This is my first post. I am glad to see there is some discussion on the rain ‘sensor.’ The numbers I have been getting from the sensor don’t even come close to what my official CoCoRaHs rain gauge measures. I cringe at the thought of a smartweather user providing their weather stations rain observation to the NWS. I’ve seen it report both extremes… 0.06" when I had 0.25" in the gauge to yesterday when 3.43" was actually 1.32" in the gauge. This is a HUGE problem. The data is useless and wrong, and new users should be warned of this.


My rain sensor reports about 6X what my CocoRahs rain gauge is reading.

Also, I suspect my anemometer is reading low. We had a recent dust storm event where my highest gust reported was 22 mph even though there were multiple trees down within a few blocks, and this was a very wide scale event - a monsoonal haboob in Phoenix, AZ. The event was August 30th about 7:15PM MST ( UTC-7). Here is the link for that: https://www.wunderground.com/personal-weather-station/dashboard?ID=KAZSCOTT344&cm_ven=localwx_pwsdash#history/s20180730/e20180730/mdaily

What do I do about these things?

Hi. Thanks for your feedback and welcome to the forum! Please see my previous post, above:


I bought a NOAA rain gauge to compare my results after noticing how wrong Weatherflow was. They don’t need AI to solve the problem, although it could work. They need proper benchmarking and a good set of observations to make a linear regression fit. That should have been done before our units shipped.

They needed to calibrate against old, well known instruments. From all my emails to support, it is not clear they did that sort of benchmarking and adjustments. To make it worse, it’s not clear they understand that AI wont fix the problem without the right strategy.

For your reference, my rain gauge is between 1/3rd to 1/4th of the WF measurement consistently. Happy to provide photographic evidence as needed.

Current WF measurement 1” today. Current rain gauge .31 inches. Rain type- thunderstorm

Last night my sensor recorded 5.414" of rain, actual CocoRahs 1.05". And what is it with that 22 mph? I estimated gale force winds associated with a supercell thunderstorm but the peak gust was 22 mph with peak actual wind only 14 mph. In fact, since June peak wind gusts generally strangely average around 22 mph per hour. I had assumed that the sensor simply isn’t high enough off the ground although well exposed to an large open field but now suspect the readings are indeed too low. Unfortunately, don’t have a wind device to compare to be sure.

rain on the wind sensor can interfere with the wind readings a bit
but also there was one firmware that was causing gusty windspeeds readings to be ignored wrongly, for some
the next firmware update , due out soon, should fix that

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Today WF measurement 2.697”. NOAA rain gauge 0.92”. Noticing a 3x error still.

Another update after a period of Rain…

Vue - 8.9mm

Sky - 0.41mm

Tbh i am starting to lose a little faith in the device - humidity has been out and the rain is way out, often either too notably high or too low.

I’m aware is a low cost device with a brave and innovative series of sensors (to be applauded) - however the range of data coming in it feels increasingly random and sadly i now look more towards the Vue for my data. Even my my old Netamo is beginning to seem more reliable.


Thanks for your help. I’m glad you agree AI may help! A few points here:

  • We’ve collected many station-years worth of both laboratory and field observations, compared them to several “well known instruments” (some old, some new, and all independently and recently calibrated)
  • The haptic rain sensor is a very different beast than a tipping bucket or CoCoRaHs collector tube. For one thing, its basic response to vertically-falling rain is not linear, it’s exponential. So all the linear regression in the world won’t help.
  • We have developed a factory calibration process that works very well for adjusting the basic response of the sensor so that device-to-device variation is very small.

This approach works great most of the time. However, we have learned a few things:

  1. the specific installation conditions can have a significant effect on the rain sensor calibration.
  2. The rain sensor’s response is dependent on more than simply the amount of rain falling on it.

To elaborate on that first point, let’s say you have a particular SKY unit that was calibrated at the factory. If you then install that SKY on a 3 meter PVC pole bolted to a wooden roof, the same rain event will likely register very differently than if you install it on a 10 meter steel pole hammered into the ground.

As a result, it’s not enough to have a factory calibration. Each individual installation needs a custom calibration. That’s what we’re doing now, in a simple way: After recording a few rain events, your SKY’s data, along with other relevant data (from both models and observations) is analyzed and run through a set of algorithms (some that use artificial intelligence and machine learning, some that use fewer buzz-words). And the result of that analysis may lead to an adjustment of your rain sensor’s calibration, if necessary. And this works reasonably well in many cases.

However, thanks to the second point, above, this simple calibration approach does not work all of the time. That’s because the response of the sensor is also sensitive to other conditions like rain rate, wind speed, and temperature. That’s another issue where we’re using AI and ML and all kinds of fancy data techniques to work it out.

The bottom line is that under- and over-reporting is a significant issue for the rain sensor. We are still learning how all the various factors affect the rain sensor. This is a work in progress, but accumulation accuracy will improve as we collect more data and adjust both the calibration parameters and the very shape of the calibration curves.

Keep the faith, Andy! Both of these issues will be resolved soon. We are working on it non-stop (except when we have to stop and read the community forum :slight_smile: ) You’ll be able to retire both your Vue and Netatmo soon!


I have had my station for about 4 months now and I do not think the rain sensor works at all. When it is clear as a bell out I get It’s Raining and when it rains, quite a bit, I get no indication and nothing showing it actually is or did rain. I may have a lemon.

Sounds like it is time for you to e-mail support@weatherflow.com. They’ll be able to get you back on track.


any chance birds are landing on it (for rain when there is none)?

Is there a limit on the angle of incidence for rainfall?
I’ve had zero rainfall recorded since 11th Aug and it has rained to some extend each day.
Very little of the rain is “straight down” on the sensor often it is drifting in from the side and not necessarily large drops.
I see my hub upgraded to v91 this morning - will this help?

The angle affects calibration but you should get some signal at any angle. If your SKY has never recorded rain and you know it has rained, one of two things could be going on:

  1. The rain may be so light that it doesn’t generate a response from the signal. This would be extremely light (aka “misting”) rain.
  2. It’s possible your rain sensor is bad. You can test this by lightly tapping on the top of the SKY with your fingers for a few seconds.

Pretty sure that is what happened to me this morning. When I got up the road, cars were wet, and when I left the house there was visible rain, but extremely light. Sky had not notified me of any rain. By the time I reached the train station it was raining a bit heavier, and sure enough I had the rain notification when I checked the phone.

That said, it was not what I would refer to as fog or mist (where moisture tends to hang in the air), there was clear rain falling, but what I would call drizzle in its intensity (you know, the horrible stuff which completely soaks you to your bones, despite seeming to hardly be raining!) :slight_smile: