Tag: meteotracker

MeteoTracker soon on Kickstarter!

Final preparations for Kickstarter launch!

It’s been an intense few weeks of development in addition to production and distribution agreements, but finally we can make the announcement: in the next few days the MeteoTracker campaign will begin on Kickstarter!
The crowdfunding campaign will allow us to raise funds for the production of MeteoTracker and to deliver it to those who have placed an order once the funding goal has been reached.

Your support is vital!
Thanks to Kickstarter you can purchase MeteoTracker at a special price: early bird backers will be rewarded with a bigger discount so it’s really important to pledge early!

Why Kickstarter?
It’s one of the leading platforms worldwide, the perfect space to showcase our offer to all climate and technology enthusiasts!

What can you do for now?

►       If you haven’t signed up to Kickstarter yet, you can create an account for free at this link.
►       Keep following us!

Soon you’ll get a sneak peek at our project page and you can support us by subscribing to it.

Whether you pledge or spread the word, your help is essential!

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Instant and accurate measurements even under solar exposure for correct data acquisition in mobility. The MeteoTracker solution

Sensor fully exposed to air flow to have a fast measurement response but well shielded to get accurate measurements even under sun exposure. 

But, if the sensor is appropriately shielded, the air flow, and thus the measurement response speed, drops consistently, compromising the ability of the system to catch the sharp temperature variations met in mobility.

On the contrary, if the sensor is fully exposed to air-flow, it is the solar shielding, and thus the accuracy, that gets lost.

This is the requirements conflict that makes it really tricky to perform proper mobile air temperature measurements.

The MeteoTracker multi-sensor implements a patented system that allows to fully overcame it.


Let’s step back.

The physical quantity is the same – the air temperature – but when it comes to moving from static measurements (fixed station) to mobile measurements, its nature changes considerably: from a slow time-changing parameter to a fast time-changing one that may record up to 10 °C variation in some tens of seconds.

A test we performed proves it: while MeteoTracker recorded a variation of 10.2 °C (from +4.9 °C to -5.3 °C) over 400 m distance (travel time of 37 seconds), the car thermometer indicated only a 2 °C variation. A 8 °C error.

Tabella di confronto tra misure effettuate con MeteoTracker e altri sistemi di misura

The point is that combining fast measurement response and accuracy under solar radiation is a puzzle very tough to solve.

In fact, a proper shielding, apart from not being fit for mobile usage, has a geometric structure that inevitably drastically reduces the air-flow that hits the temperature sensor inside the shelter. As a consequence, the measurement speed decreases considerably, as well.

“An ideal radiation shield would block all solar radiation; however, this is currently impossible because openings are necessary to allow airflow through the shield”  [American Journal of Meteorology] http://journals.ametsoc.org/doi/full/10.1175/1520-0426%282001%29018%3C0851%3ATEOTAM%3E2.0.CO%3B2


In the static measurement context, the issue is of low importance since the air temperature, as said before, changes very slowly compared to the mobile scenario (10 ° C in only 34 seconds), so that the slowness of a measurement system does not introduce significant errors. What is needed is an effective solar shield.


In mobility, instead, the co-existence of the two requirements (fast measurement and accuracy under solar radiation) is essential.


MeteoTracker addresses the issue by means of a patented “differential, dual-sensor” system (Radiation Error Correction System), where two identical sensors are hit by the solar radiation with different intensity, whose ratio is properly calibrated.

The different temperature reading from the two sensors (higher when the solar radiation is strong, lower when the solar radiation is weaker) is the parameter that allows to determine and fix the error due to solar radiation.

This way, the temperature data reported by MeteoTracker preserves high accuracy even under strong solar radiation and at very low-speed (which means very low ventilation) or while stopping for a limited time.

Moreover, since shielding structures are not required, a huge exposure to air flow is kept obtaining a very fast measurement response.

Thanks to our solution, a third issue that would manifest itself with the ordinary approach is resolved: under solar radiation, the temperature reported by the measurement system would increase when the speed is reduced and, vice versa, decrease when accelerating:

Higher speed  = higher ventilation → lower radiation error


The patented MeteoTracker system establishes a negative feedback so that when the vehicle speed is reduced the difference in temperature reading increases, which in turns increases the corrective factors, thus re-aligning the reported value to the correct one.



To stay up to date on all things MeteoTracker, visit and subscribe to our website meteotracker.com.

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Mobile measurements. A field that is surprising, a source of significant weather knowledge, and has yet to be fully explored

What’s the temperature?

Will it be cold where we’re heading?

Where was the coldest place last night?

A quick look on the internet or at the screensaver of your smartphone would provide you with what would appear to be answers to these questions.

But is that really the temperature value that awaits us just outside of our homes, or in the place we’re travelling towards?

No, it isn’t. Or at least, it is in no way a given that it will be.

Let’s see why.

The data that comes from a fixed weather station network is generally accurate and reliable. Less so, the data we see on the screensaver of our smartphones, this is often due to interpolation as we seek to compensate for the lack of weather stations in specific locations.

But this is not the point.

No matter how accurate and reliable the temperature data may be, during certain common meteorological situations, the data derived from a fixed weather station will never be able to provide an exact representation of the thermal distribution across a reference geographical area.

For reasons well-known to meteorological experts – air temperature often has very notable spatial variability and the data measured at one specific point may be very different to that measured at a distance of several hundred metres, sometimes just tens of metres away.



We measured a difference of more than 10 °C between two points in the same village, at a distance of 400 m apart. Temperatures ranged from values well over zero to negative values. For this reason, specifying what the temperature was in Hauzenberg (Germany) during the night between 1st and 2nd January 2020 becomes rather complicated. The correct answer to this question would be all values between 4.9 °C and -5.3 °C.

Data Hauzenberg

The data measured by MeteoTracker in Hauzenberg (Germany) during the night between 1st and 2nd January 2020


At a lower latitude and during a different season, we came across some other very interesting data.

During the night of 7th July 2019, on a coastal stretch covering approximately 20 km in Southeastern Sardinia, we detected thermal variation ranging between 32.8 °C and 22.1 °C whose peak, in terms of rate of spatial variation, was recorded in the location of Geremeas where we measured a difference of 8.5 °C along a 400-meter section of the route (from 30.6 °C to 22.1 °C).

Data Hauzenberg

The thermal profile recorded during the first hour of 7th July 2019 along the Southeastern coast of Sardinia


Many other mobile data acquisition sessions, each with their own peculiarities, demonstrate that the extreme spatial variability of temperature data does not represent an anomaly at all rather a typical condition in common meteorological situations.

Aside from conditions of thermal inversion, that in many geographical areas prevail in the cold half of the year (but not only), very pronounced spatial temperature changes can also arise from breezes, interference between mountain ranges and sustained winds (Stau/Föhn), specific elevation profiles, the basic characteristics of the soil, the “urban heat island” effect and other territorial-environmental factors of anthropic origin.

On the one hand, these situations reveal the intrinsic limit of a fixed weather station network, whose information flow, in such cases, is greatly weakened; on the other hand, they highlight the potential and utility of mobile measurements, a source of weather knowledge that has yet to be fully explored and which assumes a significant contingent (item of data in that specific moment, at that specific point) and statistical (climatic characterisation at a high level of spatial resolution) value.

Nowadays, technological advances – from global connectivity to sensor improvements – enable mobile weather exploration by pursuing the vehicle as weather station paradigm, in which a means of transport becomes a mobile weather station through the use of low-cost devices.

But before the measurement system can become mobile, it must satisfy very specific requirements that are by no means a given.

We’ll talk about this in our next post.


To stay up to date on all things MeteoTracker, visit and subscribe to our website meteotracker.com.

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