Can cars provide high quality temperature observations for use in weather forecasting?

By Diego de Pablos

I am an Undergraduate student in the University of Reading that has recently finished his UROP placement (Undergraduate Research Opportunities Programme) in Reading University, this project was funded by the University and was in partnership with the Met Office. Since I am currently undertaking the Environmental Physics course at the Meteorology department, this project was of interest to me for two reasons: first, I plan on getting a PhD at Reading University and wanted to have a feel for that experience and secondly, the research topic seemed to have potential to improve weather forecasting and road safety overall. The project consisted on having a first look at the temperature observations from the built-in thermometer of a car, and compare them with the UKV model surface temperatures and nearby WOW [1] sites observations.

Even though the use of vehicles in weather forecasting has been studied before [2], advanced thermometers were installed on the vehicles to get the observations in most cases, or other parameters were used (i.e antilock brakes or windshield wipers states). This project aimed to assess the potential of the native ambient air temperature sensor most modern cars (less than ten years old) have. Having these observations available when predicting the road state in the nearby future.

A series of days of temperature observations registered by a car’s built-in thermometer were studied. The method used to extract these observed temperatures was an OBD dongle, which would be connected to the car’s engine management system via the standard OBD port cars have installed behind the steering wheel. The dongle would then send this information to the driver’s phone via Bluetooth. In the phone app, observations and other parameters available from the dongle are decrypted, and are later sent to a selected URL via 3G/4G connections. The data would then be stored in metdb, the database used by the Met Office in the UK, and made available for forecasting.


The trial showed a need for further testing regarding the thermometers, as it was suggested that the sensor readings could have a bias with height and speed. However, the potential availability of data, by sheer quantity alone is outstanding, as around 20 million cars would be available to take part in the data collection in the UK.

All in all, using car sensors for weather forecasting seems to have potential and will be studied thoroughly in the near future, to hopefully tie its advancements with those of car technologies.


[1] Weather Observations Website – Met Office. Accessed: 10th of August 2017.

[2] William P. Mahoney III and James M. O’Sullivan. “Realizing the Potential of Vehicle-Based Observations”. In: Bulletin of the American Meteorological Society 94.7 (2013), pp. 1007– 1018. doi: 10.1175/BAMS-D-12-00044.1. eprint: url:

UFMRM WG Webinar: “DARE to use CCTV images to improve urban flood forecasts”

It is difficult to accurately predict urban floods; there are many sources of error in urban flood forecast due to unknown model physics, computational limits, input data accuracy etc. However, many sources of model and input errors can be reduced through the use of data assimilation methods – mathematical techniques that combine model predictions with observations to produce more accurate forecast.

In this talk I will motivate and introduce the idea of using CCTV images as a new and valuable additional source of information in cities for improving the urban flood predictions through data assimilation methods. This work is part of the Data Assimilation for REsilient City (DARE) project.

You can see the whole presentation on YouTube here or view slides here.