The University Corporation for Atmospheric Research (UCAR) has added a new set of remote-sensing capabilities to its suite of 3D-printed weather stations, enabling them to measure streamflow, storm surges and snowfall depth. This will provide greater low-cost data gathering capabilities for remote and isolated areas.
The 3D-Printed Automatic Weather Station (3D-PAWS) initiative was launched five years ago to make the collection of weather data more accessible globally. Designing instruments out of 3D-printed parts means underserved communities can collect their own data for weather forecasting for a fraction of the cost without sacrificing accuracy.
“Our goal is to enable our end users to make and sustain their own networks rather than getting commercial sensors, which could cost several thousand dollars,” said Paul Kucera, project leader for 3D-PAWS, UCAR.
The 3D-printing capability of the instruments enables communities to print and create their own instruments, rather than relying on expensive manufacturers. Now 3D-printed weather stations are currently filling data gaps in regions in Barbados, Kenya, Uganda, and Zambia.
After the initial success of the weather stations – which collect rainfall, humidity, temperature and pressure data – the 3D-PAWS project is working with community partners to produce a new set of remote-sensing capabilities. One type of ultrasonic sensor can be used in three distinct ways: detecting streamflow changes, sudden storm surge rising on the shore, and snowfall in remote mountain areas.
Martin Steinson, mechanical engineer and instrument designer for 3D-PAWS, said, “We are getting much closer to creating a useful warning system. We will be able to combine weather stations and stream gauges to provide information that can impact people’s daily lives.”
The new 3D-PAWS sensor was initially developed to measure the flow of water to help predict potential flooding and snowmelt runoff. The project partnered with streamflow sensing expert Anne Heggli, graduate research assistant at the Desert Research Institute (DRI), to help produce and test a low-cost stream gauge that would be easy to handle in the field. Heggli’s expertise helped the team settle on an ultrasonic sensor.
“Regions that are data poor don’t need something super accurate like radar, which is also expensive. They can benefit just as much from a sensor that is reliable and cost effective, and that is what we are doing,” explained Heggli.
Ultrasonic sensors use sound waves to send and receive pulses, measuring the time it takes between sending the ultrasonic wave, then receiving it when it has bounced off the surface of the stream, to measure the changing height of the water.
Heggli put the 3D-printed instruments through their paces of field deployment, bringing feedback and suggestions back to the 3D-PAWS team to help them improve the product.
“Users should be in charge of their own sensors, deploying them and fixing them themselves,” she said. “Providing users autonomy over their own data and their own networks is important.”
Once streamflow monitoring proved successful in the field, Kucera and his colleagues saw potential for applying the same sensor to monitor storm surge. Partners at the National Office of Meteorology (ONAMET) in the Dominican Republic are now testing the sensors’ ability to monitor and warn coastal communities of sudden and potentially deadly flooding from the sea.
Andres Miguel Campusano Lasose, meteorologist and ONAMET deputy director, said, “It is extremely important to have real-time information of the changing tides associated with the arrival of a tropical cyclone.
“The instruments help strengthen our early warning systems, which translates into early forecasts to be able to safeguard lives and property, which are in high-risk areas for storm surges in a country that is highly threatened every year by tropical cyclones.”
The third application of the new 3D-PAWS sensor is measuring snowfall, which is also currently in the testing phase at the University of California, Berkeley’s Central Sierra Snow Laboratory (CSSL). Located at Donner Pass in the Sierra Nevada mountain range, two snow sensors are being tested against the capabilities of tried-and-true snowfall measurement systems.
Andrew Schwartz, station manager and lead scientist at CSSL, said, “What is needed is a durable, low-maintenance sensor that can transmit data, so someone does not need to travel to collect it. The benefit of the 3D-PAWS sensors is that they are self-contained and don’t need all the expensive equipment taking up a lot of space.”
Schwartz already has some preliminary feedback on the snowfall sensors from the first field deployment that measured a record-breaking snowfall of 214in (544cm), which accumulated across two and a half weeks in December of 2021. “The 3D-PAWS sensors have done exceedingly well, even with the heavy snow,” he said.
According to his measurements, there was about an inch difference in the snowpack height reading between the 3D-PAWS sensors and the established sonic snow-depth sensor at the laboratory. Though still early in the testing phase, he noted that the data difference is likely due to the distance between the two types of sensors, which are located approximately 50ft (15m) apart. “That is more than enough distance for the snowpack to change by an inch,” he said. “It is an exciting start to the project.”
Though these instruments are just in the preliminary stages of development, the 3D-PAWS scientists and engineers are hoping to create a sensor to monitor air quality in urban environments.
“Air quality measurements are a challenge. There is a fine balance between instrument cost and sensitivity where it can capture things like ozone,” said Kucera. The new air quality sensor is currently in the lab testing stage, but field deployments for testing are on the horizon.
Simultaneously, Kucera and his colleagues are working on a sensor that can monitor soil moisture and temperature levels and help farmers better anticipate when they need to plant crops or irrigate. This new instrument was a suggestion from some of the current partners employing the 3D-PAWS weather stations. “Our partners and contributors are the ones who pointed out they could use soil moisture measurements to save crops and improve yield,” said Kucera. “It is feedback from the end user that informs the science.”