Deployment of low-cost, accurate weather station and other observation instruments
ABOUT THIS INITIATIVE
3D-PAWS (3D-Printed Automatic Weather Station) is an initiative to provide low-cost, reliable, and sustainable environmental observation platform solutions to primarily data sparse regions of the world. 3D-PAWS also provides educational and outreach opportunities to build and deploy observation platforms for training purposes. Currently, 3D-PAWS sensors currently measure pressure, temperature, relative, humidity, wind speed, wind direction, precipitation, and visible/infrared/UV light. Future measurements will include soil, stream, and air quality monitoring solutions.
- Build capacity to reduce weather and hydrology related risk in data sparse regions
- Observe and communicate weather and climate information to rural communities
- Develop observation networks and applications
- Design a system that that can be assembled locally in country
- “Print and replace” components when systems fail
- Enable local agencies to take ownership in building and maintaining observation networks
Many surface weather stations across the globe suffer from incorrect siting, poor maintenance and limited communications for real-time monitoring. To expand observation networks in sparsely observed regions, the 3D-PAWS (3D-Printed Automatic Weather Station) initiative has been launched by the University Corporation for Atmospheric Research (UCAR) and the US National Weather Service International Activities Office (NWS IAO), with support from the USAID Office of U.S. Foreign Disaster Assistance (OFDA).
A high quality 3D-PAWS surface weather station can be manufactured in about a week, at a cost of only $200-400 USD, using locally sourced materials, microsensor technology, low-cost single board computers, and a 3D printer. 3D-PAWS sensors currently measure pressure, temperature, relative humidity, wind speed, wind direction, precipitation, and visible/infrared/UV light. The system uses a Raspberry Pi single-board computer for data acquisition, data processing, and communications.
3D-PAWS has been assessed at the NCAR Marshall Field Site in Boulder, CO, the NOAA Testbed facility in Sterling, VA, and at selected international locations. The Boulder site provides sampling conditions in a high-altitude semi-arid environment with subfreezing temperatures and frozen precipitation (the latter is not measured). The NOAA site provides sampling for a more temperate and humid climate near sea-level. The assessment of data quality is ongoing to compare 3D-PAWS sensors compare to calibrated reference sensors.
Station Pilot Networks
3D-PAWS systems have been deployed in the United States (17), Kenya (25), Uganda (14), Zambia (6), Barbados (33), Curacao (1), Senegal (1), Germany (1), Austria (1), and France (1) with new stations planned for installation in central America. The stations installed in the United States have been deployed at schools, colleges, and research facilities. The sites in Kenya are co-located with schools with a test site at the Kenya Met Department (KMD). The sites in Zambia are installed at radio stations, schools, and rural missions with a test site at the Zambia Met Department (ZMD). The sites in the Caribbean are located at the Curacao Met Department (CMD) and the Caribbean Institute for Meteorology and Hydrology (CIMH) with the primary focus on testing and evaluation. The other deployments around the world are being used for education and assessment.
3D-PAWS real-time data are available on the CHORDS project data servers: Barbados, Kenya, Zambia, and 3D-PAWS (for testing and evaluation). CHORDS (Cloud-Hosted Real-time Data Services for Geosciences) is a US National Science Foundation (NSF) EarthCube initiative to provide a platform for sharing geosciences datasets. It is supported and managed by the UCAR/National Center for Atmospheric Research (NCAR) Earth Observing Laboratory (EOL).
3D-PAWS observations can be used for a variety of hydrometeorological applications:
Regional weather forecasting
Observations from the 3D-PAWS network can be assimilated into regional numerical weather prediction systems such as the Weather Research and Forecast (WRF: http://www.wrf-model.org) model to improve mesoscale weather forecasts.
Early alert and regional decision support systems
Real-time monitoring of precipitation in ungauged or minimally gauged river basins can provide input to flash flood guidance and early warning decision support systems to support delivery of flood alerts.
3D-PAWS can support water resource management tools to improve reservoir operation for fresh water supplies and the generation of hydroelectric power. Other applications include operation of irrigation systems (e.g., center pivots) and agricultural crop monitoring.
3D-PAWS can help monitor conditions leading to outbreaks of diseases such as meningitis and malaria.