Leveraging the 3D-PAWS to Expand In-Situ Observations for the Famine Early Warning System Network

In many food insecure regions of the world, particularly across the African continent, the number of reliable and accessible weather observation sites is declining, while the number of climate extreme weather events (e.g., prolonged drought and extreme flooding) has been increasing. Without reliable precipitation observations, the uncertainty of monitoring and predicting these risks to society will increase. To address this issue, the COMET International Capacity Development Program (ICDP) and the Climate Hazards Center (CHC) at the University of California Santa Barbara have partnered with African meteorological agencies to form the Enhancing Meteorological Networks Partnership (EMNP), funded by the Famine Early Warning System Network (FEWS NET) and USAID. The EMNP leverages the 3D-Printed Automatic Weather Station (3D-PAWS) as a cost effective and sustainable means for national meteorological and hydrological services (NMHSs) to install, maintain, and expand their weather station observation networks.

In the first phase of the project, the EMNP is collaborating with the Kenya Meteorological Department (KMD) and the Zimbabwe Meteorological Services Department (ZMSD), with ICDP providing training workshops on the fabrication, installation, and communications of the 3D-PAWS. Each station includes two rain gauges and temperature, pressure, and relative humidity sensors and will provide data observations every 15 minutes. After the initial training workshop, the local met department will assume responsibility for building their respective 3D-PAWS networks (approximately 25 new stations in each country). The ICDP conducted the first training workshop with the KMD in July 2023. A training workshop for Zimbabwe is planned for early 2024, and the project will eventually expand to include 10 African countries over 5 years.

At this time, 14 3D-PAWS stations are being deployed in Kenya. Some of these stations are co-located with sites with historically good GTS reporting, as ICDP and CHC plan to conduct validation of the 3D-PAWS data. Other stations will be located in data-sparse regions to fill gaps in observational coverage. Data from the 3D-PAWS stations will be used by the KMD (and in the future, other met services with 3D-PAWS networks) to enhance climate services for their local populaces.

The ICDP and CHC are working to establish seamless end-to-end data acquisition, archiving, and data quality workflow processes into the product generation that will support FEWS NET. The ICDP has developed and implemented quality control procedures for the 3D-PAWS data workflow to the CHC. These procedures involve the detection and subsequent removal of observations that fall outside of prescribed ranges depending on sensor specifications, local and global climatological records, and physical limitations. The 3D-PAWS data is then subjected to additional QC steps at the CHC. These include comparisons with other stations and other sources of information, such as satellite precipitation estimates. Ultimately, the QC’d observations will be used to enhance the Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS) rainfall product.

The CHC is currently testing the workflow, with the goal of having the 3D-PAWS data included in the operational processing of the CHIRPS-v3 product including the preliminary CHIRPS pentads updated six times a month with a two-day lag. The 3D-PAWS data could also enhance CHC’s agro-meteorological season rainfall monitoring products, such as the Seasonal Monitoring Probability Generation tool, which combines climatology, model forecasts, and environmental monitoring data to produce seasonal outlooks for probability of drought.