AUTHOR=Faniriantsoa Rija , Dinku Tufa TITLE=ADT: The automatic weather station data tool JOURNAL=Frontiers in Climate VOLUME=4 YEAR=2022 URL=https://www.frontiersin.org/journals/climate/articles/10.3389/fclim.2022.933543 DOI=10.3389/fclim.2022.933543 ISSN=2624-9553 ABSTRACT=

Climate data are essential in an array of climate research and applications. Climate data also provide the foundation for the provision of climate services. However, in many parts of Africa, weather stations are sparse, and their numbers have been declining over the last half-century. Moreover, the distribution of existing meteorological stations is uneven, with most weather stations located in towns and cities along the main roads. To address these data gaps, efforts over the last decade, largely driven by external donor funding, have focused on expanding meteorological observation networks in many parts of Africa, mainly through the provision of Automatic Weather Stations (AWS) to National Meteorological Services (NMS). While AWS offer a number of advantages over the conventional ones, which include automated reporting at a very fine temporal resolution (15 min, on average), they also have several disadvantages and accompanying challenges to their use. Some of these well-known challenges are the high maintenance requirements and associated costs that arise from the need to procure replacement parts that may not be available locally. However, another major, under-discussed challenge confronting NMS is the disparities between the different station types provided by different donors that has given rise to barriers to pragmatically using the plethora of data collected by AWS in decision-making processes. These disparities include major differences in the way the data from various AWS types are formatted and stored, which result in poorly coordinated, fragmented, and unharmonized datasets coming from different AWS networks. The end result is that while top-of-the-line AWS networks may systematically be collecting highly needed data, the inability of NMS to efficiently, combine, synchronize, and otherwise integrate these data coherently in their databases limits their use. To address these challenges, a free web-based application called Automatic Weather Station Data Tool (ADT) with an easy-to-use graphical user interface was developed to help NMS to access, process, perform quality control, and visualize data from different AWS networks in one place. Now implemented in five African countries (Ethiopia, Ghana, Kenya, Rwanda, and Zambia), ADT also enables real-time monitoring of stations to see which ones are working and which ones are offline. This tool emerged from a wider climate services approach, the Enhancing National Climate Services (ENACTS), recognizing that availability of high-quality climate data does not automatically translate to ease of access or effective use.