The Climate Data Tool: Enhancing Climate Services Across Africa

Dinku, Tufa; Faniriantsoa, Rija; Islam, Shammunul; Nsengiyumva, Gloriose; Grossi, Amanda

doi:10.3389/fclim.2021.787519

Cited by 21 publications

(19 citation statements)

References 34 publications

(28 reference statements)

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“…All the values flagged as erroneous are passed to the second method of the spatial test. The second method performs a spatial regression test used by the Climate Data Tool (Dinku et al, 2022b). The spatial regression test is a quality control approach that checks whether the variable falls within the confidence interval formed from the values of neighboring stations during a given time period called window length (Hubbard and You, 2005;You et al, 2008).…”

Section: Quality Controlmentioning

confidence: 99%

“…Here it should be noted that though ADT can be used to do basic QC of AWS data, it is not created to do extensive QC of historical climate data such as from conventional meteorological stations. Another tool, the Climate Data Tool (CDT), has been developed to do this and many other functions (Dinku et al, 2022b). This tool, which has been installed by over 20 NMS in Africa alone, is used for data organization, extensive quality control (including homogenization), an array of data analyses, and visualization.…”

Section: Quality Controlmentioning

confidence: 99%

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ADT: The automatic weather station data tool

Faniriantsoa

Dinku²

2022

Front. Clim.

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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.

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Section: Quality Controlmentioning

confidence: 99%

Section: Quality Controlmentioning

confidence: 99%

ADT: The automatic weather station data tool

Faniriantsoa

Dinku²

2022

Front. Clim.

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“…An observed dataset which running from 1983 to 2016 with a spatial resolution of 0.0375 • × 0.0375 • was provided by NMA. The ENACTS have demonstrated strong performance when considered at station locations throughout the country [22,[46][47][48].…”

Section: Study Areamentioning

confidence: 99%

Spatiotemporal Changes in Mean and Extreme Climate: Farmers’ Perception and Its Agricultural Implications in Awash River Basin, Ethiopia

Damtew

Teferi

Ongoma

et al. 2022

Climate

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The increase in the intensity and frequency of climate extremes threatens socioeconomic development. This study examines variability of mean and extreme climate, farmers’ perception of the changes, and impacts in the Awash River Basin. Daily rainfall and temperature data were used to analyze 23 extreme climate indices. The Mann–Kendall test was used to assess the magnitude and significance of the changes. Results show an increase in minimum (0.019–0.055 °C/year) and maximum temperatures (0.049–0.09 °C/year), while total rainfall is on a downward trend (from −3.84 mm/year to −10.26 mm/year). Warm extreme temperature indicators, including warmest day (TXx), warmest night (TNx), warm day (TX90p), warm night (TN90p), and warm spell duration indicator (WSDI), show a significant increasing trend (p < 0.05). Nevertheless, except the tepid–cool humid agroecology zone, cold extreme temperature indicators in cool days (TN10p), cool nights (TX10p), and cold spell duration (CSDI) are declining. Extreme precipitation indices, including maximum 1-day precipitation amount (RX1day), count of days when precipitation ≥10 mm (R10 mm), maximum 5-day precipitation amount (RX5day), count of days when precipitation ≥20 mm (R20mm), very wet days (R95p), extreme wet days (R99p), and total precipitation (PRCPTOT), show a decreasing trend. The perception of most farmers’ on climate change and climate extremes agreed with climate records. The major impacts perceived and asserted over all agroecologies are food price inflation, crop productivity decline, crop pests and diseases spread, livestock disease increase, and the emergence of pests and weeds. The increasing trend in extreme warm temperatures, decreasing trend in the cold extreme, and declining trend in precipitation indicators affected agricultural productivity and farmers whose livelihood depends on rainfed agriculture. This agroecology-specific study provides critical information to policymakers, decision makers, and farmers about the potential impacts of climate change and extreme events, leading to the development of agroecology-based adaptation measures.

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“…Through this merging method of on-the-ground station data with satellite rainfall estimates and climate model reanalysis products, ENACTS enabled Ethiopia to fill temporal and spatial gaps in the observational record extending back to 1981, helping the country to better characterize its past and current climate as well as predict its future one (Research Outreach, 2020;Dinku et al, 2022a). Moreover, the ACToday approach's incorporation of ENACTS advanced the use of an open-source R-based software with an easy-to use graphical user interface called the Climate Data Tool (CDT) in Ethiopia and 23 other primarily African countries, which ensures quality-control of rainfall and temperature observations, alongside the performance of an array of analyses and visualization capabilities that are important for other pillars of climate services (Dinku et al, 2022b). It did this by carrying out targeted capacity building trainings not just with the EMI, but with agricultural research institutions such as the Ethiopian Institute of Agricultural Research (EIAR), which is the main gatekeeper for the introduction of new technology, including climate services, in the country, as well as universities like Arba Minch University, which carry out research to understand linkages between climate and multiple sectors such as that of agriculture.…”

Section: Figurementioning

confidence: 99%

From research to practice: Adapting agriculture to climate today for tomorrow in Ethiopia

Grossi

Dinku

2022

Front. Clim.

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Eighty percent of the world's agriculture is rainfed, making it highly vulnerable to climate fluctuations and stresses, such as those brought about by climate variability and change. Sub-Saharan Africa and Ethiopia in particular have experienced a significant increase in climate variability over the past decade, which has led to more frequent weather extremes such as floods and droughts. Because 85% of Ethiopia depends upon agriculture for its livelihoods, such rainfall shortages or excesses can impede food production, access to financial and natural assets, and the ability to recover in subsequent crop seasons. This means that climate variability in agriculture not only affects the availability of the food Ethiopians consume, but also the income of its smallholder farmers. Variability in rainfall and temperature can also have adverse effects on livestock and the pastoralists whose livelihoods depend upon it. Thus, all development planning and practice in the agriculture and related sectors need to take climate variability and long-term climate change into account. Climate services can contribute to the alleviation of a range of climate-sensitive development challenges, including agricultural production and food security. The Adapting Agriculture to Climate Today for Tomorrow (ACToday) approach of the International Research Institute for Climate and Society (IRI), Columbia University, USA, aims to develop climate service solutions through enhancement of the availability and effectiveness of climate information in national policy, planning, management, and other decision-making processes in countries that are particularly dependent on agriculture and vulnerable to the effects of climate variability and change. It targets improved food security, nutrition, environmental sustainability and economic outcomes in these countries by promoting the use of climate information and services to manage current climate risks, while laying the foundation for adaptation to future climatic conditions. In this Perspective, we share experiences from the implementation of the ACToday project and approach in Ethiopia, outlining its accomplishments and challenges. In doing so, we characterize best practices and pitfalls to avoid to ensure climate knowledge and information truly meet the needs of climate-informed decision making and climate-smart policy and planning. We also outline pragmatic guidance to ensure activities designed to evolve climate research into services are done so appropriately, responsibly, and sustainably to bridge the gap between those who produce climate information and those who ultimately use it.

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The Climate Data Tool: Enhancing Climate Services Across Africa

Cited by 21 publications

References 34 publications

ADT: The automatic weather station data tool

ADT: The automatic weather station data tool

Spatiotemporal Changes in Mean and Extreme Climate: Farmers’ Perception and Its Agricultural Implications in Awash River Basin, Ethiopia

From research to practice: Adapting agriculture to climate today for tomorrow in Ethiopia

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