The cardboard box is covered with a layer of dust so thick it must have been tucked away in this Kenyan basement for decades. The researcher wipes off the dust and rummages through the papers stored inside by someone long since retired. Sheet after sheet of neatly typed paper emerges, the faded rows of numbers detailing rainfall, temperature, and wind speed. In a way, the researcher is hunting for treasure. And she is not alone.
In sub-Saharan Africa, dozens of her colleagues are searching for weather data collected decades ago, but now lying hidden in remote meteorological offices. Many nations in the region are working on data rescue: the salvaging of old paper records and the digitizing of the data they contain. They hope it can fill some of the gaping holes in Africa’s climate history and, ultimately, predict the continent’s future.
Weather data is a precious research tool. But collecting quality data is not a priority in countries where more pressing issues — such as poverty, healthcare, and education — attract most attention and funding. “The lack of digitized data is holding back climate research. It’s a huge problem,” says Sarah O’Keefe, a PhD student at the Environmental Change Institute of the University of Oxford in the UK, which runs a modeling initiative called climateprediction.net.
And without this research, uncertainty remains. O’Keefe describes how, during a trip to Kenya, policymakers approached her with many different queries, ranging from “How will climate change affect my country’s economic growth?” to “What should I tell farmers when they ask me if a recent drought has been caused by global warming?”
For mode ing to work, an abundance of data is needed from ground observations. In this, Africa is lagging behind. “We need observations to validate our models and find out whether they are actually capable of simulating the specific weather patterns of a certain area,” says O’Keefe. “There is a lot of observed data in Africa, but, to a large degree, these are just observations written on paper lying in some cupboard, out of reach for anyone outside the local weather office.”
Political indifference worsens the problem. “As a politician, you wouldn’t boast about having funded 30 years’ worth of rain gauges along a river — nobody is going to be excited about that,” O’Keefe says.
Automated weather stations
But in Kenya, attempts are under way to blend data collection with broader development goals, such as economic growth. Kenya’s economy is largely based on agriculture, forestry, and livestock — economic activities that generally lead to high emissions and are also extremely vulnerable to the effects of climate change.
Last year, the Kenya Meteorological Department teamed up with Delft University of Technology in the Netherlands and Oregon State University in the United States to deploy a dense network of cheap, automated weather stations in the country as part of a wider project. Although still a pilot, the project’s ambitious goal is to place monitoring stations 30 kilometers (approximately 19 miles) apart throughout sub-Saharan Africa.
Rolf Hut, a Delft University researcher working on the project, called TAHMO, says better weather data could leave low-income farmers better off. For example, it could help reduce micro-insurance premiums by enabling insurers to assess weather-related claims remotely.
“Farmers can insure their harvest, on a very small scale,” Hut says. “But, at the moment, companies have to verify impacts [in person] at the end of the season on a case-by-case basis, which makes their expenses, and eventually the premiums, much higher.” With more-detailed weather data, insurance companies could simply check the records for each patch of land for which a claim is made, with the savings leading to cheaper premiums, he says.
To make this work, though, companies need independent, unbiased information, something the Kenyan system strives to provide. Insurers would pay for detailed data, while the basic data would be available to the public for free, according to the project plans.
Over time, the partnership aims to produce long-term data series that would also feed into local scientific efforts to better understand the country’s climate. “As academics, we recognize how little data is available in Africa,” Hut says. “It’s one of the biggest and most complex land areas of the planet, but there are no ground observations.”
The UN’s next major climate summit is providing a further push to improve weather data gathering. Ahead of the talks in Paris, France, this December, countries must submit voluntary plans for reducing carbon emissions from 2020. Some developing countries are working with international funders to develop ways to measure emissions and cuts.
For example, the philanthropic Clinton Foundation is helping build a system to pull together data from various sources and measure how much atmospheric carbon dioxide (CO2) Kenya produces. This System for Land-based Emissions Estimation in Kenya, or SLEEK, is meant to enable the Kenyan government to report more accurately on its efforts to reduce emissions. The system will integrate data about crops, soil, forestry and weather, making information accessible to governments and to people who may use it to better manage their activities.
Interested in finding out more on this topic? The Research Data Alliance 6th Plenary Meeting will have a special focus on 'research data for climate change'.
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