Can real-time climate data help avert disasters?

Freya Roberts

If monsoon rains fail in the African Sahel, devastating famines and large scale humanitarian crises often follow. It’s almost impossible to predict the near term weather in the region, let alone the future climate, making it difficult to avoid food shortages. But a new article suggests watching weather events unfold could give scientists vital information about when to dispatch life-saving food aid.

The article shows how real-time climate data helped one country in sub-Saharan Africa avoid the worst impacts of a bad monsoon season in 2011. We take a closer look at how it worked, and consider whether real-time data could also help climate-vulnerable countries prepare for an unpredictable future.

Unpredictable climate

The article shows a novel way to use climate data where it’s needed most; places like the African Sahel, a strip of countries below the Sahara desert, where people are especially vulnerable to changeable weather.

Not only does the region face conflict and instability, it also has to deal with an unpredictable climate. Currently, people living there have to wait out the monsoon season, hoping it brings enough rain for crops to grow. It can take months before it becomes clear if there will be enough food to last the year.  

The problem is that in many of these countries, forecasting the weather in the short-term or for the season ahead is almost impossible. This makes it very difficult for governments and aid agencies to intervene early and avoid widespread famine if rains fail.

Collecting climate data as each monsoon season starts, however, could be the next best thing. According to the new article, looking at how much rain is falling in real-time could help scientists make reasonable assumptions about how the season will pan out, and whether to intervene to avoid food crises.

Real-time rainfall

Back in 2011, scientists working on the Rainwatch Project used a simple model to determine whether enough rain had fallen in Niger for crops to grow.

The model monitored how much rain fell each day, totting up the total as it went along. But it also showed how the current year’s rainfall compared to the same date in years gone by. This meant that just a couple of months into the monsoon season, scientists could tell that not enough rain was falling for crops to survive.

Having this information allowed the government and charities in Niger to set relief plans into action much sooner than normal. Unusually wet conditions the following year made it impossible to avoid food shortages altogether, but the interventions put in place early in the 2011 monsoon season helped limit the extent to which people went hungry.

The Nature Climate Change article contrasts this approach to the situation in the Greater Horn of Africa, where there was no proactive response to 2011’s dry monsoon season. An international aid response didn’t kick in until famine was declared in Somalia. Nearly 260,000 people died as a result of the famine, according to United Nations estimates.

A future for live climate data

Niger’s clever approach demonstrates there are ways to use climate data even when traditional methods of forecasting fail. And finding new, useful ways to use climate data is something the international science community is starting to think more about.

Earlier this month the Met Office launched a new initiative to help give the UK government, businesses and industry the information they need to manage their exposure to climate variability and change. It’s part of a wider project by the World Meteorological Organisation, aiming to deliver climate services to a global audience.

The Rainwatch Project in Niger demonstrates that using climate data creatively can help countries become more resilient in the face of current climate fluctuations. These same tools will enable people to respond better if and when climate change starts to affect their surroundings.

That’s especially important in parts of the world like sub-Saharan Africa and the Sahel where climate models can’t predict what the future may bring.
 

🗂️ back to the index