What can seasonal forecasts bring to agriculture and food security? Pete Falloon of the Met Office predicts progress.
They say it often pays to look ahead. Farmers have been doing just that for thousands of years, searching for the signals or patterns that might tell them the best time to sow seeds, or seek shelter for their animals.
Here in the 21st century, our desire to predict the weather is no less diminished. Now we are developing the tools, technology and models to make better predictions, not just a few days ahead, but to cover whole growing seasons and climactic events.
Climate variability and extreme weather events (PDF) can cause wide-ranging impacts on agriculture. Too much rain floods vast swathes of land, washes away soil and nutrients, and even short-lived heavy rainfall can lead to water-logging and lodging, when the crop collapses under the extra weight.
At the other end of the spectrum, the 2003 heat wave in Europe was the hottest summer on record for hundreds of years and reduced maize yields in France and Italy by 30-35%. Summer 2012 was a remarkably wet year from the climatological perspective and reduced wheat yields in the UK (XLS) by 14%; yet in the same year a drought in the US reduced maize yields by up to 25%.
Hence, seasonal weather forecasts for agriculture can lead to significant economic and humanitarian benefits.
What are seasonal weather forecasts?
The questions we can answer in seasonal forecasting are different to the questions for short-term weather.
A seasonal weather prediction aims to estimate the change in the likelihood of a climatic event happening in the coming months. It is a forecast of the possible conditions averaged over a large region (e.g. country-wide) and over a specified period of time (e.g. three months). We try to address questions like:
- If the average temperature in Devon (UK) in winter is 5.2°C, what is the chance of having warmer or colder temperatures this year?
- If, on average, the first frost in South East England is on 3 November, what is the probability that this winter will have frosts earlier than this?
This is the essence of what we are trying to do in seasonal forecasting: to estimate the difference between the chance of an event happening this year and the frequency with which it has happened in the past.
Does it work?
Seasonal climate forecasts have found fairly widespread user applications in some regions of the world, notably Africa, Brazil, the US and Australia. For example, the Brazilian state of Ceará adopted seasonal predictions as early as 1989 to manage drought conditions. In 1992, the government used forecasts to warn local farmers of an imminent El Niño and provide them with drought-tolerant seeds, substantially increasing farmers’ yields compared to what was expected.
Since then, the Ceará’s weather forecasting agency (FUNCEME) has been continuously developing seasonal forecasts to inform government sectors involved in agricultural policy-making and drought relief for subsistence farmers.
Elsewhere, AgroClimate provides a range of outlooks relevant to local producers in the southeast US, such as seasonal predictions of temperature and rainfall, alongside short-term rainfall forecasts, a drought outlook, hurricane forecasts, and a range of agriculture-focused tools such as a planting date planner and disease advisories.
And the EU’s Joint Research Centre provides Europe-wide monitoring bulletins and crop yield forecasts, which includes an agrometeorological overview looking back at the weather over the past month, and a forecast for the next ten days. The content varies according to the time of year – there is frost kill analysis for winter crops, and more detailed observed information such as heatwave/rainfall forecasts around ripening. The main purpose of these bulletins is for policy decisions – they contribute to the evaluation of global crop production estimates which feed into the management of the Common Agricultural Policy.
But overall there has been relatively little uptake in Europe, at least by farmers and producers. This is partly driven by the relatively limited accuracy of long-range climate forecasts in Europe. If farmers were to rely solely on these forecasts to make planting choices, these could result in poor results with negative economic impacts.
Rather than technical aspects (e.g. accuracy, lead time, and spatial/temporal scale) potential economic and environmental benefits may be the dominant drivers of user uptake of seasonal forecasts. Seasonal predictions are also commonly uncertain and presented as probabilities, which brings additional challenges in communicating forecast information to end-users.
To tackle this challenge, The Met Office is leading the EU project EUPORIAS that aims to maximize the usefulness of seasonal to decadal forecasts by assessing users’ needs and using this information to develop tools to forecast impacts.
As part of EUPORIAS, we have been working closely with a small group of land managers from Clinton Devon Estates (CDE) to develop a working prototype to provide seasonal winter weather forecasts, say 1-3 months ahead, in support of land management decision making. We are focusing on winter decision making because recent advances in long-range weather forecasting mean it is often possible to provide advance notice of a colder and drier, or warmer and wetter winter than average conditions over the UK.
We provided draft email forecasts each month during winter 2014-15 and are now involving a wider range of land managers and farmers from CDE and the National Farmers Union (NFU) in helping us design the second prototype for winter 2015-16.
So far, we have learnt a great deal from our interactions with the farmers – about their needs for weather information, and how their businesses and decisions depend on the weather. There are still many challenges in building a successful prototype, such as providing information that is useful to them but is also scientifically robust.
The science behind the seasonal forecasts themselves will continue to improve in the years ahead. Given a good understanding of users’ needs and their appreciation of how, when and where to apply these tools, there is a promising future for seasonal forecasts to support agriculture and food security.
About Pete Falloon
Dr Pete Falloon has nearly 20 years of experience in modelling environmental systems. Pete worked at the University of Greenwich on pesticides in river systems, then moved to Rothamsted Research in 1996, where he worked on modelling soil, climate and vegetation interactions for eight years and was awarded a PhD from the University of Nottingham in 2001. He has worked on the impacts of climate and land use change on agriculture, soils and hydrology at the Met Office Hadley Centre since 2004 and currently manages the Climate Impacts Modelling group.