22 July 2011 | EN | FR
Satellite data may help better predict future climate change in Africa
[LONDON] A comprehensive 30-year dataset of African rainfall could soon help test climate change predictions and improve climate models, according to a UK researcher.
David Grimes, who studies satellite data at the University of Reading, told SciDev.Net that his group will release the complete, open-access data set within a year.
Researchers can already provide good short-term forecasts of Africa's weather but lack the detailed and consistent long-term data needed for accurate climate predictions.
The new data come from a European Meteosat satellite that has been collecting data over Europe and Africa. The data will supplement the poor ground data on rainfall to help improve climate predictions, which are often contradictory.
"Some models predict an increase in rainfall in some areas, other models predict a decrease of rainfall in the same area, and part of the reason for that is that data coming out of Africa [are] very poor and very sparse," Grimes said.
Many experts think that climate change will make the African climate more variable, with more extreme events, such as this summer's drought in the Horn of Africa.
This increased variability may also raise the risk of floods. Geoff Pegram, emeritus professor at the University of KwaZulu-Natal in South Africa, expects "longer periods of dryness and, when we do have rain, it is likely to be heavier".
The lack of good rainfall data has prevented climate models making robust predictions about how the climate will change at specific locations.
The new data "can tell us whether the rainfall and the climate in particular areas, at particular times of year or seasons, have been changing in the past 30 years, and then we can compare that with what climate models predict," said Grimes. "If the climate models say the same thing as our data sets that would give us much more confidence in their future predictions."
Previous data sets have lacked consistency. The Global Precipitation Climatology Project, for example, has global rainfall data but uses different methods of calculation for different periods, said Grimes, making it harder to understand how the climate has changed.
Tufa Dinku, a researcher at the International Research Institute for Climate and Society at the Columbia University, United States, said: "This data set is unique in that it uses a single algorithm and single satellite sensor, which ensures the consistency of the time series. There is no other satellite rainfall product that goes back to 1983 at ten-daily time scale and spatial resolution of about five kilometres.
"But the dataset is as good as the number of stations used for calibration," he said. Before the data set can be used, it must be calibrated against ground data. Satellites provide rainfall estimates, but they must be compared with ground data to know how they translate to actual amounts of rainfall.
Grimes said that he is planning to run a series of workshops in Africa to calibrate the estimates against their rain-gauge data and train scientists on how to use the data set.
"Africa is the worst continent, outside Antarctica, for the distribution of rain gauges — that's really the reason we do the satellite monitoring, because if you just use the gauges you can't get a complete picture of what's happening," he said.
"If you don't know what the climate is to start with, then you can't really decide whether it's changing or not."
Tom Miller ( United States of America )
25 July 2011
Can this data be used to predict desert locust populations surges?
Ellie Hopkins ( Practical Action | United Kingdom )
27 July 2011
Data like this is vital in reducing the impacts of a changing climate that people will, and indeed already do, feel. Climate modelling can input into a wide range of decisions, including what crop varieties should be introduced that will enable continued food production through changing rainfall patterns, or where housing should be located based on predicted river changes, or plans for where organisations will need to focus their work over the coming years.
But let us not forget that there is still a chasm between those who have and those who need this sort of data. The challenge we face is being able to communicate this information to those who need it most, but are often the hardest to reach. Projects like Practical Action’s podcasting go a long way towards bridging this disconnect and getting information to farmers. But how to reach nomadic farmers who cannot be guaranteed to be in one place, or to have access to communications technologies, prove harder to reach. We also need to ensure that the data is clear, understandable and useful to the recipient.
Nevertheless, it’s great to hear that climate modelling like this is taking such a step forward. These countries are home to some of the most climate vulnerable people in the world, and in the face of the current East African crisis, an increase in accuracy and detail like this can’t come too soon.
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