Climate Services: Bringing Smallholder Farmers into the Space Age!
This post is written by Steven D. Prager and Julian Ramirez-Villegas, Alliance Bioversity CIAT
When you think about a farmer getting ready for their season, what is the first image that comes to mind? Is it something about getting the fields ready, images of a healthy crop emerging from the soil, a good rain, or something altogether different? For us, it is something that looks like this:
The above images are of sea surface temperature (SST), showing the SST anomalies around the El Nino 3.4 region. SSTs in the Pacific Ocean (and especially so in a region named the Niño 3.4) are major drivers of local climate conditions at the seasonal time scale in many regions of the world. We use this fact to help generate crop-specific seasonal forecasts that can, in turn, be used by farmers and other agricultural experts to help make better decisions about when to initiate their planting process, what crop varieties to plant, expected yields, and more. The SST data are collected via a combination of satellites (like the MODIS instrument onboard NASA's Aqua satellite or the VIIRS instrument on board the Suomi NPP satellite) and measurement stations in the water (for example, on board buoys or ships). They are then analyzed and provided to users throughout the world by the National Oceanic and Atmospheric Administration (NOAA). Through these seasonal forecasts, smallholder farmers are benefiting from state-of-the-art earth observation and climate science!
Climate services for agriculture — the systematic provision of these agroclimatic forecasts — cannot be developed in isolation. There are many important actors involved, from the farmers themselves with specific knowledge of their crops to the national hydrological and meteorological service (NHMS) agencies that collect weather data and generate and disseminate seasonal forecasts. The NHMS, especially, has a central role in the climate services process as their expertise and data are always a cornerstone of demand-driven climate services.
To truly help farmers make better decisions, agroclimatic forecasts need to be reliable. This means developing and using state-of-the-art models, based on best-in-kind data. In simplest terms, the better the data collection, the better the seasonal forecast. Be it crop information for calibrating the “agro” component of the seasonal agroclimatic forecast, or the station data used to support validation of forecast models and understanding of the local variation in weather patterns, good data are crucial. This is why, when we think about a farmer getting ready for the season, we also see this image:
Collecting good weather data requires good equipment. This equipment can fail, therefore generating data gaps. In many instances, we are interested in weather data in areas where we do not have station data available. Filling those gaps, and measuring in areas where no stations exist, is an example where smallholder farmers are benefiting from earth observation data. Space-based collection of information helps us fill in any gaps in the direct observations out there.
Ultimately, when we imagine a smallholder farmer thinking about their upcoming season, this is what we would like to see:
With earth observation data coupled with state of the art approaches to seasonal forecast generation, the farmer can start the season much more confident about how the season will finish. Investments by USAID, working groups such as CSRD, and global priorities established by the World Meteorological Organization (WMO) have made this possible around the world.
To learn more, see:
- Climate services for smarter farming -- what's it all about?
- Agroclimatic forecasts to the rescue...
- CIAT-led climate adaptation work in Latin America wins coveted UN award