Problem: What problem is this project trying to address?
Weather forecasts in the tropical areas of the world—around the equator—have consistently had low accuracy (around 38%) due to the chaotic nature of the atmosphere, the massive computational power required to solve the equations that describe the atmosphere, error involved in measuring the initial conditions, and an incomplete understanding of atmospheric processes. The fundamental barriers to advancing climate diagnosis and prediction on time-scales from years to days are partly attributable to gaps in knowledge and the limited capability of contemporary operational and research numerical prediction systems. Twenty percent of the world’s area doesn’t have reliable weather forecasts, yet the majority of the world’s population live in these areas.
Further, although data from satellites has improved significantly within the last decade, there are only two major meteorological centers in the world—the European Center for Medium-range Weather Forecasts (ECMWF) and the National Center of Atmospheric Research (NCAR). Neither of these facilities—located in the UK and the US respectively—specializes in weather forecasts in the tropics. Furthermore, there is an increasing need to study weather patterns in the tropics as it is the area that has been and will continue to be most affected by climate change.
The agricultural sector is the most weather-dependent sector and is thus hugely affected by the inaccurate weather predictions and lack of data for weather in the tropics. Weather prediction is one of the most important factors in the success or failure of an agricultural enterprise as well as the economic independence of small-scale farmers. Bad weather predictions lead to loss of crop, supplies (i.e. fertilizer), time, and money. For example, farmers have to be extremely weather conscience when they initially plant their crop. They cannot plant if it is too dry and will also lose 100% of their fertilizer if it rains the day following the planting. They often lose money when they hire people to help on farms when it rains because of cultural norms to not work in the rain. Without accurate weather predictions, farmers have to take many risks and make uninformed decisions. In addition to directly affecting the livelihood, security, nutrition, income, and well-being of the farmers, it has further affects agricultural production as a whole—resulting in recurring problems with food security and large dependencies on imports.
Solution: What is the proposed solution? Please be specific!
Liisa developed the first reliable weather forecasting model for near-equator areas, which produces highly accurate weather predictions with regional and seasonal outlooks, monthly trends, and rain predictions. Making this information available and easily accessible to farmers in the tropical areas of Ghana, she is bridging a gap in the value chain, enabling farmers to make informed decisions, mitigating adverse impacts from weather patterns, and optimizing conditions for the agricultural sector.
Due to climate change, weather in the tropics is extremely sporadic, inconsistent, and changing. By creating an entirely new and accurate formula for predicting weather in these parts of the world, Liisa can provide customized weather forecasts, early warning alerts, and climate data sets allow farmers to increase their yield and efficiency by timing planting, cultivating, and harvesting. In so doing Liisa is improving not only the livelihood and economic independence of farmers, but is also contributing to farm productivity, income, environment, and the agricultural industry.
The tropics account for 20% of the world’s land and the majority of the world’s population. There is a high demand to have accurate weather information for these parts of the world. Although Liisa has begun working in Ghana, she is quickly spreading to other countries in West Africa, and has clear plans to expand to India and eventually all 16 countries through which the equator passes.