Agriculture sector is a key source of food and income security for farmers in Ghana. However, the sector is heavily impacted by climate variability and change. Providing reliable and accessible agrometeorological information is crucial for smallholder farmers adaptive capacity. This Thesis aims to improve the quality of weather and climate forecast information to support the decision making of local farmers in Ghana by developing methods, ICT-based tools and processes that use and/or integrate both scientific and local forecasting knowledge and data. In this thesis, I provide insights on the tailoring of model-based forecasts, integration between local and scientific forecasting systems, and design principles of an effective ICT-based climate service co-design with and for small-scale farmers. These insights contribute to enlighten science and policy for addressing weather and climate risks faced by vulnerable farmers in and outside Ghana.