Humanitarian agencies are able to use weather (and other) forecasts to act in anticipation of humanitarian crises. For example, when a heatwave or hurricane is forecast, supplies can be moved into position early and emergency supplies positioned or pre-distributed. This reduces the overall impact and the cost of responding to the disaster. However, financing in advance of a disaster requires a high level of confidence in the forecast, to avoid the possibility of misallocated or wasted resources. Many forecasts are currently available but not all are accompanied by an assessment of the forecast quality. For example, it may be that the forecast is over-confident, predicting an event more times than it is actually observed, or it could be under confident, failing to predict events which do then occur. We propose to develop and demonstrate a general method of measuring and displaying the information content of forecasts, using a novel idea which is based on existing research and freely available data. This will allow humanitarian agencies to act confidently in anticipation of humanitarian crises when there is sufficient information in the forecast, and to implement forecast-based financing schemes such as insurance or anticipatory funding allocation only when there is known to be confidence that the scheme will be effective.