  There is unison is the scientific community about human induced climate
change. Despite this, we see the web awash with claims around climate change
scepticism, thus driving the need for fact checking them but at the same time
providing an explanation and justification for the fact check. Scientists and
experts have been trying to address it by providing manually written feedback
for these claims. In this paper, we try to aid them by automating generating
explanation for a predicted veracity label for a claim by deploying the
approach used in open domain question answering of a fusion in decoder
augmented with retrieved supporting passages from an external knowledge. We
experiment with different knowledge sources, retrievers, retriever depths and
demonstrate that even a small number of high quality manually written
explanations can help us in generating good explanations.
