Knowledge production is a co-evolutionary process where scientific topics and concepts are debated, discussed and assessed between scientists. We assess, we analyze, we “interpret” the world, and, at the same time, we communicate with one another, and we value certain knowledge more than other knowledge, based on some measure of prestige, conformism or past events. Here we analyze the evolution of research topics over the past 30 years (from 1990 to 2019) and assess how research topics have evolved by jointly analyzing topic evolution and the citation network related to climate change adaptation, mitigation or transformation. We found that (1) the research focus has evolved from emissions and modelling to social impacts (i.e. local policies), (2) research on climate change (and possibly research in general) is often confined within specific research areas, hinting that interdisciplinary and convergent work may open opportunities for integrative research able to foster innovative thinking in climate science, and (3) the climate change literature is increasing in overall complexity, requiring novel tools to make sense of the literature such as the implementation of more refined machine learning and natural language process algorithms to identify causal mechanisms and synthesize the body of work to generate new knowledge.

知识生产是一个共同进化的过程，在这个过程中，科学家之间对科学主题和概念进行辩论、讨论和评估。我们评估，我们分析，我们“解释”世界，同时，我们彼此交流，我们更重视某些知识，而不是其他知识，基于某种声望、墨守成规或过去的事件。在这里，我们分析了过去 30 年（从 1990 年到 2019 年）研究主题的演变，并通过联合分析主题演变和与气候变化适应、减缓或转变相关的引文网络来评估研究主题的演变。我们发现 (1) 研究重点已从排放和建模发展到社会影响（即地方政策），