After decades of research, the response of clouds to a change in climate, and in particular to a global climate warming induced by anthropogenic activities, remains poorly understood and is still identified as a key source of uncertainty for climate sensitivity estimates. Given the slow progress in this area over the last fi fteen years, one may wonder what strategy might help to reduce this uncertainty. There are so many physical processes and cloud properties that need to be better understood, and so many weaknesses in the representation of clouds in climate models.

When proposing an observational strategy, it would be helpful to know whether there is a hierarchy among the different problems; whether there are some priorities among the different processes that need to be better understood, better observed, or better simulated in climate models. Therefore, we think that an observational strategy to reduce uncertainties in cloud-climate feedbacks should be composed of two steps: (a) determine what are the most critical uncertainties, (b) determine how observations might be used to reduce some of these uncertainties.

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