Climate change is expected to have large, negative effects on the global economy. Adaptation by individuals and firms will determine, in part, how much damage ultimately occurs. Estimating adaptation is challenging, leading to increased uncertainty about climate damages and, therefore, the optimal aggressiveness of climate policy. This study clarifies the theoretical conditions under which the private benefit of adaptation can be identified and makes progress toward estimating policy-relevant adaptation and climate damages. The theoretical results give conditions under which adaptation can be identified. In one case, the value of adaptation can be identified from weather realizations given a measure of firm or consumer welfare. If such a measure is not available, then additional data is needed. For instance, changes in expectations about the weather can be used to identify the value of forward-looking adaptation if firm revenue is available instead of profit. The empirical results apply this method. For the first empirical study, I build a novel dataset of El Nino/Southern Oscillation (ENSO) forecasts and estimate adaptation by North Pacific albacore harvesters to ENSO-driven climate variation. The results show that, in this setting, nearly all of the effect of climate variation can be controlled through adaptation. Detailed, firm-level data allows for exploration of mechanisms, showing that vessels primarily adapt by timing entry into the fishery.