Well-known detection metrics based on Johnson criteria or Target Task Performance (TTP) models were developed for land-based targets [1,2]. In this paper we investigate how (whether) we can apply these metrics to especially recognition and identification of ships at sea. Large sea targets distinguish themselves from land-based targets by their large aspect ratio, when seen broad side, and their relatively large and hot plume. We shall only address the second of these two issues here. First, however, we shall investigate how the simple Johnson approach to recognition and identification stacks up against a TTP approach. The Johnson approach has clear and simple criteria to measure the target task performance. To apply the TTP model N50 (V50) values need to be found through observer trials. We avoid these trials here but estimate the criteria based on a comparison of the models. From analysis of LWIR and MWIR recordings of a multipurpose ship running outbound and inbound tracks, we find little difference between the two metrics. As mentioned, we study the effect of the plume on task performance ranges, by considering two different estimates for the target contrast: the average contrast and the root of the squares of this contrast and the standard deviation of the contrast. We argue that the plume skews the recognition and identification ranges to much too optimistic values when the standard deviation is included. In other words, although the plume helps to detect the target, it does not help the recognition or identification task. It seems a more careful definition of the temperature contrast needs to be applied when these models are used.