payload: {"action":"created","issue":{"url":"https://api.github.com/repos/bradyrx/climpred/issues/96","repository_url":"https://api.github.com/repos/bradyrx/climpred","labels_url":"https://api.github.com/repos/bradyrx/climpred/issues/96/labels{/name}","comments_url":"https://api.github.com/repos/bradyrx/climpred/issues/96/comments","events_url":"https://api.github.com/repos/bradyrx/climpred/issues/96/events","html_url":"https://github.com/bradyrx/climpred/issues/96","id":437784566,"node_id":"MDU6SXNzdWU0Mzc3ODQ1NjY=","number":96,"title":"Keyword for how to treat lead year 1","user":{"login":"bradyrx","id":8881170,"node_id":"MDQ6VXNlcjg4ODExNzA=","avatar_url":"https://avatars0.githubusercontent.com/u/8881170?v=4","gravatar_id":"","url":"https://api.github.com/users/bradyrx","html_url":"https://github.com/bradyrx","followers_url":"https://api.github.com/users/bradyrx/followers","following_url":"https://api.github.com/users/bradyrx/following{/other_user}","gists_url":"https://api.github.com/users/bradyrx/gists{/gist_id}","starred_url":"https://api.github.com/users/bradyrx/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/bradyrx/subscriptions","organizations_url":"https://api.github.com/users/bradyrx/orgs","repos_url":"https://api.github.com/users/bradyrx/repos","events_url":"https://api.github.com/users/bradyrx/events{/privacy}","received_events_url":"https://api.github.com/users/bradyrx/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2019-04-26T18:03:18Z","updated_at":"2019-04-26T18:36:50Z","closed_at":null,"author_association":"OWNER","body":"Currently, `compute_reference` treats the lead year 1 forecast as a lag-0 correlation between the initialized ensemble and reference product. This is because it was built originally for CESM-DPLE annual averages. The first time step of DPLE is the annual average following the November initialization.\r\n\r\nhttps://github.com/bradyrx/climpred/blob/98082c68223ad88508db7587b5246cecb3eaf262/climpred/prediction.py#L777\r\n\r\nFor monthly/seasonal resolution (https://github.com/bradyrx/climpred/issues/44) and probably most annual ensembles, this isn't the case. As we address #44, we should figure out how to implement a keyword in `compute_reference` that determines whether it starts at lag-0 or lag-1 (and it should probably default to the latter).\r\n"},"comment":{"url":"https://api.github.com/repos/bradyrx/climpred/issues/comments/487159072","html_url":"https://github.com/bradyrx/climpred/issues/96#issuecomment-487159072","issue_url":"https://api.github.com/repos/bradyrx/climpred/issues/96","id":487159072,"node_id":"MDEyOklzc3VlQ29tbWVudDQ4NzE1OTA3Mg==","user":{"login":"aaronspring","id":12237157,"node_id":"MDQ6VXNlcjEyMjM3MTU3","avatar_url":"https://avatars0.githubusercontent.com/u/12237157?v=4","gravatar_id":"","url":"https://api.github.com/users/aaronspring","html_url":"https://github.com/aaronspring","followers_url":"https://api.github.com/users/aaronspring/followers","following_url":"https://api.github.com/users/aaronspring/following{/other_user}","gists_url":"https://api.github.com/users/aaronspring/gists{/gist_id}","starred_url":"https://api.github.com/users/aaronspring/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/aaronspring/subscriptions","organizations_url":"https://api.github.com/users/aaronspring/orgs","repos_url":"https://api.github.com/users/aaronspring/repos","events_url":"https://api.github.com/users/aaronspring/events{/privacy}","received_events_url":"https://api.github.com/users/aaronspring/received_events","type":"User","site_admin":false},"created_at":"2019-04-26T18:36:50Z","updated_at":"2019-04-26T18:36:50Z","author_association":"COLLABORATOR","body":"I don't get it. Is it about the result? Whether skill.isel(time=0) will be 1 (perfect forecast) or whether it will be skill(time=first after initialization)?\r\n\r\nI probably dont get your point now. I just want to mention that we cannot put keywords for all cases and try to see whether this can be avoided with smartly designed input files. Predictions will never run totally out of the box."}}
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