Vivek Srikrishnan
@vsrikrish.bsky.social did:plc:io6uw55e2r7fmltqysfpupjw
Climate uncertainty and risk. Decision-making under deep uncertainty. Assistant Professor, Cornell Biological & Environmental Engineering. Cat caretaker, Tottenham and the Knicks until they kill me. https://viveks.me
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Vivek Srikrishnan (@vsrikrish.bsky.social) es un usuario de Bluesky que se unió el 6 noviembre 2024. Tiene 392 seguidores, sigue a 309 cuentas y ha publicado 398 posts.
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3. Striving to parsimoniously model core dynamic with as few assumptions and uncertain parameters as possible. This minimizes thumbs-on-scales opportunities and facilitates model auditing. 4. Including sensitivity analyses that vary assumptions or input data and show how model outputs respond.
Ver postWhat does transparencly look like? In my view: 1. Clearly explaining the model structure (ie, the equations that link assumptions A to conclusions C) and the assumptions it entails. 2. Clearly enumerating the input data and discussing the associated uncertainties.
Ver postDoes this mean that all energy modeling is useless, untrustworthy? I don't think so. However, I do think that it places a very high responsibility on modelers to be as transparent as possible about their assumptions and their potential influence on their conclusions.
Ver postThis process is VERY SUSCEPTIBLE to thumbs on scales. Any energy modeler who claims otherwise is lying to you. The larger and more complex the model is, the more opportunities there are to tweak assumptions in A such that conclusions in C support the modelers' ideological or political goals.
Ver postInstead, we use intuition and discussion with other experts to come up with plausible assumptions. We plug them into A, run the model, derive conclusions C, and check whether the conclusions make sense. If they don't, we go back, tweak the assumptions, repeat. This is the process of energy modeling.
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