Cold Stunning CRPS model ‐ Meeting notes - conrad-blucher-institute/semaphore GitHub Wiki

Jeret Presentation Notes: CRPS_and_NLL_Experiments_Details.pptx CRPS and NLL Experiments -> Title CRPS -> Continuously ranked probability score NLL -> Negative Log Likelihood ^ Use two different activation functions 1 CRPS Model = 10 members = 10 Keras Files 1 NLL Ensemble Model = 30 Members = 30 Keras Files What Makes members a part of a certain ensemble model? Each member for the ensemble model has the same architecture (code, activation function, loss function, same inputs) and the difference is the random weights and biases from the model training. Each ensemble model is for one time stamp. Inputs: 24Hrs of water temp and air temp current to past Predicted air temperature with the same number as the lead time Is this also TWC stuff… -> more clarification on this Ordering: It SEEMS everything is in ascending order.. We have requested that they double check CRPS outputs 100 predictions per member NLL output 1 prediction per member (cold stunning team’s slide more detailed) Dr. Tissot Notes: Input vector set rather than ensemble input? Distribution of input vector! Since this denotes the togetherness of the input vector. We perhaps need to come up with more terminology for these things (100 outputs, etc) for discussion and also for how we store them in the database. Will need to support providing more than one .keras file for one dspec. Ensemble group id and member group id? To change database architecture or to store the output in one long row Two different output tables one with the longer string for the ensemble outputs Is that worth it or do it how we normally do it and then Do a report on the projected DB growth Miss Tissot thinks we need to stick with if we run a single model single row output SO 30 members would have 30 rows in the database. Something we would want to do is be able to identify if this model run was a part of something, an ensemble run? Etc. Miss Tissot is also wondering if we should calculate and store some of the calculated values based on the model outputs to be stored in the semaphore database Storing raw and post processed predictions CRPS uses a cron job to calculate the kinds of post processing that the cold stunning team wants, stored in semaphore database so that Flare isn’t doing too much work when querying data from semaphore. There might be a way we can triggers this like right after the models run and or smth etc.

Dr. Tissot’s dream is to have the spaghetti, the ribbon, and the box plot for this model. But unsure if the spaghetti diagram would be too visually busy with the way these models work. Leaning towards the CRPS model unless there are big advantages to the NLL in semaphore implementation. Cold stunning might have specifications for the visualization of the data visa via color, etc. Transfer to flare what’s needed to do a box plot Dr. Tissot will continue to think about the spaghetti