This page visualizes the forecasts and forecast performance for the focal target variables.
Most recent forecasts
Forecasts submitted on 2024-05-17
{r} # if("IceCover_binary_max" %in% unique(df$variable)){ # # ggobj_df <- df |> # filter(variable == c("IceCover_binary_max")) |> # mutate(observation = as.numeric(NA)) # # if(nrow(ggobj_df) > 0){ # # ggobj <- ggobj_df |> # ggplot(aes(x = datetime, y = mean, color = model_id)) + # geom_line_interactive(aes(datetime, mean, col = model_id, # tooltip = model_id, data_id = model_id), # show.legend=FALSE) + # facet_wrap(~site_id) + # ylim(0,1) + # labs(y = "Predicted probability") + # theme_bw() # # girafe(ggobj = ggobj, # width_svg = 8, height_svg = 4, # options = list( # opts_hover_inv(css = "opacity:0.20;"), # opts_hover(css = "stroke-width:2;"), # opts_zoom(max = 4) # )) # } # } #
Forecast analysis
Below are forecasts submitted 30 days ago and include the observations used to evaluate them (black points). Mouse over the figure to see the team id, and scroll to zoom.
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Aggregated scores
Average skill scores of each model are shown for each target variable, aggregated across model (top), time of year (middle), and forecast horizon (bottom). The evaluation metrics being used here are Continuous Ranked Probability Score (CRPS) and log score (logs).
Scores are shown by reference date and forecast horizon (in days).
Scores are averaged across all submissions of the model with a given horizon or a given reference_datetime
using submissions made since 2024-04-17.