In addition to showcasing displaying global RPSSs on the AI Weather Quest website, we perform automated regional forecast evaluations to provide model developers with insights into areas where forecasts may be underperforming. The regional forecast evaluation webpage should update on day 37 of the forecast workflow, once the AI Weather Quest leaderboards have been published.
The following sections are organised by competitive period (e.g., evaluation is being regularly performed to inform AI model developers of locations of forecast deficiency. The following section is divided into individual competitive periods, i.e. SON 2025 and DJF 2025/2026. For each competitive period, the same analysis has been performed). The same analysis is applied for each period. Please note, that these webpages are an area of dynamic represent a dynamic, continuously updated forecast evaluation and . Content will regularly change throughout the Quest.
Format of individual periodic pages
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change as new data and forecast initialisations become available.
Structure of regional forecast analysis
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pages
Introduction
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Each page begins with an introduction that specifies the competitive period under review. It also highlights the forecast initializations used to compute the model evaluation.
Regional skill score files
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Excel spreadsheets provide all regional skill scores for every submission to the AI Weather Quest, enabling detailed comparison of performance across regions.
Top 10 team tables
Tables
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summarise regional, variable-averaged RPSSs for the teams with the top 10 global, period-aggregated
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RPSSs. Scores are presented for two forecast windows
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: days
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19–25 and days 26–32.
Aggregated RPSS figures
For the highest-performing model from the top 10 teams
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, figures show global maps
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of aggregated
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RPSSs
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for each variable and forecast window. Note that during the early stages of
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a competitive period, only a
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limited number of forecast initializations may be available to compute grid-point values.
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