Ensemble and parameter uncertainty
Models are run across parameter sets and forcing ensembles; the spread is reported as the range, not collapsed to a mean.
GCRI · Water Nexus
Uncertainty quantification is what makes the evidence honest: every modelled value on this platform carries a range, a label and the assumptions behind it, so a decision-maker can see how much weight it bears.
Uncertainty quantification and model validation characterise how uncertainty in inputs, parameters and model structure affects predictions. They establish how much confidence a model’s outputs deserve. In water, climate and hazards and 重要インフラ, uncertainty quantification shows where risk estimates are robust and where they are fragile. It guides where better data or models would change decisions. The canonical description is on STEM Commons.
Models are run across parameter sets and forcing ensembles; the spread is reported as the range, not collapsed to a mean.
Uncertainty in inflow is carried into storage, generation, treatment and health effects, so the final range reflects every step.
Each value is labelled observed, published statistics, modelled, estimated, forecast or unknown, and the label travels with the value into every figure and table.
The sectors uncertainty quantification for water models touches and how strongly they depend on each other: what a study has to observe and model together.
署名
水とそのパートナー
水は食料に灌漑(0.8)を、エネルギーに冷却水と水力(0.6)を、生物多様性に環境流量(0.6)をもたらします。
W · E · I · F · H · B
Datasets and records used by uncertainty quantification and model validation on this platform, with the role each plays and the label its values carry. Sources are listed in 出典の登録簿.
| データ | 役割 | ラベル |
|---|---|---|
| Model ensembles | Spread and sensitivity | モデル化 |
| Observation error estimates | Input uncertainty | 推定 |
| 専門家の意見聴取 | Where no data exist | 推定 |
モデル、その仮定、データ、不確実性を、科学者やエンジニアが確認する形で示します。構造は公表された手法に従っています。描かれた値は例示であり、知見ではありません。
How far the outlook for uncertainty quantification for water models could spread, shown as ranges rather than a single line.
Predictive distributions are tested for calibration and sharpness against held-out observations. Verification confirms that code solves the intended equations.
| 確認 | 実施方法 |
|---|---|
| 感度分析 | The inputs that drive most of the output range are identified and reported |
| Calibration of probabilities | Stated probabilities are checked against outcomes where a record exists |
| Label audit | A sample of published values is traced back to the evidence behind its label |
Structural uncertainty and unknown unknowns are difficult to represent. Computational cost limits exploration of high-dimensional models.
Process explorer · Process
10 steps·4 段階
プロセス
In IPCC AR6 Working Group II, climate risk results from interactions between hazards and a system’s exposure and vulnerability, and responses can add risk.
外部の標準または手法の概要を、その公開情報源に基づいて示したものです。フレームワークが述べていることを説明するものであり、いかなる実施の記録でもありません。Nexus やいずれかのパートナーがあるステップを実施、認証、承認していることを示すものではありません。ゲートは手法のステップであり、Nexus による承認ではありません。
システム科学とモデリング stewards uncertainty quantification and model validation for the Consortium and reviews how it is applied across platforms.
報告書 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
個人データ、重要インフラの機微な詳細、共有する権利のないものは決して送らないでください。寄稿は利用前にレビューされます。送付によって著作者としての権利や編集上の権利が生じることはなく、スポンサーシップで調査結果を買うことは決してできません。
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