Detection and attribution of change
Observed trends are compared with model simulations with and without human influence to judge whether a change is detectable and attributable, with confidence stated in calibrated language.
GCRI · 气候与灾害
Climate and atmospheric science is the core science this platform stewards for the network. It explains how energy, water and carbon move through the climate system, why extremes change as the world warms, and how confident each statement can be, using the assessed language of the IPCC.
Climate science studies the physical processes that govern the atmosphere, oceans, cryosphere and land surface over seasons to centuries. It provides the basis for understanding changes in hazard frequency and intensity that propagate through economic and social 系统. In climate and hazards and disaster and crisis, climate projections frame long-horizon scenarios for infrastructure, insurance, food systems and public finance. They allow correlated hazards across regions and sectors to be examined together. The canonical description is on STEM Commons.
Observed trends are compared with model simulations with and without human influence to judge whether a change is detectable and attributable, with confidence stated in calibrated language.
The probability or intensity of a specific event is compared between the current climate and a counterfactual without warming, using observations and models with documented protocols.
Models are evaluated on the physical processes that drive regional extremes, such as blocking or monsoon onset, before their projections are used.
来自 NASA GIBS 的全球日间地表热量、降雨和海洋热浪数据。每个图层都标注各自的日期。
交互式地图需要JavaScript;图层列表和来源见下文。
图层 3
本页的气候信号
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最新可用
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap贡献者 (ODbL) · Natural Earth
正在加载最新的NASA影像。
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气候信号,以全球为取景。NASA 发布的卫星和模型产品,各带自己的日期。它们是指标,而非对任何地点的评估。
图层与日期
Datasets and records used by climate and atmospheric science on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| ERA5 reanalysis | Consistent historical fields | 模型生成 |
| HadCRUT5 and other observational datasets | Observed temperature trends | 观测 |
| CMIP6 historical and natural-only experiments | Attribution counterfactuals | 模型生成 |
| Station records from national services | Local evaluation | 观测 |
团队遵循该方法时会使用的界面:其指标、状态与决策。名称为示例,数值仅作示意。
Climate and hazards · Climate science for hazards · Run R-3858
held-out period
| T+2 | 0.15 | 0.28 | 0.29 | Skilful |
| T+4 | 0.32 | 0.22 | 0.13 | Marginal |
| T+6 | 0.21 | 0.22 | 0.16 | Marginal |
| T+8 | 0.28 | 0.09 | 0.38 | Skilful |
Models are evaluated against observed climatology, historical trends and paleoclimate records. Multi-model comparison and process-based diagnostics expose structural differences.
| 核查 | 如何开展 |
|---|---|
| Multi-dataset comparison | Findings are tested against several observational products before they are described |
| Calibrated confidence | Statements carry IPCC-style confidence and likelihood terms tied to evidence and agreement |
| Model fitness | Models used for attribution must reproduce the relevant process and statistics in the historical period |
Projections depend on emission pathways and on parameterised processes such as clouds and convection. Regional detail and changes in rare extremes carry wide uncertainty.
两个存量,即压力和 适应能力,由一个增强的增长回路、一个延迟的平衡响应以及压力超过能力时产生的损害相连;越过阈值后,系统可能发生突变。这是使用明示示例数值的教学模型,不是预测。
控制措施
读数
| 年份 | 压力 | 能力 | 感知 |
|---|---|---|---|
| 0 | 20.0 | 50.0 | 20.0 |
| 4 | 23.3 | 44.9 | 21.2 |
| 8 | 27.2 | 42.2 | 24.0 |
| 12 | 31.7 | 42.3 | 27.7 |
| 16 | 36.8 | 45.5 | 32.2 |
| 20 | 42.3 | 51.5 | 37.2 |
| 24 | 47.9 | 60.3 | 42.6 |
| 28 | 53.2 | 71.3 | 48.0 |
| 32 | 57.8 | 84.3 | 53.1 |
| 36 | 66.4 | 98.4 | 58.4 |
| 40 | 82.7 | 115.9 | 69.7 |
| 44 | 97.8 | 139.7 | 83.8 |
| 48 | 109.1 | 169.4 | 97.3 |
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
贯穿六大支柱,由 Nexus Consortium 牵头
Assembled from the Nexus Standards area profile 气候风险标准: the hazards it names, the 系统 and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
灾害
控制措施
NS-0 章程与原则NS-1 维持社会运转的 UNI 与制品目录(语法 v0.2:领域、部门、区域和环境分段)NS-3 风险记录 UNI(语法、旧编码对照、分配机构)NS-3b 数据集与产品元数据规范(STAC、DCAT、PROV-O)NS-9 情境 UNI(部署、实例、计划实例)NS-11 验证与监测(证据、证明、零信任符合性观测)NS-14 符合性及与外部标准的对照NRS-H65 危害类别:超越行星边界(NHS-1 planet.boundary)NRS-H62 危害类别:复合与多危害事件(NHS-1 sys.compound)NRS-H71 危害类别:深时与宇宙灾难(NHS-1 planet.deep-time)NRS-H79 危害类别:精神卫生危机(NHS-1 health.mental)NRS-H75 危害类别:气候敏感性疾病(NHS-1 health.climate-sensitive)NRS-H7 危害类别:大尺度环流异常(NHS-1 atmo.climate-mode)观测
示例地理范围
Climate and Hazards stewards climate and atmospheric science for the Consortium and reviews how it is applied across platforms.
模型、其假设、数据和不确定性,以科学家或工程师会核查的形式呈现。结构遵循已发表的方法。所取数值仅为示意,不是研究发现。
How far the outlook for climate science for hazards could spread, shown as ranges rather than a single line.
报告 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.
切勿发送个人数据、敏感基础设施细节或您无权分享的任何内容。贡献在使用前会经过审查;发送贡献不赋予署名权或编辑权,赞助也绝不能换取研究结论。
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