GCRI · 气候与灾害
气候基线
Every statement about a changing climate or an unusual event is a comparison with a baseline: a reference period of observed weather, averaged and described. Baselines come from station records, satellites and reanalyses, each with gaps and biases. This page sets out how baselines are built, why the choice of period and dataset matters, and what evidence they serve for the institutions that plan against today’s climate and tomorrow’s.
Climate baselines: how the risk develops.
Historical trends and reference periods. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Reference periods move
Climate normals are averages over a fixed thirty-year period. As the climate warms, a recent normal makes today’s extremes look less unusual than an earlier one would, so the period must always be stated.
Stations are unevenly spread
Long station records cluster in wealthier, populated and low-lying places. Mountains, oceans, deserts and much of Africa are sparsely observed, so gridded products interpolate or model across large gaps.
Reanalysis blends model and observation
Reanalyses run a weather model through the past, constrained by every available observation. They give complete, consistent fields, but where observations are few the model’s own biases dominate.
Records need homogenising
Station moves, new instruments and urban growth create jumps in records that are not climate. Homogenisation detects and adjusts them, and the adjustments must be documented to be trusted.
全球气候信号。
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
关于本图层
- 证据
- 观测（持续云层仍会造成缺口）
- 来源
- VIIRS NOAA-20 Level 3，8 天（NASA LANCE）
- 提供方
- NASA LANCE
- 许可协议
- NASA 开放数据
- 年份版本
- 8 天；卫星 8 天合成；持续云层仍会造成缺口
- 构建时的最新内容
- 2026-09-14
- 处理结果
- 约 1 公里网格
- 不确定性
- 截至所示日期的 8 天内地表的卫星皮肤温度，是高温风险暴露指标；不是气温、热指数，也不是高温预警。
- 经由以下途径到达
- gibs.earthdata.nasa.gov，仅在您允许实时地图后访问
关于本图层
- 证据
- 估计值
- 来源
- GPM IMERG（NASA GES DISC）
- 提供方
- NASA GES DISC
- 许可协议
- NASA 开放数据
- 年份版本
- 每日；近实时卫星估算
- 构建时的最新内容
- 2026-10-12
- 处理结果
- 约 2 公里网格
- 不确定性
- 近实时卫星估算。卫星或模型栅格数据，按提供方发布的原样呈现。云层、条带缺口和反演误差会造成缺口和噪声；数值是指标，而非某地的测量值。
- 经由以下途径到达
- gibs.earthdata.nasa.gov，仅在您允许实时地图后访问
关于本图层
关于本图层
- 证据
- 观测
- 来源
- VIIRS NOAA-20 校正反射率（NASA LANCE）
- 提供方
- NASA LANCE
- 许可协议
- NASA 开放数据
- 年份版本
- 每日；卫星图像
- 构建时的最新内容
- 2026-10-14
- 处理结果
- 约 250 米网格
- 不确定性
- 卫星图像。卫星或模型栅格数据，按提供方发布的原样呈现。云层、条带缺口和反演误差会造成缺口和噪声；数值是指标，而非某地的测量值。
- 经由以下途径到达
- gibs.earthdata.nasa.gov，仅在您允许实时地图后访问
关于本图层
- 证据
- 模型生成（GIBS 发布的最新年份）
- 来源
- MODIS Terra 和 Aqua 土地覆盖（MCD12Q1）（NASA LP DAAC）
- 提供方
- NASA LP DAAC
- 许可协议
- NASA 开放数据
- 年份版本
- 每年；卫星分类；GIBS 发布的最新年份
- 构建时的最新内容
- 2024-01-01
- 处理结果
- 约 500 米网格
- 不确定性
- 所示年份的卫星土地覆盖类别，含农田；该分类存在已知误差，并非农场登记册。
- 经由以下途径到达
- gibs.earthdata.nasa.gov，仅在您允许实时地图后访问
关于本图层
- 证据
- 观测
- 来源
- GHRSST MUR（NASA JPL PO.DAAC）
- 提供方
- NASA JPL PO.DAAC
- 许可协议
- NASA 开放数据
- 年份版本
- 每日；卫星分析
- 构建时的最新内容
- 2026-10-12
- 处理结果
- 约 1 公里网格
- 不确定性
- 卫星分析。按提供方发布形式呈现的卫星或模型栅格。云层、扫描带间隙和反演误差会造成缺口和噪声；数值是指标，而非某一地点的实测值。
- 经由以下途径到达
- gibs.earthdata.nasa.gov，仅在您允许实时地图后访问
键盘操作，地图获得焦点时
按住 Ctrl 或 ⌘ 并滚动以缩放
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。
拖动以移动。按住 Ctrl 或 ⌘ 并滚动、双指缩放或使用按钮缩放；悬停可查看指针下的数值；重置可返回该区域。
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。
数据：NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap 贡献者 · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERT · NASA AIRS来源与许可
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
- We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA 开放数据
- VIIRS 近实时产品（洪水、地表温度、积雪覆盖、校正反射率），NASA LANCE；影像来自 NASA GIBS。颜色依据已发布的色标重绘；显示处的数值已按六边形网格平均（经修改）。 NASA 开放数据
- GPM IMERG 降水，NASA 降水处理系统；由 NASA 戈达德地球科学数据和信息服务中心（GES DISC）分发；影像来自 NASA GIBS。颜色依据已发布的色标重绘；显示处的数值已按六边形网格平均（经修改）。 NASA 开放数据
- GHRSST Level 4 MUR 分析，NASA 喷气推进实验室；由 NASA 物理海洋学 DAAC（PO.DAAC）分发；影像来自 NASA GIBS。颜色依据已发布的色标重绘；显示处的数值已按六边形网格平均（经修改）。 NASA 开放数据
- MODIS 陆地产品（植被指数、总初级生产力、土地覆盖），NASA LP DAAC 和 LANCE；影像来自 NASA GIBS。颜色依据已发布的色标重绘；显示处的数值已按六边形网格平均（经修改）。 NASA 开放数据
- ASTER GDEM 是 METI 和 NASA 的产品（ASTER Global Digital Elevation Model V003，NASA LP DAAC）；影像来自 NASA GIBS。颜色依据已发布的色标重绘；显示处的数值已按六边形网格平均（经修改）。引用格式：NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA 开放数据
- 使用 Natural Earth 制作。免费矢量和栅格地图数据，见 naturalearthdata.com。 公有领域
- © OpenStreetMap 贡献者（ODbL），经由 NASA GIBS（海岸线、边界、道路和地名）。颜色依据已发布的色标重绘；显示处的数值已按六边形网格平均（经修改）。 ODbL
- Blue Marble，NASA Earth Observatory；影像来自 NASA GIBS。颜色依据已发布的色标重绘；显示处的数值已按六边形网格平均（经修改）。 NASA 开放数据
- 地球仪和平面地图上的背景信息：海岸线、边界、道路和地名来自 NASA GIBS 参考图层（OpenStreetMap 数据，ODbL，© OpenStreetMap contributors）；Blue Marble 影像可作为可选底图；3D 地形和高程读数来自 ASTER GDEM 高程色彩指数（5 m 至 200 m 分级，为便于辨识而作了夸张处理）。边界按已发布的样式绘制，不代表对任何领土的立场。
- 实时事件：NASA Earth Observatory Natural Event Tracker（EONET）；事件仅供参考，并保留其原始来源链接。
- 实时：NASA EONET。事件仅供参考，不是主管机构的预警。
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- Observed (EO): NASA AIRS. We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
- 空气质量预报，5 天，PM2.5（CAMS，经由 Open-Meteo）：包含经修改的 Copernicus 大气监测服务 2026 年信息。
- 过去一年的每日气温（ERA5，经由 Open-Meteo）：包含经修改的 Copernicus 气候变化服务 2026 年信息。
- 过去一年的每日气温和日照（NASA POWER）：这些数据来自 NASA 兰利研究中心（LaRC）POWER 项目，该项目由 NASA 地球科学/应用科学计划资助。
- 天气数据来自 Open-Meteo.com (https://open-meteo.com/), 依据 CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). 授权。
- Optional layers (22 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.
图层与日期
- 地表温度，日间，8 天合成：VIIRS NOAA-20 3 级产品，8 天，NASA LANCE · 2026年9月14日
- 降水率，日均值：GPM IMERG，NASA GES DISC · 2026年10月12日
- 海面温度距平：GHRSST MUR25，NASA JPL PO.DAAC · 2026年10月12日
- 真彩色：VIIRS NOAA-20 校正反射率，NASA LANCE · 2026年10月13日
- 土地覆盖类型（IGBP），年度：MODIS Terra 和 Aqua 土地覆盖（MCD12Q1），NASA LP DAAC · 2024
- 海冰密集度：GHRSST MUR，NASA JPL PO.DAAC · 2026年10月12日
A baseline is the reference every domain measures change against.
- 水耦合Rainfall and evaporation normals set expected water availability.What to watchNormals period stated with each anomaly
- 食品耦合Crop calendars and suitability rest on temperature and rainfall baselines.What to watchGrowing season shifts
- 能源耦合Degree-day baselines set heating and cooling demand.What to watchDegree days against the reference period
Baseline datasets are designed for the Observatory Signal 系列. WMO recommends the 1991–2020 normals for operational use and keeps 1961–1990 for long-term change; every anomaly states its reference period and would carry NS-3b metadata under the proposed Nexus Standards.
- Digitised station records that lengthen local baselines.
- Homogenisation notes for station series.
多灾种展望。
团队跟踪该主题时会使用的界面：其指标、状态与决策。名称为示例，数值仅作示意。
衡量什么，以及衡量得如何。
每个指标都注明其单位、频率、背后的来源类型以及数值将附带的证据标签。此处不显示数值：数值由计划依据其自身权限提供。
| 指标 | 单位 | 节奏 | 来源类型 | 标签 |
|---|---|---|---|---|
| Temperature anomaly | degrees Celsius against a stated reference period | 每月 | Station and gridded observations | 观测 |
| Precipitation anomaly | percent of reference-period mean | 每月 | Gauge and satellite precipitation products | 观测 |
| Station record completeness | percent of days with valid observations | 年度 | National station networks | 观测 |
| Reanalysis temperature | degrees Celsius | hourly | Global reanalysis | 模型生成 |
| Observing network density | stations per ten thousand square kilometres | 年度 | WMO observing system records | 已发布统计 |
| Homogenisation adjustments applied | count of breakpoints adjusted | 每次发布 | Dataset documentation | 已报告 |
存量、流量、延迟和一个临界阈值。
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
- 压力增长
- 每年 6.0%
- 能力在降低压力方面的效力
- 每年 4.0%
- 对感知压力的投资响应
- 20%
- 感知延迟
- 4.0 年
- 压力的临界阈值
- 60 项指数
- 越过阈值后的放大
- 2.0 倍
- 模拟年数
- 50 年
读数
- 峰值压力
- 113 指数
- 期末能力
- 186 指数
- 超过阈值的年数
- 15.8 年
数字、方法与来源
| 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 |
方法
- 系统动力学 Forrester (1961), Industrial Dynamics, MIT Press; Sterman (2000), Business Dynamics
- 临界转变与临界点 Scheffer and others (2009), Early-warning signals for critical transitions, Nature 461
- 因果回路图 Sterman (2000), Business Dynamics, McGraw-Hill
- 不确定性扇形图（参数蒙特卡罗） Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- 单因素敏感性（龙卷风图） Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
数据
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
- 实验 实验室
- 构建于 Foundry 中的气候与灾害
- 检验地点 Universe 中的气候与灾害
- 编入 Standards 中的气候与地球系统
- 发表于 Reports 中的气候与灾害
- 授课于 Academy 中的地球与环境科学学院
证据来自何处。
具名公共数据集与机构记录，各自注明许可类别。依协议获得的来源仅按其条款使用，绝不再次发布。
| 来源 | 它提供什么 | 许可类别 |
|---|---|---|
| ERA5 reanalysis (Copernicus 气候变化 Service, ECMWF) | Hourly global atmospheric, land and ocean fields from the mid-twentieth century | Free and open with attribution, Copernicus licence (to check current terms) |
| NOAA Global Historical Climatology Network daily (GHCN-Daily) | Daily station temperature and precipitation worldwide | Public domain, US government data |
| HadCRUT5 (Met Office Hadley Centre and University of East Anglia) | Global gridded surface temperature anomalies with uncertainty ensemble | 开放政府许可 |
| Berkeley Earth surface temperature | Gridded land and ocean temperature series | Open, CC BY-NC 4.0 |
| GPCC precipitation (Deutscher Wetterdienst) | Gridded gauge-based precipitation over land | Free with attribution, DWD terms (to check) |
| CHIRPS (Climate Hazards Center, UC Santa Barbara) | Blended satellite and station rainfall for the tropics and subtropics | Open, licence to check |
Model climate baselines as a system. Run the cascade.
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
- 海平面上升
- Coastal flood （在下游引发）
- 风暴潮 （在下游引发）
- High-tide flooding (set off downstream)
- Coastal erosion (set off downstream)
- Saltwater intrusion (set off downstream)
- Estuary flood (set off downstream)
- Coastal habitat squeeze (set off downstream)
- Wetland loss (set off downstream)
- Mangrove loss (set off downstream)
- Groundwater flood (set off downstream)
- Climate-driven migration and relocation (set off downstream)
- 大规模流离失所（在下游引发）
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
- ERA5 再分析（Copernicus Climate Data Store）（仅列作参考）
- CMIP6 气候预估（Copernicus Climate Data Store）（仅列作参考）
- NGFS Scenario Explorer（仅列作参考）
- INFORM Risk Index（仅列作参考）
- 每100,000人中因灾害死亡、失踪和直接受影响的人数
- Total greenhouse gas emissions per year
- 灾害造成的直接经济损失与全球国内生产总值之比
示例地理范围
- 太平洋岛国：150 个六边形网格
- 今夜夜间灯光与停电（VIIRS 昼夜波段），NASA GIBS
- 穿透云层的地表水，30 m（OPERA DSWx-S1 雷达），NASA GIBS
- 过去半小时降雨率（IMERG），NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
由谁决定，以及证据服务于什么。
Climate and Hazards prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| 谁来决定 | 问题 | 本页面服务的证据 |
|---|---|---|
| National meteorological and hydrological services | Which reference period and products to publish as the national baseline | Product comparisons; station completeness; homogenisation records |
| Infrastructure and building standards bodies | Which climate values to use as design inputs | Baselines with periods and uncertainty stated |
| Ministries of environment and planning | Where observing networks need strengthening | Station density and gap maps |
该主题产生的产出
- Baseline climatologies with reference period and dataset stated
- Comparisons of observational products for a region, with spread shown
- Station network gap maps for national services
- Anomaly series labelled by evidence class
How climate baselines is modelled, measured and tested.
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。
不确定性区间
How far the outlook for climate baselines could spread, shown as ranges rather than a single line.
- 中心估计值
- 集合的中位数
- 范围
- IPCC 校准用语中的“可能”和“很可能”
- 集合
- 明示成员、情景和初始条件
- 配合阅读
- 结果对每项输入的敏感性
专家提出的问题。
Baseline questions concern the record and the reference.
- How long and how reliable is the observational record at a given place?
- Which reference period is being used, and does it already include warming?
- How have the mean and the extremes of temperature, rainfall and other variables changed?
- How much of an observed change can be attributed to human influence rather than natural variability?
- Is the past still a sound guide to design and planning?
机制与驱动因素。
Climate varies naturally from year to year and decade to decade, through phenomena such as El Niño and the Southern Oscillation. A baseline must be long enough to average over that variability, which is why multi-decade reference periods are used. When the climate is warming, however, a recent baseline already includes part of the change, and an older baseline may understate the conditions people now experience.
Extremes can change faster than averages: a modest shift in the mean temperature can make formerly rare hot extremes much more common, because the tail of the distribution moves. Changes in measurement, such as relocated stations, new instruments or urban growth around a site, can introduce artificial trends that must be identified and corrected.
如何研究，以及方法止于何处。
| 方法或数据 | 显示内容 | 局限 |
|---|---|---|
| Station records | Long local histories of temperature, rainfall and wind | Gaps, relocations and instrument changes require homogenisation |
| Gridded observational datasets | Consistent coverage across regions | Sparse stations in many regions mean values are interpolated |
| 再分析 | Physically consistent reconstructions of past weather | Model-dependent, especially where observations are sparse |
| Satellite records | Global coverage of many variables | Records are relatively short and need calibration across missions |
| Detection and attribution studies | Whether change exceeds natural variability and why | Depend on models and on the framing of the question |
Where this page’s references lead.
阅读本页时所对照的机构和文件。状态和版本会变化；每个链接都指向发布机构。
问题与解答。
What is a climate normal?
What is a reanalysis?
Why do temperature datasets disagree?
Why do different reports use different baselines?
Is the historical record still useful?
Does the platform publish climate normals?
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