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Climate

vr.wm-ear-002 · wm-ear-002-climate

Climate normals, extremes and trends for a place or region over a reference period.

World Models Physical world and living systems PHY.EAR.CLI
Bundle → Layer → Finding → QuestionsClassifiersWhat it isWhy it existsDistinguishing featuresWhat robots and AI may and may not doMoral aspectsOwnersLinks to other meta-modelsIdentity and identifiersDirect propertiesRecognitionCapabilities and actionsHazards and failure modesStandards and interfacesContext of useSources

Bundle → Layer → Finding → Questions Filled

2 bundles · 3 layers · 6 findings · 12 questions

Observations Weather observations that feed climate records.

Observation record

Single observations with their place, time and method.

Observed value

A measured variable at a station or grid point and time.

  1. Which variable was observed, at which location and time, and in which unit?
  2. Which instrument and method produced the value?

Quality control

Flags and checks applied to the observation.

  1. Which quality flags apply to this value?
  2. Was the value corrected or homogenised, and by which procedure?
Climate state Statistics that describe climate over a period.

Normals and extremes

Reference-period statistics for a place or region.

Climate normal

An average of a variable over a stated reference period.

  1. Which reference period and how many years of data does the normal use?
  2. How many missing values were allowed in its calculation?

Recorded extreme

The highest or lowest value on record and its verification.

  1. Which extreme value is claimed, and on what date was it recorded?
  2. Has the extreme been verified by the responsible meteorological service?

Change and projection

Trends and modelled future states.

Trend or anomaly

A change against a baseline with its uncertainty.

  1. Against which baseline period is the anomaly or trend stated?
  2. What uncertainty range is given for it?

Projection

A modelled future state under a stated scenario.

  1. Which scenario, model ensemble and horizon does the projection use?
  2. Is the projection presented as a projection rather than a forecast?

Classifiers Filled

Family
World Models
Category
Physical world and living systems
Entry kind
standalone-mm
Navigation path
NAV.PHY.EAR.CLI
Domain
PHY.EAR.CLI
Industry
Cross-industry
Tags
climatephy.ear.cli
Also called
P4

What it is Filled

Climate is the statistical state of the atmosphere and connected systems at a place or region over a reference period, built up from weather observations. A single weather observation is a datum; a climate record is a summary such as a normal, an extreme or a trend over many years. Short-range weather events and their hazards belong to the weather and natural hazard models.

Why it exists Filled

Climate normals, extremes and trends for a place or region over a reference period.

Distinguishing features Filled

  • Describes long-term statistics over a reference period, not the weather at a moment.
  • A narrower model than the broad atmosphere, weather and climate subject, focused on observations and climate state.
  • Projections are conditional on scenarios and differ from weather forecasts.
  • Distinct from emission flows, which are causes recorded in their own model.

What robots and AI may and may not do Filled

Must not

  • Present a projection as a forecast or a certainty.
  • Compare values computed over different reference periods without saying so.
  • Alter or drop observations to fit an expected trend.
  • Present an unverified extreme as an official record.
  • Mix units or time zones without conversion and labelling.

Only with a human decision

  • Declaring an official climate record or extreme.
  • Using projections for decisions on safety-critical infrastructure.

May

  • Retrieve observations, normals and anomalies with their reference periods and units.
  • Compute summaries from quality-controlled data and state the method used.
  • Report uncertainty ranges with every trend or projection.
  • Point out gaps and inhomogeneities in a station record.

Moral aspects Filled

  • Climate information drives costly adaptation and policy choices, so its uncertainty must be stated honestly.
  • Regions with sparse observations are poorly represented, which can hide risks for vulnerable people.
  • Selective presentation of data can mislead the public in either direction.

Who is affected

  • People in climate-exposed regions
  • Public decision makers
  • Farmers, insurers and planners

Owners Filled

Steward

The national meteorological and hydrological service that keeps the official observation and climate record for its territory.

Master systems

  • National climate data archive
  • Global climate data centre

Links to other meta-models Filled

related

  • world-p4-atmosphere-weather-and-climate - The broader legacy model of atmosphere, weather and climate.

references

  • wm-ear-012-environmental-monitoring-station - Observations come from monitoring stations.
  • wm-dat-010-time-series-observation-collection - Climate records are built on observation time series.

What else AI and robots need to interact with it Filled

Identity and identifiers required Filled

  • Observations are identified by station identifier, variable, time and the producing network.
  • Gridded climate datasets are identified by dataset name, version and persistent identifier.
  • Normals are identified by station or region, variable and reference period.

Direct properties required Filled

  • Air temperature in degrees Celsius, with exposure height and averaging time stated.
  • Precipitation amount in millimetres per stated accumulation period.
  • Relative humidity in percent and atmospheric pressure in hectopascals, with station elevation stated.
  • Wind speed in metres per second and direction in degrees, with measurement height and averaging time.
  • Sunshine duration in hours and solar radiation in watts per square metre or joules per square metre.

Recognition required Filled

  • A climate record carries a variable, a location or region, a reference period and a statistic.
  • Often confused with a single weather observation, a forecast or a scenario-based projection.

Capabilities and actions required Filled

  • Can be aggregated over time and space and compared between periods.
  • Can be updated as new observations arrive and baselines are revised.

Hazards and failure modes required Filled

  • Wrong baselines or inhomogeneous series produce false trends.
  • Misread projections lead to under- or over-built adaptation.
  • Outdated normals understate current extremes.

Standards and interfaces required Filled

  • CF Metadata Conventions for gridded and station data in NetCDF.
  • WMO data exchange through the WMO Information System.
  • Climate normals and indices published by meteorological services.

Context of use required Filled

  • Used in planning, agriculture, insurance, energy and health.
  • Official climate statistics are produced by national meteorological services under WMO practice.

Sources Filled

  1. Guide to Climatological Practices (WMO-No. 100), World Meteorological Organization
  2. Sixth Assessment Report, Intergovernmental Panel on Climate Change
  3. NetCDF Climate and Forecast (CF) Metadata Conventions, CF community

Open questions

  • Planned model: boundary questions, research and every section remain to be written.

Machine files

Card as JSON Specification AGENTS.md Card backlog vercy.card/1

Provenance

planned (registry candidate) · todo

Built from: models/runtime-index.json, ver-cy/world-models/card-supplements/wm-ear-002-climate.json

Planned entry, hidden from the catalogue until researched.