GCRI · Energy Nexus
Heat and cooling
Heat waves raise electricity demand for cooling at the same time as they lower what the system can supply: lines carry less, thermal plants lose efficiency and cooling water, and solar panels produce less per unit of sunlight. Cold spells do the same to heating demand and gas supply. This page sets out how temperature extremes stress energy systems, how cooling access shapes health risk, and what evidence operators, health agencies and planners use.
Heat and cooling on the record.
Heat and cooling: how the risk develops.
Cooling requirements and extreme heat. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Demand rises with temperature
Cooling demand climbs steeply above a comfort threshold, and electric heating does the same in cold spells. Summer peaks arrive in the late afternoon and evening, when solar output is already falling and the grid leans on other resources.
Supply falls with temperature
Overhead lines sag and must be derated, transformers overheat, and thermal plants lose output or are curtailed when river water exceeds discharge temperature limits. In cold extremes, gas wells, pipelines and plant equipment can freeze.
Coincident stress
A heat dome raises demand across a whole region and its neighbours at once, so imports are scarce exactly when they are needed. Wildfire risk in the same days may force operators to de-energise lines preventively.
Cooling is a health service
Where air conditioning is the main protection against heat illness, an outage during a heat wave becomes a public health emergency. Older people, those living alone and households without cooling carry most of the risk.
Climate signals in Europe.
Daytime surface heat, night-time surface heat and rain over Europe, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Climate signals, for this page
About this layer
- Evidence
- Observed (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground at night, when lack of cooling matters for health; not air temperature or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- GPM IMERG (NASA GES DISC)
- Provider
- NASA GES DISC
- Licence
- NASA open data
- Vintage
- daily; Satellite estimate, near real time
- Newest at build
- 2026-10-12
- Resolution
- about 2 km grid
- Uncertainty
- Satellite estimate, near real time. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- GHRSST MUR25 (NASA JPL PO.DAAC)
- Provider
- NASA JPL PO.DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite analysis
- Newest at build
- 2026-10-12
- Resolution
- about 2 km grid
- Uncertainty
- Satellite analysis of how far sea temperature departs from its usual value for the date shown; a marine heat indicator, not a coral bleaching alert.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
Climate signals, framed on Europe.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA JPL OPERA DIST-ALERT · NASA AIRSSources and licences
- 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 open data
- 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 open data
- VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- GHRSST Level 4 MUR analyses, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: 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 open data
- Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
- © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- 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).
- Air quality forecast, 5 days, PM2.5 (CAMS via Open-Meteo): Contains modified Copernicus Atmosphere Monitoring Service information 2026.
- Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- 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.
Layers and dates
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- Land surface temperature, night, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
- True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
- Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Sea surface temperature anomaly: GHRSST MUR25, NASA JPL PO.DAAC · 12 Oct 2026
Heat raises cooling demand just as it weakens the systems that supply it.
| Domain | How it couples here | What to watch |
|---|---|---|
| Health | Cooling protects people during heatwaves; loss of power during heat is a direct health risk. See environmental health. | Heat-health warnings coinciding with grid stress |
| Water | Hot rivers limit cooling of thermal plants exactly when demand peaks. | River temperature at plant intakes |
| Food | Refrigeration keeps food safe; heat raises cold chain load. See storage and cold chain. | Cold store energy use in heatwaves |
| Biodiversity | Refrigerants with high warming potential are being phased down under the Kigali Amendment. | Refrigerant transition in national plans |
Cooling demand is estimated from cooling degree days (degree Celsius days above a base temperature) and appliance ownership. The IEA’s The Future of Cooling (2018) and UNEP’s Global Cooling Watch (2023) describe how fast demand is growing and how efficiency and passive design can limit it.
Model heat and cooling as a system. Run the cascade.
Assembled from the Nexus Standards area profile Energy risk standards: the hazards it names, the systems 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.
Hazards
- Heatwave
- Windstorm
- Widespread power outage (set off downstream)
- Large forest disturbance (set off downstream)
- Wildfire (set off downstream)
- Extreme fire weather (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
- Flash drought (set off downstream)
- Snow drought (set off downstream)
- Ground-level ozone episode (set off downstream)
- Meteorological drought (set off downstream)
- Extreme night-time heat (set off downstream)
- Lake and river heatwave (set off downstream)
- Cooling-water curtailment of power plants (set off downstream)
- Heat-induced track buckling (set off downstream)
- Shoreline ice shove (set off downstream)
- Seiche (set off downstream)
Systems and couplings
- Energy risk standards
- Water risk standards Common driver
- Critical infrastructure and critical entities Cascade
- Climate risk standards Feedback
- Space weather, spectrum and timing risk standards Common driver
Controls
NS-0Constitution and principlesNS-1The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H84Hazard family: Energy system instability and shortfall (NHS-1 infra.energy)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-U8Universe platform profile: Energy NexusNRS-H48Hazard family: Utility and communication network outage (NHS-1 infra.utilities)NRS-H109Hazard family: Energy-transition technology failures (NHS-1 tech.energy-transition)NRS-H54Hazard family: Signal and platform disruption (NHS-1 cyber.platform)
Observation
- Global Power Plant Database (listed for reference)
- NASA Black Marble night-time lights (VNP46) (listed for reference)
- Ember electricity data (listed for reference)
- ENTSO-E Transparency Platform (listed for reference)
- EIA Open Data API (listed for reference)
- Proportion of population with access to electricity
- Renewable energy share in total final energy consumption
- Number of disruptions to basic services attributed to disasters
- Damage to critical infrastructure attributed to disasters
Example geography
- Europe: 113 hexagonal cells
- Surface air temperature, daytime (AIRS), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
Heat and cooling evidence.
Heat-season stress tests across power, water and health are designed for the Scenario and Stress-Test series. Contributions that help: hourly demand during past heatwaves, building and cooling access surveys, and city cooling plans with their results.
Coupled risk, applied response.
The sectors heatwave touches and how strongly they depend on each other: what a study has to observe and model together.
Choose a context
Sectors · HeatwaveStress
Pillars · HeatwaveKPI
In this contextDependence or handoff, heavier is strongerOutside this context
Programme yearAll phases
Context
Heatwave
Cooling demand peaks the grid while rivers warm; heat stress fills hospitals and wilts crops.
W · E · I · F · H · B
Risk
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.43 share of total
Hover a corner, a line or a row to trace it across both sides.
Route
Applied to heatwave
L · F · U · S · R · A
Response
- Pillars
- 4 of 6
- Handoffs
- 10 of 18
- Loops
- 5 closed
Expected value
- What is at stake
- –no published benchmark
- Return on resilience
- –no published benchmark
- Avoided loss
- 1,190deaths avoided a yearHess et al., J. Environ. Public Health, 2018
Hover a pillar, a line or a row to read how it is applied.
A: a teaching cascade (shock 0.6, gain 0.35, four rounds) over teaching values for a typical city-region, not measurements. B: illustrative applications and the KPI each pillar answers for; values are published benchmarks, cited, not forecasts. Open events: NASA EONET, live.
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Cooling and heating degree days | degree days | daily and annual | Reanalysis and station temperature | OBSERVED |
| Peak demand sensitivity to temperature | megawatts per degree Celsius | seasonal | Operator load records and weather | ESTIMATED |
| Overhead line derating | percent of nominal rating | hourly | Operator dynamic line rating | MODELLED |
| Thermal plant curtailment for cooling water | megawatts; hours | per event | Plant and operator notifications | REPORTED |
| Household access to cooling | percent of households | periodic survey | Household surveys | ESTIMATED |
| Universal thermal climate index | degrees Celsius | hourly | Reanalysis-derived heat stress | MODELLED |
| Heat-related emergency admissions during outages | admissions | per event | Health surveillance linked to outage records | REPORTED |
How heat and cooling is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
System model
The couplings between the systems in heat and cooling: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| ERA5 and ERA5-HEAT (Copernicus) | Hourly temperature and thermal comfort indices worldwide | Free and open, attribution |
| Eurostat cooling and heating degree days | Degree days by country and region | Free reuse, attribution |
| ENTSO-E and EIA hourly demand data | Load records to estimate temperature sensitivity | ENTSO-E terms; public domain |
| ENTSO-E unavailability of generation units | Notified outages and derating of thermal plants | Free, registration, ENTSO-E terms |
| IEA cooling and buildings data | Air-conditioner stocks and cooling energy use by region | IEA terms |
| National heat-health warning systems and surveillance | Heat alerts, excess mortality and hospital admissions | Public records, terms per agency |
Who decides, and what the evidence serves.
Energy Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Transmission system operators | How much reserve to hold ahead of a forecast heat wave or cold spell | Temperature-demand curves, derating estimates, neighbouring systems‘ expected peaks |
| Public health agencies | Which neighbourhoods and facilities need priority protection from heat during an outage | Cooling dependence maps, outage exposure, heat-stress forecasts |
| Environmental regulators | Whether and when to grant temporary derogations from cooling-water temperature limits | River temperature records, plant curtailment, ecological evidence |
| Building and planning authorities | How cooling standards and passive design reduce peak demand | Demand response curves and building stock data |
Outputs this topic produces
- Temperature-demand response curves by system and season
- Heat and cold stress scenarios for supply and demand together
- Maps of cooling dependence and outage exposure for health planning
- Briefs on derating and cooling-water limits across thermal fleets
What experts ask about heat and cooling.
- How will peak demand change as heatwaves become more frequent and air conditioning spreads?
- How much do high temperatures reduce the capacity of lines, cables, transformers and power plants?
- Which populations face the greatest health risk if power fails during extreme heat?
- How will electrified heating change winter peaks and the risk of cold-weather shortfalls?
Why heat stresses energy systems from both sides.
On the demand side, cooling load rises steeply with temperature, especially when nights stay hot and buildings cannot shed heat. On the supply side, conductors sag and must carry less current when hot, transformers age faster, and thermal and nuclear plants lose efficiency or must reduce output when cooling water is too warm or environmental limits on discharge temperature are reached. Solar panels also produce less per unit of sunlight when hot.
Heat often coincides with drought, low wind and wildfire risk, which can force preventive shutdowns of lines. The result is a common-cause stress that standard planning, which assumes independent failures, may underestimate. In cold climates, electrified heating creates the mirror image: very high demand during cold, still periods.
How heat risk is analysed.
- 01
Temperature-demand models
Statistical and building-physics models link weather to load, using forecasting and time-series methods. They are less reliable beyond the range of observed temperatures.
- 02
Equipment derating
Engineering standards describe how capacity falls with temperature. Actual behaviour depends on equipment age and local conditions.
- 03
Climate projections
Downscaled climate model outputs describe future heat. They carry model and scenario uncertainty that must be carried into energy results.
- 04
Health-outage studies
Epidemiological evidence links heat and power loss to health harm. Data on outage exposure by household is often limited.
How it is studied, and what the methods cannot say.
- 01Forecasting and time-series analysisLoad forecasting with weather · Wind and solar power forecasts · Seasonal adequacy outlooksApplied here
- 02Power systems engineeringContingency and load flow studies · Frequency stability with less inertiaApplied here
- 03Energy generation, storage and grid technologyWeather-driven generation profiles · Storage technology comparisonApplied here
- 04Reliability and resilience engineeringRestoration curve analysis · Fault trees for critical sites · Fragility curves for grid assetsApplied here
- 05Optimisation and operations researchCapacity expansion planning · Unit commitment and dispatch · Restoration sequencingApplied here
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
Why do heat waves stress grids from both sides?
What is a degree day?
Is cooling access an energy issue or a health issue?
Why can a heatwave cause outages even with enough power plants?
Is cooling demand an energy problem or a health problem?
Does Energy Nexus run heat warnings?
Contribute evidence from this page.
Reports 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.
- EmailGateway GW-GCRISend it from this pageEvidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.
- ZenodoOpen depositDeposit it and submit to the communityPublish your own record on Zenodo with your ORCID iD, then submit it to the Reports community there. Curators review it; the DOI stays yours.
- ReportsGCRISee every way to contributeThe contribution types, how each is reviewed, what credit you receive, the licence and what is never accepted.
Never send personal data, sensitive infrastructure detail or anything you have no right to share. A contribution is reviewed before use; sending it confers no authorship or editorial rights, and sponsorship never buys a finding.
Bring a method, a dataset or a question.
Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.
Legal documents.
Maps, data and figures on this site are shown for context and general information. They are not advice, forecasts or warnings; the limits of the information are set out in the Disclaimers and Data Notices.