Climate projections by scenario, 2030–2060 – Cities and FUAs in San Francisco del Rincon

About this data

Indicator

Climate projections by scenario, 2030–2060 – Cities and FUAs — Projected air temperature change compared to 1981-2010 average

Unit

Degrees celsius

Source

Organisation for Economic Co-operation and Development

Licence

OECD Terms and Conditions (attribution required)

Coverage

1,374 places, 42,594 data points, 2030–2060

Last refreshed

17 August 2026

This dataset provides sub-national indicators on 2030-2060 projections by scenario on air temperature, hot days, icing days, tropical nights, total precipitation and extreme precipitation days in FUAs and Cities. Data sources and methodology Projections are based on NASA NEX-GDDP CMIP6 data, which provides average air temperature projections at a 0.25° spatial resolution for different scenarios - Shared Socioeconomic Pathways (SSPs). Hot days refer to days during which the maximum temperature is higher than 35°C) Tropical nights refer to nights during which the minimum temperature is higher than 20°C. Icing days are defined as days during which the maximum temperature is lower than 0°C. Extreme precipitation days are defined as days during which the total precipitation is higher than 20 mm. SSPs are climate scenarios up to 2100 that model how socio‑economic factors may change over the next century. These scenarios are combined with Representative Concentration Pathways (RCPs), which outline different greenhouse gas (GHG) concentration levels and their radiative forcings. Radiative forcing quantifies how factors like GHGs, aerosols and solar changes affect Earth’s atmospheric energy balance. This dataset covers highlights four scenarios: SSP1-2.6: Sustainability. 2.6 watts per square metre (W/m2) radiative forcing, 1.8°C warming by 2100. SSP2-4.5: Middle-of-the-road. 4.5 W/m2 radiative forcing, 2.7°C warming by 2100. SSP3-7.0: Regional rivalry. 7.0 W/m2 radiative forcing, 3.6°C warming by 2100. SSP5-8.5: Fossil fuel development. 8.5 W/m2 radiative forcing, 4.4°C warming by 2100. Defining FUAs and cities The OECD, in cooperation with the EU, has developed a harmonised definition of functional urban areas (FUAs) to capture the economic and functional reach of cities based on daily commuting patterns (OECD, 2012). FUAs consist of: A city – defined by urban centres in the degree of urbanisation, adapted to the closest local administrative units to define a city. A commuting zone – including all local areas where at least 15% of employed residents work in the city. The delineation process includes: Assigning municipalities surrounded by a single FUA to that FUA. Excluding non-contiguous municipalities. The definition identifies 1 285 FUAs and 1 402 cities in all OECD member countries except Costa Rica and three accession countries. Cite this dataset OECD Regions, cities and local areas database (Climate projections by scenario, 2030-2060 – Cities and FUAs), http://oe.cd/geostats Further information OECD Local Data Portal OECD Regions and Cities at a Glance For questions and/or comments, please email CitiesStat@oecd.org