Heat stress - Cities and FUAs — Mean population exposure to heat in Coquimbo-La Serena
Coquimbo-La Serena: Heat stress - Cities and FUAs — Mean population exposure to heat was 0.0582 Days per year in 2025. ◆ Volatile
Heat stress - Cities and FUAs — Mean population exposure to heat in Coquimbo-La Serena, 1981–2025
Source: Organisation for Economic Co-operation and Development. Measured in Days per year.
Analysis
The most recent figure for heat stress - cities and fuas — mean population exposure to heat in Coquimbo-La Serena is 0.0582 Days per year, measured in 2025.
Compared with earlier readings it is down 97.7% on the previous year and down 90.6% over ten years.
Over the whole period, heat stress - cities and fuas — mean population exposure to heat in Coquimbo-La Serena peaked at 7.05 Days per year in 1983 and was at its lowest, 0.0146 Days per year, in 2022.
Coquimbo-La Serena ranks 1247th of 1315 regions on this measure, in the bottom quarter.
The series is highly variable year to year, so single readings are best treated with caution.
Heat stress - Cities and FUAs — Mean population exposure to heat in Coquimbo-La Serena, year by year
| Year | Days per year | Change |
|---|---|---|
| 1981 | 1.29 Days per year | — |
| 1982 | 0.055 Days per year | -95.7% |
| 1983 | 7.05 Days per year | +12733.0% |
| 1984 | 0.8955 Days per year | -87.3% |
| 1985 | 0.9017 Days per year | +0.7% |
| 1986 | 0.0784 Days per year | -91.3% |
| 1987 | 3.87 Days per year | +4829.5% |
| 1988 | 0.0269 Days per year | -99.3% |
| 1989 | 0.0354 Days per year | +31.8% |
| 1990 | 0.1395 Days per year | +293.6% |
| 1991 | 0.9114 Days per year | +553.3% |
| 1992 | 0.905 Days per year | -0.7% |
| 1993 | 0.0613 Days per year | -93.2% |
| 1994 | 1.51 Days per year | +2365.1% |
| 1995 | 0.0772 Days per year | -94.9% |
| 1996 | 0.0201 Days per year | -74.0% |
| 1997 | 2 Days per year | +9870.2% |
| 1998 | 3.29 Days per year | +64.3% |
| 1999 | 0.0178 Days per year | -99.5% |
| 2000 | 0.0388 Days per year | +117.2% |
| 2001 | 0.0976 Days per year | +151.8% |
| 2002 | 0.9772 Days per year | +901.4% |
| 2003 | 0.9337 Days per year | -4.4% |
| 2004 | 0.0429 Days per year | -95.4% |
| 2005 | 1.54 Days per year | +3500.4% |
| 2006 | 0.0536 Days per year | -96.5% |
| 2007 | 0.0628 Days per year | +17.0% |
| 2008 | 0.0411 Days per year | -34.6% |
| 2009 | 0.0735 Days per year | +79.1% |
| 2010 | 0.0434 Days per year | -40.9% |
| 2011 | 0.0403 Days per year | -7.2% |
| 2012 | 0.0595 Days per year | +47.7% |
| 2013 | 1.23 Days per year | +1959.7% |
| 2014 | 0.0405 Days per year | -96.7% |
| 2015 | 0.6165 Days per year | +1421.6% |
| 2016 | 1.17 Days per year | +89.3% |
| 2017 | 4.21 Days per year | +260.9% |
| 2018 | 0.5811 Days per year | -86.2% |
| 2019 | 2.57 Days per year | +341.9% |
| 2020 | 1.22 Days per year | -52.4% |
| 2021 | 0.015 Days per year | -98.8% |
| 2022 | 0.0146 Days per year | -2.5% |
| 2023 | 1.25 Days per year | +8428.2% |
| 2024 | 2.58 Days per year | +106.9% |
| 2025 | 0.0582 Days per year | -97.7% |
Biggest year-on-year movements
Years where Heat stress - Cities and FUAs — Mean population exposure to heat in Coquimbo-La Serena changed far more than this series normally does. A large move can be a real event or a change in how the figure was measured — the source note below says who published it.
| Year | Change | From | To |
|---|---|---|---|
| 1983 | +12733.0% | 0.055 Days per year | 7.05 Days per year |
| 1997 | +9870.2% | 0.0201 Days per year | 2 Days per year |
| 2023 | +8428.2% | 0.0146 Days per year | 1.25 Days per year |
| 1987 | +4829.5% | 0.0784 Days per year | 3.87 Days per year |
| 2005 | +3500.4% | 0.0429 Days per year | 1.54 Days per year |
| 1994 | +2365.1% | 0.0613 Days per year | 1.51 Days per year |
Averages by decade
| Decade | Average | Lowest | Highest | Years |
|---|---|---|---|---|
| 1980s | 1.58 Days per year | 0.0269 Days per year | 7.05 Days per year | 9 |
| 1990s | 0.893 Days per year | 0.0178 Days per year | 3.29 Days per year | 10 |
| 2000s | 0.3864 Days per year | 0.0388 Days per year | 1.54 Days per year | 10 |
| 2010s | 1.06 Days per year | 0.0403 Days per year | 4.21 Days per year | 10 |
| 2020s | 0.8552 Days per year | 0.0146 Days per year | 2.58 Days per year | 6 |
More population data for Coquimbo-La Serena
- Population by age and sex - Cities and FUAs 513,860 Persons (2024)
- Population and built-up density - Cities and FUAs — Urbanised area 28 Square kilometres (2030)
Frequently asked questions
- What is heat stress - cities and fuas — mean population exposure to heat in Coquimbo-La Serena?
- Heat stress - cities and fuas — mean population exposure to heat in Coquimbo-La Serena was 0.0582 Days per year in 2025, according to Organisation for Economic Co-operation and Development.
- What is the highest heat stress - cities and fuas — mean population exposure to heat recorded in Coquimbo-La Serena?
- The highest recorded value was 7.05 Days per year in 1983.
- What is the lowest heat stress - cities and fuas — mean population exposure to heat recorded in Coquimbo-La Serena?
- The lowest recorded value was 0.0146 Days per year in 2022.
- How does Coquimbo-La Serena rank for heat stress - cities and fuas — mean population exposure to heat?
- Coquimbo-La Serena ranks 1247th out of 1315 regions with data for 2025.
- Is heat stress - cities and fuas — mean population exposure to heat rising or falling in Coquimbo-La Serena?
- Over the last ten years it is down 90.6%. The long-run trend across the full record is volatile.
- Where does this Coquimbo-La Serena data come from?
- The figures come from Organisation for Economic Co-operation and Development, published as part of Heat stress - Cities and FUAs — Mean population exposure to heat stress. Statizoid updates them automatically from the source API.
Download this data
CSV · JSON — 45 observations, free to reuse under OECD Terms and Conditions (attribution required).
About this data
This dataset provides an indicator of population exposure to heat stress. Data sources and methodology The indicator uses the Universal Thermal Comfort Index (UTCI). The UTCI enables to assess the impact of atmospheric conditions on the human body by considering air temperature, wind, radiation and humidity. UTCI values from 32°C to 38°C are considered as strong heat stress, from 38°C to 46°C as very strong heat stress, and above 46°C as extreme heat stress. Population exposure to heat stress was computed using the hourly thermal comfort indices grids from the Copernicus Climate Data Store (Di Napoli C. et al.). For each 0.25° by 0.25° grid cell, the number of days for which the maximum UTCI value is above each heat stress threshold (32°C, 38°C and 46°C) is computed. FUA and city level indicators correspond to the population-weighted average number of days above each heat stress threshold, obtained by intersecting the computed grid with the Global Human Settlement Population layer (European Commission, GHSL Data Package 2023). These estimates may differ from official subnational climate statistics due to differences in methodological approaches, such as the use of reanalysis based top down modelling versus in situ observations, along with variations in input data sources, spatial resolution, and the models and algorithms used to generate temperature estimates. 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 correspondence table between SAUs and FUAs/cities is available in parquet and csv format. The definition identifies 1 272 FUAs and 1 269 cities in all OECD member countries except Costa Rica and three accession countries. Cite this dataset OECD Regions, cities and local areas database (Heat stress - 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