Temperature trends since 1900 in and around Split

Using data from the European Centre for Medium-Range Weather Forecasts, we analysed 118 years of weather data in and around the city of Split. The area analysed also includes the surroundings of Split, which might include mountains or bodies of water, so that the temperatures shown here do not correspond exactly to the temperatures recorded by the weather stations of Split (see Methodology for details). This is what we found:

  • The temperature in and around Split between 2000 and 2018 was 1.3°C above the 20th century average.
  • The number of hot days (above 28°C over a 24-hour average) went from 0.2 days per year in the 20th century to 6.5 per year in the years since 2000.
  • The number of freezing days (below −1°C over a 24-hour average) went from 2 days per year in the 20th century to 0.8 per year since 2000.

Changes in weather patterns

Temperature changes

Since 1900, the average temperature in and around Split increased from an average of 14.7°C between 1900 and 1999 to an average of 15.9°C between 2000 and 2018. The warmest years in and around Split were 2018, 2015, 2014, 2003, and 2000.

Temperature in and around Split from 1900 to 2018. (png|svg|eps)

Hot days

In the 20th century, the average number of hot days (days for which the 24-hour average temperature is above 28°C) per year was 0.2. Between 2000 and 2018, the average number of hot days were 6.5 per year.

A day is considered hot when its average temperature is over two standard deviations of the normal average.

Number of days when the average temperature was above 28°C in and around Split, each year. (png|svg|eps)

Freezing days

Temperature averaged −1°C or less for 2 days per year in the 20th century, on average. Between 2000 and 2018, the number of freezing days were 0.8 per year.

Number of freezing days in and around Split, each year. (png|svg|eps)

What does it mean for Split?

Health and heat waves

Higher temperatures lead to excess mortality. The heatwave of July and August 2003, for instance, killed over 52,000 people in Europe, according to the Earth Policy Institute (Larsen, 2006), a think-tank. The elderly and infants are most at risk.

Rising temperatures may also cause the number of deaths related to extremely cold weather to drop.

Rail buckling and tarmac softening

In high temperatures, asphalt exposed to the sun starts to soften. This causes delays and some roads have to be closed to traffic.

When temperatures rise above 30°C, rails exposed to the sun can move or buckle. This can cause trains to derail, as happened many times in Europe already, and forces them to run more slowly, causing major delays.

Tick and mosquito-borne diseases

Tick-borne encephalitis, and more recently ehrlichiosis have been spreading in the past decades, probably due to higher temperatures (Gray et al., 2009).

Education

Researchers showed that when the daily average temperature increases above 22°C (Graff Zivin et al., 2018), cognitive abilities of school children decrease, especially in mathematics.

In Split, the number of school days above 22°C went from 5.8 per school year in the 20th century to 15.1 since 2000. It might not seem much but if exams took place on these days, pupils of Split were at a disadvantage.

Split and its environs in context

Split and nearby cities

Here are the five locations closest to Split, among the 558 we analyzed:

LocationDistanceTemperature change
Split+1.3
Zadar118 km+1.2
Banja Luka152 km+1.5
Sarajevo160 km+1.2
Tuzla212 km+1.2
Pescara215 km+1.1

Cities of Croatia

Split is one of seven locations in Croatia we have analyzed. This is how temperature has changed in the rest of them.

LocationTemperature change
Rijeka+1.3
Split+1.3
Zagreb+1.2
Zadar+1.2
Slavonski Brod+1.0
Osijek+1.0
Pula+0.9
Cities of Croatia
Cities of Croatia(png|svg|webp)

Methodology

We analyzed two data sets from the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA-20C for the period 1900–1979 and ERA-interim for the period 1979–2018.

Both data sets are re-analysis, which means that ECMWF scientists used observations from a variety of sources (satellite, weather stations, buoys, weather balloons) to estimate a series of variables for squares of about 80 kilometers in side width (125 kilometers for ERA-20C). While weather stations offer a much better record for immediate daily observations, using the ECMWF re-analyses is much more adequate for the study of long-term trends. Weather stations might move, or the city might expand around them, making their data unreliable when looking at centennial trends. However, the ECMWF data does not take into account micro-climates or “heat island” effects, so that the actual weather in the streets of Split was probably one or two degrees warmer than the values reported here (the trend, however, is the same).

Since the start of this project, ECMWF has adjusted the way historical temperatures are calculated, to give better estimates for e.g. coastal cities. Because of this, some figures published here in 2019 may differ slightly from corresponding figures published in 2018.

This report was produced by the European Data Journalism Network. Partners include OBC Transeuropa (Italy), J++ (Sweden), Spiegel Online (Germany), Vox Europe (France), Pod Crto (Slovenia), Mobile Reporter (Belgium), Rue89 (France), Alternatives Economiques (France), and El Confidencial (Spain).

References

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Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553–597. doi: 10.1002/qj.828

Graff Zivin, Joshua, Solomon M. Hsiang, and Matthew Neidell. "Temperature and Human Capital in the Short and Long Run." Journal of the Association of Environmental and Resource Economists 5.1 (2018): 77-105.

Gray, J. S., et al. "Effects of climate change on ticks and tick-borne diseases in Europe." Interdisciplinary perspectives on infectious diseases (2009).

Laloyaux, P., Balmaseda, M., Dee, D., Mogensen, K. and Janssen, P. (2016), A coupled data assimilation system for climate reanalysis. Q.J.R. Meteorol. Soc., 142: 65-78. doi:10.1002/qj.2629

Larsen, Janet. "Plan B Updates", Earth Policy Institute, 28 July 2006.

Michailidou, Alexandra V., Christos Vlachokostas, and Νicolas Moussiopoulos. "Interactions between climate change and the tourism sector: Multiple-criteria decision analysis to assess mitigation and adaptation options in tourism areas." Tourism Management 55 (2016): 1-12.

Scott, D., and Chr Lemieux. "Weather and climate information for tourism." Procedia Environmental Sciences 1 (2010): 146-183.

Zeller, H., et al. "Mosquito‐borne disease surveillance by the European Centre for Disease Prevention and Control." Clinical microbiology and infection 19.8 (2013): 693-698.