1  How It Works

LogoClim uses raster data to represent climate variables such as temperature and precipitation over time. It incorporates historical data (1951-2024) and future climate projections (2021-2100) derived from global climate models under various Shared Socioeconomic Pathways (SSPs) (O’Neill et al., 2017).

Figure 1.1: Historical Climate Data series at 30-second resolution (~1 km² at the equator), displaying the Water Vapor Pressure (kPa) for France in December, averaged over the 1970–2000 period. Click on the image to enlarge it.

The model operates on a grid of patches, where each patch represents a geographical area and stores values for latitude, longitude, and selected climate variables. During the simulation, patches update their colors based on the data values. The results can be visualized on a map, accompanied by plots that display the mean, minimum, maximum, and standard deviation of the selected variable over time.

All climate inputs come from WorldClim 2.1, a widely used source of high-resolution climate datasets based on weather station observations worldwide (Fick & Hijmans, 2017). These data series are offered at various spatial resolutions, ranging from 10 minutes (~340 km² at the equator) to 30 seconds (~1 km² at the equator), and can be chosen within the model interface.

Learn more about the data series in the WorldClim section.

Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302–4315. https://doi.org/10.1002/joc.5086

O’Neill, B. C., Kriegler, E., Ebi, K. L., Kemp-Benedict, E., Riahi, K., Rothman, D. S., van Ruijven, B. J., van Vuuren, D. P., Birkmann, J., Kok, K., Levy, M., & Solecki, W. (2017). The roads ahead: Narratives for shared socioeconomic pathways describing world futures in the 21st century. Global Environmental Change, 42, 169–180. https://doi.org/10.1016/j.gloenvcha.2015.01.004