The climate science community sources a suite of global climate models to help decision makers understand the projections of future climate change and related impacts, among the most widely used are the Coupled Model Intercomparison Project, Phase 5 (CMIP5) models included in the IPCC's Fifth Assessment Report (AR5). Climate projections can be presented via individual models or through multi-model ensembles. The Climate Change Knowledge Portal (CCKP) supports the analysis of climate impacts using multi-model ensembles, as they represent the range and distribution of the most plausible projected outcomes when representing expected changes.
- It is forecast that there will be a continuous increase in temperature during the period 2025-2100.
- Synthesized results from several models predict average increases in air temperatures in Macedonia to be 1.0°C (0.9-1.1) by 2025, 1.9°C (1.6-2.2) by 2050, 2.9°C (2.2-3.6) by 2075, and 3.8°C (2.7-5.4) by 2100, in comparison with the reference period.
- Compared with the period 1961-1990, the predicted changes for the period 2025-2100 will be most intense and temperature rises will be greatest in summer.
- During winter, the air temperatures are also expected to increase, though with less intensity. It is possible that the average monthly temperatures at the turn of winter into spring will be levelled between 2025-2100.
- A decrease in annual precipitation is predicted in the period 2025-2100.
- Precipitation reductions are forecast for all four seasons, with the maximum decrease in summer (June, July and August).
- The average sum of precipitation is expected to decrease -5% by 2050 and -13% by 2100, in comparison with the reference period.
- The intensity of changes is forecast to be greatest in July and August (when there may be no precipitation at all) and will be most severe in the eastern regions. Less intense decreases in precipitation are expected in the cold part of the year.
This section provides a summary of key natural hazards and their associated socioeconomic impacts in a given country. And it allows quick evaluation of most vulnerable areas through the spatial comparison of natural hazard data with development data, thereby identifying exposed livelihoods and natural systems.