Climate outlook#

Hydro-meteorological hazards are affected by climate forcing, and, as such, climate change should be accounted when estimating future risk conditions. A forward-looking analysis makes use of climate projections to explore how environmental risks could develop spatially over time.

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The long-term averages of climate indices (observed or simulated) serve as the baseline conditions, against which the effects of climate change are measured for future scenarios. Changes in projected climate indices against this baseline (anomalies) and used to estimate changes in natural hazard frequency and intensity.

Table 1 Climate variables underlying hazard projections#

Hazard

Associated climate indices

Unit of measurement

Floods and Landslides

Rainfall > 10 mm

Days per year

Floods and Landslides

Consecutive wet days

Days per year

Floods and Landslides

Maximum 5-day precipitation

mm

Floods and Landslides

Extremely wet days

mm

Coastal floods

Sea Level Rise

m

Drought

Annual SPEI

[-]

Drought

Consecutive dry days

Days per year

Heat stress

Heat index (WBGT or UTCI) for moderate or extreme stress

Days per year

Given that specific unit of measurement varies across climate indices, in order to give a comparable metric of change the projected anomalies against the baseline are expressed in terms of Standard Deviation (SD) of the anomaly compared to historical variability E3CI, 2020. Data from climate models released under the IPCC Sixth Assessment Report (AR) framework are used to establish estimates of baseline and future projected climate anomalies. ARs are supported by coordinated climate modeling efforts referred to as Coupled Model Intercomparison Projects (CMIP).

The analysis relies on CMIP6 data for modeling into the future, and takes into account four climate change scenarios, referred to as Shared Socioeconomic Pathways (SSPs) in CMIP6. These pathways cover the range of possible future scenarios of anthropogenic drivers of climate change by accounting for various future greenhouse gas emission trajectories, as well as a specific focus on carbon dioxide (CO2) concentration trajectories (IPCC 2021b).

Guidance for aligned scenario selection is provided by the shared CCDR Global Climate Scenarios note.

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Fig. 8 Recommended CCDR Global Scenarios and characteristics for adaptation and development planning.#

  • SSP1-1.9 / RCP2.6: emissions peak between 2040 and 2060, declining by 2100. This results in warming of 3-3.5 °C by 2100.

  • SSP2-4.5 / RCP4.5: emissions continue to increase through the end of the century, with resulting warming of 3.8-4.2 °C by 2100.

  • SSP3-7.0 / RCP8.5: models describe a large emission variability for this scenario. Warming is estimated at 3.9-4.6 °C by 2100.

Each climate scenarios predicts different spatial patterns, resulting into a range of possible futures in terms of intensities, and frequencies of natural hazards. Key climate variables connected to the changing patterns of precipitation and temperature are collected from the Climate Change Knowledge Portal and the Copernicus Data Store.

See also

  • The Climate Knowledge Portal by the World Bank provides a large selection of climate indices for both trends and extremes as table, geodata and charts.

  • The Climate analytics repository by the Global Operational Support Team (GOST) describes a list of data provider, derived products, step-by-step to do the analysis to produce climate analytics.

  • The CLIMADA project by ETH Zurich provides global coverage of major climate-related extreme-weather hazards at high resolution via data API.

  • The European Extreme Events Climate Index based on the Actuaries Climate Index (ACI) offers an ensemble of indices to describe different types of weather-induced hazards and their severity.