Climate Indicators are calculated from two well trusted and globally known climate scientific communities:
- Global Climate Models (GCM) used in the Coupled Model Intercomparison project Phase 5 (CMIP5)
- Coordinated Regional Downscaling experiment (CORDEX) Regional Climate Models
The climate indicators are calculated for different Representative Concentration Pathways (RCP), 2.6, 4.5, and 8.5.
Indicators are calculated from raw (non-bias adjusted) GCM and RCM daily precipitation and daily mean, maximum and minimum temperature (see the grey arrows in the figure below). The data are retrieved from Earth System Grid Federation (ESGF). ESGF is where climate modelling teams make climate simulations available, following quality standards defined by the CMIP5 and CORDEX communities. The spatial resolution for indicators from GCM is 2 degrees (200 km), and for indicators from RCM, the resolution is 0.5 degrees (about 50km).
View list: Available indicators
Daily precipitation and temperature variables from both GCM and RCM are bias adjusted using the Distribution-Based Scaling method (DBS, Yang et al., 2010) with HydroGFD, a global gridded reference dataset (Berg et al., 2018). The bias adjusted variables are then used as forcing input for the global hydrological model World-Wide-Hype (WW-Hype, Arheimer et. al., 2020) to calculate water related indicators at catchment resolution. The bias adjustment method, reference dataset and global hydrological model are developed by the Swedish Meteorological and Hydrological Institute (SMHI, for more information, visit www.hypeweb.smhi.se).
Bias adjusted variables from RCM are used to calculate the climate indicators at a 0.5 degree spatial resolution.
To help make assessments for the future, indicators are provided for different time periods:
- a reference period (1981-2010, absolute values)
- early century (2011-2040, expected future change values)
- mid-century (2041-2070, expected future change values)
- end-century (2071-2100, expected future change values).
An ensemble of model results is provided to indicate confidence in the estimates.
Expert Teams (ET) such as the ETCCDI (ET on Climate Change Detection and Indices) and ET-SCI (ET on Sector-specific Climate Indices) define the different climate indicators and how they are calculated. Indicators from water variables are defined by experts in the Hydrological Research and Development unit at SMHI. All indicators are calculated and quality assured by SMHI.
Read more: Quality assurance procedure
In the visualisation platform, some regions show no data for change in precipitation and river discharge. No change data occurs when there is no precipitation in the reference period, and try to calculate the percentage change for a future period. It is not possible to calculate a percentage with zero as reference.
If you find no data for change in precipitation and river discharge, have a look at the downloadable data for the two reference and future time periods. You will probably discover the precipitation amount is very small in your region of interest.
Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M., Hasan, A., and Pineda, L.: Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation, Hydrol. Earth Syst. Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, 2020.
Berg, P., Donnelly, C., and Gustafsson, D.: Near-real-time adjusted reanalysis forcing data for hydrology, Hydrol. Earth Syst. Sci., 22, 989–1000, https://doi.org/10.5194/hess-22-989-2018, 2018
Yang, W., Andréasson, J., Graham, P. L., Rosberg, J. and Wetterhall, F.: Distribution-based scaling to improve usability of regional climate model projections for hydrological climate change impacts studies, Hydrology Research, 41 (3-4): 211–229, https://doi.org/10.2166/nh.2010.004, 2010