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Table of Contents

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Acronyms

Acronym	Description
C3S	Copernicus Climate Change Service
CDS	Climate Data Store
SIS	Sectoral Information System
ETCCDI	Expert Team on Climate Change Detection and Indices
WFDE5	WATCH Forcing Data methodology applied to ERA5 reanalysis data
CMIP6	Coupled Model Intercomparison Project Phase 6
ISIMIP	Inter-Sectoral Impact Model Intercomparison Project
HSI	Heat stress indicator
SSP	Shared Socioeconomic Pathway

Introduction

Executive Summary

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Version 2: The equation used in Version 1 to calculate WBT was erroneous. We updated the calculation method (see section 2.4. Method for more details) and recalculated WBT and WBGT. Version 2 contains these updated WBT and WBGT data.

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Known issues

Version 1 of this dataset contained an inadequate equation for calculating WBT (using the WBT calculation used by Dunne et al., 2013), which led to unreliable WBT and WBGT estimates.

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	table1
	table1

Table 1: Overview of key characteristics of the dataset.

Data Description
Dataset title	Climate extreme indices and heat stress indicators derived from CMIP6 global climate projections
Data type	Indicators
Topic category	Climate extremes and heat stress
Sector	Atmosphere (surface)
Keyword	Extreme temperature and precipitation, heat stress, cmip6
Dataset language	Eng
Domain	Global
Horizontal resolution	From 0.5°x0.5° to 2.8125°x2.8125° depending on the model
Temporal coverage	01/01/1850 - 31/12/2014 (historical for ETCCDI indices) 01/01/1849 - 31/12/2014 (historical for ETCCDI indices for EC-Earth3) 01/01/1850 - 31/12/2016 (historical for ETCCDI indices for FGOALS-g3) 01/01/1951 - 31/12/2014 (historical HSI data) 01/01/1951 - 31/12/2010 (historical bias-adjusted HSI data) 01/01/2015 - 31/12/2100 (SSPs barring bias-adjusted HSI data) 01/01/2015 - 31/12/2300 (SSPs for ETCCDIs for CanESM5) 01/01/2011 - 31/12/2100 (SSPs bias-adjusted HSI data) 01/01/1981 - 31/12/2010 (WFDE5 reference dataset)
Temporal resolution	Yearly, monthly, and daily, depending on the indicator
Vertical coverage	Surface data
Update frequency	Static dataset
Version	1.0, 2.0
Model	Calculated from CMIP6 ensemble
Experiment	historical, ssp126, ssp245, ssp370 and ssp585
Provider	CICERO
Terms of Use	The ETCCDI and heat stress indicators for CMIP6 historical and future scenarios are available free of charge from the Copernicus Climate Data Store. These data are strictly for use in non-commercial research and education projects only. Scientific results based on these data must be submitted for publication in the open literature without delay. Although care has been taken in preparing and testing the data products, we cannot guarantee that the data are correct in all circumstances; neither do we accept any liability whatsoever for any error or omission in the data products, their availability, or for any loss or damage arising from their use. Citation and acknowledgement Whenever you publish research or applications based in whole or in part on these data, include the following acknowledgement. Relevant references to be cited are listed below the suggested acknowledgement statements. For the ETCCDI indices: "We acknowledge the ETCCDI indices for CMIP6 provided through the Copernicus Climate Data Store, documented in Sillmann et al. (2013) and Kim et al (2020)." Sillmann, J., V. V. Kharin, X. Zhang, F. W. Zwiers and D. Bronaugh, 2013: Climate extremes indices in the CMIP5 multi-model ensemble. Part 1: Model evaluation in the present climate. J. Geophys. Res. Atmos., 118, 1716-1733, doi: 10.1002/jgrd.50203 Kim, Y.-H., S. Min, X. Zhang, J. Sillmann, and M. Sandstad, 2020: Evaluation of the CMIP6 multi-model ensemble for climate extreme indices, Weather and Climate Extremes, 29, doi: 10.1016/j.wace.2020.100269." For the heat stress indicators: "We acknowledge the heat stress indicators for CMIP6 provided through the Copernicus Climate Data Store and documented in Schwingshackl et al (2021)." Schwingshackl, C., Sillmann, J., Vicedo-Cabrera, A. M., Sandstad, M., & Aunan, K. (2021). Heat Stress Indicators in CMIP6: Estimating Future Trends and Exceedances of Impact-Relevant Thresholds. Earths Future, 9, e2020EF001885. https://doi.org/10.1029/2020EF001885

Variable Description

The variables contained in the dataset are ETCCDI indices on monthly and yearly resolution, and daily resolved heat stress indicators HI, Humidex, UTCI, WBT and WBGT.

Table 2: Overview and description of variables.

Variables
Long Name	Short Name in NetCDF	Unit	Description
Consecutive dry days	cddETCCDI	day	Maximum number of days in a row with precipitation below 1 mm in a year. If a dry spell spans across multiple calendar years (as may happen in very dry regions), then CDD is not reported for that year and the accumulated dry days are carried forward to the year when the spell ends.
Cold spell duration index	csdiETCCDI	day	Annual count of days that are part of a spell of at least 6 consecutive days when daily minimum temperature is below the calendar day 10^th percentile of minimum temperature centered on a 5-day sliding window during the base period.
Consecutive wet days	cwdETCCDI	day	Maximum number of days in a row with 1 mm or more precipitation in a year. If a wet spell spans across multiple calendar years (as may happen in very wet regions), then CWD is not reported for that year and the accumulated wet days are carried forward to the year when the spell ends.
Diurnal temperature range	dtrETCCDI	°C	Annual mean daily difference between minimum and maximum temperature
Frost days	fdETCCDI	day	Annual count of days when daily minimum temperature < 0°C
Growing season length	gslETCCDI	day	Annual (January 1^st to December 31^st in the Northern hemisphere and July 1^st to June 30^th in the Southern hemisphere) count of days between first period of at least 6 days with daily mean temperature above 5 °C and first span after July 1^st (NH) or January 1^st (SH) of at least 6 days with daily mean temperature below 5 °C
Ice days	idETCCDI	day	Annual count of days when daily maximum temperature < 0°C
Total wet day precipitation	prcptotETCCDI	mm	Total annually summed precipitation on days with precipitation ≥ 1mm. Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Number of wet days	r1mmETCCDI	day	Number of days per year with 1 mm or more precipitation. Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Heavy precipitation days	r10mmETCCDI	day	Number of days per year with 10 mm or more precipitation. Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Very heavy precipitation days	r20mmETCCDI	day	Number of days per year with 20 mm or more precipitation. Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Very wet day precipitation	r95pETCCDI	mm	Total annually summed precipitation on days with more daily precipitation than the 95^th daily precipitation percentile on wet days in the base period. Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Extremely wet day precipitation	r99pETCCDI	mm	Total annually summed precipitation on days with more daily precipitation than the 99^th daily precipitation percentile on wet days in the base period. Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Maximum 1-day precipitation	rx1dayETCCDI	mm	Maximum precipitation on a single day in period (year or month). Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Maximum 5-day precipitation	rx5dayETCCDI	mm	Maximum precipitation in five consecutive days in period (year or month). Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Simple daily intensity index	sdiiETCCDI	mm/day	Total annually summed precipitation on wet days (days with ≥ 1mm), divided by total number of wet days. Precipitation is deposition of water on the Earth's surface, either rain, snow, ice or hail.
Summer days	sdETCCDI	day	Annual count of days when daily maximum temperature > 25 °C.
Cold nights	tn10pETCCDI	%	Percentage of days with minimum temperature below the corresponding calendar day 10^th percentile of minimum temperature for a 5-day moving window in the base period.
Warm nights	tn90pETCCDI	%	Percentage of days with minimum temperature above the corresponding calendar day 90^th percentile of minimum temperature for a 5-day moving window in the base period.
Minimum value of daily minimum temperature	tnnETCCDI	°C	Minimum of daily minimum temperature in period (year or month).
Maximum value of daily minimum temperature	tnxETCCDI	°C	Maximum of daily minimum temperature in period (year or month).
Tropical nights	trETCCDI	day	Annual count of days when daily minimum temperature > 20 °C.
Cold days	tx10pETCCDI	%	Percentage of days with maximum temperature below the corresponding calendar day 10^th percentile of minimum temperature for a 5-day moving window in the base period.
Warm days	tx90pETCCDI	%	Percentage of days with maximum temperature above the corresponding calendar day 90^th percentile of minimum temperature for a 5-day moving window in the base.
Minimum value of daily maximum temperature	txnETCCDI	°C	Minimum of daily maximum temperature in period (year or month)
Maximum value of daily maximum temperature	txxETCCDI	°C	Maximum of daily maximum temperature in period (year or month)
Warm spell duration index (WSDI)	wsdiETCCDI	day	Annual count of days that are part of a spell of at least 6 consecutive days when daily maximum temperature is above the calendar day 90^th percentile of maximum temperature centered on a 5-day sliding window during the base period.
Heat index	HI	°C	Heat index is a heat stress indicator used by the US National Oceanic and Atmospheric Administration (NOAA) National Weather Service for issuing heat warnings. It is calculated using multiple linear regression based on near-surface air temperature and relative humidity (https://www.wpc.ncep.noaa.gov/html/heatindex_equation.shtml).
Humidex	Humidex	°C	Humidex is a heat stress indicator used by Canadian meteorological services. It is calculated as linear combination of near-surface air temperature and vapour pressure (Masterson & Richardson, 1979; as cited in Blazejczyk et al., 2012).
Indoor Universal Thermal Climate Index	UTCI	°C	UTCI is a multinode model of human heat transfer (Fiala et al., 2012), which can be approximated by a polynomial equation based on near-surface air temperature, solar radiation, vapour pressure, and wind speed (Bröde et al. (2013). In the present dataset, the influence of solar radiation and wind speed is not considered, and UTCI is calculated from temperature and vapour pressure solely, thus representing indoor conditions.
Wet-bulb temperature	WBT	°C	Wet-bulb temperature considers the cooling capacity of a human body through sweating by indicating the temperature an air parcel would have in case of complete water evaporation. We employ the WBT formula derived by Buzan et al. (2015), which combines equations from Davies-Jones (2008, 2009) to iteratively calculate WBT from near-surface air temperature, relative humidity, and pressure. We used a Matlab implementation of the WBT formula (https://github.com/jrbuzan/WetBulb.m/blob/master/WetBulb.m) and translated it into python.
Indoor wet-bulb globe temperature	WBGT	°C	Indoor wet-bulb globe temperature is defined as weighted mean of WBT and near-surface air temperature (WBGT = 0.7WBT + 0.3T).

Input Data

The main input data for this dataset is CMIP6 data (Eyring et al 2016) from experiments historical, ssp126, ssp245, ssp370 and ssp585. In addition, the WFDE5 v1.0 (Cucchi et al. 2020) dataset is used for bias adjustment of heat stress indicators. Mean, maximum and minimum daily temperature, and total daily precipitation is used for calculation of ETCCDI indices, whereas maximum daily temperature, daily mean surface pressure and daily mean surface specific humidity is used to calculate the heat stress indicators.

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	table3
	table3

Table 3: Overview of climate model CMIP6 data, summarising the model properties and scenario simulations used.

Input Data
Model name	Model centre	Scenario	Period	Resolution
ACCESS-CM2	CSIRO-ARCCSS	historical, ssp126, ssp245, ssp370, sssp585	1850-2100	1.875°x1.25°
ACCESS- ESM1-5	CSIRO	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.875°x1.24°
BCC-CSM2- MR	BCC	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.125°x1.125°
CNRM-CM6-1	CNRM-CERFACS	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.40625°x1.40625°
CNRM-CM6- 1-HR	CNRM-CERFACS	historical, ssp126, ssp585	1850-2100	0.5°x0.5°
CNRM-ESM2- 1	CNRM-CERFACS	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.40625°x1.40625°
CanESM5	CCCma	historical, ssp126, ssp245, ssp370, ssp585	1850-2100 1850-2300 for r1 SSP126	2.8125°x2.8125°
EC-Earth3	EC-Earth-Consortium	historical, ssp126, ssp245, ssp370, ssp585	1849-2100 for r11, r13 and r15 1850-2100 for other members	0.703125°x0.703125°
EC-Earth3-Veg	EC-Earth-Consortium	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	0.703125°x0.703125°
FGOALS-g3	CAS	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	2.0°x2.25°
GFDL-CM4	NOAA-GFDL	historical, ssp245, ssp585	1850-2100	1.25°x1.0°
GFDL-ESM4	NOAA-GFDL	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.25°x1.0°
HadGEM3- GC31-LL	MOHC	historical, ssp126, ssp245, ssp585	1850-2100	1.875°x1.25°
HadGEM3- GC31-MM	MOHC	historical, ssp126, ssp585	1850-2100	0.83°x0.56°
INM-CM4-8	INM	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	2.0°x1.5°
INM-CM5-0	INM	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	2.0°x1.5°
KACE-1-0-G	NIMS-KMA	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.875°x1.25°
KIOST-ESM	KIOST	historical, ssp126, ssp245, ssp585	1850-2100	1.875°x1.875°
MIROC-ES2L	MIROC	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	2.8125°x2.8125°
MIROC6	MIROC	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.40625°x1.40625°
MPI-ESM1-2- HR	MPI-M/DKRZ	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	0.9375°x0.9375°
MPI-ESM1-2- LR	MPI-M	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.875°x1.875°
MRI-ESM2-0	AER/AOGCM/BGC/CHEM	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.125°x1.125°
NESM3	NUIST	historical, ssp126, ssp245, ssp585	1850-2100	1.875°x1.875°
NorESM2-LM	NCC	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	2.5°x1.875°
NorESM2-MM	NCC	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.25°x0.9375°
UKESM1-0-LL	AER/AOGCM/BGC/CHEM	historical, ssp126, ssp245, ssp370, ssp585	1850-2100	1.875°x1.25°
WFDE5 v1.0	C3S	n/a	1981-2010	0.5°x0.5°

Note
Please note that Table 3 provides and overview of the input datasets. The table and its content as drafted above is indicative and may be adjusted accordingly depending on the type of model input

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	table4
	table4

Table 4: Overview of key characteristics of CMIP6 data.

Data Description
Main variables	tas (K), tasmax (K), tasmin (K), pr (mm), huss (kg/kg), psl (Pa)
Domain	Global
Horizontal resolution	From 0.5°x0.5° to 2.8125°x2.8125° depending on the model
Temporal coverage	1850-01-01/to/2014-12-31 (historical) 2015-01-01/to/2100-31-12 (ssp126, ssp245, ssp370 and ssp585)
Temporal resolution	daily
Vertical coverage	Surface
Update frequency	Sporadic updates, typically in the case of errors in the data
Model	ACCESS-CM2, ACCESS-ESM1-5, BCC-CSM2-MR, CanESM5, CNRM- CM6-1, CNRM-CM6-1-HR, CNRM-ESM2-1, EC-Earth3, EC-Earth-3- Veg, FGOALS-g3, GFDL-CM4, GFDL-ESM4, HadGEM3-GC31-LL, HadGEM3-GC31-MM, INM-CM4-8, INM-CM5-0, KACE-1-0-G, KIOST- ESM, MIROC6, MIROC-ES2L, MPI-ESM1-2-HR, MPI-ESM1-2-LR, MRI- ESM2-0, NESM3, NorESM2-LM, NorESM2-MM, UKESM1-0-LL
Experiment	historical, ssp126, ssp245, ssp370, ssp585
Provider	Earth System Grid Federation (ESGF)

WDEF5 data

WDEF5 (Cucchi et al. 2020) is a bias-adjusted version of meteorological surface data from the widely used reanalysis dataset ERA5.

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	table5
	table5

Table 5. Overview of key characteristics of the WFDE5 data.

Data Description
Main Variables	Near-surface air temperature (K), near-surface specific humidity (kg/kg), surface air pressure (Pa)
Domain	Global
Horizontal resolution	0.5°x0.5°
Temporal coverage	1981-01-01 /to/2010-12-31
Temporal resolution	daily
Vertical coverage	Surface
Update frequency	Updates at irregular intervals
Model	WATCH Forcing Data methodology applied to ERA5
Experiment	Not applicable
Provider	Copernicus Data Store (CDS)

References

Blazejczyk, K., Epstein, Y., Jendritzky, G., Staiger, H., & Tinz, B. (2012). Comparison of UTCI to selected thermal indices. International Journal of Biometeorology, 56(3), 515–535. https://doi.org/10.1007/s00484-011-0453-2

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Acronyms

Introduction

Executive Summary

Known issues

Variable Description

Input Data

WDEF5 data

References

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Versions Compared

Old Version 6

New Version 7

Key

Acronyms

Introduction

Executive Summary

Known issues

Variable Description

Input Data

WDEF5 data

References