CMIP6 Climate Projections, model MPI-ESM1-2-HR (DKRZ)

This dataset features a selection of future climate projections variables generated by the MPI-ESM1-2-HR Earth system model as part of the Coupled Model Intercomparison Project Phase 6 (CMIP6).

The data covers the future simulation period 2015–2100 and includes two Shared Socioeconomic Pathways (SSPs):

SSP1-2.6: A low-emission "Sustainability" scenario emphasizing inclusive development and environmental stewardship, representing a pathway compatible with keeping global warming below 2°C.

SSP2-4.5: A "Middle-of-the-Road" scenario representing intermediate greenhouse gas emissions and historical patterns of development, with medium challenges to mitigation and adaptation.

SSP3-7.0: A high-emission "Regional Rivalry" scenario driven by resurgent nationalism and regional conflicts, resulting in slow economic growth and high challenges to both mitigation and adaptation.

SSP5-8.5: A very high-emission "Fossil-fueled Development" scenario driven by rapid, energy-intensive global growth, representing the upper boundary of plausible future pathways

The data is distributed in a compressed Zarr format with near-zero precision loss. It features a daily temporal resolution and is structurally optimized for high-throughput regional assessments and time-series analysis.

Accessing this dataset requires a Zarr v3-compatible library (e.g., zarr-python >= 3.x). Python users can upgrade via pip install "zarr>3".

How to download the data

The default (and preferred) way to access the data requires accessing the api.earthdatahub.destine.eu domain and a valid API key.

Method 1: quick access

It is possible to include the token directly in the URL.

1import xarray as xr
2
3xr.open_dataset(
4    "https://edh:<your personal access token>@api.earthdatahub.destine.eu/cmip6/DKRZ-MPI-ESM1-2-HR-ScenarioMIP-r1i1p1f1-day-gn-v0.zarr",
5    chunks={},
6    engine="zarr",
7    zarr_format=3,
8)

Method 2: advanced access

The Python snippet gather the token from a netrc file.

It's required to before running the code snippet below.

1import xarray as xr
2
3xr.open_dataset(
4    "https://api.earthdatahub.destine.eu/cmip6/DKRZ-MPI-ESM1-2-HR-ScenarioMIP-r1i1p1f1-day-gn-v0.zarr",
5    storage_options={"client_kwargs":{"trust_env":True}},
6    chunks={},
7    engine="zarr",
8    zarr_format=3,
9)

Variables

Short Name	Units	Description
clt	%	Total Cloud Cover Percentage
hfls	W m-2	Surface Upward Latent Heat Flux
hfss	W m-2	Surface Upward Sensible Heat Flux
hurs	%	Near-Surface Relative Humidity
hursmax	%	Daily Maximum Near-Surface Relative Humidity
hursmin	%	Daily Minimum Near-Surface Relative Humidity
huss	1	Near-Surface Specific Humidity
pr	kg m-2 s-1	Precipitation
prc	kg m-2 s-1	Convective Precipitation
prsn	kg m-2 s-1	Snowfall Flux
psl	Pa	Sea Level Pressure
rlds	W m-2	Surface Downwelling Longwave Radiation
rlus	W m-2	Surface Upwelling Longwave Radiation
rlut	W m-2	TOA Outgoing Longwave Radiation
rsds	W m-2	Surface Downwelling Shortwave Radiation
rsus	W m-2	Surface Upwelling Shortwave Radiation
sfcWind	m s-1	Daily-Mean Near-Surface Wind Speed
sfcWindmax	m s-1	Daily Maximum Near-Surface Wind Speed
tas	K	Near-Surface Air Temperature
tasmax	K	Daily Maximum Near-Surface Air Temperature
tasmin	K	Daily Minimum Near-Surface Air Temperature
uas	m s-1	Eastward Near-Surface Wind
vas	m s-1	Northward Near-Surface Wind