A new release of the Max Planck Institute for Meteorology Earth System Model version 1.2 (MPI‐ESM1.2) is presented. The development focused on correcting errors in and improving the physical processes representation, as well as improving the computational performance, versatility, and overall user friendliness. In addition to new radiation and aerosol parameterizations of the atmosphere, several relatively large, but partly compensating, coding errors in the model's cloud, convection, and turbulence parameterizations were corrected. The representation of land processes was refined by introducing a multilayer soil hydrology scheme, extending the land biogeochemistry to include the nitrogen cycle, replacing the soil and litter decomposition model and improving the representation of wildfires. The ocean biogeochemistry now represents cyanobacteria prognostically in order to capture the response of nitrogen fixation to changing climate conditions and further includes improved detritus settling and numerous other refinements. As something new, in addition to limiting drift and minimizing certain biases, the instrumental record warming was explicitly taken into account during the tuning process. To this end, a very high climate sensitivity of around 7 K caused by low‐level clouds in the tropics as found in an intermediate model version was addressed, as it was not deemed possible to match observed warming otherwise. As a result, the model has a climate sensitivity to a doubling of CO₂ over preindustrial conditions of 2.77 K, maintaining the previously identified highly nonlinear global mean response to increasing CO₂ forcing, which nonetheless can be represented by a simple two‐layer model.

A simple plume implementation of the second version (v2) of the Max Planck Institute Aerosol Climatology, MACv2-SP, is described. MACv2-SP provides a prescription of anthropogenic aerosol optical properties and an associated Twomey effect. It was created to provide a harmonized description of post-1850 anthropogenic aerosol radiative forcing for climate modeling studies. MACv2-SP has been designed to be easy to implement, change and use, and thereby enable studies exploring the climatic effects of different patterns of aerosol radiative forcing, including a Twomey effect. MACv2-SP is formulated in terms of nine spatial plumes associated with different major anthropogenic source regions. The shape of the plumes is fit to the Max Planck Institute Aerosol Climatology, version 2, whose present-day (2005) distribution is anchored by surface-based observations. Two types of plumes are considered: one predominantly associated with biomass burning, the other with industrial emissions. These differ in the prescription of their annual cycle and in their optical properties, thereby implicitly accounting for different contributions of absorbing aerosol to the different plumes. A Twomey effect for each plume is prescribed as a change in the host model's background cloud-droplet population density using relationships derived from satellite data. Year-to-year variations in the amplitude of the plumes over the historical period (1850–2016) are derived by scaling the plumes with associated national emission sources of SO₂ and NH₃. Experiments using MACv2-SP are performed with the Max Planck Institute Earth System Model. The globally and annually averaged instantaneous and effective aerosol radiative forcings are estimated to be −0.6 and −0.5 W m⁻², respectively. Forcing from aerosol–cloud interactions (the Twomey effect) offsets the reduction of clear-sky forcing by clouds, so that the net effect of clouds on the aerosol forcing is small; hence, the clear-sky forcing, which is more readily measurable, provides a good estimate of the total aerosol forcing.

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short) scales, the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similar to past studies we find an improved representation of precipitation at kilometer scales, as compared to models with parameterised convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered – most notably over the Tropical ocean. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hecto-meter scales. Hectometer scales appear more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when reducing the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with an already improved simulation as compared to more parameterised models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change.

The representation of tropical precipitation is evaluated across three generations of models participating in phases 3, 5, and 6 of the Coupled Model Intercomparison Project (CMIP). Compared to state-of-the-art observations, improvements in tropical precipitation in the CMIP6 models are identified for some metrics, but we find no general improvement in tropical precipitation on different temporal and spatial scales. Our results indicate overall little changes across the CMIP phases for the summer monsoons, the double-ITCZ bias, and the diurnal cycle of tropical precipitation. We find a reduced amount of drizzle events in CMIP6, but tropical precipitation occurs still too frequently. Continuous improvements across the CMIP phases are identified for the number of consecutive dry days, for the representation of modes of variability, namely, the Madden–Julian oscillation and El Niño–Southern Oscillation, and for the trends in dry months in the twentieth century. The observed positive trend in extreme wet months is, however, not captured by any of the CMIP phases, which simulate negative trends for extremely wet months in the twentieth century. The regional biases are larger than a climate change signal one hopes to use the models to identify. Given the pace of climate change as compared to the pace of model improvements to simulate tropical precipitation, we question the past strategy of the development of the present class of global climate models as the mainstay of the scientific response to climate change. We suggest the exploration of alternative approaches such as high-resolution storm-resolving models that can offer better prospects to inform us about how tropical precipitation might change with anthropogenic warming.

We evaluate the new icosahedral nonhydrostatic atmospheric (ICON‐A) general circulation model of the Max Planck Institute for Meteorology that is flexible to be run at grid spacings from a few tens of meters to hundreds of kilometers. A simulation with ICON‐A at a low resolution (160 km) is compared to a not‐tuned fourfold higher‐resolution simulation (40 km). Simulations using the last release of the ECHAM climate model (ECHAM6.3) are also presented at two different resolutions. The ICON‐A simulations provide a compelling representation of the climate and its variability. The climate of the low‐resolution ICON‐A is even slightly better than that of ECHAM6.3. Improvements are obtained in aspects that are sensitive to the representation of orography, including the representation of cloud fields over eastern‐boundary currents, the latitudinal distribution of cloud top heights, and the spatial distribution of convection over the Indian Ocean and the Maritime Continent. Precipitation over land is enhanced, in particular at high‐resolution ICON‐A. The response of precipitation to El Niño sea surface temperature variability is close to observations, particularly over the eastern Indian Ocean. Some parameterization changes lead to improvements, for example, with respect to rain intensities and the representation of equatorial waves, but also imply a warmer troposphere, which we suggest leads to an unrealistic poleward mass shift. Many biases familiar to ECHAM6.3 are also evident in ICON‐A, namely, a too zonal SPCZ, an inadequate representation of north hemispheric blocking, and a relatively poor representation of tropical intraseasonal variability.

Recent trends within computational and data sciences show an increasing recognition and adoption of computational workflows as tools for productivity and reproducibility that also democratize access to platforms and processing know-how. As digital objects to be shared, discovered, and reused, computational workflows benefit from the FAIR principles, which stand for Findable, Accessible, Interoperable, and Reusable. The Workflows Community Initiative’s FAIR Workflows Working Group (WCI-FW), a global and open community of researchers and developers working with computational workflows across disciplines and domains, has systematically addressed the application of both FAIR data and software principles to computational workflows. We present recommendations with commentary that reflects our discussions and justifies our choices and adaptations. These are offered to workflow users and authors, workflow management system developers, and providers of workflow services as guidelines for adoption and fodder for discussion. The FAIR recommendations for workflows that we propose in this paper will maximize their value as research assets and facilitate their adoption by the wider community.