ALBERT

Description: A new Earth system model, the Flexible Ocean and Climate Infrastructure (FOCI), is introduced. A first version of FOCI consists of a global high-top atmosphere (European Centre Hamburg general circulation model; ECHAM6.3) and an ocean model (Nucleus for European Modelling of the Ocean v3.6; NEMO3.6) as well as sea-ice (Louvain-la-Neuve sea Ice Model version 2; LIM2) and land surface model components (Jena Scheme for Biosphere Atmosphere Coupling in Hamburg; JSBACH), which are coupled through the OASIS3-MCT software package. FOCI includes a number of optional modules which can be activated depending on the scientific question of interest. In the atmosphere, interactive stratospheric chemistry can be used (ECHAM6-HAMMOZ) to study, for example, the effects of the ozone hole on the climate system. In the ocean, a biogeochemistry model (Model of Oceanic Pelagic Stoichiometry; MOPS) is available to study the global carbon cycle. A unique feature of FOCI is the ability to explicitly resolve mesoscale ocean eddies in specific regions. This is realized in the ocean through nesting; first examples for the Agulhas Current and the Gulf Stream systems are described here. FOCI therefore bridges the gap between coarse-resolution climate models and global high-resolution weather prediction and ocean-only models. It allows to study the evolution of the climate system on regional and seasonal to (multi)decadal scales. The development of FOCI resulted from a combination of the long-standing expertise in ocean and climate modeling in several research units and divisions at the Helmholtz Centre for Ocean Research Kiel (GEOMAR). FOCI will thus be used to complement and interpret long-term observations in the Atlantic, enhance the process understanding of the role of mesoscale oceanic eddies for large-scale oceanic and atmospheric circulation patterns, study feedback mechanisms with stratospheric processes, estimate future ocean acidification, and improve the simulation of the Atlantic Meridional Overturning Circulation changes and their influence on climate, ocean chemistry and biology. In this paper, we present both the scientific vision for the development of FOCI as well as some technical details. This includes a first validation of the different model components using several configurations of FOCI. Results show that the model in its basic configuration runs stably under pre-industrial control as well as under historical forcing and produces a mean climate and variability which compares well with observations, reanalysis products and other climate models. The nested configurations reduce some long-standing biases in climate models and are an important step forward to include the atmospheric response in multidecadal eddy-rich configurations.

Description: This study introduces the Monash Simple Climate Model (MSCM) experiment database. The simulations are based on the Globally Resolved Energy Balance (GREB) model to study three different aspects of climate model simulations: (1) understanding processes that control the mean climate, (2) the response of the climate to a doubling of the CO2 concentration, and (3) scenarios of external forcing (CO2 concentration and solar radiation). A series of sensitivity experiments in which elements of the climate system are turned off in various combinations are used to address (1) and (2). This database currently provides more than 1300 experiments and has an online web interface for fast analysis and free access to the data. We briefly outline the design of all experiments, give a discussion of some results, put the findings into the context of previously published results from similar experiments, discuss the quality and limitations of the MSCM experiments, and also give an outlook on possible further developments. The GREB model simulation is quite realistic, but the model without flux corrections has a root mean square error in the mean state of the surface temperature of about 10 ∘C, which is larger than those of general circulation models (2 ∘C). It needs to be noted here that the GREB model does not simulate circulation changes or changes in cloud cover (feedbacks). However, the MSCM experiments show good agreement to previously published studies. Although GREB is a very simple model, it delivers good first-order estimates, is very fast, highly accessible, and can be used to quickly try many different sensitivity experiments or scenarios. It builds a basis on which conceptual ideas can be tested to first order and it provides a null hypothesis for understanding complex climate interactions in the context of response to external forcing or interactions in the climate subsystems.

Description: This study introduces the Monash Simple Climate Model (MSCM) experiment database. The model simulations are based on the Globally Resolved Energy Balance (GREB) model. They provide a basis to study three different aspects of climate model simulations: (1) understanding the processes that control the mean climate, (2) the response of the climate to a doubling of the CO2 concentration, and (3) scenarios of external CO2 concentration and solar radiation forcings. A series of sensitivity experiments in which elements of the climate system are turned off in various combinations are used to address (1) and (2). This database currently provides more than 1,300 experiments and has an online web interface for fast analysis of the experiments and for open access to the data. We briefly outline the design of all experiments, give a discussion of some results, and put the findings into the context of previously published results from similar experiments. We briefly discuss the quality and limitations of the MSCM experiments and also give an outlook on possible further developments. The GREB model simulation of the mean climate processes is quite realistic, but does have uncertainties in the order of 20–30%. The GREB model without flux corrections has a root mean square error in mean state of about 10°C, which is larger than those of general circulation models (2°C). However, the MSCM experiments show good agreement to previously published studies. Although GREB is a very simple model, it delivers good first-order estimates, is very fast, highly accessible, and can be used to quickly try many different sensitivity experiments or scenarios.