Impact of melt ponds on Arctic sea ice in past and future climates as simulated by MPI-ESM

The impact of melt ponds on Arctic sea ice is estimated from model simulations of the historical and future climate. The simulations were performed with and without the effect of melt ponds on sea ice melt, respectively. In the last thirty years of the historical simulations, melt ponds develop predominantly in the continental shelf regions and in the Canadian archipelago. Accordingly, the ice albedo in these regions is systematically smaller than in the no-pond simulations, the sea ice melt is enhanced, and both the ice concentration and ice thickness during the September minimum are reduced. Open ponds decrease the ice albedo, resulting in enhanced ice melt, less sea ice and further pond growth. This positive feedback entails a more realistic representation of the seasonal cycle of Northern Hemisphere sea ice area. Under the premise that the observed decline of Arctic sea ice over the period of modern satellite observations is mainly externally driven and, therefore, potentially predictable, both model versions underestimate the decline in Arctic sea ice. This presupposition, however, is challenged by our model simulations which show a distinct modulation of the downward Arctic sea ice trends by multidecadal variability. At longer time scales, an impact of pond activation on Arctic sea ice trends is more evident: In the Representative Concentration Pathway scenario RCP45, the September sea ice is projected to vanish by the end of the 21st century. In the active-pond simulation, this happens up to two decades earlier than in the no-pond simulations

The atmospheric general circulation model ECHAM5 Part II: Sensitivity of simulated climate to horizontal and vertical resolution

The most recent version of the Max Planck Institute for Meteorology atmospheric general circulation model, ECHAM5, is used to study the impact of changes in horizontal and vertical resolution on seasonal mean climate. In a series of AMIP-style experiments with resolutions ranging between T21L19 and T159L31, the systematic errors and convergence properties are assessed for two vertical resolutions. At low vertical resolution (L19) there is no evidence for convergence to a more realistic climate state for resolutions higher than T42. At higher vertical resolution (L31), on the other hand, the root-mean-squared-errors decrease monotonously with increasing horizontal resolution. Furthermore, except for T42, the L31 versions are superior to their L19 counterparts, and the improvements become more evident at increasingly higher horizontal resolutions. This applies, in particular, to the zonal mean climate state and also to stationary wave patterns in boreal winter. As in previous studies, increasing horizontal resolution leads to a warming of the troposphere, most prominently at mid-latitudes and, hence, to a poleward shift and intensification of the mid-latitude westerlies. Increasing the vertical resolution has the opposite effect, almost independent of horizontal resolution: Whereas the atmosphere is colder at low and middle latitudes, it is warmer at high latitudes and close to the surface. In addition, increased vertical resolution results in a pronounced warming in the polar upper troposphere and lower stratosphere where the cold bias is reduced by up to 50% compared to L19 simulations. Consistent with these temperature changes is a decrease and equatorward shift of the mid-latitude westerlies. The substantial benefits in refining both horizontal and vertical resolution are in accord with scaling arguments deduced from quasi-geostrophic theory implying that horizontal and vertical resolution ought to be chosen consistentl

The Global Atmosphere-aerosol Model ICON-A-HAM2.3-Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness

The Hamburg Aerosol Module version 2.3 (HAM2.3) from the ECHAM6.3-HAM2.3 global atmosphere-aerosol model is coupled to the recently developed icosahedral nonhydrostatic ICON-A (icon-aes-1.3.00) global atmosphere model to yield the new ICON-A-HAM2.3 atmosphere-aerosol model. The ICON-A and ECHAM6.3 host models use different dynamical cores, parameterizations of vertical mixing due to sub-grid scale turbulence, and parameter settings for radiation balance tuning. Here, we study the role of the different host models for simulated aerosol optical thickness (AOT) and evaluate impacts of using HAM2.3 and the ECHAM6-HAM2.3 two-moment cloud microphysics scheme on several meteorological variables. Sensitivity runs show that a positive AOT bias over the subtropical oceans is remedied in ICON-A-HAM2.3 because of a different default setting of a parameter in the moist convection parameterization of the host models. The global mean AOT is biased low compared to MODIS satellite instrument retrievals in ICON-A-HAM2.3 and ECHAM6.3-HAM2.3, but the bias is larger in ICON-A-HAM2.3 because negative AOT biases over the Amazon, the African rain forest, and the northern Indian Ocean are no longer compensated by high biases over the sub-tropical oceans. ICON-A-HAM2.3 shows a moderate improvement with respect to AOT observations at AERONET sites. A multivariable bias score combining biases of several meteorological variables into a single number is larger in ICON-A-HAM2.3 compared to standard ICON-A and standard ECHAM6.3. In the tropics, this multivariable bias is of similar magnitude in ICON-A-HAM2.3 and in ECHAM6.3-HAM2.3. In the extra-tropics, a smaller multivariable bias is found for ICON-A-HAM2.3 than for ECHAM6.3-HAM2.3.ISSN:1942-246

ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales

International audienceState-of-the-art Earth system models typically employ grid spacings of O(100 km), which is too coarse to explicitly resolve main drivers of the flow of energy and matter across the Earth system. In this paper, we present the new ICON-Sapphire model configuration, which targets a representation of the components of the Earth system and their interactions with a grid spacing of 10 km and finer. Through the use of selected simulation examples, we demonstrate that ICON-Sapphire can (i) be run coupled globally on seasonal timescales with a grid spacing of 5 km, on monthly timescales with a grid spacing of 2.5 km, and on daily timescales with a grid spacing of 1.25 km; (ii) resolve large eddies in the atmosphere using hectometer grid spacings on limited-area domains in atmosphere-only simulations; (iii) resolve submesoscale ocean eddies by using a global uniform grid of 1.25 km or a telescoping grid with the finest grid spacing at 530 m, the latter coupled to a uniform atmosphere; and (iv) simulate biogeochemistry in an ocean-only simulation integrated for 4 years at 10 km. Comparison of basic features of the climate system to observations reveals no obvious pitfalls, even though some observed aspects remain difficult to capture. The throughput of the coupled 5 km global simulation is 126 simulated days per day employing 21 % of the latest machine of the German Climate Computing Center. Extrapolating from these results, multi-decadal global simulations including interactive carbon are now possible, and short global simulations resolving large eddies in the atmosphere and submesoscale eddies in the ocean are within reach

ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales

International audienceState-of-the-art Earth system models typically employ grid spacings of O(100 km), which is too coarse to explicitly resolve main drivers of the flow of energy and matter across the Earth system. In this paper, we present the new ICON-Sapphire model configuration, which targets a representation of the components of the Earth system and their interactions with a grid spacing of 10 km and finer. Through the use of selected simulation examples, we demonstrate that ICON-Sapphire can (i) be run coupled globally on seasonal timescales with a grid spacing of 5 km, on monthly timescales with a grid spacing of 2.5 km, and on daily timescales with a grid spacing of 1.25 km; (ii) resolve large eddies in the atmosphere using hectometer grid spacings on limited-area domains in atmosphere-only simulations; (iii) resolve submesoscale ocean eddies by using a global uniform grid of 1.25 km or a telescoping grid with the finest grid spacing at 530 m, the latter coupled to a uniform atmosphere; and (iv) simulate biogeochemistry in an ocean-only simulation integrated for 4 years at 10 km. Comparison of basic features of the climate system to observations reveals no obvious pitfalls, even though some observed aspects remain difficult to capture. The throughput of the coupled 5 km global simulation is 126 simulated days per day employing 21 % of the latest machine of the German Climate Computing Center. Extrapolating from these results, multi-decadal global simulations including interactive carbon are now possible, and short global simulations resolving large eddies in the atmosphere and submesoscale eddies in the ocean are within reach

ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales

International audienceState-of-the-art Earth system models typically employ grid spacings of O(100 km), which is too coarse to explicitly resolve main drivers of the flow of energy and matter across the Earth system. In this paper, we present the new ICON-Sapphire model configuration, which targets a representation of the components of the Earth system and their interactions with a grid spacing of 10 km and finer. Through the use of selected simulation examples, we demonstrate that ICON-Sapphire can (i) be run coupled globally on seasonal timescales with a grid spacing of 5 km, on monthly timescales with a grid spacing of 2.5 km, and on daily timescales with a grid spacing of 1.25 km; (ii) resolve large eddies in the atmosphere using hectometer grid spacings on limited-area domains in atmosphere-only simulations; (iii) resolve submesoscale ocean eddies by using a global uniform grid of 1.25 km or a telescoping grid with the finest grid spacing at 530 m, the latter coupled to a uniform atmosphere; and (iv) simulate biogeochemistry in an ocean-only simulation integrated for 4 years at 10 km. Comparison of basic features of the climate system to observations reveals no obvious pitfalls, even though some observed aspects remain difficult to capture. The throughput of the coupled 5 km global simulation is 126 simulated days per day employing 21 % of the latest machine of the German Climate Computing Center. Extrapolating from these results, multi-decadal global simulations including interactive carbon are now possible, and short global simulations resolving large eddies in the atmosphere and submesoscale eddies in the ocean are within reach

Developments in the MPI‐M Earth System Model version 1.2 (MPI‐ESM1.2) and Its Response to Increasing CO2

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