The representation of tropical precipitation is evaluated across three generations of models participating in the Coupled Model Intercomparison Project (CMIP), phases 3, 5 and 6. 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, the representation of modes of variability, namely the Madden-Julian Oscillation and the El Niño Southern Oscillation, as well as the trends in dry months in the 20th 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 20th 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 to explore 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.

International audienceThis study aims to relate the intra-seasonal rainfall variability over the Amazon basin to atmospheric circulation patterns (CPs), with particular attention to extreme rainfall events in the Amazon–Andes region. The CPs summarize the intra-seasonal variability of atmospheric circulation and are defined using daily low-level winds from the ERA-Interim (1.5° × 1.5°) reanalysis for the 1979–2014 period. Furthermore, observational data of precipitation and high-resolution TRMM 3B42 (∼25 km), 2A25 PR (∼5 km) and CHIRPS (∼5 km) data products are related to the CPs throughout the Amazon basin. Nine CPs are determined using a hybrid method that combines a neural network technique (self-organizing maps, SOM) and hierarchical ascendant classification. The CPs are characterized by a specific cycle with alternative transitions and a duration of 14 days on average. This configuration initially results in northerly winds to southerly winds towards the northern or eastern Amazon basin. The related rainfall suggests that it is driven mainly by CP dynamics. In addition, we demonstrate a good agreement amongst the four rainfall data sets: observed precipitation, TRMM 3B42, TRMM 2A25 PR and CHIRPS. Furthermore, special attention is given to the Amazon–Andes transition region. Over this region, two particular CPs (CP4 and CP5) are identified as the key contributors of maximum and minimum daily rainfall, respectively. Thus, during the dry season, 40.8% (11.4%) of the CP5 (CP4) days demonstrate rainfall of less than 1 mm day⁻¹, while during the wet season, 6.2% (14.6%) of the CP5 (CP4) days show rainfall amounts higher than the seasonal 90th percentile (10.4 mm day⁻¹). This study provides additional information concerning the intra-seasonal circulation variability in Amazonia and demonstrates the value of using remote sensing precipitation data in this region as a tool for forecast in areas lacking observable information

Abstract. State-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.

Abstract. State-of-the-art Earth System models typically employ grid spacings of O(100 km), 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 already now (i) be run coupled globally on seasonal time scales with a grid spacing of 5 km and on monthly time scales with a grid spacing of 2.5 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 a finest grid spacing of 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 to observations of these various configurations reveals no obvious pitfall. 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.

This study investigates whether the representation of explicit and parameterized convection influences the response to the Atlantic Meridional Mode (AMM). The main focus is on the precipitation response to the AMM-SST pattern, but possible implications for the atmospheric feedback on SST are also examined by considering differences in the circulation response between explicit and parameterized convection. Based on analysis from observations, SST composites are built to represent the positive and negative AMM. These SST patterns, in addition to the March-May climatology, are prescribed to the atmospheric ICON model. High-resolution simulations with explicit (E-CON) and coarse-resolution simulations with parameterized (P-CON) convection are used over a nested tropical Atlantic and a global domain, respectively. Our results show that a meridional shift of about 1° in the precipitation climatology explains most of the response to the AMM-SST pattern, both in simulations with explicit and with parameterized convection. Our results also indicate a linearity in the precipitation response to the positive and negative AMM in E-CON, in contrast to P-CON. Further analysis of the atmospheric response to the AMM reveals that anomalies in the wind-driven enthalpy fluxes are generally stronger in E-CON than in P-CON. This suggests that SST anomalies would be amplified more strongly in coupled simulations using an explicit representation of convection.