Impacto de modelos regionales de clima acoplados océano-atmósfera y de la alta resolución en la simulación de medicanes sobre el mar Mediterráneo: análisis multimodelo con las simulaciones de EURO-CORDEX y Med-CORDEX

Ponencia presentada en: XXXIV Jornadas Científicas de la AME y el XVII Encuentro Hispano Luso de Meteorología celebrado en Teruel, del 29 de febrero al 2 de marzo de 2016

The worldwide C3S CORDEX grand ensemble: A major contribution to assess regional climate change in the IPCC AR6 Atlas

peer reviewedAbstract The collaboration between the Coordinated Regional Climate Downscaling Experiment (CORDEX) and the Earth System Grid Federation (ESGF) provides open access to an unprecedented ensemble of Regional Climate Model (RCM) simulations, across the 14 CORDEX continental-scale domains, with global coverage. These simulations have been used as a new line of evidence to assess regional climate projections in the latest contribution of the Working Group I (WGI) to the IPCC Sixth Assessment Report (AR6), particularly in the regional chapters and the Atlas. Here, we present the work done in the framework of the Copernicus Climate Change Service (C3S) to assemble a consistent worldwide CORDEX grand ensemble, aligned with the deadlines and activities of IPCC AR6. This work addressed the uneven and heterogeneous availability of CORDEX ESGF data by supporting publication in CORDEX domains with few archived simulations and performing quality control. It also addressed the lack of comprehensive documentation by compiling information from all contributing regional models, allowing for an informed use of data. In addition to presenting the worldwide CORDEX dataset, we assess here its consistency for precipitation and temperature by comparing climate change signals in regions with overlapping CORDEX domains, obtaining overall coincident regional climate change signals. The C3S CORDEX dataset has been used for the assessment of regional climate change in the IPCC AR6 (and for the interactive Atlas) and is available through the Copernicus Climate Data Store (CDS)

The added value of high resolution in estimating the surface mass balance in southern Greenland

The polar version of the regional climate model RACMO2, version 2.3p1, is used to study the effect of model resolution on the simulated climate and surface mass balance (SMB) of south Greenland for the current climate (2007–2014). The model data at resolutions of 60, 20, 6.6, and 2.2 km are intercompared and compared to SMB observations using three different data refinement methods: nearest neighbour, bilinear interpolation, and a statistical downscaling method utilising the local dependency of fields on elevation. Furthermore, it is estimated how the errors induced by model resolution compare to errors induced by the model physics and initialisation. The results affirm earlier studies that SMB components which are tightly linked to elevation, like runoff, can be refined successfully, as soon as the ablation zone is reasonably well resolved in the source dataset. Precipitation fields are also highly elevation dependent, but precipitation has no systematic correlation with elevation, which inhibits statistical downscaling to work well. If refined component-wise, 20 km resolution model simulations can reproduce the SMB ablation observations almost as well as the finer-resolution model simulations. Nonetheless, statistical downscaling and regional climate modelling are complementary; the best results are obtained when high-resolution RACMO2 data are statistically refined. Model estimates in the accumulation zone do not benefit from statistical downscaling; hence, a resolution of about 20 km is sufficient to resolve the majority of the accumulation zone of the Greenland Ice Sheet with respect to the limited measurements we have. Furthermore, we demonstrate that using RACMO2, a hydrostatic model, at 2.2 km resolution led to invalid results as topographic and synoptic vertical winds exceed 10 m s−1, which violates the hydrostatic model assumptions. Finally, additional tests show that model resolution is as important as properly resolving spatial albedo patterns, correctly initialising the firn column, and uncertainties in the modelled precipitation and turbulent exchange