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The Indian Ocean Dipole (IOD) is the main coupled mode of interannual variability in the equatorial Indian Ocean. Despite its socio-economic importance, the Indian Ocean region suffers large biases in weather and climate models used for seasonal forecasts and climate projections.In this study, the performance of 42 models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) in reproducing the observed climate over the Indian Ocean is examined. We investigate whether the ability of a model to capture characteristics of the IOD and simulate IOD teleconnection patterns is related to its representation of the mean state. Skill metrics are calculated to quantify precipitation biases in the mean state during Boreal summer (JJA) in models from the Atmospheric Model Intercomparison Project (AMIP) and 20th-century historical all-forcings experiments. Cluster analysis is performed to determine whether biases in the seasonal cycle during JJA impact the response of the atmosphere to the IOD. The IOD behaviour in the AMIP and coupled models is assessed and the response of the atmospheric circulation to IOD forcing is examined by performing regression analysis. The next phase of this work will be to examine the development of systematic errors in the Indian Ocean in a seasonal forecasting system. The work will contribute to our understanding of Indian Ocean biases in weather and climate models, and their likely sources, and thus the wider implications for predictability of the IOD., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

17 USC 105 interim-entered record; under review. The article of record as published may be found at https://doi.org/10.1175/BAMS-D-19-0070.1 C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp. An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper. This research was funded by ONR Grant N00014-18-1-2472 as a Multidisciplinary Initiative. The Pacific Northwest National Laboratory is operated by BattelleMemorial Institute for the DOE under Contract DE-AC05-76 RL01830