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In tropical coastal environments, simulating the diurnal cycle of wind and precipitation in numerical weather and climate models presents unique challenges due to the interaction of intraseasonal and mesoscale dynamics. This can lead not only to incorrect short-term weather forecasts but also to unphysical energy and momentum transport by convective processes. In particular, the sea/land-breeze circulation and its role in initiating convection has been identified as a possible source of errors in the timing and offshore extent of coastal precipitation in the Tropics. In this study, the offshore land/sea breeze around Darwin, Australia, is examined using scatterometer wind observations and two regional atmospheric models. Although the comparison is limited by satellite swath times which cluster around two times of day, useful results are obtained by sub-sampling the simulated data to match the coverage of the scatterometer data. We find that offshore surface sea-breeze characteristics (intensity and horizontal spatial extent) from the models and satellite estimates are generally in good agreement, with intensity differences less than 2 m s−1, and offshore extents not varying by more than approximately 150 km. The variation in offshore extent and amplitude of the land/sea-breeze wind perturbations with monsoon regime is well simulated. Furthermore, despite the simplifying assumptions of linear sea-breeze theory, the model and scatterometer results are in broad agreement with theoretical values, particularly in the presence of the weak background winds during the monsoon break period. [ABSTRACT FROM AUTHOR]

ABSTRACT High-quality tall mast and wind lidar measurements over the North and Baltic Seas are used to validate the wind climatology produced from winds simulated by the Weather, Research and Forecasting ( WRF) model in analysis mode. Biases in annual mean wind speed between model and observations at heights around 100 m are smaller than 3.2% at offshore sites, except for those that are affected by the wake of a wind farm or the coastline. These biases are smaller than those obtained by using winds directly from the reanalysis. We study the sensitivity of the WRF-simulated wind climatology to various model setup parameters. The results of the year-long sensitivity simulations show that the long-term mean wind speed simulated by the WRF model offshore in the region studied is quite insensitive to the global reanalysis, the number of vertical levels, and the horizontal resolution of the sea surface temperature used as lower boundary conditions. Also, the strength and form (grid vs spectral) of the nudging is quite irrelevant for the mean wind speed at 100 m. Large sensitivity is found to the choice of boundary layer parametrization, and to the length of the period that is discarded as spin-up to produce a wind climatology. It is found that the spin-up period for the boundary layer winds is likely larger than 12 h over land and could affect the wind climatology for points offshore for quite a distance downstream from the coast. [ABSTRACT FROM AUTHOR]

The Maritime Continent is a densely populated area of complex topography located between the Pacific and Indian Oceans. It is an area where model skill is particularly important but also difficult to obtain. In this study we examine interannual austral summer rainfall variability in the region and the teleconnection to the El Niño–Southern Oscillation (ENSO) in observation‐based data, reanalyses, and global and regional atmosphere‐only model simulations. We show that model ability to capture interannual rainfall variability is strongly related to model skill in reproducing the ENSO teleconnection to the region, despite strong spatial variability in the ENSO‐rainfall response in coastal areas. Model ability in capturing the spatial pattern of both the midtropospheric moisture and circulation response to ENSO is a strong predictor for model performance in capturing the ENSO‐Maritime Continent rainfall teleconnection. High‐resolution regional simulations and better performing models have opposing ENSO‐rainfall teleconnections between land and sea areas. Plain Language Summary: The Maritime Continent experiences substantial rainfall variability resulting in droughts and flooding. It is also a region of complex topography that is poorly resolved in global climate models. Here we analyze the year‐to‐year rainfall variability of the region in more detail. We find that models that perform well in capturing year‐to‐year variability have more realistic teleconnections to the El Niño–Southern Oscillation (ENSO). Models that have better represented ENSO‐rainfall relationships capture the observed spatial pattern of both the atmospheric moisture and circulation responses to ENSO. A high‐resolution model exhibits much more detailed representation of the atmospheric state with opposing ENSO‐rainfall relationships over land and sea that are not captured by the worst performing global models. The large range in model performance in the region should be considered when making climate projections for the Maritime Continent. Key Points: There is a large range in model skill in capturing interannual Maritime Continent rainfall variabilityMore skillful models capture El Niño–Southern Oscillation (ENSO) teleconnection to midlevel moisture and circulation over regionA high‐resolution regional model shows a different ENSO‐moisture teleconnection over land and sea that is missing from some global models [ABSTRACT FROM AUTHOR]