Impact of high‐resolution ocean–atmosphere coupling on fog formation over the North Sea

Abstract

Sea‐surface temperature (SST) is a key driver for various interactions and feedbacks between components of the Earth System and can control local weather and climate. The formation of marine fog, for example, can be sensitive to small changes in SST at a scale of a few kilometres. As a contribution to understanding processes at the interface between air and sea, this article discusses results from a state‐of‐the‐art fully coupled regional atmosphere–land–ocean–wave prediction system for the UK at km scale. This study focuses on the impact of the changes in surface forcing resulting from coupling SST in the marine boundary layer and formation of summertime coastal fog over the North Sea. A study from July 2013 provided a good case to evaluate the role of SST in fog evolution. The benefit of an evolving SST in the coupled simulation is shown in capturing a warming trend in observed SST over the five‐day case study period, with a root‐mean‐square error (RMSE) against in situ observations of 1.1 K. In contrast, in uncoupled atmosphere‐only simulations, the initial‐condition SST is persisted for the duration of the case, as is more typical in current operational numerical weather prediction (NWP). In the uncoupled simulations, a cold bias develops over the modelling period and the RMSE against observed SST is 2.4 K. The impact of coupling is shown to propagate into the overlying marine boundary layer and therefore affect the formation of coastal fog. Increased heat flux from a relatively warmer sea surface in the coupled simulations led to near‐surface atmospheric instability, hampering stratus lowering and destroying the fog‐promoting inversion layer. This significantly reduced fog fractions in selected regions. The value of model coupling was assessed by comparing coupled and uncoupled simulations initialized at different times ahead of fog development.

Impact of a sharp, small‐scale SST front on the marine atmospheric boundary layer on the Iroise Sea: Analysis from a hectometric simulation

“…For instance, a better forecast of the near-surface temperature and dew-point can improve the forecast of clouds and fog formation and dissipation at sea and near the coasts (e.g. Fallmann et al, 2019). Assessing the possible impact of the Ushant SST front either on the local weather or on the climate was not the subject of the present high-resolution study, but it is certainly a matter of interest and dedicated studies should address this point in the near future.…”

The UKC3 regional coupled environmental prediction system

“…The impact of coupling on the atmospheric boundary layer and associated features such as cloud development and near surface visibility are the subject of ongoing research, focussing on more specific case studies periods and regions of interest (e.g. Fallmann et al, 2018). Table 11 summarises the typical computational resource usage and run times for a day of simulation on the Met Office Cray 25 XC40 for each configuration used.…”

“…The four monthly experiments presented here also represent the first runs conducted of the UKC3 (or UKC2) system of extended duration beyond the 5-day case study duration simulations described by Lewis et al (2018), or used in the studies of Fallmann et al, (2017) and Fallmann et al, (2018). That the results continue to show robust and representative predictions 5 across atmosphere, ocean and surface wave components in coupled mode throughout these periods provides confidence in the scientific integrity of these tools, and of their suitability for application over longer-timescales in future.…”

“…While based on observations over land, this change 10 is considered important in the context of the UK regional coupled prediction system development given the strong sensitivity of fog and near surface cloud to air-sea coupling (e.g. Fallmann et al, 2017;Fallmann et al, 2018).…”

The Role of Stakeholders in Creating Societal Value From Coastal and Ocean Observations

“…One specific case is that of the presence of fog at airports can which lead to delays and cancellations and in turn economic penalties and reputational damage to airlines (Roquelaure and Bergot, 2009). Fog has been shown to be particularly sensitive to air-sea interactions (Fallmann et al, 2019) and as such forecasts of fog can only be improved by ocean observations and derived models. San Francisco International Airport (SFO) provides a real case of where an improved knowledge of fog and low cloud would be advantageous.…”