The impact of time‐varying sea surface temperature on UK regional atmosphere forecasts. (24th March 2021) - Mahmood, Sana; Lewis, Huw; Arnold, Alex; Castillo, Juan; Sanchez, Claudio; Harris, Chris
Abstract: A new approach to improve the ocean surface boundary condition used in regional numerical weather prediction is proposed. Typically, regional atmosphere forecast systems assume a fixed sea surface temperature during a simulation. The study assesses the use of ocean temperature from an operational regional ocean model as an evolving lower boundary in a kilometre‐scale regional atmosphere configuration centred on the UK. Simulations of a winter and two five day duration summer case studies associated with anomalously warm temperatures are considered. The largest impact is found in summer, when a growing cold bias in mean temperature over land compared with observations is apparent when using a fixed global‐scale analysis lower boundary condition. The mean error is improved by 0.1 K when using a fixed temperature boundary condition from a kilometre‐scale regional ocean model initial condition. When using hourly surface temperature data from the same regional ocean model, the error is improved by 0.5 K for this case. Prediction of daytime maximum air temperature is also improved during the summer heat wave cases. A winter case study shows marginal improvement over the ocean and negligible changes over land. These results are confirmed in longer duration experiments using an hourly cycling regional forecast system with data assimilation for summer and winter periods. A systematic and statistically significant improvement of near‐surface temperature verification relative to the observations over land is demonstrated for both summer and winter using the new approach. This study supports future operational implementation of a time‐varying lower boundary for regional numerical weather prediction. Abstract : Using ocean temperatures from an operational regional ocean model as an evolving lower boundary improves regional numerical weather prediction simulation of mean and maximum temperature. Case study results show a cold bias is improved by 0.5 K when using the proposed approach for a time‐varying lower boundary. An extended operational‐like simulation experiment demonstrates systematic and statistically significant improvement of near‐surface temperature verification relative to the observations over land for the summer and winter.