Evaluation of wind forecasts over Svalbard using the high-resolution Polar WRF with 3DVAR

Abstract

In this study, the performance of wind forecasts over Svalbard, located between the Arctic Ocean and the Norwegian Sea, was evaluated using the Polar Weather Research and Forecasting (PWRF) model and three-dimensional variational data assimilation (DA) system. The forecasts of the analysis-forecast cycling experiment using the PWRF 3DVAR were compared with those of the cold start experiment using reanalysis as the initial condition. Three strong wind cases that occurred during January and February 2011-2012 were selected, where polar lows were generated on the east coast of Greenland and generated a wind speed above 20 m s −1 in Svalbard. The wind speed forecasts for both cycling and cold start experiments were similar to the highest 10minute average wind speed for the last 1 hour (HAW). The average root mean square error (RMSE) of the forecasts in the cold start experiment from HAW was 3.78 m s −1 for three cases and was greater than that in the cycling experiment. The forecast performance in the cycling experiment was comparable to, or even better than, that in the cold start experiment, which implies that the cycling system with DA is more useful than the cold start system in forecasting polar weather to support research activities.

On the configuration of a regional Arctic Numerical Weather Prediction system to maximize predictive capacity

“…8-10, 15 March). For WS10, a modest improvement in wind over Svalbard is seen (1-7.5%) similar to what was reported by Kim et al (2019). For precip the impact is small or modest and mixed.…”

Polar low research: recent developments and promising courses of research

“…For instance, Renfrew et al (2021) have found that the gradients of the surface fluxes and near-surface atmospheric fields over the marginal ice zone simulated by Met Office's Unified Model (MetUM, Bush et al, 2020), which has a 2.2-km grid mesh, were not as sharp as observed during the Iceland-Greenland Seas Project (Renfrew et al, 2019) since the sea ice field in the surface boundary conditions was too smooth. When simulating PLs, the use of data assimilation provides better results compared to a "cold start" (i.e., using analyses and reanalyses) (Kim et al, 2019;Xue et al, 2021), and the assimilation of satellite radiances is recommended (Xue et al, 2021). Assimilating adaptively thinned cloud-cleared hyperspectral infrared radiances from the Atmospheric Infrared Sounder instrument on board the NASA Aqua satellite can have a positive impact on the representation of PLs (Ganeshan et al, 2022).…”

The stable atmospheric boundary layer over snow‐covered sea ice: Model evaluation with fine‐scale ISOBAR18 observations

“…A detailed comparison of the differences between these schemes is provided by Cohen et al (2015). All of these three boundary-layer schemes are, a priori, reasonable choices for mesoscale WRF simulations at either high latitudes or under stable stratification (Mäkiranta et al, 2011;Mayer et al, 2012;Cohen et al, 2015;Tastula et al, 2015;Kim et al, 2019). We want to verify the different WRF3D simulations against observations to determine the best-suited parametrization for air temperature and wind speed during IOP-14, so that we obtain a WRF3D model run that is accurate enough to provide boundary conditions for the SCM experiments on IOP-14 in Section 4.…”