Impacts of initial conditions and model configuration on simulations of polar lows near Svalbard using Polar WRF with 3DVAR

Abstract

The impacts of initial conditions and model configuration on the simulations of polar lows (PLs) near Svalbard, the global “hotspot” for PL activity, were investigated using the Polar Weather Research and Forecasting (Polar WRF or PWRF) model and WRF three‐dimensional data assimilation (3DVAR). The well‐documented PL case presented by Sergeev et al., in 2017 from March 26, 2013 featuring in situ aircraft observations is revisited using PWRF and 3DVAR to identify the most suitable model configuration to simulate PLs. The simulation results using initial conditions from PWRF and 3DVAR cycling runs were compared with those of cold‐start experiments using reanalysis as the initial condition. For cycling runs, the impacts of initial conditions from synoptic observations together with satellite radiances were superior to the assimilation of synoptic data alone. Several additional experiments were undertaken to further refine the PWRF configuration by considering the horizontal resolution, analysis nudging, digital filter initialization, and two boundary‐layer and four microphysics schemes. Based on the chosen configuration of Polar WRF and 3DVAR from the case‐study, the monthly reanalysis mode with 3 hr time window cycling data assimilation and short‐term forecasts using PWRF alone were performed for March 2013 and the PLs that formed over the Nordic Seas were evaluated. Manual identification and verification of PLs were performed using thermal infrared satellite imagery and 10 m scatterometer winds. Overall, nine PLs were identified in addition to the case presented by Sergeev et al., in 2017. Both the case‐study and monthly simulation results show that the high‐resolution initial condition is the most important factor, but a reasonable forecast model configuration can help to improve the simulation performance. Satellite radiance data are very important for producing the high‐resolution initial conditions for Polar WRF to simulate PLs successfully; the best performance was obtained by assimilating both synoptic data and satellite radiances.

Evaluation of Performance of Polar WRF Model in Simulating Precipitation over Qinghai-Tibet Plateau

“…Polar WRF is based on the standard WRF (ARW) and has been improved by the Polar Meteorology Group at the Byrd Polar and Climate Research Center of Ohio State University. The primary task of the modifications is to make the model keep state-of-the-art skills in operational weather forecasting and research simulation over polar regions (Xue et al [66] ; Bromwich et al [67] ; Wilson et al [72,73] ; Kumar et al [74] ; Powers et al [75,76] ; Walsh et al [77] ). Hence, it focuses on the "polar environmental characteristics" such as optimizing heat transfer for ice sheets and revised surface energy balance in the Land Surface Model (LSM), comprehensively describing the ice, snow process, and optimal treatment of the ice/snowair feedback, improving and testing cloud microphysics for polar conditions.…”

“…The results of the benchmark over the Antarctic and the Southern Ocean indicate that the model has good skills for variables, including surface and vertical of the atmosphere, for intraannual variations in large-scale atmospheric circulation (Xue et al [65] ). For the polar mesoscale system, the model was applied over the Arctic region by simulating polar lows that demonstrated good performance (Xue et al [66] ). Considering the model performance under multiple polar conditions and the better utilization experience needed to investigate further, the Polar WRF V4.1.1 is continuously utilized in this study.…”

“…Inherited from the WRF, Polar WRF can afford to nudge u, v, t, and q from driving fields with spectral and grid nudge methods. Previous studies have shown that model skills are very sensitive to nudge settings when long-term runs or dynamic aspects need to be addressed (Xue et al [66] ; Cha et al [100] ; Liu et al [101] ; Otte et al [102] ; von Storch et al [103] ). Therefore, the 6 experiments (nudging category in Table 1 ) for methods and nudging coefficients are investigated to increase the knowledge of nudging settings.…”

“…Here, MPs are studied based on the research advances that have been extensively tested in the Arctic, Antarctica, and TP (Gao et al [48] ; You et al [49] ; Xue et al [65,66] ; Bromwich et al [68] ; Hines et al [78] ; Hines and Bromwich [80] ; Gao et al [97] ; Qian et al [106] ; Zhu et al [116] ; Li et al [117] ; Ma et al [118] ; Shen et al [119] ; Yang et al [120] ; Zhang et al [121] ). Modify the liquid water droplet concentration in Morrison 2-mom to 50 cm -3 which has been verified to significantly improve the performance of polar clouds such as supercooled water in clouds (Xue et al [66] ; Hines et al [78] ; Hines and Bromwich [80] ). TP, similar to the Antarctic and Arctic, is a colder region, and the liquid water of clouds more easily exists in the form of supercooled water.…”

“…This study aims to (1) investigate the impacts of multiple options to study the "better-performing" configuration suite enhancing the accuracy and reliability representation of precipitation for using Polar WRF; (2) generally evaluate whether precipitation can be reasonably simulated with this polaroptimized model over the TP by a full calendar year and thus are more statistically robust than sensitivity test and case studies. This investigation is also an extension of the utilization and test of the Polar WRF (V4.1.1) beyond the Antarctic and Arctic (Xue et al [65,66] ). It follows the series of verification studies documenting ongoing Polar WRF comprehensive evaluations and focuses on the "hottest topics" of modeling precipitation over the TP.…”