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We developed the height correction algorithm based on the Monin–Obukhov similarity theory for application in Weather Research and Forecasting (WRF) model outputs to correct the 10-m height definition and match weather station observations. Thirty simulations were conducted for April 2012 to validate the height correction algorithm against observations such as the automated surface observing system and automatic weather stations. The WRF model simulations were constructed with two nested domains with horizontal grid spacings of 10 and 1 km. The root mean square error of the diagnosed 10-m wind speed after applying the height correction algorithm was consistently reduced compared to the one before applying the algorithm over the innermost domain during the analysis period. The impact of the height correction on diagnosed wind speed was greater when the environment was unstable and the magnitude of the roughness length was large. Evaluation showed that a strong synoptic forcing condition results in a significant reduction in the bias of wind speed. • Developed the height correction algorithm based on Monin–Obukhov similarity theory. • The 10-m height definition in the model is corrected to match the height of observation. • Alleviated positive bias in wind speed of weather research and forecasting model. [ABSTRACT FROM AUTHOR]

Arctic tundra is undergoing a rapid transition due to global warming and will be exposed to snow-free conditions for longer periods under projected climate scenarios. Regional climate modeling is useful for understanding and predicting climate change in the Arctic tundra, however, the lack of in-situ observations of surface energy fluxes and the planetary boundary layer (PBL) structure hinders accurate predictions of local and regional climate around the Arctic. In this study, we investigate the performance of the Polar-optimized version of the Weather Research and Forecasting model (PWRF) in the Arctic tundra on clear days in summer. Based on simultaneous observations of surface fluxes and the PBL structure in Cambridge Bay, Nunavut, Canada, our validation shows that the PWRF simulates a drier environment, leading to a larger Bowen ratio and a warmer atmosphere compared to observations. Further sensitivity analyses indicate that the model biases are mainly from the uncertainties in physical parameters such as surface albedo and emissivity, the solar constant, and the model top height, rather than structural flaws in the model physics. Importantly, the PWRF reproduces the observations more accurately when the observed soil moisture is fed into the simulation. This indicates that there must be improvements in simulations of the land-atmosphere interaction at the Arctic tundra, not only in the accuracy of the initial soil moisture conditions but also in soil hydraulic properties and drainage processes. The mixing diagram analysis also shows that the entrainment process between the PBL and the overlying atmosphere needs to be improved for better weather and climate simulation. Our findings shed light on modeling studies in the Arctic region by disentangling the model error sources from uncertainties by parameters and physics package options. • Arctic tundra is exposed to warmer conditions with a warming global climate. • Polar WRF has bias in simulating climate near the surface on clear summer days. • Polar WRF reproduces the observations accurately with the observed soil moisture. • Regional climate simulation improves with proper numerical design over the Arctic. [ABSTRACT FROM AUTHOR]