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Kilometre-scale Weather Research and Forecasting (WRF) simulations over terrain with steep slopes often require strong smoothing to prevent numerical instability, but conventional domain-wide filters alter terrain at every grid point, regardless of whether local slopes require reduction. Slope-Constrained Orography (SCO) is an offline terrain preprocessing method that prescribes a target slope angle θ and adjusts only those grid points whose eight-neighbour elevation differences exceed the implied bound, leaving the remaining terrain unchanged while permitting stable numerical integration. By prescribing the slope constraint directly, SCO replaces the trial-and-error of filter-based smoothing with a single, geometrically interpretable control parameter. In a 1 km WRF case over the highly complex terrain of the southeastern Tibetan Plateau, the least-modified stable SCO member modifies 14 % of points with a mean elevation change of 8.2 m, compared with 100 % modification and 108.1 m for the corresponding WRF Preprocessing System (WPS) member. The stable SCO member produces lower near-surface wind and temperature errors in this case, consistent with improved terrain representation.
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Ma et al. (2026) studied this question.
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