Application of Probability Density Function Matching Method for Visibility Forecasting in Xinjiang of China

Visibility greatly impacts people's daily activites, such as transportation. However, numerical models often exhibit substantial errors in visibility forecasting. The objective of this study is to reduce the systematic errors in visibility forecasting products from the European Center for Medium-Range Weather Forecasts (ECMWF), thereby enhancing the forecasting performance. Taking the visibility observations from 105 national meteorological stations in Xinjiang of China as an objective criteria, the visibility forecasts from model products of the ECMWF within the 72-hour forecast period from November 2022 to March 2023 are corrected using the probability density function (PDF) matching method. On this basis, an objectively-corrected forecasting product with an interval of 3-h is established for the next three days in Xinjiang through a rolling modeling approach, and the visibility forecasts before and after correction are further evaluated and analyzed. The results show that the visibility in ECMWF forecasts is overestimated under low-visibility conditions in most areas of Xinjiang. The PDF matching method can effectively reduce these errors, with all evaluation metrics being obviously improved after the correction. The forecasted visibility within the 72-hour forecast period before correction is 3.3–3.8 km higher than the observation, while it is 1.4–2.1 km lower than the observation after correction, with the mean absolute error being reduced by over 20%. For forecasts of visibility below 1 km, the threat score increases from 0.05 to 0.09 after correction. Spatially, 88 stations across Xinjiang exhibit positive improvement with varying degrees, mainly concentrated in the urban agglomerations on the northern slope of Tianshan Mountains (with the improvement exceeding 70%) and in most areas of southern Xinjiang (with the improvement ranging from 50% to 70%). Additionally, the analysis of typical fog-haze and sand-dust weather processes further reveals that the visibility corrected using the PDF matching method becomes much closer to the observations, providing more accurate references for visibility forecasting of Xinjiang meteorological departments.