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To understand and improve the performance and quality of Global Precipitation Measurement (GPM) satellite-derived precipitation products during the typhoon process, with gauge observations from ground meteorological stations, this study used the successive and optimal interpolation correction methods to correct the GPM precipitation products. The performance of GPM products (Version 6) before and after the correction at different time scales are evaluated with the products during the two landfalls of Typhon"In-Fa". Results show that the original GPM precipitation products fail to describe the strong rainfall center over the high terrain area, which significantly underestimates the precipitation by approximately 45%. This is mainly due to the underestimation of the large values in the northeast region of Zhejiang province. The analysis of precipitation classification inspection suggests that the uncorrected GPM satellite-derived products have good capability for light rain, but poor for other rainfall levels. After the successive and optimal interpolation correction, significant improvement can be found in the cumulative, daily, and hourly rainfall products. The products with successive correction are better, while the product with optimal interpolation slightly overestimates the actual precipitation. The corrected GPM products can not only describe the heavy precipitation center related to the terrain but also reflect heavy rainstorms and heavy precipitation with hourly rainfall intensity greater than 23 mm·h-1.

Numerical models and correct predictions are important for marine forecasting, but the forecasting results are often unable to satisfy the requirements of operational wave forecasting. Because bias between the predictions of numerical models and the actual sea state has been observed, predictions can only be released after correction by forecasters. This paper proposes a spatiotemporal interactive processing bias correction method to correct numerical prediction fields applied to the production and release of operational ocean wave forecasting products. The proposed method combines the advantages of numerical models and Forecast Discussion; specifically, it integrates subjective and objective information to achieve interactive spatiotemporal corrections for numerical prediction. The method corrects the single-time numerical prediction field in space by spatial interpolation and sub-zone numerical analyses using numerical model grid data in combination with real-time observations and the artificial judgment of forecasters to achieve numerical prediction accuracy. The difference between the original numerical prediction field and the spatial correction field is interpolated to an adjacent time series by successive correction analysis, thereby achieving highly efficient correction for multitime forecasting fields. In this paper, the significant wave height forecasts from the European Centre for Medium-Range Weather Forecasts are used as background field for forecasting correction and analysis. Results indicate that the proposed method has good application potential for the bias correction of numerical predictions under different sea states. The method takes into account spatial correlations for the numerical prediction field and the time series development of the numerical model to correct numerical predictions efficiently. [ABSTRACT FROM AUTHOR]