Assessment of Nowcasting Precipitation Schemes Initialized from LAPS Analysis Fields over the Attica Region

Accurate short-term precipitation nowcasting remains challenging in complex terrain regions, where storm displacement, evolution, and orographic enhancement strongly affect precipitation distribution. This study evaluates three precipitation nowcasting schemes initialized from LAPS analysis fields: first-order advection (Control), advection–diffusion (AD), and advection–diffusion coupled with the linear theory of orographic precipitation (ADLOP). The schemes are tested over the Attica region of Greece using three high-impact precipitation events representing different synoptic weather regimes and verified against high-resolution weather radar observations. Forecast performance is assessed using continuous, categorical, and neighborhood-based spatial verification metrics. Results show that the Control performs competitively for light precipitation and at larger neighborhood sizes in localized events. The inclusion of diffusion in the AD scheme generally reduces random errors. In this limited three-case sample, aggregated results show that ADLOP reduces systematic bias, with reductions reaching approximately 33% at longer lead times and showing higher detection scores. However, its added value is strongly dependent on the terrain-influenced precipitation regime and may be accompanied by increased error at longer lead times. Overall, the benefits of incorporating diffusion and simplified linear orographic forcing depend on precipitation regime, lead time, and verification metric; therefore, the results should be interpreted as diagnostic case-study evidence rather than as a general assessment of ADLOP performance.