A Review: Anomaly-Based versus Full-Field-Based Weather Analysis and Forecasting

Abstract

AbstractComparisons between anomaly and full-field methods have been carried out in weather analysis and forecasting over the last decade. Evidence from these studies has demonstrated the superiority of anomaly to full field in the following four aspects: depiction of weather systems, anomaly forecasts, diagnostic parameters, and model prediction. To promote the use and further discussion of the anomaly approach, this article summarizes those findings. After examining many types of weather events, anomaly weather maps show at least five advantages in weather system depiction: 1) less vagueness in visually connecting the location of an event with its associated meteorological conditions, 2) clearer and more complete depictions of vertical structures of a disturbance, 3) easier observation of time and spatial evolution of an event and its interaction or connection with other weather systems, 4) simplification of conceptual models by unifying different weather systems into one pattern, and 5) extension of model forecast length due to earlier detection of predictors. Anomaly verification is also mentioned. The anomaly forecast is useful for raising one’s awareness of potential societal impact. Combining the anomaly forecast with an ensemble is emphasized, where a societal impact index is discussed. For diagnostic parameters, two examples are given: an anomalous convective instability index for convection, and seven vorticity and divergence related parameters for heavy rain. Both showed positive contributions from the anomalous fields. For model prediction, the anomaly version of the beta-advection model consistently outperformed its full-field version in predicting typhoon tracks with clearer physical explanation. Application of anomaly global models to seasonal forecasts is also reviewed.