Operationalisation of the NAO and EA indices for climate monitoring and seasonal variability assessment in Mainland Portugal

This work assesses the relationship between the IPMA-computed NAO (North Atlantic Oscillation) and EA (East-Atlantic) indices, determined using ERA5 reanalysis, and climate variability over mainland Portugal. Additionally, it aims to operationalise both indices for routine production and public dissemination. Both indexes were computed using a methodology based on NOAA reference computations of NAO and EA. The results show that NAO-IPMA index shows a moderate-to-strong correlations with the NOAA reference index and with precipitation anomalies over mainland Portugal, particularly during the extended winter season (November to March; NDJFM), when the influence of the North Atlantic Oscillation (NAO) is most pronounced.

This way, the relationship between the NAO-IPMA index and precipitation anomalies over mainland Portugal is significant between December and March, with negative correlations ranging from −0.6 to −0.7, peaking in February. Thus, it is highlighted the key role of the NAO in modulating winter precipitation in mainland Portugal, with negative (positive) NAO phases associated with wetter (drier) conditions. In contrast, the relationship with mean air temperature is generally weak. The joint analysis of the NAO-IPMA and EA-IPMA indices with the rainfall anomaly proxy index (Standardized Precipitation Index; SPI-3) supports these results, showing that wetter periods tend to occur under negative NAO conditions or when negative NAO coincides with a positive EA. In contrast, drier periods are associated with positive NAO or the combination of a positive NAO and negative EA.

The assessment of the seasonal forecasting system ECMWF SEAS5.1 indicates limited predictive skill for the NAO and EA, with moderate correlations only for the forecast month (lead time = 0) between January and March, followed by a rapid decline in skill as lead time increases. Overall, the NAO-IPMA and EA-IPMA are robust indexes for climate monitoring and interpretation of precipitation variability over mainland Portugal, particularly during winter, even though seasonal predictability remains limited. Nevertheless, the operational implementation and combined use of the NAO and EA indices, together with proxy indicators for rainfall anomalies, such as the SPI, can help understand atmospheric conditions leading to wetter or drier periods, thereby supporting improved monitoring and prediction of climate variability in mainland Portugal.