Fisher Shannon analysis of drought/wetness episodes along a rainfall gradient in Northeast Brazil

We applied the informational approach of the Fisher‐Shannon method to study the time series of Standardized Precipitation Index (SPI) derived from monthly rainfall data at 133 gauging stations in Northeast (NE) Brazil. The climate in the study region ranges from tropical humid in the coastal area Zona de Mata to tropical semiarid inland Sertão, passing through a sub‐humid transition region Agreste. The time span is from 1962 to 2012, and SPI was calculated for 1, 3, 6, and 12 ‐ month time scales. We calculate information quantifiers Shannon entropy power (SEP) and Fisher information measure (FIM) that quantify signal disorder and structural organization, respectively, and define its position in the Fisher Shannon plane (FS). We find that the SPI‐1 series that describes short term dry/wet conditions display a higher degree of organization (higher FIM) and a lower degree of disorder (lower SEP) than SPI's that describe medium and long term conditions (SPI‐3, SPI‐6, and SPI‐12). By analysing the spatial distribution of information quantifiers, we find that short term dry/wet conditions (SPI‐1) show the lowest disorder and highest organization degree in the deep inland Sertão region and highest disorder and lowest organization degree in the coastal Zona de Mata region, while long term conditions (SPI‐12) show the opposite trend. For medium‐term conditions (SPI‐3 and SPI‐6), the SEP is highest and FIM lowest in the transition sub‐humid Agreste region. Our findings indicate that information theory‐based methods, particularly FS have the potential to discriminate among different climatic regimes. The Fisher‐Shannon method is an effective tool to describe the dynamics of complex signals. We used it to study the time series of Standardized Precipitation Index (SPI) derived from monthly rainfall data at 133 gauging stations in Northeast (NE) Brazil. We calculate the Shannon entropy power (SEP) (shown in the image) and Fisher information measure (FIM) to quantify signal disorder and structural organization of SPI at different time scales. Our findings indicate that information theory‐based methods, particularly FS have the potential to discriminate among different climatic regimes.