Paleosecas no nordeste do Brasil: diagnóstico e modelagem dos padrões de ocorrência em múltiplas escalas espaciais e temporais - Dias, Tyhago Aragão (2019)
Low-frequency climate variability is natural to the climate system and is part of the climatic evolution. Understand the climate variation modes is challenging due to the time-limited data. Such modes of variability are related to the impacts on the frequency and intensity of drought / flood events occurring in NEB, making the assessment of this risk dynamic. Water resource management systems are based on stationary series with a static risk. which may lead to misjudgment. An alternative to reduce the uncertainty and incorporate the dynamic risk in the management instruments, taking into account the low frequency variability with the paleoclimatic models of the Paleoclimatic Modeling Intercomparison Project (PMIP) and the proxies of the National Environmental Information Center (NCEI). This information was interpreted together with an instrumental database of Climate Research Unit (CRU) as well as data from Kaplan et al (2001) and historical data. Using time series decomposition techniques, the low frequency variability in the 20th century was evaluated for the observed data and paleoclimatic models for the Historical period (1950 to 2005), verifying the performance of the models in representing the region of study, and reproducing the statistics of drought / flood events. The analysis of the simulations of the Past1000 period (850 to 1850), can be used to detect the modes of variability in the decadal and multidecal scale, characterizing the droughts / floods for the whole studied period. The results suggest the existence of a low frequency variability, modifying the precipitation distribution and with consequences in the intensity and frequency of the events of droughts / floods in the NEB, indicating that these events are associated with the coupling oceans atmosphere. This suggests that the dynamic risk associated with low frequency variability needs to be incorporated into water resource management tools. This information can be used as support for adaptive planning, assisting decision-makers with a broader view of the risk of droughts.