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    Indonesian Throughflow, spatial–temporal variability, and its relationship to ENSO events in the Lombok Strait
    (2025-03-01)
    Lubis, Muhammad Zainuddin
    ;
    Situmorang, Edriyan
    ;
    Simanjuntak, Andrean V.H.
    ;
    Riama, Nelly F.
    ;
    Pasma, Gumilang R.
    Understanding the interactions between ocean currents and climate variability is crucial for predicting future oceanic and climatic shifts in the Lombok Strait and beyond. Our study examines the Lombok Strait from 2013 to 2018, focusing on the impact of interannual and seasonal variability driven by climatic events such as the El Niño-Southern Oscillation. Our findings reveal significant fluctuations in oceanographic parameters, including temperature, salinity, and ocean currents. The lowest recorded temperature was ∼27.2 °C, and the minimum salinity was ∼32.3 psu, linked to the strong El Niño event in 2015, which altered local rainfall and evaporation patterns. Analysis of meridional and zonal velocities showed enhanced water flow, with maximum meridional velocities reaching around ∼0.04 m/s and zonal velocities peaking at ∼0.18 m/s in early 2018. Seasonal variations in sea surface height show higher values during warmer months, reflecting the influence of ENSO phenomena. The vertical distribution of salinity indicated stratification, with values ranging from ∼27.5 psu to ∼34.0 psu across different depths, corresponding to water density ranging from 22.50 σ<inf>θ</inf> to 24.0 σ<inf>θ</inf>, highlighting the interaction between Pacific and Indian Ocean waters. Water mass transport averages at 100 m and 200 m show values of −1.21 ± 0.97 Sv and −1.350 ± 1.069 Sv, with the lowest transport occurring during the summer at −1.97 Sv with a depth range of 0–100 m, suggesting robust outflow. Our findings underscore the critical role of the ITF in shaping regional oceanographic conditions and their implications for global climate dynamics.
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    Urban rainfall in the Capitals of Brazil: Variability, trend, and wavelet analysis
    (2022-04-01)
    Oliveira-Júnior, José Francisco de
    ;
    Correia Filho, Washington Luiz Félix
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    Monteiro, Lua da Silva
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    Shah, Munawar
    ;
    Hafeez, Amna
    The patterns of urban rainfall in Brazil's capitals are critical, due to population growth and extreme weather. Therefore, the objectives are: i) to identify homogeneous rainfall groups and meteorological systems, ii) to evaluate the trend of the monthly rainfall time series and iii) to apply wavelet analysis to estimate the variance at different frequencies in the rainfall series in the capitals of the Brazil. Monthly rainfall data during 1960–2020 for 27 stations located in the capitals of Brazil were used. The data were flawed, and data imputation (mtsdi package) was applied via Fully Conditional Specification (FCS). Rainfall data were submitted to descriptive, exploratory statistics (boxplot), multivariate analysis (Cluster Analysis - CA) and the Mann-Kendall (MK) test. Seven CA methods (Ward, Single, Complete, Average, McQuity, Median and Centroid) were tested using the cophenetic correlation coefficient (CCC) with a significance level of 5%, the Average method obtained CCC > 0.81 (S). The CA identified three homogeneous regions (G1, G2 and G3) in the capitals of Brazil. The G1 group is formed by the capitals of the Northeast of Brazil (NEB), except for Boa Vista, (North of Brazil - NB). The G2 group is the largest group formed by the capitals of the Midwest (MWB), Southeast (SEB) and South (SB) of Brazil. The G3 group is the smallest group, with the capitals of the NB and some of the NEB. The capitals with the category of significant growth trend were only Porto Alegre and Florianópolis (SB), Vitória (SEB) and Belém (NB). The category of non-significant increase trend prevailed in most capitals of Brazil, with emphasis on the corridor formed between the NB and the Center-South, except for Natal (NEB). The without trend category prevailed in the North, Northeast and Midwest regions of Brazil. Monthly precipitation analyzes for trend detection purposes via Wavelet Analysis showed that ENSO phases are significant in rainfall variability in Brazilian capitals.