Ozone and Aerosol Influence on Ultraviolet Radiation on the East Coast of the Brazilian Northeast

The purpose of this research is to determine the influence of Total Ozone and Aerosols about variability of Ultraviolet Radiation (UV) in the east coast of the Northeastern region of Brazil through measures from multispectral sensor GUV (Ground-based Ultraviolet Radiometer). The methodology consisted of descriptive study and cluster analyses using data of UV in channels UVB (305 nm) and UVA (320 nm, 340 nm and 380 nm) and data of UV index, Total Ozone, Aerosol, Global Solar Radiation, Cloudiness and Wind. The results for city of Natal indicated that an annual event occurs in September/October which stabilizes the UV or UV Index when Total Ozone levels reach their annual maximum. This event is influenced by marine Aerosol that is found on mainland at a higher concentration in September due to greater Wind intensity and their southeasterly direction (sea for land). The cluster analysis using the variables above allowed us to detect three different groups: the first group is formed by Natal, Recife and Jo?o Pessoa and so determined that this event occurs in these three cities;the second group is formed by Maceió, Aracaju and Salvador and the third group includes only Fortaleza and had different results.

UV Index Modeling by Autoregressive Distributed Lag (ADL Model)

The objective of this work is to model statistically the ultraviolet radiation index (UV Index) to make forecast (extrapolate) and analyze trends. The task is relevant, due to increased UV flux and high rate of cases non-melanoma skin cancer in northeast of Brazil. The methodology utilized an Autoregressive Distributed Lag model (ADL) or Dynamic Linear Regression model. The monthly data of UV index were measured in east coast of the Brazilian Northeast (City of Natal-Rio Grande do Norte). The Total Ozone is single explanatory variable to model and was obtained from the TOMS and OMI/AURA instruments. The Predictive Mean Matching (PMM) method was used to complete the missing data of UV Index. The results mean squared error (MSE) between the observed UV index and interpolated data by model was of 0.36 and for extrapolation was of 0.30 with correlations of 0.90 and 0.91 respectively. The forecast/extrapolation performed by model for a climatological period (2012-2042) indicated a trend of increased UV (Seasonal Man-Kendall test scored τ = 0.955 and p-value 0.001) if the Total Ozone remain on this tendency to reduce. In those circumstances, the model indicated an increase of almost one unit of UV index to year 2042.

Precipitation Extremes Analysis over the Brazilian Northeast via Logistic Regression

This work diagnosed the precipitation extremes over the Brazilian Northeast (NEB) based on logistic regression for obtaining associations between precipitation extremes and the meteorological variables by Odd Ratio (OR). Data of ten meteorological variables to the NEB (North (NNEB), East (ENEB), South (SNEB) and Semiarid (SANEB)) were used daily. The OR results evidenced that the outgoing longwave radiation was the key variable on the precipitation extremes detection in three sub-regions: ENEB with 2.91 times (95% confidence interval (CI): 2.11, 4.02), NNEB with 3.63 times (95% CI: 1.93, 6.83), and SANEB with 5.40 times (95% CI: 3.04, 9.61);while on SNEB, it was relative humidity with 3.88 times (95% CI: 2.89, 5.20) more chance to favor the precipitation extremes. The maximum temperature, zonal wind component, evaporation, specific humidity and RH also had influence on these extremes. Goodness-of-fit and ROC analysis demonstrated that all models had a good fit and good predictive capability.