Wet Days in the Dry Quarter of the Alcântara Launch Center Region: Observational Features

Abstract

Precipitation events are infrequent in the dry quarter (SON) of the Alcântara Launch Center (Centro de Lançamento de Alcântara, CLA), the main launch site of the Brazilian Space Program. However, their occurrence could be a risk for activities during launch missions. In this work, the observational features of wet days (daily precipitation total ≥ 1 mm/day) in the dry quarter of the CLA region were studied. Daily precipitation totals over the course of 37 years (1979-2016, except 2006), outgoing longwave radiation (OLR) data and ERA-Interim reanalysis data were used. On average, in the dry quarter, there were 9 wet days, which accumulated 32 mm. The number and quarterly precipitation total of wet days showed pronounced interannual variability. This variability was negatively and significantly correlated with the interhemispheric sea surface temperature anomalies gradient in the Atlantic Ocean and the wind speed at 925 hPa over the CLA region. Based on a theoretical distribution (log-normal), the probability of occurrence of heavy precipitation days (daily total ≥ 10 mm/day) was only 0.5%. For days with heavy precipitation and deep convection (OLR ≤ 230 W·m-2), over a large area along the northeastern coast of South America including the CLA region, negative OLR differences (from the mean) and the strengthening of favorable conditions for deep convection were found. The large-scale organization of the convective activity and atmospheric features for higher precipitation events obtained in this work could be helpful for nowcasting and short-range weather forecasting during launch missions at the CLA.

Impact of the Indian Ocean SST on Wintertime Total Column Ozone Over the Tibetan Plateau

“…The SST data are obtained from the U.K. Met Office Hadley Center for Climate Prediction and Research SST (HadSST) dataset (Rayner et al, 2003). The outgoing longwave radiation (OLR) data are from the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (Costa et al, 2019;Liebmann & Smith, 1996).…”