Increase in the number of explosive low‒level cyclones around King George Island in the last three decades.

This paper documents an increase in the number of observed explosive cyclones (EC) at King George Island, South Shetland Islands, Antarctica, over the 1989‒2020 period. In ECs at 60o latitudes the surface atmospheric pressure drops ≥24 hPA in 24 hours. The annual EC frequency time series shows a significant positive trend of ~2.7 cyclones/decade, with a break in 2003 and average numbers of 7.3 and 11.8 events before and after that break, respectively. The increase follows closely earlier documented global sea surface temperature (SST) anomaly trends for the 1981‒2018 period, partially attributed to global warming and to the Pacific Decadal Oscillation (PDO). Connections between EC frequency and SST might occur through variations in SST in the southeastern Pacific and southwestern Atlantic, with anomalous cold conditions favoring an increase in ECs. We also found close relations between the number of ECs with simultaneous occurrences of PDO and Atlantic multidecadal oscillation in opposite phases, so that after 2003 they were in the cold and warm phases, respectively, and vice-versa before 2003. Both low-frequency modes seem to modulate the number of ECs. As per the authors knowledge these results have not been discussed before and may help climate modeling studies and weather forecasts.

Missing data estimation in extreme rainfall indices for the Metropolitan area of Cali - Colombia: An approach based on artificial neural networks.

Changes observed in the current climate and projected for the future significantly concern researchers, decision-makers, and the general public. Climate indices of extreme rainfall events are a trend assessment tool to detect climate variability and change signals, which have an average reliability at least in the short term and given climatic inertia. This paper shows 12 climate indices of extreme rainfall events for annual and seasonal scales for 12 climate stations between 1969 to 2019 in the Metropolitan area of Cali (southwestern Colombia). The construction of the indices starts from daily rainfall time series, which although have between 0.5% and 5.4% of missing data, can affect the estimation of the indices. Here, we propose a methodology to complete missing data of the extreme event indices that model the peaks in the time series. This methodology uses an artificial neural network approach known as Non-Linear Principal Component Analysis (NLPCA). The approach reconstructs the time series by modulating the extreme values of the indices, a fundamental feature when evaluating extreme rainfall events in a region. The accuracy in the indices estimation shows values close to 1 in the Pearson's Correlation Coefficient and in the Bi-weighting Correlation. Moreover, values close to 0 in the percent bias and RMSE-observations standard deviation ratio. The database provided here is an essential input in future evaluation studies of extreme rainfall events in the Metropolitan area of Cali, the third most crucial urban conglomerate in Colombia with more than 3.9 million inhabitants.

Comparison of spatial interpolation methods for annual and seasonal rainfall in two hotspots of biodiversity in South America.

The Colombian Biogeographic Choco (CBC) and the La Plata Basin (LPB) are regions with high biodiversity. However, these areas are characterized by scarce climatological information, complex orography, and rain-gauge network unevenly distributed. Interpolated data from the ground station might overcome these aspects. For this reason, is necessary to identify the best technique for the spatial interpolation of rainfall. Hence, the spatial interpolation techniques were applied to annual and seasonal rainfall in the CBC and LPB. Geostatistical results and deterministic approaches were compared by cross-validation. Cokriging with spherical (gaussian) model is the best interpolator in the CBC (LPB), as indicated by the lowest root mean square error (RMSE) and a standardized RMSE close to one. The CBC shows three rainfall cores: the northern, 9,000 mm/year; the central-southern, 10,000 mm/year; and the southern, 7,000 mm/year. The LPB shows a west-east rainfall gradient, with a minimum to the west (450 mm/year) and a maximum in the mid-west (2,000 mm/year). To the north of the LPB, rainfall reaches 1,500 mm/year, while in the south it reaches only 900 mm/year. The results in our study may be useful for scientists and decision-makers for use in environmental and hydrological models for the CBC and the LPB.

Impact of biomass burning on a metropolitan area in the Amazon during the 2015 El Niño: The enhancement of carbon monoxide and levoglucosan concentrations.

Extreme droughts associated with changes in the climate have occurred every 5 years in the Amazon during the 21st century, with the most severe being in 2015. The increase in biomass burning (BB) events that occurred during the 2015 drought had several negative socioeconomic and environmental impacts, one of which was a decrease in the air quality. This study is an investigation into the air quality in the Manaus Metropolitan Region (MMR) (central Amazon, Brazil) during the dry (September to October) and wet (April to May) seasons of 2015 and 2016. A strong El Niño event began during the wet season of 2015 and ended during the wet season of 2016. Particulate matter samples were collected in the MMR during 2015 and 2016, and analyses of the satellite-estimated total carbon monoxide (CO) column and observed levoglucosan concentrations were carried out. Levoglucosan has been shown to be significantly correlated with regional fires and is a well-established chemical tracer for the atmospheric particulates emitted by BB, and CO can be treated as a gaseous-phase tracer for BB. The number of BB events increased significantly during the El Niño period when compared to the average number during 2003-2016. Consequently, the total CO column and levoglucosan concentration values in the MMR increased by 15% and 500%, respectively, when compared to the normal conditions. These results indicate that during the period that was analyzed, the impacts of BB were exacerbated during the strong El Niño event as compared to the non-El Niño period. In this study, we provided evidence that the air quality in the MMR will degrade in the future if droughts and BB occurrences continue to increase.