Hydro-climatic and ecological behaviour of the drought of Amazonia in 2005

In 2005, southwestern Amazonia experienced the effects of an intense drought that affected life and biodiversity. Several major tributaries as well as parts of the main river itself contained only a fraction of their normal volumes of water, and lakes were drying up. The consequences for local people, animals and the forest itself are impossible to estimate now, but they are likely to be serious. The analyses indicate that the drought was manifested as weak peak river season during autumn to winter as a consequence of a weak summertime season in southwestern Amazonia; the winter season was also accompanied by rainfall that sometimes reached 25% of the climatic value, being anomalously warm and dry and helping in the propagation of fires. Analyses of climatic and hydrological records in Amazonia suggest a broad consensus that the 2005 drought was linked not to El Niño as with most previous droughts in the Amazon, but to warming sea surface temperatures in the tropical North Atlantic Ocean

Domain choice in an experimental nested modeling prediction system for South America

The purposes of this paper are to evaluate the new version of the regional model, RegCM3, over South America for two test seasons, and to select a domain for use in an experimental nested prediction system, which incorporates RegCM3 and the European Community-Hamburg (ECHAM) general circulation model (GCM). To evaluate RegCM3, control experiments were completed with RegCM3 driven by both the NCEP/NCAR Reanalysis (NNRP) and ECHAM, using a small control domain (D-CTRL) and integration periods of January–March 1983 (El Niño) and January–March 1985 (La Niña). The new version of the regional model captures the primary circulation and rainfall differences between the two years over tropical and subtropical South America. Both the NNRP-driven and ECHAM-driven RegCM3 improve the simulation of the Atlantic intertropical convergence zone (ITCZ) compared to the GCM. However, there are some simulation errors. Irrespective of the driving fields, weak northeasterlies associated with reduced precipitation are observed over the Amazon. The simulation of the South Atlantic convergence zone is poor due to errors in the boundary condition forcing which appear to be amplified by the regional model. To select a domain for use in an experimental prediction system, sensitivity tests were performed for three domains, each of which includes important regional features and processes of the climate system. The domain sensitivity experiments were designed to determine how domain size and the location of the GCM boundary forcing affect the regional circulation, moisture transport, and rainfall in two years with different large scale conditions. First, the control domain was extended southward to include the exit region of the Andes low level jet (D-LLJ), then eastward to include the South Atlantic subtropical high (D-ATL), and finally westward to include the subsidence region of the South Pacific subtropical high and to permit the regional model more freedom to respond to the increased resolution of the Andes Mountains (D-PAC). In order to quantify differences between the domain experiments, measures of bias, root mean square error, and the spatial correlation pattern were calculated between the model results and the observed data for the seasonal average fields. The results show the GCM driving fields have remarkable control over the RegCM3 simulations. Although no single domain clearly outperforms the others in both seasons, the control domain, D-CTRL, compares most favorably with observations. Over the ITCZ region, the simulations were improved by including a large portion of the South Atlantic subtropical high (D-ATL). The methodology presented here provides a quantitative basis for evaluating domain choice in future studies

Deadly disasters in southeastern South America: flash floods and landslides of February 2022 in Petrópolis, Rio de Janeiro

On 15 February 2022, the city of Petrópolis in the highlands of the state of Rio de Janeiro, Brazil, received an unusually high volume of rain within 3 h (258 mm), generated by a strongly invigorated mesoscale convective system. It resulted in flash floods and subsequent landslides that caused the deadliest landslide disaster recorded in Petrópolis, with 231 fatalities. In this paper, we analyzed the root causes and the key triggering factors of this landslide disaster by assessing the spatial relationship of landslide occurrence with various environmental factors. Rainfall data were retrieved from 1977 to 2022 (a combination of ground weather stations and the Climate Hazards Group InfraRed Precipitation – CHIRPS). Remotely sensed data were used to map the landslide scars, soil moisture, terrain attributes, line-of-sight displacement (land surface deformation), and urban sprawling (1985–2020). The results showed that the average monthly rainfall for February 2022 was 200 mm, the heaviest recorded in Petrópolis since 1932. Heavy rainfall was also recorded mostly in regions where the landslide occurred, according to analyses of the rainfall spatial distribution. As for terrain, 23 % of slopes between 45–60∘ had landslide occurrences and east-facing slopes appeared to be the most conducive for landslides as they recorded landslide occurrences of about 9 % to 11 %. Regarding the soil moisture, higher variability was found in the lower altitude (842 m) where the residential area is concentrated. Based on our land deformation assessment, the area is geologically stable, and the landslide occurred only in the thin layer at the surface. Out of the 1700 buildings found in the region of interest, 1021 are on the slope between 20 to 45∘ and about 60 houses were directly affected by the landslides. As such, we conclude that the heavy rainfall was not the only cause responsible for the catastrophic event of 15 February 2022; a combination of unplanned urban growth on slopes between 45–60∘, removal of vegetation, and the absence of inspection were also expressive driving forces of this disaster.</p

Adding new evidence to the attribution puzzle of the recent water shortage over São Paulo (Brazil)

São Paulo, Brazil has experienced severe water shortages and record low levels of its water reservoirs in 2013–2014. We evaluate the contributions of Amazon deforestation and climate change to low precipitation levels using a modelling approach, and address whether similar precipitation anomalies might occur more frequently in a warming world. Precipitation records from INMET show that the dry anomaly extended over a fairly large region to the north of São Paulo. Unique features of this event were anomalous sea surface temperature (SST) patterns in the Southern Atlantic, an extension of the sub tropical high into the São Paulo region and moisture flux divergence over São Paulo. The SST anomalies were very similar in 2013/14 and 2014/15, suggesting they played a major role in forcing the dry conditions. The SST anomalies consisted of three zonal bands: a cold band in the tropics, a warm band to the south of São Paulo and another cold band poleward of 40 S. We performed ensemble climate simulations with observed SSTs prescribed, vegetation cover either fixed at 1870 levels or varying over time, and greenhouse gases (GHGs) either fixed at pre-industrial levels (280 ppm CO₂) or varying over time. These simulations exhibit similar precipitation deficits over the São Paulo region in 2013/14. From this, we infer that SST patterns and the associated large-scale state of the atmosphere were important factors in determining the precipitation anomalies, while deforestation and increased GHGs only weakly modulated the signal. Finally, analyses of future climate simulations from CMIP5 models indicate that the frequency of such precipitation anomalies is not likely to change in a warmer climate

Seasonal variations in the Amazon plume-related atmospheric carbon sink

The Amazon River plume is a highly seasonal feature that can reach more than 3000 km across the tropical Atlantic Ocean, and cover ∼2 million km². Ship observations show that its seasonal presence significantly reduces sea surface salinity and inorganic carbon. In the western tropical North Atlantic during April–May 2003, plume-influenced stations exhibited surface DIC concentrations lowered by as much as 563 μmol C kg⁻¹ (∼28%) and pCO₂ as low as 201 μatm. We combine our data with other data sets to understand the annual uptake and seasonal variability of the plume-related CO₂ sink. Using flux estimates from all seasons with monthly plume areas determined by satellite, we calculate the annual carbon uptake by the outer plume alone (28 < S < 35) to be 15 ± 6 TgC yr⁻¹. Diazotroph-supported net community production enhanced the air-sea CO₂ disequilibrium by 100x and reversed the typical CO₂ outgassing from the tropical North Atlantic. The carbon sink in the Amazon plume depends on climate-sensitive conditions that control river hydrology, CO₂ solubility, and gas exchange