Assessing current and future trends of climate extremes across Brazil based on reanalyses and earth system model projections

Ávila-Díaz, Alvaro; Benezoli, Victor Hugo; Justino, Flávio; Torres, Roger Rodrigues; Wilson, Aaron B.

doi:10.1007/s00382-020-05333-z

Cited by 91 publications

(79 citation statements)

References 126 publications

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“…The Xavier et al (2016) dataset was produced based on observations from 3625 rain gauges and 735 wheatear stations in the Brazilian territory and is extensively used as the ground-truth reference for the validation of precipitation products, including the CHIRPS, MSWEP, and the soil moisture satellite-corrected estimates (SM2RAIN; Brocca et al, 2014;Paredes-Trejo et al, 2018), the Global Precipitation Measurement (GPM; Hou et al, 2014); Gadelha et al, 2019), and the Tropical Rainfall Measuring Mission (TRMM; Huffman et al, 2007;Melo et al, 2015). Other uses of this dataset include the evaluation of precipitation from downscaled global circulation models (Almagro et al, 2020), as well as other meteorological variables used in regional studies (Battisti et al, 2019;Bender and Sentelhas, 2018;Monteiro et al, 2018), aside from being widely used for hydrological studies (Almagro et al, 2017;Avila-Diaz et al, 2020;Lima and AghaKouchak, 2017;Souza et al, 2016). The main limitation of Xavier's dataset it that it only covers Brazil.…”

Section: Comparison With the Camels-br And Broader Implications For Hydrological Studiesmentioning

confidence: 99%

CABra: a novel large-sample dataset for Brazilian catchments

Almagro

Oliveira

Neto

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT DEM) and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980–2010) of data and less than 10 % of missing records were included. Catchment areas range from 9 to 4 800 000 km2, and the mean daily streamflow varies from 0.02 to 9 mm d−1. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage area for each catchment, aside from more than 100 attributes within the attribute classes. The collection and processing methods are discussed, along with the limitations for each of our multiple data sources. CABra intends to improve the hydrology-related data collection in Brazil and pave the way for a better understanding of different hydrologic drivers related to climate, landscape, and hydrology, which is particularly important in Brazil, having continental-scale river basins and widely heterogeneous landscape characteristics. In addition to benefitting catchment hydrology investigations, CABra will expand the exploration of novel hydrologic hypotheses and thereby advance our understanding of Brazilian catchments' behavior. The dataset is freely available at https://doi.org/10.5281/zenodo.4070146 and https://thecabradataset.shinyapps.io/CABra/ (last access: 7 June 2021).

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Section: Comparison With the Camels-br And Broader Implications For Hydrological Studiesmentioning

confidence: 99%

CABra: a novel large-sample dataset for Brazilian catchments

Almagro

Oliveira

Neto

et al. 2021

Hydrol. Earth Syst. Sci.

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“…CC BY 4.0 License. Monteiro et al, 2018), aside from being widely used for hydrological studies (Almagro et al, 2017;Avila-Diaz et al, 2020;Lima and AghaKouchak, 2017;Souza et al, 2016).…”

Section: Comparison With the Camels-br And Broader Implications For Hmentioning

confidence: 99%

CABra: a novel large-sample dataset for Brazilian catchments

Almagro¹,

Oliveira²,

Neto³

et al. 2020

Preprint

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Abstract. In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land-cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980–2010) of data and less than 10 % of missing records were included. Catchment areas range from 9 to 4 800 000 km2 and the mean daily streamflow varies from 0.02 to 9 mm d-1. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage area for each catchment, aside from more than 100 attributes within the attribute classes. The collection and processing methods are discussed along with the limitations for each of our multiple data sources. The CABra intends to improve the hydrology-related data collection in Brazil and pave the way for a better understanding of different hydrologic drivers related to climate, landscape, and hydrology, which is particularly important in Brazil, having continental-scale river basins and widely heterogeneous landscape characteristics. In addition to benefitting catchment hydrology investigations, CABra will expand the exploration of novel hydrologic hypotheses and thereby advance our understanding of Brazilian catchments' behavior. The dataset is freely available at https://doi.org/10.5281/zenodo.4070147.

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“…Most of the studies indicate a very consistent warming all over the country (Skansi et al ., 2013; Geirinhas et al ., 2018; Avila‐Diaz et al ., 2020; Dereczynski et al ., 2020). This homogeneous pattern of a single sign for different regions of Brazil is not observed for changes in precipitation extremes, which show very heterogeneous signs, even within the same city.…”

Section: Introductionmentioning

confidence: 99%

Observed changes in air temperature and precipitation extremes over Brazil

Regoto

Dereczynski

Chou

2021

Intl Journal of Climatology

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We analyse seasonal and annual trends of extreme indices of air temperature and precipitation over Brazil during the period 1961–2018. The main goal is to investigate whether the climate is changing and if so, to explore if there is any marked seasonality in such changes. The daily observed datasets of maximum and minimum temperatures, and precipitation, are provided by the Brazilian National Institute of Meteorology and National Water Agency. We use the Sen Curvature and Mann‐Kendall statistical tests to compute the magnitudes and to evaluate the statistical significance of climate extremes trends, respectively. The results show that the warm extremes frequency of occurrence is increasing significantly while the opposite occurs for cold extremes, which reveals a very consistent and widespread warming over Brazil. The highest increases in warm extremes occur during austral spring and summer while for the cold extremes the greatest decreases are observed during austral winter. Unlike temperature, precipitation extremes show heterogeneous signals for most of the country. In Northeast Brazil, there are changes towards a drier climate, especially in summer and autumn. In the Southern region, the climate is becoming wetter, with a reduction in consecutive dry days, especially in spring. For the other regions, there is no strong clear change sign, but both positive and negative precipitation extreme trends, without statistical significance (mostly in Southeast Region).

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Assessing current and future trends of climate extremes across Brazil based on reanalyses and earth system model projections

Cited by 91 publications

References 126 publications

CABra: a novel large-sample dataset for Brazilian catchments

CABra: a novel large-sample dataset for Brazilian catchments

CABra: a novel large-sample dataset for Brazilian catchments

Observed changes in air temperature and precipitation extremes over Brazil

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