Large scale and synoptic features associated with extreme precipitation over South America: A review and case studies for the first decade of the 21st century

2012 ◽  
Vol 118 ◽  
pp. 27-40 ◽  
Author(s):  
Iracema Fonseca Albuquerque Cavalcanti
2020 ◽  
Vol 12 (13) ◽  
pp. 2085 ◽  
Author(s):  
Rayana Santos Araujo Palharini ◽  
Daniel Alejandro Vila ◽  
Daniele Tôrres Rodrigues ◽  
David Pareja Quispe ◽  
Rodrigo Cassineli Palharini ◽  
...  

In developing countries, accurate rainfall estimation with adequate spatial distribution is limited due to sparse rain gauge networks. One way to solve this problem is the use of satellite-based precipitation products. These satellite products have significant spatial coverage of rainfall estimates and it is of fundamental importance to investigate their performance across space–time scales and the factors that affect their uncertainties. In the open literature, some studies have already analyzed the ability of satellite-based rain estimation products to estimate average rainfall values. These investigations have found very close agreement between the estimates and observed data. However, further evaluation of the satellite precipitation products is necessary to improve their reliability to estimate extreme values. In this scenario, the main goal of this work is to evaluate the ability of satellite-based precipitation products to capture the characteristics of extreme precipitation over the tropical region of South America. The products evaluated in this investigation were 3B42 RT v7.0, 3B42 RT v7.0 uncalibrated, CMORPH V1.0 RAW, CMORPH V1.0 CRT, GSMAP-NRT-no gauge v6.0, GSMAP-NRT- gauge v6.0, CHIRP V2.0, CHIRPS V2.0, PERSIANN CDR v1 r1, CoSch and TAPEER v1.5 from Frequent Rainfall Observations on GridS (FROGS) database. Some products considered in this investigation are adjusted with rain gauge values and others only with satellite information. In this study, these two sets of products were considered. In addition, gauge-based daily precipitation data, provided by Brazil’s National Institute for Space Research, were used as reference in the analyses. In order to compare gauge-based daily precipitation and satellite-based data for extreme values, statistical techniques were used to evaluate the performance the selected satellite products over the tropical region of South America. According to the results, the threshold for rain to be considered an extreme event in South America presented high variability, ranging from 20 to 150 mm/day, depending on the region and the percentile threshold chosen for analysis. In addition, the results showed that the ability of the satellite estimates to retrieve rainfall extremes depends on the geographical location and large-scale rainfall regimes.


2020 ◽  
Author(s):  
Yangyang Xu ◽  
Lei Lin ◽  
Simone Tilmes ◽  
Katherine Dagon ◽  
Lili Xia ◽  
...  

Abstract. To mitigate the projected global warming in the 21st century, it is well recognized that society needs to cut CO2 emission and other short-lived warming agents aggressively. However, to stabilize the climate at a warming level closer to the present day, such as the well below 2 °C aspiration in the Paris agreement, a net-zero carbon emission by 2050 is still insufficient. The recent IPCC special report calls for a massive scheme to extract CO2 directly from the atmosphere, in addition to the decarbonization, to reach negative net emission at the mid-century mark. Another ambitious proposal is the solar radiation-based geoengineering schemes, including injecting sulfur gas into the stratosphere. Despite being in the public debate for years, these two leading geoengineering schemes have not been carefully examined under a consistent numerical modeling framework. Here we present a comprehensive analysis of climate impacts of these two geoengineering approaches using two recently available large-ensemble (> 10 members) model experiments conducted by a family of state-of-art Earth system models. The CO2-based mitigation simulation is designed to include both emissions cut and carbon capture. The solar radiation-based mitigation simulation is designed to inject the sulfur gas strategically at specified altitudes and latitudes and run a feedback control algorithm, to avoid common problems previously identified such as the over-cooling of the Tropics and large-scale precipitation shifts. Our analysis focuses on the projected aridity conditions over the Americas in the 21st century, in detailed terms of the mitigation potential, the temporal evolution, the spatial distribution (within North and South America), the relative efficiency, and the physical mechanisms. We show that sulfur injection, in contrast to previous notions of leading to excessive terrestrial drying (in terms of precipitation reduction) while offsetting the global mean greenhouse gas (GHG) warming, will instead mitigate the projected drying tendency under RCP8.5. The surface energy balance change induced by Sulfur injection, in addition to the well-known response in temperature and precipitation, plays a crucial role in determining the overall terrestrial hydroclimate response. However, when normalized by the same amount of avoided global warming, in these simulations, sulfur injection is less effective in limiting the worsening trend of regional land aridity in the Americas, when compared with carbon capture. Temporally, the climate benefit of Sulfur injection will emerge more quickly, even when both schemes are hypothetically started in the same year of 2020. Spatially, both schemes are effective in curbing the drying trend over North America. However, for South America, the Sulfur Injection scheme is particularly more effective for the sub-Amazon region (South Brazil), while the Carbon Capture scheme is more effective for the Amazon region. We conclude that despite the apparent limitations (such as inability to address ocean acidification) and potential side effects (such as changes to the ozone layer), innovative means of Sulfur Injection should continue to be explored as a potential low-cost option in the climate solution toolbox, complementing other mitigation approaches such as emissions cut and carbon capture (Cao et al., 2017). Our results demonstrate the urgent need for multi-model comparison studies and detailed regional assessment in other parts of the world.


2020 ◽  
Vol 11 (3) ◽  
pp. 673-695 ◽  
Author(s):  
Yangyang Xu ◽  
Lei Lin ◽  
Simone Tilmes ◽  
Katherine Dagon ◽  
Lili Xia ◽  
...  

Abstract. To mitigate the projected global warming in the 21st century, it is well-recognized that society needs to cut CO2 emissions and other short-lived warming agents aggressively. However, to stabilize the climate at a warming level closer to the present day, such as the “well below 2 ∘C” aspiration in the Paris Agreement, a net-zero carbon emission by 2050 is still insufficient. The recent IPCC special report calls for a massive scheme to extract CO2 directly from the atmosphere, in addition to decarbonization, to reach negative net emissions at the mid-century mark. Another ambitious proposal is solar-radiation-based geoengineering schemes, including injecting sulfur gas into the stratosphere. Despite being in public debate for years, these two leading geoengineering schemes have not been directly compared under a consistent analytical framework using global climate models. Here we present the first explicit analysis of the hydroclimate impacts of these two geoengineering approaches using two recently available large-ensemble (>10 members) model experiments conducted by a family of state-of-the-art Earth system models. The CO2-based mitigation simulation is designed to include both emission cuts and carbon capture. The solar-radiation-based mitigation simulation is designed to inject sulfur gas strategically at specified altitudes and latitudes and run a feedback control algorithm to avoid common problems previously identified such as the overcooling of the tropics and large-scale precipitation shifts. Our analysis focuses on the projected aridity conditions over the Americas in the 21st century in detailed terms of the potential mitigation benefits, the temporal evolution, the spatial distribution (within North and South America), the relative efficiency, and the physical mechanisms. We show that sulfur injection, in contrast to previous notions of leading to excessive terrestrial drying (in terms of precipitation reduction) while offsetting the global mean greenhouse gas (GHG) warming, will instead mitigate the projected drying tendency under RCP8.5. The surface energy balance change induced by sulfur injection, in addition to the well-known response in temperature and precipitation, plays a crucial role in determining the overall terrestrial hydroclimate response. However, when normalized by the same amount of avoided global warming in these simulations, sulfur injection is less effective in curbing the worsening trend of regional land aridity in the Americas under RCP8.5 when compared with carbon capture. Temporally, the climate benefit of sulfur injection will emerge more quickly, even when both schemes are hypothetically started in the same year of 2020. Spatially, both schemes are effective in curbing the drying trend over North America. However, for South America, the sulfur injection scheme is particularly more effective for the sub-Amazon region (southern Brazil), while the carbon capture scheme is more effective for the Amazon region. We conclude that despite the apparent limitations (such as an inability to address ocean acidification) and potential side effects (such as changes to the ozone layer), innovative means of sulfur injection should continue to be explored as a potential low-cost option in the climate solution toolbox, complementing other mitigation approaches such as emission cuts and carbon capture (Cao et al., 2017). Our results demonstrate the urgent need for multi-model comparison studies and detailed regional assessments in other parts of the world.


2019 ◽  
Vol 40 (8) ◽  
pp. 3701-3713
Author(s):  
Chenghai Wang ◽  
Danyang Cui ◽  
Jerasorn Santisirisomboon

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Adeoluwa Akande ◽  
Ana Cristina Costa ◽  
Jorge Mateu ◽  
Roberto Henriques

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.


Author(s):  
Sheree A Pagsuyoin ◽  
Joost R Santos

Water is a critical natural resource that sustains the productivity of many economic sectors, whether directly or indirectly. Climate change alongside rapid growth and development are a threat to water sustainability and regional productivity. In this paper, we develop an extension to the economic input-output model to assess the impact of water supply disruptions to regional economies. The model utilizes the inoperability variable, which measures the extent to which an infrastructure system or economic sector is unable to deliver its intended output. While the inoperability concept has been utilized in previous applications, this paper offers extensions that capture the time-varying nature of inoperability as the sectors recover from a disruptive event, such as drought. The model extension is capable of inserting inoperability adjustments within the drought timeline to capture time-varying likelihoods and severities, as well as the dependencies of various economic sectors on water. The model was applied to case studies of severe drought in two regions: (1) the state of Massachusetts (MA) and (2) the US National Capital Region (NCR). These regions were selected to contrast drought resilience between a mixed urban–rural region (MA) and a highly urban region (NCR). These regions also have comparable overall gross domestic products despite significant differences in the distribution and share of the economic sectors comprising each region. The results of the case studies indicate that in both regions, the utility and real estate sectors suffer the largest economic loss; nonetheless, results also identify region-specific sectors that incur significant losses. For the NCR, three sectors in the top 10 ranking of highest economic losses are government-related, whereas in the MA, four sectors in the top 10 are manufacturing sectors. Furthermore, the accommodation sector has also been included in the NCR case intuitively because of the high concentration of museums and famous landmarks. In contrast, the Wholesale Trade sector was among the sectors with the highest economic losses in the MA case study because of its large geographic size conducive for warehouses used as nodes for large-scale supply chain networks. Future modeling extensions could potentially include analysis of water demand and supply management strategies that can enhance regional resilience against droughts. Other regional case studies can also be pursued in future efforts to analyze various categories of drought severity beyond the case studies featured in this paper.


Plant Ecology ◽  
2021 ◽  
Author(s):  
Emma-Liina Marjakangas ◽  
Otso Ovaskainen ◽  
Nerea Abrego ◽  
Vidar Grøtan ◽  
Alexandre A. de Oliveira ◽  
...  

AbstractSpecies co-occurrences in local communities can arise independent or dependent on species’ niches. However, the role of niche-dependent processes has not been thoroughly deciphered when generalized to biogeographical scales, probably due to combined shortcomings of data and methodology. Here, we explored the influence of environmental filtering and limiting similarity, as well as biogeographical processes that relate to the assembly of species’ communities and co-occurrences. We modelled jointly the occurrences and co-occurrences of 1016 tropical tree species with abundance data from inventories of 574 localities in eastern South America. We estimated species co-occurrences as raw and residual associations with models that excluded and included the environmental effects on the species’ co-occurrences, respectively. Raw associations indicate co-occurrence of species, whereas residual associations indicate co-occurrence of species after accounting for shared responses to environment. Generally, the influence of environmental filtering exceeded that of limiting similarity in shaping species’ co-occurrences. The number of raw associations was generally higher than that of the residual associations due to the shared responses of tree species to the environmental covariates. Contrary to what was expected from assuming limiting similarity, phylogenetic relatedness or functional similarity did not limit tree co-occurrences. The proportions of positive and negative residual associations varied greatly across the study area, and we found a significant tendency of some biogeographical regions having higher proportions of negative associations between them, suggesting that large-scale biogeographical processes limit the establishment of trees and consequently their co-occurrences.


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