Studies integrating climate modelling output into hydrological modelling have grown substantially... more Studies integrating climate modelling output into hydrological modelling have grown substantially in the last two decades worldwide; however, there has not been a systematic review about those applications in the Brazilian territory. The aim of this study is to identify how the scientific community has been dealing with the topic in Brazil. The study is based on a systematic review of available peer-reviewed literature. We identify regions and socioeconomic sectors of interest and propose a method to evaluate the methodological consistency of the studies with the current state-of-the-art. The review shows that the topic has grown substantially in this decade, reaching 63 documents until 2018. The sectors under highest concern are the hydropower and the drinking water supply. The Paraná and Atlântico Nordeste Oriental hydrographic regions received great attention; whereas the Atlântico Sudeste did not. In terms of methodology, the use of multi-model ensemble leaves room for improvement. The results suggest a lack of human resources and access to computational infrastructure to handle climate data. Given the current challenges that Brazilian science is facing, we suggest the synchronization of efforts among research institutions. This systematic review provides information to help guiding decision makers to improve the topic in Brazil. RESUMO Estudos que integram modelagem climática em modelagem hidrológica têm crescido substancialmente nas últimas duas décadas em todo o mundo; entretanto, pouco se sabe sobre estes no território brasileiro. O objetivo deste estudo é identificar como a comunidade científica tem lidado com o tema no Brasil. O estudo baseia-se numa revisão sistemática da literatura revisada por pares disponível. Identificamos regiões e setores socioeconômicos de interesse e propomos um método para avaliar a consistência metodológica dos estudos com o atual estado-da-arte. A análise mostra que o tema cresceu substancialmente nesta década, abrangendo 63 documentos até 2018. Os setores de maior interesse são o de energia hidrelétrica e de abastecimento de água potável. As regiões hidrográficas do Paraná e do Atlântico Nordeste Oriental receberam grande atenção; enquanto a região Atlântico Sudeste pouca. Em termos de metodologia, o uso do conjunto de multi-modelos deixa espaço para melhorias. Os resultados sugerem limitações em capacidade técnica e em acesso à infraestrutura computacional para lidar com dados climáticos. Diante dos atuais desafios que a ciência brasileira enfrenta, sugerimos a sincronização de esforços entre instituições de pesquisa. Esta revisão sistemática fornece informações que podem ajudar os tomadores de decisão em ações de aprimoramento do tema no Brasil. Palavras-chave: Modelos de clima; Modelos hidrológicos; Revisão sistemática.
This study investigates trends and the effects of the interannual and intraseasonal climate varia... more This study investigates trends and the effects of the interannual and intraseasonal climate variability on the extreme weather of Brazil's capital city Distrito Federal (DF). This area is highly vulnerable to climate variability, having suffered from droughts and floods that affected the drinking water supply and agriculture. We perform trend analysis of 12 rainfall‐related indices from 13 ground observation stations and assess the influence of El Niño southern oscillation (ENSO) and Madden–Julian oscillation (MJO) on rainfall totals and extreme indices. The trend analysis confirms: (a) the increase of the dry spells length and (b) the anticipation of the onset of dry periods at regional level. That is also true when considering dry spells in the rainy season, a hazard known in the agriculture sector as “verânico.” On the other hand, extreme wet conditions became less severe in the last decades. Supressed monthly rainfall conditions, and some wet indices, are associated with La Niña episodes. The MJO's intraseasonal variability seems to play a substantial role in DF's climate. MJO phases 3, 7 and 8 are associated to enhanced rainfall conditions; whereas rainfall is supressed during phase 5. Moreover, dry spells during the rainy season, or “verânico,” often coincide with MJO phase 5. When combined with ENSO, the basic response of rainfall to MJO activity changes substantially showing statistically significant influence of El Niño on phases 2 and 8; while La Niña on phases 4, 6 and 7. The findings contribute to a better understanding of the ongoing changes in extreme climate as well as the influence of natural climate variability on local's climate, information that can be used in the management of water resources and land use of DF.
The Intergovernmental Panel on Climate Change (IPCC) has put a lot of efforts to describe uncerta... more The Intergovernmental Panel on Climate Change (IPCC) has put a lot of efforts to describe uncertainties and to judge the confidence level of its major conclusions. Despite a guidance to communicate uncertainty, the assignment of confidence is not sufficiently clear and, thus, hard to be reproduced by the extern community. By conducting a synthesis assessment about the impacts of climate change on the Brazilian water resources, we identified an opportunity to illustrate the characterization of evidence as adopted in IPCC reports. We propose a method to describe the evidence from model outputs wherein the quality and amount of studies, as well as the consistency among their conclusions, are subject of a transparent rating procedure. In summary, the more comprehensive the study in sampling uncertainties, the higher its quality. Likewise, the amount and consistency among conclusions is assigned in a systematic way. The method is applied for synthesizing a collection of 42 peer-reviewed articles. It reveals important aspects about the evidence of the potential impacts of climate change in the Brazilian water resources, such as changes into a drier hydrological regime. However, the use of multi-model ensemble, the evaluation of models, and the observational data is limited. The proposed method enables consistent communication of the degree of evidence in a transparent, traceable, and comprehensive fashion. The method can be used as a tool to support experts on their judgment. The approach is reproducible and can guide synthesis work not only in Brazil but anywhere else.
Available climatological information of Distrito Federal does not satisfy the requirements for de... more Available climatological information of Distrito Federal does not satisfy the requirements for detailed climate diagnosis, as they do not provide the necessary spatial resolution for water resources management purposes. Annual and seasonal climatology (1971–2000) of precipitation from 6 meteorological stations and 54 rain gauges from Central Brazil were used to test eight different spatial interpolation methods. Geographical factors (i.e., altitude, longitude and latitude) explain a large portion of precipitation in the region, and therefore, multivariate models were included. The performance of estimations was assessed through independent validation using mean square error, correlation coefficient and Nash–Sutcliffe efficiency criterion. Inverse distance weighting (IDW), ordinary kriging (OK) and the multivariate regression with interpolation of residuals by IDW (MRegIDW) and OK (MRegOK) have performed the lowest errors and the highest correlation and Nash–Sutcliffe efficiency criterion. In general, interpolation methods provide similar spatial distributions of rainfall wherever observation network is dense. However, the inclusion of geographical variables to the interpolation method should improve estimates in areas where the observation network density is low. Nevertheless, the assessment of uncertainties using a geostatistical method provides supplementary and qualitative information which should be considered when interpreting the spatial distribution of rainfall.
Johannes Franke,
Yumiko Marina Tanaka da Anunciação,
Holger Weiss,
Christian Bernhofer
A key challenge for climate projection science is to serve the growing needs of impact assessment... more A key challenge for climate projection science is to serve the growing needs of impact assessments in an environment with substantial differences in the projections of climate models and an increasing number of relevant climate model results. In order to assist the assessment of water resources impacts under future climate change, this work provides a synthesis of the simulations of General Circulation Models (GCMs) for the region of Distrito Federal, Brazil. The work analyzes projections of mean surface air temperature and precipitation of 22 GCMs, as well as seven extreme indices of 10 GCMs. Trends of the multi-model ensemble median, as well as their significance, were calculated. The consistency in the sign of change was assessed through the percentage of agreement of simulations with the median. Finally, the probability density function of the multi-model ensemble provides valuable information about the uncertainties of projections. Investigations were performed for annual and seasonal temporal scales for the period 2011–2050. The main results here identified are: (a) a consensus of the multi-model ensemble and median to increasing temperature; (b) a slightly, but less consistent, decrease of precipitation in the dry season; and (c) increase of heat waves and droughts events, although changes in precipitation extremes are much less coherent than for temperature. The approach used gives a comprehensive assessment of the possible future climate until the middle of the twenty-first century, as well as the uncertainties involved in the multi-model ensemble projections.
In the framework of the IWAS/Água-DF project, this study focuses on changes in mean surface air t... more In the framework of the IWAS/Água-DF project, this study focuses on changes in mean surface air temperature and accumulated precipitation in Central Brazil over the past 40 years. It has two main objectives: (1) comparison between two climatological periods (2001–2010 and 1971–2000) and (2) trend analysis of climate variables. Time series of meteorological and rain gauge stations from Central Brazil have been organized in a databank, which contains tools for homogeneity tests. From that, 4 temperature and 55 precipitation time series were sufficient homogeneous, while 1 temperature and 5 precipitation time series were identified as inhomogeneous. Reliable spatial distribution was produced using proper interpolation method. Trends and significance levels were calculated by Rapp’s estimator of slope and Mann–Kendall test, respectively. The most important results of the comparisons and trend analysis in the last four decades are: (1) marked increase in annual and seasonal mean surface air temperature, (2) evident decreases of accumulated rainfall in winter and autumn, and (3) apparent increase of precipitation amounts in the rainy season.
Studies integrating climate modelling output into hydrological modelling have grown substantially... more Studies integrating climate modelling output into hydrological modelling have grown substantially in the last two decades worldwide; however, there has not been a systematic review about those applications in the Brazilian territory. The aim of this study is to identify how the scientific community has been dealing with the topic in Brazil. The study is based on a systematic review of available peer-reviewed literature. We identify regions and socioeconomic sectors of interest and propose a method to evaluate the methodological consistency of the studies with the current state-of-the-art. The review shows that the topic has grown substantially in this decade, reaching 63 documents until 2018. The sectors under highest concern are the hydropower and the drinking water supply. The Paraná and Atlântico Nordeste Oriental hydrographic regions received great attention; whereas the Atlântico Sudeste did not. In terms of methodology, the use of multi-model ensemble leaves room for improvement. The results suggest a lack of human resources and access to computational infrastructure to handle climate data. Given the current challenges that Brazilian science is facing, we suggest the synchronization of efforts among research institutions. This systematic review provides information to help guiding decision makers to improve the topic in Brazil. RESUMO Estudos que integram modelagem climática em modelagem hidrológica têm crescido substancialmente nas últimas duas décadas em todo o mundo; entretanto, pouco se sabe sobre estes no território brasileiro. O objetivo deste estudo é identificar como a comunidade científica tem lidado com o tema no Brasil. O estudo baseia-se numa revisão sistemática da literatura revisada por pares disponível. Identificamos regiões e setores socioeconômicos de interesse e propomos um método para avaliar a consistência metodológica dos estudos com o atual estado-da-arte. A análise mostra que o tema cresceu substancialmente nesta década, abrangendo 63 documentos até 2018. Os setores de maior interesse são o de energia hidrelétrica e de abastecimento de água potável. As regiões hidrográficas do Paraná e do Atlântico Nordeste Oriental receberam grande atenção; enquanto a região Atlântico Sudeste pouca. Em termos de metodologia, o uso do conjunto de multi-modelos deixa espaço para melhorias. Os resultados sugerem limitações em capacidade técnica e em acesso à infraestrutura computacional para lidar com dados climáticos. Diante dos atuais desafios que a ciência brasileira enfrenta, sugerimos a sincronização de esforços entre instituições de pesquisa. Esta revisão sistemática fornece informações que podem ajudar os tomadores de decisão em ações de aprimoramento do tema no Brasil. Palavras-chave: Modelos de clima; Modelos hidrológicos; Revisão sistemática.
This study investigates trends and the effects of the interannual and intraseasonal climate varia... more This study investigates trends and the effects of the interannual and intraseasonal climate variability on the extreme weather of Brazil's capital city Distrito Federal (DF). This area is highly vulnerable to climate variability, having suffered from droughts and floods that affected the drinking water supply and agriculture. We perform trend analysis of 12 rainfall‐related indices from 13 ground observation stations and assess the influence of El Niño southern oscillation (ENSO) and Madden–Julian oscillation (MJO) on rainfall totals and extreme indices. The trend analysis confirms: (a) the increase of the dry spells length and (b) the anticipation of the onset of dry periods at regional level. That is also true when considering dry spells in the rainy season, a hazard known in the agriculture sector as “verânico.” On the other hand, extreme wet conditions became less severe in the last decades. Supressed monthly rainfall conditions, and some wet indices, are associated with La Niña episodes. The MJO's intraseasonal variability seems to play a substantial role in DF's climate. MJO phases 3, 7 and 8 are associated to enhanced rainfall conditions; whereas rainfall is supressed during phase 5. Moreover, dry spells during the rainy season, or “verânico,” often coincide with MJO phase 5. When combined with ENSO, the basic response of rainfall to MJO activity changes substantially showing statistically significant influence of El Niño on phases 2 and 8; while La Niña on phases 4, 6 and 7. The findings contribute to a better understanding of the ongoing changes in extreme climate as well as the influence of natural climate variability on local's climate, information that can be used in the management of water resources and land use of DF.
The Intergovernmental Panel on Climate Change (IPCC) has put a lot of efforts to describe uncerta... more The Intergovernmental Panel on Climate Change (IPCC) has put a lot of efforts to describe uncertainties and to judge the confidence level of its major conclusions. Despite a guidance to communicate uncertainty, the assignment of confidence is not sufficiently clear and, thus, hard to be reproduced by the extern community. By conducting a synthesis assessment about the impacts of climate change on the Brazilian water resources, we identified an opportunity to illustrate the characterization of evidence as adopted in IPCC reports. We propose a method to describe the evidence from model outputs wherein the quality and amount of studies, as well as the consistency among their conclusions, are subject of a transparent rating procedure. In summary, the more comprehensive the study in sampling uncertainties, the higher its quality. Likewise, the amount and consistency among conclusions is assigned in a systematic way. The method is applied for synthesizing a collection of 42 peer-reviewed articles. It reveals important aspects about the evidence of the potential impacts of climate change in the Brazilian water resources, such as changes into a drier hydrological regime. However, the use of multi-model ensemble, the evaluation of models, and the observational data is limited. The proposed method enables consistent communication of the degree of evidence in a transparent, traceable, and comprehensive fashion. The method can be used as a tool to support experts on their judgment. The approach is reproducible and can guide synthesis work not only in Brazil but anywhere else.
Available climatological information of Distrito Federal does not satisfy the requirements for de... more Available climatological information of Distrito Federal does not satisfy the requirements for detailed climate diagnosis, as they do not provide the necessary spatial resolution for water resources management purposes. Annual and seasonal climatology (1971–2000) of precipitation from 6 meteorological stations and 54 rain gauges from Central Brazil were used to test eight different spatial interpolation methods. Geographical factors (i.e., altitude, longitude and latitude) explain a large portion of precipitation in the region, and therefore, multivariate models were included. The performance of estimations was assessed through independent validation using mean square error, correlation coefficient and Nash–Sutcliffe efficiency criterion. Inverse distance weighting (IDW), ordinary kriging (OK) and the multivariate regression with interpolation of residuals by IDW (MRegIDW) and OK (MRegOK) have performed the lowest errors and the highest correlation and Nash–Sutcliffe efficiency criterion. In general, interpolation methods provide similar spatial distributions of rainfall wherever observation network is dense. However, the inclusion of geographical variables to the interpolation method should improve estimates in areas where the observation network density is low. Nevertheless, the assessment of uncertainties using a geostatistical method provides supplementary and qualitative information which should be considered when interpreting the spatial distribution of rainfall.
Johannes Franke,
Yumiko Marina Tanaka da Anunciação,
Holger Weiss,
Christian Bernhofer
A key challenge for climate projection science is to serve the growing needs of impact assessment... more A key challenge for climate projection science is to serve the growing needs of impact assessments in an environment with substantial differences in the projections of climate models and an increasing number of relevant climate model results. In order to assist the assessment of water resources impacts under future climate change, this work provides a synthesis of the simulations of General Circulation Models (GCMs) for the region of Distrito Federal, Brazil. The work analyzes projections of mean surface air temperature and precipitation of 22 GCMs, as well as seven extreme indices of 10 GCMs. Trends of the multi-model ensemble median, as well as their significance, were calculated. The consistency in the sign of change was assessed through the percentage of agreement of simulations with the median. Finally, the probability density function of the multi-model ensemble provides valuable information about the uncertainties of projections. Investigations were performed for annual and seasonal temporal scales for the period 2011–2050. The main results here identified are: (a) a consensus of the multi-model ensemble and median to increasing temperature; (b) a slightly, but less consistent, decrease of precipitation in the dry season; and (c) increase of heat waves and droughts events, although changes in precipitation extremes are much less coherent than for temperature. The approach used gives a comprehensive assessment of the possible future climate until the middle of the twenty-first century, as well as the uncertainties involved in the multi-model ensemble projections.
In the framework of the IWAS/Água-DF project, this study focuses on changes in mean surface air t... more In the framework of the IWAS/Água-DF project, this study focuses on changes in mean surface air temperature and accumulated precipitation in Central Brazil over the past 40 years. It has two main objectives: (1) comparison between two climatological periods (2001–2010 and 1971–2000) and (2) trend analysis of climate variables. Time series of meteorological and rain gauge stations from Central Brazil have been organized in a databank, which contains tools for homogeneity tests. From that, 4 temperature and 55 precipitation time series were sufficient homogeneous, while 1 temperature and 5 precipitation time series were identified as inhomogeneous. Reliable spatial distribution was produced using proper interpolation method. Trends and significance levels were calculated by Rapp’s estimator of slope and Mann–Kendall test, respectively. The most important results of the comparisons and trend analysis in the last four decades are: (1) marked increase in annual and seasonal mean surface air temperature, (2) evident decreases of accumulated rainfall in winter and autumn, and (3) apparent increase of precipitation amounts in the rainy season.
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Papers by Pablo Borges
Johannes Franke,
Yumiko Marina Tanaka da Anunciação,
Holger Weiss,
Christian Bernhofer
Johannes Franke,
Yumiko Marina Tanaka da Anunciação,
Holger Weiss,
Christian Bernhofer