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Towards a comprehensive characterization of evidence in synthesis assessments: the climate change impacts on the Brazilian water resources

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Abstract

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.

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Abbreviations

ALT:

Atlântico Leste

AMZ:

Amazônica

AOC:

Atlântico Nordeste Ocidental

AOR:

Atlântico Nordeste Oriental

ASD:

Atlântico Sudeste

ASU:

Atlântico Sul

BC:

Bias correction

BCS:

Bias correction score

CBC:

Score of the calibration criteria of BC

CDS:

Score of the calibration criteria of DS

CHM:

Score of the calibration criteria of HM

CM:

Climate modeling

CMIP3:

Coupled Model Intercomparison Project Phase 3

CMIP5:

Coupled Model Intercomparison Project Phase 5

CMS:

Climate modeling score

DS:

Downscaling

DSS:

Downscaling score

ECM:

Score of ensemble size of CM

EDS:

Score of the ensemble size of DS

EHM:

Score of the ensemble size of HM

ES:

Emission/radiative forcing scenarios

ESD:

Empirical statistical downscaling

ESS:

Emission/radiative forcing scenarios score

GCM:

Global climate model

HM:

Hydrological modeling

HMS:

Hydrological modeling score

IPCC:

Intergovernmental Panel on Climate Change

OBC:

Score of observational network density of rainfall data of BC

ODH:

Score of observational network density of river discharge data of HM

ODS:

Score of observational network density of rainfall data of DS

OND:

Observational network density

ORH:

Score of observational network density of rainfall data of HM

PNB:

Parnaíba

PRG:

Paraguai

PRN:

Paraná

Qmax:

Maximum discharge

Qmean:

Mean discharge

Qmin:

Minimum discharge

QS:

Quality score

RCM:

Regional climate model

RCP:

Representative concentration pathways

RES:

Score of range of ES

SFO:

São Francisco

SRES:

Special report on emissions scenarios

TBC:

Score of the type of BC

TES:

Score of type of ES

THM:

Score of the type of HM

TOC:

Tocantins-Araguaia

URU:

Uruguai

VBC:

Score of the validation criteria of BC

VCM:

Score of version of CM

VDS:

Score of the validation criteria of DS

VHM:

Score of the validation criteria of HM

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Funding

The authors acknowledge the Brazilian National Council for Scientific and Technological Development (CNPq) for funding this study (Grant Numbers: 150768/2017-6 and 159528/2018-6)

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Borges de Amorim, P., Chaffe, P.B. Towards a comprehensive characterization of evidence in synthesis assessments: the climate change impacts on the Brazilian water resources. Climatic Change 155, 37–57 (2019). https://doi.org/10.1007/s10584-019-02430-9

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