Collischonn, Walter

Fan, Fernando Mainardi

Freitas, Camila

Gama, Cléber Henrique Araújo

Paiva, Rodrigo Cauduro Dias de

Paranhos, Cassia Silmara Aver

Petry, Ingrid

Quedi, Erik Schmitt

Silveira, Reinaldo Bomfim da

Siqueira, Vinícius Alencar

English

Lume 5.8

EGU23-4540, updated on 24 Mar 2023https://doi.org/10.5194/egusphere-egu23-4540EGU General Assembly 2023© Author(s) 2023. This work is distributed underthe Creative Commons Attribution 4.0 License.Continental-scale evaluation of subseasonal–to–seasonal (S2S)streamflow forecasts over South AmericaErik Quedi1, Fernando Fan1, Vinicius Siqueira1, Walter Collischonn1, Ingrid Petry1, Cleber Gama1,Rodrigo Paiva1, Reinaldo Silveira2, Cassia Paranhos3, and Camila Freitas31Federal University of Rio Grande do Sul (UFRGS), Instituto de Pesquisas Hidráulicas (IPH), Hidrologia de Grande Escala(HGE), Brazil2Meteorological System of Paraná (SIMEPAR), Brazil3Paraná State electric company (COPEL GeT), BrazilHydrological forecasts ranging from two weeks to months in advance are critical for decisionmaking in water resources management and economic sectors. In the subseasonal timescale,there is an opportunity to anticipate events of hydrological interest, such as periods of floods anddroughts. The development of subseasonal forecasts with good quality for decision supportsystems is still a great challenge for the technical and scientific community, as it fits into apredictability gap between medium-range weather (3 to 15 days) and seasonal climate prediction(2 to 7 months). In South America, the climate and weather variability can represent risk toactivities such as agriculture and hydropower energy production. For instance, Brazil, the largercountry in terms of area and economy in the continent, has an electrical power generation matrixwith 63% of hydropower and rely on weather forecasts spanning multiple timescales for itsintegrated system operation. This work evaluated the potential skill of subseasonal streamflowforecasts over South America based on ECMWF ensemble forecasts with lead times up to 46 daysobtained from the Subseasonal-to-Seasonal (S2S) project database. A continental-scale hydrologic-hydrodynamic model was used to carry out the simulation runs for obtaining subseasonalensemble streamflow forecasts. Forecast bias was evaluated against a reference model run (i.e.,pseudo-observations) for both raw and bias corrected precipitation, and the forecast skill wasevaluated against the Ensemble Streamflow Prediction (ESP) method. Forecasts and pseudo-observations were aggregated into weekly averages, ranging 6 weeks for verification, and weredivided into subsets for each season of the year (DJF, MAM, JJA, SON) to access seasonal patternsover South American regions. The results highlight that the forecast skill is dependent oninitialization month, season, basin, and forecast lead time, with greater skill on shorter lead times.Bias correction was able to reduce the mean forecast error over most regions of the continent. Inaddition, the bias correction improved skill and maintained positive skill after the third week offorecast, especially in northeastern regions and on wet seasons (DJF, MAM), meanwhile in centralregions the improvements were not clear. However, the ESP method outperformed the ECMWF-based ensemble in many regions. Finally, the results presented here provide insights forinvestigations and applications of S2S forecasts in the operational scope on a continental scale,which can bring benefits, for example, in the optimization of the operation of electricity generationreservoirs.Acknowledgments: This work presents part of the results obtained during the project granted bythe Brazilian Agency of Electrical Energy (ANEEL) under its Research and Development programProject PD 6491-0503/2018 – “Previsão Hidroclimática com Abrangência no Sistema InterligadoNacional de Energia Elétrica” developed by the Paraná State electric company (COPEL GeT), theMeteorological System of Paraná (SIMEPAR) and the RHAMA Consulting company. The HydraulicResearch Institute (IPH) from the Federal University of Rio Grande do Sul (UFRGS) contribute topart of the project through an agreement with the RHAMA company (IAP-001313).Powered by TCPDF (www.tcpdf.org)

Continental-scale evaluation of subseasonal–to–seasonal (S2S) streamflow forecasts over South America

https://lume.ufrgs.br/bitstream/10183/256814/1/001165718.pdf

Continental-scale evaluation of subseasonal–to–seasonal (S2S) streamflow forecasts over South America

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