Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0

Emerton, Rebecca; Zsótér, Ervin; Arnal, Louise; Cloke, Hannah; Muraro, Davide; Prudhomme, Christel; Stephens, Elisabeth; Salamon, Peter; Pappenberger, Florian

doi:10.5194/gmd-11-3327-2018

Cited by 89 publications

(93 citation statements)

References 41 publications

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“…There are some exceptions, however, such as high latitude Canada and Siberia, where the HistProbs are more useful. These correspond to regions where GloFAS-Seasonal has been shown to generally be less skilful than climatology [15]. As the PDO is a decadal oscillation varying on much longer timescales than ENSO, it is likely to influence El Niño impacts over several events in turn.…”

Section: Discussionmentioning

confidence: 95%

“…The AROC is used to infer the potential usefulness of the forecast; a forecast that is more skilful than a forecast of climatology is said to be potentially useful, whereas a forecast that is less skilful than a forecast of climatology is not useful. This approach has previously been used in the evaluation of seasonal river flow forecasts [15,23]. Often, seasonal forecasts are provided in terms of the likelihood that a given variable will be above or below normal (based on terciles) in the coming months.…”

Section: Evaluation Data and Methodsmentioning

confidence: 99%

“…For this study, we make use of the GloFAS-Seasonal reforecasts, which were produced using the SEAS5 reforecasts [15,19] initialised with the ERA5-R river flow reanalysis [15]. ERA5 [20] is currently still in production, and as such, 34 years of data were available with which to produce the reforecasts: 1981-1983, and 1986-2016.…”

Section: Forecasting Approaches 21 Dynamical Approach: Glofas-seasonalmentioning

confidence: 99%

“…The two forecasts are evaluated over the same 34-year period (1981-2015), using river flow observations obtained from the Global Runoff Data Centre (GRDC; [25]), alongside observations that have been made available to GloFAS [15]. To ensure a large enough sample size for the forecast evaluation, alongside the best possible spatial coverage, the following criteria are applied to the data:…”

Section: Observed Datamentioning

confidence: 99%

“…The first operational global seasonal river flow forecasting system was implemented in 2017, as part of the Global Flood Awareness System (GloFAS; [1]). GloFAS-Seasonal [15] provides openly-available dynamical forecasts of high and low river flow out to 4 months ahead by forcing a hydrological river routing model with seasonal forecast output from a GCM.…”

Section: Introductionmentioning

confidence: 99%

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What is the most useful approach for forecasting hydrological extremes during El Niño?

Emerton

Stephens

Cloke

2019

Environ. Res. Commun.

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In the past, efforts to prepare for the impacts of El Niño-driven flood and drought hazards have often relied on seasonal precipitation forecasts as a proxy for hydrological extremes, due to a lack of hydrologically relevant information. However, precipitation forecasts are not the best indicator of hydrological extremes. Now, two different global scale hydro-meteorological approaches for predicting river flow extremes are available to support flood and drought preparedness. These approaches are statistical forecasts based on large-scale climate variability and teleconnections, and resource-intensive dynamical forecasts using coupled ocean-atmosphere general circulation models. Both have the potential to provide early warning information, and both are used to prepare for El Niño impacts, but which approach provides the most useful forecasts? This study uses river flow observations to assess and compare the ability of two recently-developed forecasts to predict high and low river flow during El Niño: statistical historical probabilities of ENSO-driven hydrological extremes, and the dynamical seasonal river flow outlook of the Global Flood Awareness System (GloFAS-seasonal). Our findings highlight regions of the globe where each forecast is (or is not) skilful compared to a forecast of climatology, and the advantages and disadvantages of each forecasting approach. We conclude that in regions where extreme river flow is predominantly driven by El Niño, or in regions where GloFAS-seasonal currently lacks skill, the historical probabilities generally provide a more useful forecast. In areas where other teleconnections also impact river flow, with the effect of strengthening, mitigating or even reversing the influence of El Niño, GloFAS-seasonal forecasts are typically more useful.

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Section: Discussionmentioning

confidence: 95%

Section: Evaluation Data and Methodsmentioning

confidence: 99%

Section: Forecasting Approaches 21 Dynamical Approach: Glofas-seasonalmentioning

confidence: 99%

Section: Observed Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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What is the most useful approach for forecasting hydrological extremes during El Niño?

Emerton

Stephens

Cloke

2019

Environ. Res. Commun.

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Calibration of Global Flood Models

Hirpa

Lorini

Dadson

et al. 2021

Global Drought and Flood

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Forecasting annual maximum water level for the Negro River at Manaus

et al. 2021

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More frequent and stronger flood hazards in the last two decades have caused considerable environmental and socio-economic losses in many regions of the Amazon basin. It is therefore critical to advance predictions for flood levels, with adequate lead times, to provide more effective and earlier warnings to safeguard lives and livelihoods. Water-level variations in large, low-lying, free-flowing river systems in the Amazon basin, such as the Negro River, follow large-scale precipitation anomalies. This offers an opportunity to predict maximum water levels using observed antecedent rainfall. This study aims to investigate possible improvements in the performance and extension of the lead time of existing operational statistical forecasts for annual maximum water level of the Negro River at Manaus, occurring between May and July. We develop forecast models using multiple linear regression methods, to produce forecasts that can be issued in March, February and January. Potential predictors include antecedent catchment rainfall and water levels, large-scale modes of climate variability and the long-term linear trend in water levels. Our statistical models gain one month of lead time against existing models for same skill level, but are only moderately better than existing models at similar lead times. All models lose performance at longer lead times, as expected. However, our forecast models can issue skilful operational forecasts in March or earlier. We show the forecasts for the Negro River maximum water level at Manaus for 2020 and 2021.

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Developing a global operational seasonal hydro-meteorological forecasting system: GloFAS-Seasonal v1.0

Cited by 89 publications

References 41 publications

What is the most useful approach for forecasting hydrological extremes during El Niño?

What is the most useful approach for forecasting hydrological extremes during El Niño?

Calibration of Global Flood Models

Forecasting annual maximum water level for the Negro River at Manaus

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