Evaluating forecasts of extreme events for hydrological applications: an approach for screening unfamiliar performance measures

Cloke, Hannah; Pappenberger, Florian

doi:10.1002/met.58

Cited by 68 publications

(55 citation statements)

References 45 publications

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“…It is important that the forcing of the model cascade is evaluated in a hydrologically meaningful way (Cloke and Pappenberger, 2008;Pappenberger et al, 2008b). In this case study the input precipitation fields were evaluated on a monthly basis using continuous ranked probability scores (CRPS) (Hersbach, 2000).…”

Section: Precipitation Map Evaluationmentioning

confidence: 99%

“…An ensemble of weather forecasts from one Ensemble Prediction System (EPS), when used on catchment hydrology, can provide improved early flood warning as some of the uncertainties can be quantified (Cloke and Pappenberger, 2008). Recent research has been conducted in real-time flood forecasting using such EPSs in conjunction with spatially distributed catchment models.…”

Section: Introductionmentioning

confidence: 99%

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Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions

Wetterhall

Cloke

et al. 2009

Meteorological Applications

119

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ABSTRACT:The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. Weather forecasts using multiple NWPs from various weather centres implemented on catchment hydrology can provide significantly improved early flood warning. The availability of global ensemble weather prediction systems through the 'THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for the development of state-of-theart early flood forecasting systems. This paper presents a case study using the TIGGE database for flood warning on a meso-scale catchment (4062 km 2 ) located in the Midlands region of England. For the first time, a research attempt is made to set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE database. The study shows that precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial precipitation variability on such a comparatively small catchment, which indicates need to improve NWPs resolution and/or disaggregating techniques to narrow down the spatial gap between meteorology and hydrology. The spread of discharge forecasts varies from centre to centre, but it is generally large and implies a significant level of uncertainties. Nevertheless, the results show the TIGGE database is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation.

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Section: Precipitation Map Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions

Wetterhall

Cloke

et al. 2009

Meteorological Applications

119

View full text Add to dashboard Cite

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“…There are also quite different uses in different domains of the environmental sciences. In meteorological modeling it is standard practice to present information on different model verification statistics in the evaluation of weather forecasts [e.g., Pappenberger et al, 2008;Cloke and Pappenberger, 2008]. In other domains, model verification is normally only used for the evidence that a computer code is consistent with the definition of the model concepts that it purports to represent, without any requirement that the resulting outputs will be consistent with observations in a particular application.…”

Section: The Language Of Model Evaluationmentioning

confidence: 99%

A guide to good practice in modeling semantics for authors and referees

Beven

Young

2013

Water Resources Research

105

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[1] This opinion piece makes some suggestions about guidelines for modeling semantics that can be referred to by authors and referees. We discuss descriptions of model structures, different forms of simulation and prediction, descriptions of different sources of uncertainty in modeling practice, the language of model validation, and concepts of predictability and fitness-for-purpose. While not expecting universal agreement on these suggestions, given the loose usage of words in the literature, we hope that the discussion of the issues involved will at least give pause for thought and encourage good practice in model development and applications.Citation: Beven, K., and P. Young (2013), A guide to good practice in modeling semantics for authors and referees, Water Resour.

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“…Cloke and Pappenberger, 2008). We use two measures of skill to verify forecasts at larger streamflow thresholds: the Brier score and the loglikelihood ratio.…”

Section: Accuracy Of Forecasts For Large Threshold Eventsmentioning

confidence: 99%

The challenge of forecasting high streamflows 1–3 months in advance with lagged climate indices in southeast Australia

Bennett

Wang

Pokhrel

et al. 2014

Nat. Hazards Earth Syst. Sci.

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Abstract. Skilful forecasts of high streamflows a month or more in advance are likely to be of considerable benefit to emergency services and the broader community. This is particularly true for mesoscale catchments (< 2000 km 2 ) with little or no seasonal snowmelt, where real-time warning systems are only able to give short notice of impending floods. In this study, we generate forecasts of high streamflows for the coming 1-month and coming 3-month periods using large-scale ocean-atmosphere climate indices and catchment wetness as predictors. Forecasts are generated with a combination of Bayesian joint probability modelling and Bayesian model averaging. High streamflows are defined as maximum single-day streamflows and maximum 5-day streamflows that occur during each 1-month or 3-month forecast period. Skill is clearly evident in the 1-month forecasts of high streamflows. Surprisingly, in several catchments positive skill is also evident in forecasts of large threshold events (exceedance probabilities of 25 %) over the next month. Little skill is evident in forecasts of high streamflows for the 3-month period. We show that including lagged climate indices as predictors adds little skill to the forecasts, and thus catchment wetness is by far the most important predictor. Accordingly, we recommend that forecasts may be improved by using accurate estimates of catchment wetness.

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Evaluating forecasts of extreme events for hydrological applications: an approach for screening unfamiliar performance measures

Cited by 68 publications

References 45 publications

Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions

Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions

A guide to good practice in modeling semantics for authors and referees

The challenge of forecasting high streamflows 1–3 months in advance with lagged climate indices in southeast Australia

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