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

He, Yi; Wetterhall, F.; Cloke, Hannah; Pappenberger, Florian; Wilson, Matthew; Freer, J. E.; McGregor, Glenn R.

doi:10.1002/met.132

Cited by 120 publications

(91 citation statements)

References 29 publications

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“…Figure 1 depicts the Upper Severn catchment, which is approximately 4062 km 2 , with urban, forest and agricultural land accounting for 3%, 7.1% and 48.5% of the area respectively, and loosely packed peat soil dominating the catchment. River levels are generally high in autumn and winter and low in summer (He et al, 2009). The observed discharge data were provided by the UK Environment Agency (EA) Midlands region and cover .…”

Section: The Upper Severn River Catchment Uk and Observed Datasetsmentioning

confidence: 99%

Modelling climate impact on floods with ensemble climate projections

Cloke

Wetterhall

et al. 2012

Quart J Royal Meteoro Soc

109

104

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The evidence provided by modelled assessments of future climate impact on flooding is fundamental to water resources and flood risk decision making. Impact models usually rely on climate projections from global and regional climate models (GCM/RCMs). However, challenges in representing precipitation events at catchment-scale resolution mean that decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs. Here the impacts on projected high flows of differing ensemble approaches and application of Model Output Statistics to RCM precipitation are evaluated while assessing climate change impact on flood hazard in the Upper Severn catchment in the UK. Various ensemble projections are used together with the HBV hydrological model with direct forcing and also compared to a response surface technique. We consider an ensemble of single-model RCM projections from the current UK Climate Projections (UKCP09); multi-model ensemble RCM projections from the European Union's FP6 'ENSEMBLES' project; and a joint probability distribution of precipitation and temperature from a GCM-based perturbed physics ensemble.The ensemble distribution of results show that flood hazard in the Upper Severn is likely to increase compared to present conditions, but the study highlights the differences between the results from different ensemble methods and the strong assumptions made in using Model Output Statistics to produce the estimates of future river discharge. The results underline the challenges in using the current generation of RCMs for local climate impact studies on flooding.

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Section: The Upper Severn River Catchment Uk and Observed Datasetsmentioning

confidence: 99%

Modelling climate impact on floods with ensemble climate projections

Cloke

Wetterhall

et al. 2012

Quart J Royal Meteoro Soc

109

104

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“…He et al (2009) were amongst the first to use TIGGE for flood warning. They used TIGGE ensemble forecasts to drive a coupled atmospheric-hydrological-hydraulic model system for a meso-scale catchment (4062 km 2 ) located in the Midlands region of England.…”

Section: Accepted M Manuscriptmentioning

confidence: 99%

The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems

Rossa¹,

Liechti

Zappa

et al. 2011

Atmospheric Research

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Publication informationAtmospheric Research, 100 (2-3): 150-167Publisher Elsevier This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT A C C E P T E D M A N U S C R I P T ACCEPTED MANUSCRIPT AbstractQuantifying uncertainty in flood forecasting is a difficult task, given the multiple and strongly nonlinear model components involved in such a system. Much effort has been and is being invested in the quest of dealing with uncertain precipitation observations and forecasts and the propagation of such uncertainties through hydrological and hydraulic models predicting river discharges and risk for inundation. The COST 731 Action is one of these and constitutes a European initiative which deals with the quantification of forecast uncertainty in hydro-meteorological forecast systems.COST 731 addresses three major lines of development: (1) combining meteorological and hydrological models to form a forecast chain, (2) propagating uncertainty information through this chain and make it available to end users in a suitable form, (3)

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“…A prototype of such a system was successfully demonstrated by Pappenberger et al (2008) using seven weather centres in the European Flood Alert System (EFAS) to hindcast the October 2007 flood event in the Danube basin in Romania. A study carried out for a meso-scale catchment (4062 km 2 ) in the Midlands region of England set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by TIGGE ensemble forecasts to produce a probabilistic discharge and flood inundation forecast (He et al, 2009). Both studies showed that the TIGGE database can produce an improved early flood warning of up to 10 days ahead.…”

Section: Introductionmentioning

confidence: 99%

Ensemble forecasting using TIGGE for the July–September 2008 floods in the Upper Huai catchment: a case study

Wetterhall

Bao

et al. 2010

Atmospheric Science Letters

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We present a case study using the TIGGE database for flood warning in the Upper Huai catchment (ca. 30 672 km 2 ). TIGGE ensemble forecasts from 6 meteorological centres with 10-day lead time were extracted and disaggregated to drive the Xinanjiang model to forecast discharges for flood events in July-September 2008. The results demonstrated satisfactory flood forecasting skills with clear signals of floods up to 10 days in advance. The forecasts occasionally show discrepancies both in time and space. Forecasting quality could potentially be improved by using temporal and spatial corrections of the forecasted precipitation.

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

Cited by 120 publications

References 29 publications

Modelling climate impact on floods with ensemble climate projections

Modelling climate impact on floods with ensemble climate projections

The COST 731 Action: A review on uncertainty propagation in advanced hydro-meteorological forecast systems

Ensemble forecasting using TIGGE for the July–September 2008 floods in the Upper Huai catchment: a case study

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