Modelling climate impact on floods with ensemble climate projections

Cloke, Hannah; Wetterhall, F.; He, Yi; Freer, J. E.; Pappenberger, Florian

doi:10.1002/qj.1998

Cited by 108 publications

(115 citation statements)

References 53 publications

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“…The RCM/GCMs simulations are generally biased and cannot be used as forcing variables in drought projection without some form of prior bias correction. Several studies have been performed in which a bias correction method was applied to RCM data (e.g., [36][37][38][39]). In this study, the Quantile Mapping (QM) method [40][41][42] was applied for each catchment to correct the simulated precipitation and air temperature time series.…”

Section: Climate Model Projectionsmentioning

confidence: 99%

Hydro-Meteorological Drought Projections into the 21-st Century for Selected Polish Catchments

Meresa

Osuch

Romanowicz

2016

Water

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Abstract:The nature of drought conditions is estimated using a range of indices describing different aspects of drought events. Three drought indices are evaluated, namely the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Runoff Index (SRI), using observed hydroclimatic data and applying them to hydro-meteorological projections into the 21st century. The first two indices are evaluated using only meteorological variables and from this point of view, are better suited to meteorological drought projections than the third index, SRI, which is based on catchment discharge and represents hydrological drought. We assess information contained in those indices and their suitability to catchment scale climate projection drought assessment in ten selected Polish catchments, representing different hydro-climatic conditions, which are used as a case study. Projections of climatic variables (precipitation and temperature) are obtained from the EURO-CORDEX initiative derived from seven climate models at a grid resolution of 12.5 km for the time period 1971-2100. Future runoff projections for the catchments are obtained using a conceptual rainfall-runoff model (HBV). The results of analyses of indices based on observations in the reference period show consistent estimates for most of the catchments. Hydro-meteorological climate model projections for three periods, including the reference period 1971-2000, and two 30-year periods, near-future 2021-2050 and far-future 2071-2100, are used to estimate changes of future drought conditions in the catchments studied. The results show a substantial variation of temporal drought patterns over the catchments and their dependence on projected precipitation and temperature variables and the type of indices applied. Of the three indices studied, only SPEI projections indicate drier conditions in the catchments in the far-future period. The other two indices, SPI and SRI, indicate wetter climates in the future.

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Section: Climate Model Projectionsmentioning

confidence: 99%

Hydro-Meteorological Drought Projections into the 21-st Century for Selected Polish Catchments

Meresa

Osuch

Romanowicz

2016

Water

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“…Developing global-scale flood maps (Porter and Demeritt, 2012) is of increasing interest in the scientific community with great applicability in the (re)insurance industry. Global gridded precipitation data sets from satellites and reanalysis data sets derived from data assimilation systems are two main sources for deriving global flood hazard maps (Cloke et al, 2013;Kappes et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications

Seyyedi

Anagnostou

Beighley

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Deriving flood hazard maps for ungauged basins typically requires simulating a long record of annual maximum discharges. To improve this approach, precipitation from global reanalysis systems must be downscaled to a spatial and temporal resolution applicable for flood modeling. This study evaluates such downscaling and error correction approaches for improving hydrologic applications using a combination of NASA's Global Land Data Assimilation System (GLDAS) precipitation data set and a higher resolution multi-satellite precipitation product (TRMM). The study focuses on 437 flood-inducing storm events that occurred over a period of ten years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011) in the Susquehanna River basin located in the northeastern United States. A validation strategy was devised for assessing error metrics in rainfall and simulated runoff as function of basin area, storm severity, and season. The WSR-88D gauge-adjusted radar-rainfall (stage IV) product was used as the reference rainfall data set, while runoff simulations forced with the stage IV precipitation data set were considered as the runoff reference. Results show that the generated rainfall ensembles from the downscaled reanalysis product encapsulate the reference rainfall. The statistical analysis consists of frequency and quantile plots plus mean relative error and root-mean-square error statistics. The results demonstrated improvements in the precipitation and runoff simulation error statistics of the satellite-driven downscaled reanalysis data set compared to the original reanalysis precipitation product. Results vary by season and less by basin scale. In the fall season specifically, the downscaled product has 3 times lower mean relative error than the original product; this ratio increases to 4 times for the simulated runoff values. The proposed downscaling scheme is modular in design and can be applied on any gridded satellite and reanalysis data set.

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“…In smaller catchments, on the scale of a few RCM grid points and with quick response times, this can potentially lead to an underestimation of high flow situations, regardless of whether the RCM has a wet or dry mean bias over the catchment. Other reasons are smoothing between grid points and inadequate representation of the physical processes in the model code (Cloke et al, 2012). Therefore at present, impact studies that rely on a correct representation of precipitation, such as those dealing with flood risk, cannot usefully use direct RCM output.…”

Section: F Wetterhall Et Al: Conditioning Model Output Statistics Omentioning

confidence: 99%

Conditioning model output statistics of regional climate model precipitation on circulation patterns

Wetterhall

Pappenberger

et al. 2012

Nonlin. Processes Geophys.

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Abstract. Dynamical downscaling of Global Climate Models (GCMs) through regional climate models (RCMs) potentially improves the usability of the output for hydrological impact studies. However, a further downscaling or interpolation of precipitation from RCMs is often needed to match the precipitation characteristics at the local scale. This study analysed three Model Output Statistics (MOS) techniques to adjust RCM precipitation; (1) a simple direct method (DM), (2) quantile-quantile mapping (QM) and (3) a distributionbased scaling (DBS) approach. The modelled precipitation was daily means from 16 RCMs driven by ERA40 reanalysis data over the 1961-2000 provided by the ENSEM-BLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts) project over a small catchment located in the Midlands, UK. All methods were conditioned on the entire time series, separate months and using an objective classification of Lamb's weather types. The performance of the MOS techniques were assessed regarding temporal and spatial characteristics of the precipitation fields, as well as modelled runoff using the HBV rainfall-runoff model. The results indicate that the DBS conditioned on classification patterns performed better than the other methods, however an ensemble approach in terms of both climate models and downscaling methods is recommended to account for uncertainties in the MOS methods.

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Modelling climate impact on floods with ensemble climate projections

Cited by 108 publications

References 53 publications

Hydro-Meteorological Drought Projections into the 21-st Century for Selected Polish Catchments

Hydro-Meteorological Drought Projections into the 21-st Century for Selected Polish Catchments

Satellite-driven downscaling of global reanalysis precipitation products for hydrological applications

Conditioning model output statistics of regional climate model precipitation on circulation patterns

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