Weighting of model results for improving best estimates of climate change

Räisänen, Jouni; Ruokolainen, Leena; Ylhäisi, Jussi S.

doi:10.1007/s00382-009-0659-8

Cited by 80 publications

(60 citation statements)

References 18 publications

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“…Instead we made use of a repository of existing runs of a global hydrological model forced by a multi-model ensemble of climate data for both a reference period and 2071-2100 projections. Comparable weighting methods have been applied for GCM ensemble averaging of precipitation and temperature (see Giorgi and Mearns, 2002;Räisänen et al, 2010), but applying the approach to discharge is new. By weighting the simulated discharge with discharge observations a multi-model ensemble analysis of climate change effects could be made for a particular location, in this case the lower Brahmaputra at Bahadurabad station.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling

Gain

Immerzeel

Weiland

et al. 2011

Hydrol. Earth Syst. Sci.

118

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Abstract. Climate change is likely to have significant effects on the hydrology. The Ganges-Brahmaputra river basin is one of the most vulnerable areas in the world as it is subject to the combined effects of glacier melt, extreme monsoon rainfall and sea level rise. To what extent climate change will impact river flow in the Brahmaputra basin is yet unclear, as climate model studies show ambiguous results. In this study we investigate the effect of climate change on both low and high flows of the lower Brahmaputra. We apply a novel method of discharge-weighted ensemble modeling using model outputs from a global hydrological models forced with 12 different global climate models (GCMs). Our analysis shows that only a limited number of GCMs are required to reconstruct observed discharge. Based on the GCM outputs and long-term records of observed flow at Bahadurabad station, our method results in a multi-model weighted ensemble of transient stream flow for the period 1961-2100. Using the constructed transients, we subsequently project future trends in low and high river flow. The analysis shows that extreme low flow conditions are likely to occur less frequent in the future. However a very strong increase in peak flows is projected, which may, in combination with projected sea level change, have devastating effects for Bangladesh. The methods presented in this study are more widely applicable, in that existing multi-model streamflow simulations from global hydrological models can be weighted against observed streamflow data to assess at first order the effects of climate change for specific river basins.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling

Gain

Immerzeel

Weiland

et al. 2011

Hydrol. Earth Syst. Sci.

118

View full text Add to dashboard Cite

show abstract

“…the 'ability of AOGCMs to reproduce different aspects of present-day climate' (Giorgi & Mearns 2002, p. 1142, as characterized in reanalysis data. Due to a lack of general consensus, there currently exist many different GCM performance measures, which can be classified as those including (1) a single and (2) several of the time-series characteristics relevant for climate modeling (Giorgi & Mearns 2002, Räisänen et al 2010). These are: climatological mean state (Randall et al 2007, Gleckler et al 2008, frequency of extreme events (Kharin & Zwiers 2000), seasonal cycle (Errasti et al 2010), low frequency variability (Benestad 2003, Santer et al 2008, and interannual variability (Gleckler et al 2008).…”

Section: Introductionmentioning

confidence: 99%

Validation of the ENSEMBLES global climate models over southwestern Europe using probability density functions, from a downscaling perspective

Brands

Herrera²,

San-Martín³

et al. 2011

Clim. Res.

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In this study we analyzed the performance of 12 state-of-the-art global climate models (GCMs) from 2 different model generations used in the ENSEMBLES project (a European Commissionfunded climate-change research project) over southwestern Europe. For this purpose, we assessed the similarity of the simulated and quasi-observed (reanalysis) probability density functions for circulation, temperature, and humidity variables at various pressure levels, which we chose from a statisticaldownscaling point of view. Our main goals were to assess which GCM variables can be reliably used as predictors for downscaling, and which GCMs perform especially well over the region under study. Results showed that specific humidity is as reliably reproduced as circulation and temperature variables, and that overall performance is best for the Hadley Centre's HADGEM2 model. Secondary goals were to estimate the skillful scale of the models, and to measure the added value of bias correction, a post-processing step commonly used in practice. We found that all models lack performance at the scale of individual grid boxes, indicating that they are not robustly skillful at their smallest scale. We also found that model performance generally improves after removing monthly bias. However, model errors at higher-order moments, which cannot be removed by simply correcting the bias, were common in some models.

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“…However, results of several studies showed that more reliable results are obtained by using projections of a cluster of better performing models or calculating a weighted ensemble average (Sperna Weiland et al 2012). In the weighted ensemble analysis, the individual GCM weights were derived from model performance and future ensemble convergence (Giorgi and Mearns 2002;Murphy et al 2004;Räisänen et al 2010). In this study, weights were determined by using the model performance, i.e., historical relationship between model outputs and observations.…”

Section: Discussionmentioning

confidence: 99%

Thresholds of hydrologic flow regime of a river and investigation of climate change impact—the case of the Lower Brahmaputra river Basin

et al. 2013

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. (2013) AbstractThe sustainability of social-ecological systems depends on river flows being maintained within a range to which those systems are adapted. In order to determine the extent of this natural range of variation, we assess ecological flow thresholds and the occurrence of potentially damaging flood events to society in the context of the Lower Brahmaputra river basin. The ecological flow threshold was calculated using twenty-two 'Range of Variability (RVA)' parameters, considering the range between ± 1 standard deviation from the mean of the natural flow. Damaging flood events were calculated using flood frequency analysis of Annual Maxima series and using the flood classification of Bangladesh. The climate change impacts on future river flow were calculated by using a weighted ensemble analysis of twelve global circulation models (GCMs) outputs driving a large-scale hydrologic model. The simulated climate change induced altered flow regime of the Lower Brahmaputra River Basin was then investigated and compared with the calculated threshold flows. The results demonstrate that various parameters including the monthly mean of low flow (January, February and March) and high flow (June, July and August) periods, the 7-day average minimum flow, and the yearly maximum flow will exceed the threshold conditions by under the business-as-usual A1B and A2 future scenarios. The results have a number of policy level implications for government agencies of the Lower Brahmaputra River Basin, specifically for Bangladesh. The calculated thresholds may be used as a good basis for negotiations with other riparian countries of the basin. The methodological approach presented in this study can be applied to other river basins and provide a useful basis for transboundary water resources management.

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Weighting of model results for improving best estimates of climate change

Cited by 80 publications

References 18 publications

Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling

Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling

Validation of the ENSEMBLES global climate models over southwestern Europe using probability density functions, from a downscaling perspective

Thresholds of hydrologic flow regime of a river and investigation of climate change impact—the case of the Lower Brahmaputra river Basin

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Weighting of model results for improving best estimates of climate change

Cited by 80 publications

References 18 publications

Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling

Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling

Validation of the ENSEMBLES global climate ­models over southwestern Europe using probability density functions, from a downscaling perspective

Thresholds of hydrologic flow regime of a river and investigation of climate change impact—the case of the Lower Brahmaputra river Basin

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Product

Resources

About

Validation of the ENSEMBLES global climate models over southwestern Europe using probability density functions, from a downscaling perspective