Emerging megacities
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Lüdecke, Mathias K. B.; Budde, Martin; Kit, Oles; Reckien, Diana
Climate Change Scenarios for Hyderabad
Integrating uncertainties and consolidation
Emerging megacities Discussion Papers, Volume 1/2010
ISBN/EAN: 978-3-86741-839-3
First published in 2012 by Europaeischer Hochschulverlag GmbH & Co KG, Bremen, Germany.
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Climate Change Scenarios for Hyderabad
Integrating Uncertainties and Consolidation
Mathias K. B. Lüdecke*†, Martin Budde†, Oles Kit†, Diana Reckien†
September 2010
Abstract
The paper evaluates the global climate projections of 17 AOGCMs with the aim to project 4 climatic variables under two different global emission scenarios (SRES B1 and A2) for the area of Hyderabad (India) for the 21st century. The evaluated model runs were produced within the IPCC AR4-process. We applied a statistical downscaling to be able to evaluate that large number of model runs. Aggregation of results was done on the basis of model and variable specific weights reflecting the accuracy of reproduction of the current climate. Projection certainty was assessed by the degree of model consensus.
Key words: climate change, local climate projections, Hyderabad, heat waves, intense rain
* Corresponding author. Email: luedeke@pik-potsdam.de
† Potsdam Institute for Climate Impact Research (PIK), Research Domain: Climate Impacts and Vulnerabilities, P.O. Box 60 12 03, 14412 Potsdam
1 Introduction
2 Evaluation Algorithms
3 Data Sources and Preparation
4 Results
5 Discussion and Policy Implications
6 References
Appendix
This paper describes the continuation of the work from Lüdeke, Budde et al. (2009). It is about the refinement and consolidation of the projection of climate change signals which the city of Hyderabad and its peri-urban region have to expect.
The climate variables under investigation are:
One objective is to identify the effect of different global emission scenarios on the projected climate variables in Hyderabad. The question, in how far the reduction of global emissions will reduce climate change signals in, e.g., Hyderabad is closely related to efforts one is willing to undertake in contributing to and putting forward these emission reductions. To scan the range of possible future developments of the global greenhouse gas emissions, we choose in this paper the SRES-A2 scenario for a high-emission future and the SRES-B1 scenario for a significant global emission reduction path (SRES, Nakićenović and Swart 2000).
The general methodological idea (for details see Lüdeke, Budde et al., 2009) is to reflect the full range of available global climate change projections (depending on the climate variable and the emission scenario 26-30 different runs generated by 17 climate models) as their differences are decisive for differences of the downscaling results, independent from the chosen method (Hollweg et al. 2008; Orlowsky et al. 2008). So we decided to use relatively simple and fast statistical downscaling algorithms (instead of, e.g., mechanistic, nested high resolution models) to be able to evaluate the full range of Atmosphere-Ocean General Circulation Models (AOGCMs) as a basis for a proper uncertainty analysis.
The main improvements compared to the 2009-report are:
To our knowledge, this is the first time that the full range of available AOGCM projections is used to assess multivariate local climate change signals by considering a quality measure for the single AOGCMs.