Theoretical and Applied Climatology

, Volume 132, Issue 1–2, pp 153–166 | Cite as

Precipitation projections under GCMs perspective and Turkish Water Foundation (TWF) statistical downscaling model procedures

Original Paper
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Abstract

The statistical climate downscaling model by the Turkish Water Foundation (TWF) is further developed and applied to a set of monthly precipitation records. The model is structured by two phases as spatial (regional) and temporal downscaling of global circulation model (GCM) scenarios. The TWF model takes into consideration the regional dependence function (RDF) for spatial structure and Markov whitening process (MWP) for temporal characteristics of the records to set projections. The impact of climate change on monthly precipitations is studied by downscaling Intergovernmental Panel on Climate Change-Special Report on Emission Scenarios (IPCC-SRES) A2 and B2 emission scenarios from Max Plank Institute (EH40PYC) and Hadley Center (HadCM3). The main purposes are to explain the TWF statistical climate downscaling model procedures and to expose the validation tests, which are rewarded in same specifications as “very good” for all stations except one (Suhut) station in the Akarcay basin that is in the west central part of Turkey. Eventhough, the validation score is just a bit lower at the Suhut station, the results are “satisfactory.” It is, therefore, possible to say that the TWF model has reasonably acceptable skill for highly accurate estimation regarding standard deviation ratio (SDR), Nash–Sutcliffe efficiency (NSE), and percent bias (PBIAS) criteria. Based on the validated model, precipitation predictions are generated from 2011 to 2100 by using 30-year reference observation period (1981–2010). Precipitation arithmetic average and standard deviation have less than 5% error for EH40PYC and HadCM3 SRES (A2 and B2) scenarios.

Notes

Acknowledgements

This study is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) with grant number 1059B141501044. The corresponding author would like to thank TUBITAK for its support and Assist. Prof. Dr. Ahmet ÖZTOPAL for valuable contributions in this study. Also, the authors wish to thank Turkish State Meteorological Service (TSMS) for the supply of long-term monthly mean climatic variables.

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Copyright information

© Springer-Verlag Wien 2017

Authors and Affiliations

  1. 1.Civil Engineering Faculty, Department of Civil EngineeringIstanbul Technical UniversityIstanbulTurkey
  2. 2.Glenn Department of Civil EngineeringClemson UniversityClemsonUSA

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