A Non-Parametric, Statistical Down Scaling Algorithm Applied to the Rohini River Basin, Nepal, Theoretical and Applied Climatology

* If this publication is shareable, you can access it by clicking the "Download in English" button. If it is a journal article or book chapter, a link is provided in the text below. 

Overview

Climate change scenarios generated by general circulation models have too coarse a spatial resolution to be useful in planning disaster risk reduction and climate change adaptation strategies at regional to river basin scales. This study presents a new non-parametric statistical K-nearest neighbor algorithm for downscaling climate change scenarios for the Rohini River Basin in Nepal. The study is an introduction to the methodology and discusses its strengths and limitations within the context of hindcasting basin precipitation for the period of 1976?2006. The actual downscaled climate change projections are not presented here. In general, we find that this method is quite robust and well suited to the data-poor situations common in developing countries. The method is able to replicate historical rainfall values in most months, except for January, September, and October. As with any downscaling technique, whether numerical or statistical, data limitations significantly constrain model ability. The method was able to confirm that the dataset available for the Rohini Basin does not capture long-term climatology. Yet, we do find that the hindcasts generated with this methodology do have enough skill to warrant pursuit of downscaling climate change scenarios for this particularly poor and vulnerable region of the world. Keywords: Climate Modeling and Scenario Planning Keywords: Climate Modeling and Scenario Planning. Retrieve article at https://link.springer.com/article/10.1007/s00704-010-0301-z

Authors: Sarah Optiz-Stapleton; Subhrendu Gangopadhyay

Citation: Opitz-Stapleton, S., & Gangopadhyay, S. (2011). A non-parametric, statistical down scaling algorithm applied to the Rohini River Basin, Nepal. Theoretical and Applied Climatology, 103(3-4), 375-386. doi: 10.1007/s00704-010-0301-z

Funded by: UK Department for International Development (DFID); The US National Oceanic and Atmospheric Administration (NOAA)

ADDRESS

SUBSCRIBE TO OUR NEWSLETTER 

Sign up here for occasional updates to keep you in the know

PO Box 20321

Boulder, Colorado 80308 USA

Phone 303-656-9609

  • Facebook - White Circle
  • LinkedIn - White Circle
  • Twitter - White Circle
  • Blogger - White Circle
  • YouTube - White Circle
  • Google+ - White Circle

© 2020 by ISET-INTERNATIONAL