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LOCA Downscaling Analysis

A collection of notebooks and tools for analyzing the LOCA dataset

Background

The research community is developing a plethora of methods to evaluate the impacts of climate change on water resources; however, the research and applications communities currently have limited understanding on the advantages and limitations of new methodological developments, particularly in the area of climate downscaling.

The latest new method for climate impact assessments is the LOcalized Constructed Analog method (LOCA; Pierce et al., 2014). LOCA has recently been used to produce downscaled climate scenarios from multiple climate models across the contiguous USA. Further, LOCA information has been used to portray climate impacts on water resources, where LOCA scenarios are used as input to a high-resolution version of the Variable Infiltration Capacity model (VIC). As LOCA gains popularity, there is currently little information on the advantages and limitations of LOCA compared to alternative climate downscaling methods, and there is limited guidance on how changes in hydrologic processes portrayed by LOCA+VIC differ from previously published guidance.

The analysis included in this repository is intended to provide a improve the understanding of the specific advantages and limitations of emerging method for climate downscaling and climate impacts assessments, with specific focus on LOCA.

Goals:

  1. Evaluate climate downscaling by LOCA compared to alternative methods using the suite of evaluation metrics described by Gutmann et al. (2014).
  2. Assess how portrayals of climate impacts on hydrology from LOCA+VIC differ from previously published methods, using the suite of evaluation metrics described by Mizukami et al. (2016a).

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Acknowledgements

This work is jointly supported the US Bureau of Reclamation and the US Army Corps of Engineers. NCAR is supported by the National Science Foundation.

References:

  • Gutmann, Ethan, Tom Pruitt, Martyn P. Clark, Levi Brekke, Jeffrey R. Arnold, David A. Raff, and Roy M. Rasmussen, 2014: "An intercomparison of statistical downscaling methods used for water resource assessments in the United States." Water Resources Research 50, no. 9, 7167-7186.
  • Pierce, David W., Daniel R. Cayan, and Bridget L. Thrasher, 2014: "Statistical Downscaling Using Localized Constructed Analogs (LOCA)." Journal of Hydrometeorology 15, no. 6, 2558-2585.
  • Mizukami, Naoki, Martyn P. Clark, Ethan D. Gutmann, Pablo A. Mendoza, Andrew J. Newman, Bart Nijssen, Ben Livneh, Lauren E. Hay, Jeffrey R. Arnold, and Levi D. Brekke, 2016a: "Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: statistically downscaled forcing data and hydrologic models." Journal of Hydrometeorology 17, no. 1, 73-98.
  • Mizukami, Naoki, Martyn P. Clark, Roland J. Viger, Steve L. Markstrom, Lauren E. Hay, Jeffrey R. Arnold, and Levi D. Brekke, 2016b: "mizuRoute version 1: a river network routing tool for a continental domain water resources applications." Geoscientific Model Development 9, no. 6, 2223.