Towards the Application of Decadal Climate Predictions

Towards the Application of Decadal Climate Predictions AbstractDecadal prediction is a relatively new branch of climate science that bridges the gap between seasonal climate forecasts and multi-decadal to century climate change projections. This paper develops a three-step framework towards the potential application of decadal temperature predictions using the Community Climate System Model Version 4 (CCSM4). In step 1, we evaluate the predictions, finding that the temperature hindcasts show skill over some regions of the US and Canada. In step 2, we manipulate the predictions using two methods: a deterministic anomaly approach (like climate change projections) and a probabilistic tercile-based approach (like seasonal forecasts). In step 3, we translate the predictions by adding a delta (for the anomaly manipulation) and conducting a weighted resample (for the probabilistic manipulation), as well as using a new hybrid method. We demonstrate the framework predicting 2011-2015 using the 2010 initialized hindcast over two case study watersheds (Colorado and Ottawa). For the Colorado watershed, there was a noticeable shift towards higher temperatures, and the delta, weighted resample, and hybrid translations all did a better job capturing the observed temperatures than using climatology. For the Ottawa watershed, the observed temperatures over the period of prediction were only subtly different than climatology, therefore the differences between the translation methods was less noticeable. The advantages and disadvantages of the manipulation and translation approaches are discussed, as well as how their use will depend on the user context. We emphasize that skill should be tailored to particular applications and identify additional steps needed before the decadal temperature predictions can be readily incorporated into applications. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Meteorology and Climatology American Meteorological Society

Towards the Application of Decadal Climate Predictions

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1558-8432
D.O.I.
10.1175/JAMC-D-17-0113.1
Publisher site
See Article on Publisher Site

Abstract

AbstractDecadal prediction is a relatively new branch of climate science that bridges the gap between seasonal climate forecasts and multi-decadal to century climate change projections. This paper develops a three-step framework towards the potential application of decadal temperature predictions using the Community Climate System Model Version 4 (CCSM4). In step 1, we evaluate the predictions, finding that the temperature hindcasts show skill over some regions of the US and Canada. In step 2, we manipulate the predictions using two methods: a deterministic anomaly approach (like climate change projections) and a probabilistic tercile-based approach (like seasonal forecasts). In step 3, we translate the predictions by adding a delta (for the anomaly manipulation) and conducting a weighted resample (for the probabilistic manipulation), as well as using a new hybrid method. We demonstrate the framework predicting 2011-2015 using the 2010 initialized hindcast over two case study watersheds (Colorado and Ottawa). For the Colorado watershed, there was a noticeable shift towards higher temperatures, and the delta, weighted resample, and hybrid translations all did a better job capturing the observed temperatures than using climatology. For the Ottawa watershed, the observed temperatures over the period of prediction were only subtly different than climatology, therefore the differences between the translation methods was less noticeable. The advantages and disadvantages of the manipulation and translation approaches are discussed, as well as how their use will depend on the user context. We emphasize that skill should be tailored to particular applications and identify additional steps needed before the decadal temperature predictions can be readily incorporated into applications.

Journal

Journal of Applied Meteorology and ClimatologyAmerican Meteorological Society

Published: Jan 23, 2018

References

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