Probability-Weighted Ensembles of U.S. County-Level Climate Projections for Climate Risk Analysis

Probability-Weighted Ensembles of U.S. County-Level Climate Projections for... AbstractQuantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, two such methods, surrogate/model mixed ensemble (SMME) and Monte Carlo pattern/residual (MCPR), are developed and then are applied to construct joint probability density functions (PDFs) of temperature and precipitation change over the twenty-first century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections that are consistent with the Intergovernmental Panel on Climate Change’s interpretation of an equal-weighted Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble but also provide full PDFs that include tail estimates. For example, both methods indicate that, under “Representative Concentration Pathway” 8.5, there is a 5% chance that the contiguous United States could warm by at least 8°C between 1981–2010 and 2080–99. Variance decomposition of SMME and MCPR projections indicates that background variability dominates uncertainty in the early twenty-first century whereas forcing-driven changes emerge in the second half of the twenty-first century. By separating CMIP5 projections into unforced and forced components using linear regression, these methods generate estimates of unforced variability from existing CMIP5 projections without requiring the computationally expensive use of multiple realizations of a single GCM. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Applied Meteorology and Climatology American Meteorological Society

Probability-Weighted Ensembles of U.S. County-Level Climate Projections for Climate Risk Analysis

Loading next page...
 
/lp/ams/probability-weighted-ensembles-of-u-s-county-level-climate-projections-pECH2xqVld
Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1558-8432
eISSN
1558-8432
D.O.I.
10.1175/JAMC-D-15-0302.1
Publisher site
See Article on Publisher Site

Abstract

AbstractQuantitative assessment of climate change risk requires a method for constructing probabilistic time series of changes in physical climate parameters. Here, two such methods, surrogate/model mixed ensemble (SMME) and Monte Carlo pattern/residual (MCPR), are developed and then are applied to construct joint probability density functions (PDFs) of temperature and precipitation change over the twenty-first century for every county in the United States. Both methods produce likely (67% probability) temperature and precipitation projections that are consistent with the Intergovernmental Panel on Climate Change’s interpretation of an equal-weighted Coupled Model Intercomparison Project phase 5 (CMIP5) ensemble but also provide full PDFs that include tail estimates. For example, both methods indicate that, under “Representative Concentration Pathway” 8.5, there is a 5% chance that the contiguous United States could warm by at least 8°C between 1981–2010 and 2080–99. Variance decomposition of SMME and MCPR projections indicates that background variability dominates uncertainty in the early twenty-first century whereas forcing-driven changes emerge in the second half of the twenty-first century. By separating CMIP5 projections into unforced and forced components using linear regression, these methods generate estimates of unforced variability from existing CMIP5 projections without requiring the computationally expensive use of multiple realizations of a single GCM.

Journal

Journal of Applied Meteorology and ClimatologyAmerican Meteorological Society

Published: Oct 20, 2016

There are no references for this article.

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off