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Title: An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology

Journal Article · · Earth System Science Data (Online)
 [1];  [1];  [1];  [2]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Joint Global Change Research Inst.
  2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Atmospheric Sciences and Global Change Division

Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We explore the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.

Research Organization:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC05-76RL01830
OSTI ID:
1358489
Alternate ID(s):
OSTI ID: 1700523
Report Number(s):
PNNL-SA-125442; KP1703030
Journal Information:
Earth System Science Data (Online), Vol. 9, Issue 1; ISSN 1866-3516
Publisher:
CopernicusCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 17 works
Citation information provided by
Web of Science

References (24)

Estimating Linear Trends: Simple Linear Regression versus Epoch Differences journal December 2015
Statistical Emulation of Climate Model Projections Based on Precomputed GCM Runs journal March 2014
Limited sensitivity analysis of regional climate change probabilities for the 21st century journal January 2005
Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling journal January 2007
A Scaling Approach to Probabilistic Assessment of Regional Climate Change journal May 2012
Time of emergence of climate signals: TIME OF EMERGENCE OF CLIMATE SIGNALS journal January 2012
Improved pattern scaling approaches for the use in climate impact studies: IMPROVED PATTERN SCALING APPROACHES journal May 2015
Polar amplification of climate change in coupled models journal September 2003
Temperature scaling pattern dependence on representative concentration pathway emission scenarios: A letter journal March 2012
Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models posted_content November 2016
Robustness of pattern scaled climate change scenarios for adaptation decision support journal December 2013
The potential of pattern scaling for projecting temperature-related extreme indices: POTENTIAL OF PATTERN SCALING FOR EXTREME INDICES journal February 2013
Assessing the strength of regional changes in near-surface climate associated with a global warming of 2°C journal May 2011
The next generation of scenarios for climate change research and assessment journal February 2010
Pattern scaling using ClimGen: monthly-resolution future climate scenarios including changes in the variability of precipitation journal October 2015
RCP 8.5—A scenario of comparatively high greenhouse gas emissions journal August 2011
GCM-based regional temperature and precipitation change estimates for Europe under four SRES scenarios applying a super-ensemble pattern-scaling method journal March 2007
Arctic amplification decreases temperature variance in northern mid- to high-latitudes journal June 2014
Climate Change 2013 – The Physical Science Basis book March 2014
An Overview of CMIP5 and the Experiment Design journal April 2012
Pattern scaling: Its strengths and limitations, and an update on the latest model simulations journal January 2014
RCP4.5: a pathway for stabilization of radiative forcing by 2100 journal July 2011
Exploring precipitation pattern scaling methodologies and robustness among CMIP5 models journal January 2017
An Open-Access Cmip5 Pattern Library For Temperature And Precipitation: Description And Methodology. dataset January 2017