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Title: Uncertainty quantification of US Southwest climate from IPCC projections.

Abstract

The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) made extensive use of coordinated simulations by 18 international modeling groups using a variety of coupled general circulation models (GCMs) with different numerics, algorithms, resolutions, physics models, and parameterizations. These simulations span the 20th century and provide forecasts for various carbon emissions scenarios in the 21st century. All the output from this panoply of models is made available to researchers on an archive maintained by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at LLNL. I have downloaded this data and completed the first steps toward a statistical analysis of these ensembles for the US Southwest. This constitutes the final report for a late start LDRD project. Complete analysis will be the subject of a forthcoming report.

Authors:
Publication Date:
Research Org.:
Sandia National Laboratories
Sponsoring Org.:
USDOE
OSTI Identifier:
1011224
Report Number(s):
SAND2011-0393
TRN: US201109%%413
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; ALGORITHMS; CARBON; CLIMATE MODELS; CLIMATES; DIAGNOSIS; GENERAL CIRCULATION MODELS; LAWRENCE LIVERMORE NATIONAL LABORATORY; PHYSICS; SIMULATION

Citation Formats

Boslough, Mark Bruce Elrick. Uncertainty quantification of US Southwest climate from IPCC projections.. United States: N. p., 2011. Web. doi:10.2172/1011224.
Boslough, Mark Bruce Elrick. Uncertainty quantification of US Southwest climate from IPCC projections.. United States. doi:10.2172/1011224.
Boslough, Mark Bruce Elrick. Sat . "Uncertainty quantification of US Southwest climate from IPCC projections.". United States. doi:10.2172/1011224. https://www.osti.gov/servlets/purl/1011224.
@article{osti_1011224,
title = {Uncertainty quantification of US Southwest climate from IPCC projections.},
author = {Boslough, Mark Bruce Elrick},
abstractNote = {The Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) made extensive use of coordinated simulations by 18 international modeling groups using a variety of coupled general circulation models (GCMs) with different numerics, algorithms, resolutions, physics models, and parameterizations. These simulations span the 20th century and provide forecasts for various carbon emissions scenarios in the 21st century. All the output from this panoply of models is made available to researchers on an archive maintained by the Program for Climate Model Diagnosis and Intercomparison (PCMDI) at LLNL. I have downloaded this data and completed the first steps toward a statistical analysis of these ensembles for the US Southwest. This constitutes the final report for a late start LDRD project. Complete analysis will be the subject of a forthcoming report.},
doi = {10.2172/1011224},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Jan 01 00:00:00 EST 2011},
month = {Sat Jan 01 00:00:00 EST 2011}
}

Technical Report:

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  • We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies.more » At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets, and their differences quantified using two metrics. Projected changes from 2051 to 2300 under the scenario with the highest representative and extended concentration pathways (RCP8.5 and ECP8.5) have then been determined. The network of models capable of reproducing well major climate modes in the recent past, changes little during this century. In contrast, among those models the uncertainties in the projections after 2100 remain substantial, and primarily associated with divergences in the representation of the modes of variability, particularly of the El Niño Southern Oscillation (ENSO), and their connectivity, and therefore with their intrinsic predictability, more so than with differences in the mean state evolution. Additionally, we evaluated the relation between the size and the ‘strength’ of the area identified by the network analysis as corresponding to ENSO noting that only a small subset of models can reproduce realistically the observations.« less
  • No abstract provided.
  • This paper summarizes work from the Intergovernmental Panel on Climate Change (IPCC) and describes the World Meteorological Organization (WMO) program activities. Discussion of IPCC climate projections includes the subtopics of climate models, assumptions, projections, uncertainties, and implications. WMO support programs and future activities are also outlined. Future activities with high priorities include technology assessment for mitigating greenhouse gas emissions, the development of improved climate models, improvements in global and regional projections of climate change, determination of the impact of climate change on extreme weather events, and the need for better cost/benefit estimates due to climate change. 6 refs., 5 figs.