A methodology for quantifying uncertainty in climate projections

Mort D. Webster, Andrei P. Sokolov

Research output: Contribution to journalArticle

44 Citations (Scopus)

Abstract

Possible climate change caused by an increase in greenhouse gas concentrations, despite having been a subject of intensive study in recent years, is still very uncertain. Uncertainties in projections of different climate variables are usually described only by the ranges of possible values. For assessing the possible impact of climate change, it would be more useful to have probability distributions for these variables. Obtaining such distributions is usually very computationally expensive and requires knowledge of probability distributions for characteristics of the climate system that affect climate projections. A few studies of this kind have been carried out with energy balance/upwelling diffusion models. Here we demonstrate a methodology for performing a similar study with a 2 dimensional (zonally averaged) climate model that reproduces the behavior of coupled atmosphere/ocean general circulation models more realistically than energy balance models. This methodology involves application of the Deterministic Equivalent Modeling Method to derive functional approximations of the model's probabilistic response. Monte Carlo analysis is then performed on the approximations. An application of the methodology is demonstrated by deriving the uncertainty in surface air temperature change and sea level rise due to thermal expansion of the ocean that result from uncertainties in climate sensitivity and the rate of heat uptake by the deep ocean for a prescribed increase in atmospheric CO2 concentration. We also demonstrate propagation of correlated uncertainties through different models, by presenting results that include uncertainty in projected carbon emissions.

Original languageEnglish (US)
Pages (from-to)417-446
Number of pages30
JournalClimatic Change
Volume46
Issue number4
DOIs
StatePublished - Jan 1 2000

Fingerprint

methodology
climate
energy balance
ocean
Monte Carlo analysis
climate change
thermal expansion
carbon emission
general circulation model
climate modeling
upwelling
greenhouse gas
surface temperature
air temperature
atmosphere
modeling
distribution
rate
method
sea level rise

All Science Journal Classification (ASJC) codes

  • Global and Planetary Change
  • Atmospheric Science

Cite this

Webster, Mort D. ; Sokolov, Andrei P. / A methodology for quantifying uncertainty in climate projections. In: Climatic Change. 2000 ; Vol. 46, No. 4. pp. 417-446.
@article{e2d3a4666189484b990c51aac896dbf0,
title = "A methodology for quantifying uncertainty in climate projections",
abstract = "Possible climate change caused by an increase in greenhouse gas concentrations, despite having been a subject of intensive study in recent years, is still very uncertain. Uncertainties in projections of different climate variables are usually described only by the ranges of possible values. For assessing the possible impact of climate change, it would be more useful to have probability distributions for these variables. Obtaining such distributions is usually very computationally expensive and requires knowledge of probability distributions for characteristics of the climate system that affect climate projections. A few studies of this kind have been carried out with energy balance/upwelling diffusion models. Here we demonstrate a methodology for performing a similar study with a 2 dimensional (zonally averaged) climate model that reproduces the behavior of coupled atmosphere/ocean general circulation models more realistically than energy balance models. This methodology involves application of the Deterministic Equivalent Modeling Method to derive functional approximations of the model's probabilistic response. Monte Carlo analysis is then performed on the approximations. An application of the methodology is demonstrated by deriving the uncertainty in surface air temperature change and sea level rise due to thermal expansion of the ocean that result from uncertainties in climate sensitivity and the rate of heat uptake by the deep ocean for a prescribed increase in atmospheric CO2 concentration. We also demonstrate propagation of correlated uncertainties through different models, by presenting results that include uncertainty in projected carbon emissions.",
author = "Webster, {Mort D.} and Sokolov, {Andrei P.}",
year = "2000",
month = "1",
day = "1",
doi = "10.1023/A:1005685317358",
language = "English (US)",
volume = "46",
pages = "417--446",
journal = "Climatic Change",
issn = "0165-0009",
publisher = "Springer Netherlands",
number = "4",

}

A methodology for quantifying uncertainty in climate projections. / Webster, Mort D.; Sokolov, Andrei P.

In: Climatic Change, Vol. 46, No. 4, 01.01.2000, p. 417-446.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A methodology for quantifying uncertainty in climate projections

AU - Webster, Mort D.

AU - Sokolov, Andrei P.

PY - 2000/1/1

Y1 - 2000/1/1

N2 - Possible climate change caused by an increase in greenhouse gas concentrations, despite having been a subject of intensive study in recent years, is still very uncertain. Uncertainties in projections of different climate variables are usually described only by the ranges of possible values. For assessing the possible impact of climate change, it would be more useful to have probability distributions for these variables. Obtaining such distributions is usually very computationally expensive and requires knowledge of probability distributions for characteristics of the climate system that affect climate projections. A few studies of this kind have been carried out with energy balance/upwelling diffusion models. Here we demonstrate a methodology for performing a similar study with a 2 dimensional (zonally averaged) climate model that reproduces the behavior of coupled atmosphere/ocean general circulation models more realistically than energy balance models. This methodology involves application of the Deterministic Equivalent Modeling Method to derive functional approximations of the model's probabilistic response. Monte Carlo analysis is then performed on the approximations. An application of the methodology is demonstrated by deriving the uncertainty in surface air temperature change and sea level rise due to thermal expansion of the ocean that result from uncertainties in climate sensitivity and the rate of heat uptake by the deep ocean for a prescribed increase in atmospheric CO2 concentration. We also demonstrate propagation of correlated uncertainties through different models, by presenting results that include uncertainty in projected carbon emissions.

AB - Possible climate change caused by an increase in greenhouse gas concentrations, despite having been a subject of intensive study in recent years, is still very uncertain. Uncertainties in projections of different climate variables are usually described only by the ranges of possible values. For assessing the possible impact of climate change, it would be more useful to have probability distributions for these variables. Obtaining such distributions is usually very computationally expensive and requires knowledge of probability distributions for characteristics of the climate system that affect climate projections. A few studies of this kind have been carried out with energy balance/upwelling diffusion models. Here we demonstrate a methodology for performing a similar study with a 2 dimensional (zonally averaged) climate model that reproduces the behavior of coupled atmosphere/ocean general circulation models more realistically than energy balance models. This methodology involves application of the Deterministic Equivalent Modeling Method to derive functional approximations of the model's probabilistic response. Monte Carlo analysis is then performed on the approximations. An application of the methodology is demonstrated by deriving the uncertainty in surface air temperature change and sea level rise due to thermal expansion of the ocean that result from uncertainties in climate sensitivity and the rate of heat uptake by the deep ocean for a prescribed increase in atmospheric CO2 concentration. We also demonstrate propagation of correlated uncertainties through different models, by presenting results that include uncertainty in projected carbon emissions.

UR - http://www.scopus.com/inward/record.url?scp=0033830447&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033830447&partnerID=8YFLogxK

U2 - 10.1023/A:1005685317358

DO - 10.1023/A:1005685317358

M3 - Article

AN - SCOPUS:0033830447

VL - 46

SP - 417

EP - 446

JO - Climatic Change

JF - Climatic Change

SN - 0165-0009

IS - 4

ER -