The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM

The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary condi...

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Main Authors: Zukor, Dorothy J., Martinson, Douglas G., Rind, David, Healy, Richard J., Parkinson, Claire L.
Language:unknown
Published: 2000
Subjects:
Online Access:http://hdl.handle.net/2060/20010018558
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spelling ftnasantrs:oai:casi.ntrs.nasa.gov:20010018558 2023-05-15T18:17:35+02:00 The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM Zukor, Dorothy J. Martinson, Douglas G. Rind, David Healy, Richard J. Parkinson, Claire L. Unclassified, Unlimited, Publicly available [2000] application/pdf http://hdl.handle.net/2060/20010018558 unknown Document ID: 20010018558 http://hdl.handle.net/2060/20010018558 No Copyright CASI Environment Pollution 2000 ftnasantrs 2015-03-15T02:34:59Z The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest. Other/Unknown Material Sea ice NASA Technical Reports Server (NTRS)
institution Open Polar
collection NASA Technical Reports Server (NTRS)
op_collection_id ftnasantrs
language unknown
topic Environment Pollution
spellingShingle Environment Pollution
Zukor, Dorothy J.
Martinson, Douglas G.
Rind, David
Healy, Richard J.
Parkinson, Claire L.
The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM
topic_facet Environment Pollution
description The Goddard Institute for Space Studies global climate model (GISS GCM) is used to examine the sensitivity of the simulated climate to sea ice concentration specifications in the type of simulation done in the Atmospheric Modeling Intercomparison Project (AMIP), with specified oceanic boundary conditions. Results show that sea ice concentration uncertainties of +/- 7% can affect simulated regional temperatures by more than 6 C, and biases in sea ice concentrations of +7% and -7% alter simulated annually averaged global surface air temperatures by -0.10 C and +0.17 C, respectively, over those in the control simulation. The resulting 0.27 C difference in simulated annual global surface air temperatures is reduced by a third, to 0.18 C, when considering instead biases of +4% and -4%. More broadly, least-squares fits through the temperature results of 17 simulations with ice concentration input changes ranging from increases of 50% versus the control simulation to decreases of 50% yield a yearly average global impact of 0.0107 C warming for every 1% ice concentration decrease, i.e., 1.07 C warming for the full +50% to -50% range. Regionally and on a monthly average basis, the differences can be far greater, especially in the polar regions, where wintertime contrasts between the +50% and -50% cases can exceed 30 C. However, few statistically significant effects are found outside the polar latitudes, and temperature effects over the non-polar oceans tend to be under 1 C, due in part to the specification of an unvarying annual cycle of sea surface temperatures. The +/- 7% and 14% results provide bounds on the impact (on GISS GCM simulations making use of satellite data) of satellite-derived ice concentration inaccuracies, +/- 7% being the current estimated average accuracy of satellite retrievals and +/- 4% being the anticipated improved average accuracy for upcoming satellite instruments. Results show that the impact on simulated temperatures of imposed ice concentration changes is least in summer, encouragingly the same season in which the satellite accuracies are thought to be worst. Hence the impact of satellite inaccuracies is probably less than the use of an annually averaged satellite inaccuracy would suggest.
author Zukor, Dorothy J.
Martinson, Douglas G.
Rind, David
Healy, Richard J.
Parkinson, Claire L.
author_facet Zukor, Dorothy J.
Martinson, Douglas G.
Rind, David
Healy, Richard J.
Parkinson, Claire L.
author_sort Zukor, Dorothy J.
title The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM
title_short The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM
title_full The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM
title_fullStr The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM
title_full_unstemmed The Impact of Sea Ice Concentration Accuracies on Climate Model Simulations with the GISS GCM
title_sort impact of sea ice concentration accuracies on climate model simulations with the giss gcm
publishDate 2000
url http://hdl.handle.net/2060/20010018558
op_coverage Unclassified, Unlimited, Publicly available
genre Sea ice
genre_facet Sea ice
op_source CASI
op_relation Document ID: 20010018558
http://hdl.handle.net/2060/20010018558
op_rights No Copyright
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