Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment
Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of parti...
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ftnasantrs:oai:casi.ntrs.nasa.gov:19970003259 2023-05-15T18:18:24+02:00 Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment Skiles, J. W. Unclassified, Unlimited, Publicly available 1995 application/pdf http://hdl.handle.net/2060/19970003259 unknown Document ID: 19970003259 Accession ID: 97N12014 http://hdl.handle.net/2060/19970003259 No Copyright CASI Environment Pollution NASA-TM-111728 NAS 1.15:111728 Climatic Change; 30; 1-6 1995 ftnasantrs 2019-07-21T03:16:43Z Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation. Other/Unknown Material Sea ice NASA Technical Reports Server (NTRS) |
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NASA Technical Reports Server (NTRS) |
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ftnasantrs |
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unknown |
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Environment Pollution |
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Environment Pollution Skiles, J. W. Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment |
topic_facet |
Environment Pollution |
description |
Practitioners of climate change prediction base many of their future climate scenarios on General Circulation Models (GCM's), each model with differing assumptions and parameter requirements. For representing the atmosphere, GCM's typically contain equations for calculating motion of particles, thermodynamics and radiation, and continuity of water vapor. Hydrology and heat balance are usually included for continents, and sea ice and heat balance are included for oceans. The current issue of this journal contains a paper by Van Blarcum et al. (1995) that predicts runoff from nine high-latitude rivers under a doubled CO2 atmosphere. The paper is important since river flow is an indicator variable for climate change. The authors show that precipitation will increase under the imposed perturbations and that owing to higher temperatures earlier in the year that cause the snow pack to melt sooner, runoff will also increase. They base their simulations on output from a GCM coupled with an interesting water routing scheme they have devised. Climate change models have been linked to other models to predict deforestation. |
format |
Other/Unknown Material |
author |
Skiles, J. W. |
author_facet |
Skiles, J. W. |
author_sort |
Skiles, J. W. |
title |
Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment |
title_short |
Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment |
title_full |
Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment |
title_fullStr |
Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment |
title_full_unstemmed |
Modeling Climate Change in the Absence of Climate Change Data. Editorial Comment |
title_sort |
modeling climate change in the absence of climate change data. editorial comment |
publishDate |
1995 |
url |
http://hdl.handle.net/2060/19970003259 |
op_coverage |
Unclassified, Unlimited, Publicly available |
genre |
Sea ice |
genre_facet |
Sea ice |
op_source |
CASI |
op_relation |
Document ID: 19970003259 Accession ID: 97N12014 http://hdl.handle.net/2060/19970003259 |
op_rights |
No Copyright |
_version_ |
1766194975677087744 |