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...

Full description

Bibliographic Details
Main Author: Skiles, J. W.
Format: Other/Unknown Material
Language:unknown
Published: 1995
Subjects:
Online Access:http://hdl.handle.net/2060/19970003259
id ftnasantrs:oai:casi.ntrs.nasa.gov:19970003259
record_format openpolar
spelling 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)
institution Open Polar
collection NASA Technical Reports Server (NTRS)
op_collection_id ftnasantrs
language unknown
topic Environment Pollution
spellingShingle 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