IPCC Climate Change Data: GFDL99 B2a Model: 2050 Precipitation

The experiments with the GFDL model used here were performed using the coupled ocean-atmosphere model described in Manabe et al. (1991) and Stouffer et al., (1994) and references therein. The model has interactive clouds and seasonally varying solar insolation. The atmospheric component has nine fin...

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Other Authors: SEEK
Format: Dataset
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Published: 2011
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Online Access:http://hdl.handle.net/10255/dryad.20157
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collection Dryad Digital Repository (Duke University)
op_collection_id ftdryad
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topic climate
global climate change
precipitation
spellingShingle climate
global climate change
precipitation
IPCC Climate Change Data: GFDL99 B2a Model: 2050 Precipitation
topic_facet climate
global climate change
precipitation
description The experiments with the GFDL model used here were performed using the coupled ocean-atmosphere model described in Manabe et al. (1991) and Stouffer et al., (1994) and references therein. The model has interactive clouds and seasonally varying solar insolation. The atmospheric component has nine finite difference (sigma) levels in the vertical. This version of the model was run at a rhomboidal resolution of 15 waves (R15) yielding an equivalent resolution of about 4.5 degrees latitude by 7.5 degrees longitude. The model has global geography consistent with its computational resolution and seasonal (but not diurnal) variation of insolation. The ocean model is based on that of Byan and Lewis (1979) with a spacing between gridpoints of 4.5 degrees latitude and 3.7 degrees longitude. It has 12 unevenly spaced levels in the vertical dimension. To reduce model drift, the fluxes of heat and water are adjusted by amounts which vary seasonally and geographically, but do not change from one year to another. The model also includes a dynamic sea-ice model (Bryan, 1969) which allows the system additional degrees of freedom. The 1000-year unforced simulation used here is described in Manabe and Stouffer (1996). The drift in global-mean temperature during this unforced simulation is very small at about -0.023 degrees C per century. The two GFDL-R15 climate change experiments used here use the IS92a scenario of estimated past and future greenhouse gas (GGa1) and combined greenhouse gas and sulphate aerosol (GSa1) forcing for the period 1765-2065 (Haywood et al., 1997). For the GGa1 experiment only the 100-year segment from 1958-2057 are available through the IPCC DDC. The radiative effects of all greenhouse gases is represented in terms of an equivalent CO2 concentration, and the direct radiative sulphate aerosol forcing is parameterised in terms of specified spatially dependent surface albedo changes (following Mitchell et al., 1995). Results from these climate change experiments are discussed in Haywood et al. (1997). The model's climate sensitivity is about 3.7 degrees C.Like B1, the B2 world is one of increased concern for environmental and social sustainability, but the character of this world differs substantially. Education and welfare programs are widely pursued leading to reductions in mortality and, to a lesser extent, fertility. The population reaches about 10 billion people by 2100, consistent with both the United Nations and IIASA median projections. Income per capita grows at an intermediary rate to reach about US$12,000 by 2050. By 2100 the global economy might expand to reach some US$250 trillion. International income differences decrease, although not as rapidly as in scenarios of higher global convergence (A1, B1). Local inequity is reduced considerably through the development of stronger community support networks. Generally high educational levels promote both development and environmental protection. Indeed, environmental protection is one of the few remaining truly international priorities. However, strategies to address global environmental challenges are less successful than in B1, as governments have difficulty designing and implementing agreements that combine environmental protection with mutual economic benefits. The B2 storyline presents a particularly favorable climate for community initiative and social innovation, especially in view of high educational levels. Technological frontiers are pushed less than in A1 and B1 and innovations are also regionally more heterogeneous. Globally, investment in R and D continues its current declining trend, and mechanisms for international diffusion of technology and know-how remain weaker than in scenarios A1 and B1 (but higher than in scenario A2). Some regions with rapid economic development and limited natural resources place particular emphasis on technology development and bilateral co-operation. Technical change is therefore uneven. The energy intensity of GDP declines at about one percent per year, in line with the average historical experience of the last two centuries. Land-use management becomes better integrated at the local level in the B2 world. Urban and transport infrastructure is a particular focus of community innovation, contributing to a low level of car dependence and less urban sprawl. An emphasis on food self-reliance contributes to a shift in dietary patterns towards local products, with reduced meat consumption in countries with high population densities. Energy systems differ from region to region, depending on the availability of natural resources. The need to use energy and other resources more efficiently spurs the development of less carbon-intensive technology in some regions. Environment policy cooperation at the regional level leads to success in the management of some transboundary environmental problems, such as acidification due to SO2, especially to sustain regional self-reliance in agricultural production. Regional cooperation also results in lower emissions of NOx and VOCs, reducing the incidence of elevated tropospheric ozone levels. Although globally the energy system remains predominantly hydrocarbon-based to 2100, there is a gradual transition away from the current share of fossil resources in world energy supply, with a corresponding reduction in carbon intensity.
author2 SEEK
format Dataset
title IPCC Climate Change Data: GFDL99 B2a Model: 2050 Precipitation
title_short IPCC Climate Change Data: GFDL99 B2a Model: 2050 Precipitation
title_full IPCC Climate Change Data: GFDL99 B2a Model: 2050 Precipitation
title_fullStr IPCC Climate Change Data: GFDL99 B2a Model: 2050 Precipitation
title_full_unstemmed IPCC Climate Change Data: GFDL99 B2a Model: 2050 Precipitation
title_sort ipcc climate change data: gfdl99 b2a model: 2050 precipitation
publishDate 2011
url http://hdl.handle.net/10255/dryad.20157
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op_coverage Worldwide
-180.0 W 180.0 E 90.0 N -90.0 S
2050-01-01 to 2050-12-31
genre Sea ice
genre_facet Sea ice
op_relation http://metacat.lternet.edu/knb/metacat/dpennington.178.2/xml
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op_rights 1. The IPCC Data Distribution Centre permits the research results from seven climate modelling centres (Hadley Centre for Climate Prediction and Research, Deutsches Klimarechenzentrum, Canadian Centre for Climate Modelling and Analysis, Geophysical Fluids Dynamics Laboratory, the Commonwealth and Scientific Industrial Research Organisation, the National centre for Atmospheric Research and the Centre for Climate System Research) to be used freely for the purposes of bona fide research. (Bona fide research is deemed to be research which generates results that are freely and universally accessible to any interested party, i.e., if people use DDC data they must agree to publish results openly or respond willingly to requests from others for copies of the results.) 2. The climate modelling centres' research results should not be used for commercial exploitation, business use, resale or transfer to any third party. 3. No warranty is given as to the suitability of the climate modelling centres' research results for particular purposes. 4. No liability is accepted by the IPCC Data Distribution Centre and/or the climate modelling centres for any errors or omissions in the climate modelling centres' research results, associated information and/or documentation. 5. Please acknowledge the use of the corresponding climate modelling centres' research results in any publication. 6. The intellectual property rights on the climate modelling centres' research results remains the property of each of the climate modelling centres. 7. By registering with the DDC you agree to abide by this Data Statement.
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spelling ftdryad:oai:v1.datadryad.org:10255/dryad.20157 2023-05-15T18:19:04+02:00 IPCC Climate Change Data: GFDL99 B2a Model: 2050 Precipitation SEEK Worldwide -180.0 W 180.0 E 90.0 N -90.0 S 2050-01-01 to 2050-12-31 2011-04-26T19:12:07Z text/plain http://hdl.handle.net/10255/dryad.20157 http://metacat.lternet.edu/knb/metacat/dpennington.178.2/xml unknown http://metacat.lternet.edu/knb/metacat/dpennington.178.2/xml dpennington.178.2 http://hdl.handle.net/10255/dryad.20157 1. The IPCC Data Distribution Centre permits the research results from seven climate modelling centres (Hadley Centre for Climate Prediction and Research, Deutsches Klimarechenzentrum, Canadian Centre for Climate Modelling and Analysis, Geophysical Fluids Dynamics Laboratory, the Commonwealth and Scientific Industrial Research Organisation, the National centre for Atmospheric Research and the Centre for Climate System Research) to be used freely for the purposes of bona fide research. (Bona fide research is deemed to be research which generates results that are freely and universally accessible to any interested party, i.e., if people use DDC data they must agree to publish results openly or respond willingly to requests from others for copies of the results.) 2. The climate modelling centres' research results should not be used for commercial exploitation, business use, resale or transfer to any third party. 3. No warranty is given as to the suitability of the climate modelling centres' research results for particular purposes. 4. No liability is accepted by the IPCC Data Distribution Centre and/or the climate modelling centres for any errors or omissions in the climate modelling centres' research results, associated information and/or documentation. 5. Please acknowledge the use of the corresponding climate modelling centres' research results in any publication. 6. The intellectual property rights on the climate modelling centres' research results remains the property of each of the climate modelling centres. 7. By registering with the DDC you agree to abide by this Data Statement. climate global climate change precipitation dataset 2011 ftdryad 2020-01-01T14:42:02Z The experiments with the GFDL model used here were performed using the coupled ocean-atmosphere model described in Manabe et al. (1991) and Stouffer et al., (1994) and references therein. The model has interactive clouds and seasonally varying solar insolation. The atmospheric component has nine finite difference (sigma) levels in the vertical. This version of the model was run at a rhomboidal resolution of 15 waves (R15) yielding an equivalent resolution of about 4.5 degrees latitude by 7.5 degrees longitude. The model has global geography consistent with its computational resolution and seasonal (but not diurnal) variation of insolation. The ocean model is based on that of Byan and Lewis (1979) with a spacing between gridpoints of 4.5 degrees latitude and 3.7 degrees longitude. It has 12 unevenly spaced levels in the vertical dimension. To reduce model drift, the fluxes of heat and water are adjusted by amounts which vary seasonally and geographically, but do not change from one year to another. The model also includes a dynamic sea-ice model (Bryan, 1969) which allows the system additional degrees of freedom. The 1000-year unforced simulation used here is described in Manabe and Stouffer (1996). The drift in global-mean temperature during this unforced simulation is very small at about -0.023 degrees C per century. The two GFDL-R15 climate change experiments used here use the IS92a scenario of estimated past and future greenhouse gas (GGa1) and combined greenhouse gas and sulphate aerosol (GSa1) forcing for the period 1765-2065 (Haywood et al., 1997). For the GGa1 experiment only the 100-year segment from 1958-2057 are available through the IPCC DDC. The radiative effects of all greenhouse gases is represented in terms of an equivalent CO2 concentration, and the direct radiative sulphate aerosol forcing is parameterised in terms of specified spatially dependent surface albedo changes (following Mitchell et al., 1995). Results from these climate change experiments are discussed in Haywood et al. (1997). The model's climate sensitivity is about 3.7 degrees C.Like B1, the B2 world is one of increased concern for environmental and social sustainability, but the character of this world differs substantially. Education and welfare programs are widely pursued leading to reductions in mortality and, to a lesser extent, fertility. The population reaches about 10 billion people by 2100, consistent with both the United Nations and IIASA median projections. Income per capita grows at an intermediary rate to reach about US$12,000 by 2050. By 2100 the global economy might expand to reach some US$250 trillion. International income differences decrease, although not as rapidly as in scenarios of higher global convergence (A1, B1). Local inequity is reduced considerably through the development of stronger community support networks. Generally high educational levels promote both development and environmental protection. Indeed, environmental protection is one of the few remaining truly international priorities. However, strategies to address global environmental challenges are less successful than in B1, as governments have difficulty designing and implementing agreements that combine environmental protection with mutual economic benefits. The B2 storyline presents a particularly favorable climate for community initiative and social innovation, especially in view of high educational levels. Technological frontiers are pushed less than in A1 and B1 and innovations are also regionally more heterogeneous. Globally, investment in R and D continues its current declining trend, and mechanisms for international diffusion of technology and know-how remain weaker than in scenarios A1 and B1 (but higher than in scenario A2). Some regions with rapid economic development and limited natural resources place particular emphasis on technology development and bilateral co-operation. Technical change is therefore uneven. The energy intensity of GDP declines at about one percent per year, in line with the average historical experience of the last two centuries. Land-use management becomes better integrated at the local level in the B2 world. Urban and transport infrastructure is a particular focus of community innovation, contributing to a low level of car dependence and less urban sprawl. An emphasis on food self-reliance contributes to a shift in dietary patterns towards local products, with reduced meat consumption in countries with high population densities. Energy systems differ from region to region, depending on the availability of natural resources. The need to use energy and other resources more efficiently spurs the development of less carbon-intensive technology in some regions. Environment policy cooperation at the regional level leads to success in the management of some transboundary environmental problems, such as acidification due to SO2, especially to sustain regional self-reliance in agricultural production. Regional cooperation also results in lower emissions of NOx and VOCs, reducing the incidence of elevated tropospheric ozone levels. Although globally the energy system remains predominantly hydrocarbon-based to 2100, there is a gradual transition away from the current share of fossil resources in world energy supply, with a corresponding reduction in carbon intensity. Dataset Sea ice Dryad Digital Repository (Duke University)