IPCC Climate Change Data: NIES99 A1f Model: 2020 Wind Speed
The model used here is a coupled ocean-atmosphere model that consists of the CCSR/NIES atmospheric GCM, the CCSR ocean GCM, a thermodynamic sea-ice model, and a river routing model (Abe-Ouchi et al., 1996). The spatial resolution is T21 spectral truncation (roughly 5.6 degrees latitude/longitude) an...
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Knowledge Network for Biocomplexity
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Online Access: | https://doi.org/10.5063/AA/dpennington.300.2 |
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Open Polar |
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Knowledge Network for Biocomplexity (via DataONE) |
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dataone:urn:node:KNB |
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climate global climate change wind |
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climate global climate change wind Intergovernmental Panel on Climate Change (IPCC) IPCC Climate Change Data: NIES99 A1f Model: 2020 Wind Speed |
topic_facet |
climate global climate change wind |
description |
The model used here is a coupled ocean-atmosphere model that consists of the CCSR/NIES atmospheric GCM, the CCSR ocean GCM, a thermodynamic sea-ice model, and a river routing model (Abe-Ouchi et al., 1996). The spatial resolution is T21 spectral truncation (roughly 5.6 degrees latitude/longitude) and 20 vertical levels for the atmospheric part, and roughly 2.8 degrees horizontal grid and 17 vertical levels for the oceanic part. Flux adjustment for atmosphere-ocean heat and water exchange is applied to prevent a drift of the modelled climate. The atmospheric model adopts a radiation scheme based on the k-distribution, two-stream discrete ordinate method (DOM) (Nakajima and Tanaka, 1986). This scheme can deal with absorption, emission and scattering by gases, clouds and aerosol particles in a consistent manner. In the calculation of sulphate aerosol optical properties, the volumetric mode radius of the sulphate particle in dry environment is assumed to be 0.2 micron. The hygroscopic growth of the sulphate is considered by an empirical fit of d'Almeida et al. (1991). The vertical distribution of the sulphate aerosol is assumed to be constant in the lowest 2 km of the atmosphere. The concentrations of greenhouse gases are represented by equivalent-CO2. Three integrations are made for 200 model years (1890-2090). In the control experiment (CTL), the globally uniform concentration of greenhouse gases is kept constant at 345 ppmv CO2-equivalent and the concentration of sulphate is set to zero. In the experiment GG, the concentration of greenhouse gases is gradually increased, while that of sulphate is set to zero. In the experiments GS, the increase in anthropogenic sulphate as well as that in greenhouse gases is given and the aerosol scattering (the direct effect of aerosol) is explicitly represented in the way described above. The indirect effect of aerosol is not included in any experiment. The scenario of atmospheric concentrations of greenhouse gases and sulphate aerosols is given in accordance with Mitchell and Johns (1997). The increase in greenhouse gases is based on the historical record from 1890 to 1990 and is increased by 1 percent / yr (compound) after 1990. For sulphate aerosols, geographical distributions of sulphate loading for 1986 and 2050, which are estimated by a sulphur cycle model (Langer and Rodhe, 1991), are used as basic patterns. Based on global and annual mean sulphur emission rates, the 1986 pattern is scaled for years before 1990; the 2050 pattern is scaled for years after 2050; and the pattern is interpolated from the two basic ones for intermediate years to give the time series of the distribution. The sulphur emission rate in the future is based on the IPCC IS92a scenario. The sulphate concentration is offset in our run so that it starts from zero at 1890. The seasonal variation of sulphate concentration is ignored. Discussion on the results of the experiments will be found in Emori et al. (1999). Climate sensitivity of the CCSR/NIES model derived by equilibrium runs is estimated to be 3.5 degrees Celsius. Global-Mean Temperature, Precipitation and CO2 Changes (w.r.t. 1961-90) for the CCSR/NIES model. From the IPCC website: The A1 Family storyline is a case of rapid and successful economic development, in which regional averages of income per capita converge - current distinctions between poor and rich countries eventually dissolve. In this scenario family, demographic and economic trends are closely linked, as affluence is correlated with long life and small families (low mortality and low fertility). Global population grows to some nine billion by 2050 and declines to about seven billion by 2100. Average age increases, with the needs of retired people met mainly through their accumulated savings in private pension systems. The global economy expands at an average annual rate of about three percent to 2100. This is approximately the same as average global growth since 1850, although the conditions that lead to a global economic in productivity and per capita incomes are unparalleled in history. Income per capita reaches about US$21,000 by 2050. While the high average level of income per capita contributes to a great improvement in the overall health and social conditions of the majority of people, this world is not without its problems. In particular, many communities could face some of the problems of social exclusion encountered by the wealthiest countries in the 20th century and in many places income growth could come with increased pressure on the global commons. Energy and mineral resources are abundant in this scenario family because of rapid technical progress, which both reduce the resources need to produce a given level of output and increases the economically recoverable reserves. Final energy intensity (energy use per unit of GDP) decreases at an average annual rate of 1.3 percent. With the rapid increase in income, dietary patterns shift initially significantly towards increased consumption of meat and dairy products, but may decrease subsequently with increasing emphasis on health of an aging society. High incomes also translate into high car ownership, sprawling suburbanization and dense transport networks, nationally and internationally. Land prices increase faster than income per capita. These factors along with high wages result in a considerable intensification of agriculture. Three scenario groups are considered in A1 scenario family reflecting the uncertainty in development of energy sources and conversion technologies in this rapidly changing world. Near-term investment decisions may introduce long-term irreversibilities into the market, with lock-in to one technological configuration or another. The A1B scenario group is based on a balanced mix of energy sources and has an intermediate level of CO2 emissions, but depending on the energy sources developed, emissions in the variants cover a very wide range. In the fossil-fuel intensive scenario group A1FI, emissions approach those of the A2 scenarios; conversely in scenario group A1T with low labor productivity or of rapid progress in "post-fossil" energy technologies, emissions are intermediate between those of B1 and B2. These scenario variants have been introduced into the A1 storyline because of its "high growth with high tech" nature, where differences in alternative technology developments translate into large differences in future GHG emission levels Ecological resilience is assumed to be high in this storyline. Environmental amenities are viewed in a utilitarian way, based on their influence on the formal economy. The concept of environmental quality might change in thisstoryline from"conservation" of nature to active "management" - and marketing - of natural and environmental services. Data are available for the following periods: 1961-1990, 2010-2039; 2040-2069; and 2090-2099 Mean monthly and change fields. |
format |
Dataset |
author |
Intergovernmental Panel on Climate Change (IPCC) |
author_facet |
Intergovernmental Panel on Climate Change (IPCC) |
author_sort |
Intergovernmental Panel on Climate Change (IPCC) |
title |
IPCC Climate Change Data: NIES99 A1f Model: 2020 Wind Speed |
title_short |
IPCC Climate Change Data: NIES99 A1f Model: 2020 Wind Speed |
title_full |
IPCC Climate Change Data: NIES99 A1f Model: 2020 Wind Speed |
title_fullStr |
IPCC Climate Change Data: NIES99 A1f Model: 2020 Wind Speed |
title_full_unstemmed |
IPCC Climate Change Data: NIES99 A1f Model: 2020 Wind Speed |
title_sort |
ipcc climate change data: nies99 a1f model: 2020 wind speed |
publisher |
Knowledge Network for Biocomplexity |
publishDate |
|
url |
https://doi.org/10.5063/AA/dpennington.300.2 |
op_coverage |
Worldwide ENVELOPE(-180.0,180.0,90.0,-90.0) BEGINDATE: 2020-01-01T00:00:00Z ENDDATE: 2020-12-31T00:00:00Z |
genre |
Sea ice |
genre_facet |
Sea ice |
op_doi |
https://doi.org/10.5063/AA/dpennington.300.2 |
_version_ |
1782011143784497152 |
spelling |
dataone:doi:10.5063/AA/dpennington.300.2 2023-11-08T14:14:57+01:00 IPCC Climate Change Data: NIES99 A1f Model: 2020 Wind Speed Intergovernmental Panel on Climate Change (IPCC) Worldwide ENVELOPE(-180.0,180.0,90.0,-90.0) BEGINDATE: 2020-01-01T00:00:00Z ENDDATE: 2020-12-31T00:00:00Z 2005-06-21T23:00:00Z https://doi.org/10.5063/AA/dpennington.300.2 unknown Knowledge Network for Biocomplexity climate global climate change wind Dataset dataone:urn:node:KNB https://doi.org/10.5063/AA/dpennington.300.2 2023-11-08T13:31:29Z The model used here is a coupled ocean-atmosphere model that consists of the CCSR/NIES atmospheric GCM, the CCSR ocean GCM, a thermodynamic sea-ice model, and a river routing model (Abe-Ouchi et al., 1996). The spatial resolution is T21 spectral truncation (roughly 5.6 degrees latitude/longitude) and 20 vertical levels for the atmospheric part, and roughly 2.8 degrees horizontal grid and 17 vertical levels for the oceanic part. Flux adjustment for atmosphere-ocean heat and water exchange is applied to prevent a drift of the modelled climate. The atmospheric model adopts a radiation scheme based on the k-distribution, two-stream discrete ordinate method (DOM) (Nakajima and Tanaka, 1986). This scheme can deal with absorption, emission and scattering by gases, clouds and aerosol particles in a consistent manner. In the calculation of sulphate aerosol optical properties, the volumetric mode radius of the sulphate particle in dry environment is assumed to be 0.2 micron. The hygroscopic growth of the sulphate is considered by an empirical fit of d'Almeida et al. (1991). The vertical distribution of the sulphate aerosol is assumed to be constant in the lowest 2 km of the atmosphere. The concentrations of greenhouse gases are represented by equivalent-CO2. Three integrations are made for 200 model years (1890-2090). In the control experiment (CTL), the globally uniform concentration of greenhouse gases is kept constant at 345 ppmv CO2-equivalent and the concentration of sulphate is set to zero. In the experiment GG, the concentration of greenhouse gases is gradually increased, while that of sulphate is set to zero. In the experiments GS, the increase in anthropogenic sulphate as well as that in greenhouse gases is given and the aerosol scattering (the direct effect of aerosol) is explicitly represented in the way described above. The indirect effect of aerosol is not included in any experiment. The scenario of atmospheric concentrations of greenhouse gases and sulphate aerosols is given in accordance with Mitchell and Johns (1997). The increase in greenhouse gases is based on the historical record from 1890 to 1990 and is increased by 1 percent / yr (compound) after 1990. For sulphate aerosols, geographical distributions of sulphate loading for 1986 and 2050, which are estimated by a sulphur cycle model (Langer and Rodhe, 1991), are used as basic patterns. Based on global and annual mean sulphur emission rates, the 1986 pattern is scaled for years before 1990; the 2050 pattern is scaled for years after 2050; and the pattern is interpolated from the two basic ones for intermediate years to give the time series of the distribution. The sulphur emission rate in the future is based on the IPCC IS92a scenario. The sulphate concentration is offset in our run so that it starts from zero at 1890. The seasonal variation of sulphate concentration is ignored. Discussion on the results of the experiments will be found in Emori et al. (1999). Climate sensitivity of the CCSR/NIES model derived by equilibrium runs is estimated to be 3.5 degrees Celsius. Global-Mean Temperature, Precipitation and CO2 Changes (w.r.t. 1961-90) for the CCSR/NIES model. From the IPCC website: The A1 Family storyline is a case of rapid and successful economic development, in which regional averages of income per capita converge - current distinctions between poor and rich countries eventually dissolve. In this scenario family, demographic and economic trends are closely linked, as affluence is correlated with long life and small families (low mortality and low fertility). Global population grows to some nine billion by 2050 and declines to about seven billion by 2100. Average age increases, with the needs of retired people met mainly through their accumulated savings in private pension systems. The global economy expands at an average annual rate of about three percent to 2100. This is approximately the same as average global growth since 1850, although the conditions that lead to a global economic in productivity and per capita incomes are unparalleled in history. Income per capita reaches about US$21,000 by 2050. While the high average level of income per capita contributes to a great improvement in the overall health and social conditions of the majority of people, this world is not without its problems. In particular, many communities could face some of the problems of social exclusion encountered by the wealthiest countries in the 20th century and in many places income growth could come with increased pressure on the global commons. Energy and mineral resources are abundant in this scenario family because of rapid technical progress, which both reduce the resources need to produce a given level of output and increases the economically recoverable reserves. Final energy intensity (energy use per unit of GDP) decreases at an average annual rate of 1.3 percent. With the rapid increase in income, dietary patterns shift initially significantly towards increased consumption of meat and dairy products, but may decrease subsequently with increasing emphasis on health of an aging society. High incomes also translate into high car ownership, sprawling suburbanization and dense transport networks, nationally and internationally. Land prices increase faster than income per capita. These factors along with high wages result in a considerable intensification of agriculture. Three scenario groups are considered in A1 scenario family reflecting the uncertainty in development of energy sources and conversion technologies in this rapidly changing world. Near-term investment decisions may introduce long-term irreversibilities into the market, with lock-in to one technological configuration or another. The A1B scenario group is based on a balanced mix of energy sources and has an intermediate level of CO2 emissions, but depending on the energy sources developed, emissions in the variants cover a very wide range. In the fossil-fuel intensive scenario group A1FI, emissions approach those of the A2 scenarios; conversely in scenario group A1T with low labor productivity or of rapid progress in "post-fossil" energy technologies, emissions are intermediate between those of B1 and B2. These scenario variants have been introduced into the A1 storyline because of its "high growth with high tech" nature, where differences in alternative technology developments translate into large differences in future GHG emission levels Ecological resilience is assumed to be high in this storyline. Environmental amenities are viewed in a utilitarian way, based on their influence on the formal economy. The concept of environmental quality might change in thisstoryline from"conservation" of nature to active "management" - and marketing - of natural and environmental services. Data are available for the following periods: 1961-1990, 2010-2039; 2040-2069; and 2090-2099 Mean monthly and change fields. Dataset Sea ice Knowledge Network for Biocomplexity (via DataONE) |