Climate change output CSIRO Atmospheric Research Technical Paper No. 37, 1998 Kevin J. Hennessy Contents Abstract Background Global climate models Regional climate models CSIRO climate models Overview CSIRO Mark 2 global climate model with slab ocean(CSIRO slab) CSIRO regional climate model (DARLAM CSIRO global coupled ocean-atmosphere-sea-ice model (CSIRO coupled Experiments conducted Experiment 1: CSIRO Mark 2 slab GCM 1xCO2 and 2x CO2 simulations Experiment 2: DARLAM 1xCO2 and 2x COz simulations Experiment 3: CSIRO coupled GCM transient CO2 simulation Output available Value-added products Tailored output OzClim PC software Licence agreement Obtaining output Appendix 1: CSIRO Mark 2 global climate model output Appendix 2: CSIRO regional climate model(DARLAM)output Appendix 3: CSIRO coupled ocean-atmosphere global climate model output References Acknowledgments
Climate change output CSIRO Atmospheric Research Technical Paper No. 37, 1998 Kevin J. Hennessy Contents Abstract Background Global climate models Regional climate models CSIRO climate models Overview CSIRO Mark 2 global climate model with slab ocean (CSIRO slab) CSIRO regional climate model (DARLAM) CSIRO global coupled ocean-atmosphere-sea-ice model (CSIRO coupled) Experiments conducted Experiment 1: CSIRO Mark 2 slab GCM 1×CO2 and 2×CO2 simulations Experiment 2: DARLAM 1×CO2 and 2×CO2 simulations Experiment 3: CSIRO coupled GCM transient CO2 simulation Output available Value-added products Tailored output OzClim PC software Licence agreement Obtaining output Appendix 1: CSIRO Mark 2 global climate model output Appendix 2: CSIRO regional climate model (DARLAM) output Appendix 3: CSIRO coupled ocean-atmosphere global climate model output References Acknowledgments
Abstract e CSIRO Climate Change Research Program is Australia s largest and most comprehensive program investigating the greenhouse effect and global climate change. This document lists the output from CSiRo climate models that have been used to conduct enhanced greenhouse experiments. Two global climate models(GCMs)and a regional climate model( RCm)are described Three CSIRO enhanced greenhouse experiments were undertaken. Provision of output from these experiments is intended to give other scientists an intemally consistent set of detailed climatic variables for use in sensitivity studies. The first experiment was performed in 1994 with the CsIRO Mark 2 slab GCM here enhanced greenhouse conditions were represented by an instantaneous doubling of Co2 Output from this experiment was fed into the second experiment in 1995 which involed running a high resolution RCM over Australasia to produce more detailed information. The third experiment was performed in 1996 with the CSIRo coupled GCM which was driven by a gradually increasing CO2 concentration scenario for 185 years A wide range of climatic variables was saved from each experiment at various time intervals and at various vertical levels. Broad groupings of the varables include temperature, precipitation, wind pressure, cloud evaporation, radiation, humidity, soil moisture, runoff, snow, sea-ice, mxing ratio, and heat flux. Many options exist for adding value to output saved from these experiments, through manipulating data to suit specific needs. The PC-based software package called OzClim enables regional scenarios of climate change to be generated for the whole or selected parts of Australia at various spatial resolutions, for any date between 1990 and 2100, where the user canselectfom a range of greenhouse gas emission scenarios, global climate sensitivity assumptions, and GCM or RCM patterns of climate change a detailed list of output fom each experiment is supplied and steps required for obtaining output from CSIRO are explained Background The climate model data presented in this report are a product of the csIRo Climate Change Research Program(CCRP). The CCRP is Australia's largest and most comprehensive program investigating the greenhouse effect and global climate change. It involves at least nine CsiRo Divisions and integrates work from researchers in other research institutes, particularly the Bureau of Meteorology, the Antarctic Research Centre, and the Cooperative Research Centre for Southern Hemisphere Meteorology A major component of the ccrP is a project entitled " Climate Change" which draws on work from other CCRP projects to form a basis for modelling climate change. This document lists the output from CSIRO climate models that have been used to conduct enhanced greenhouse experiments. Two global climate models(GCMs)and a regional climate model ( RCM)were used
Abstract The CSIRO Climate Change Research Program is Australia’s largest and most comprehensive program investigating the greenhouse effect and global climate change. This document lists the output from CSIRO climate models that have been used to conduct enhanced greenhouse experiments. Two global climate models (GCMs) and a regional climate model (RCM) are described. Three CSIRO enhanced greenhouse experiments were undertaken. Provision of output from these experiments is intended to give other scientists an internally consistent set of detailed climatic variables for use in sensitivity studies. The first experiment was performed in 1994 with the CSIRO Mark 2 slab GCM, where enhanced greenhouse conditions were represented by an instantaneous doubling of CO2. Output from this experiment was fed into the second experiment in 1995 which involved running a high resolution RCM over Australasia to produce more detailed information. The third experiment was performed in 1996 with the CSIRO coupled GCM which was driven by a gradually increasing CO2 concentration scenario for 185 years. A wide range of climatic variables was saved from each experiment at various time intervals and at various vertical levels. Broad groupings of the variables include temperature, precipitation, wind, pressure, cloud, evaporation, radiation, humidity, soil moisture, runoff, snow, sea-ice, mixing ratio, and heat flux. Many options exist for adding value to output saved from these experiments, through manipulating data to suit specific needs. The PC-based software package called OzClim enables regional scenarios of climate change to be generated for the whole or selected parts of Australia at various spatial resolutions, for any date between 1990 and 2100, where the user can select from a range of greenhouse gas emission scenarios, global climate sensitivity assumptions, and GCM or RCM patterns of climate change. A detailed list of output from each experiment is supplied and steps required for obtaining output from CSIRO are explained. Background The climate model data presented in this report are a product of the CSIRO Climate Change Research Program (CCRP). The CCRP is Australia’s largest and most comprehensive program investigating the greenhouse effect and global climate change. It involves at least nine CSIRO Divisions and integrates work from researchers in other research institutes, particularly the Bureau of Meteorology, the Antarctic Research Centre, and the Cooperative Research Centre for Southern Hemisphere Meteorology. A major component of the CCRP is a project entitled “Climate Change” which draws on work from other CCRP projects to form a basis for modelling climate change. This document lists the output from CSIRO climate models that have been used to conduct enhanced greenhouse experiments. Two global climate models (GCMs) and a regional climate model (RCM) were used
Global climate models A global climate model is a computer model representing the atmosphere, oceans, land and icecaps. By solving mathematical equations based upon the laws of physics, a GCM simulates the behaviour of the climate system. The model divides the planet into a number of vertical layers representing levels in the atmosphere and depths in the oceans, and divides the surface of the planet into a grid of horizontal boxes separated by lines similar to latitudes and longitudes. In this way, the planet is covered by a three-dimensional grid of boxes The horizontal size of a typical grid box in the CSIRO GCM is about 625 km by 350 km, limited largely by computer power Inside eachgrid box, the mathematical equations are solved at model-timesteps of about an hour for many model-decades until a picture of the Earth's climate is built up. Global climate models capture large scale features like the deserts and tropics very well, but have difficulty capturing smaller features like cyclones and thunderstorms because they occur at scales much smaller than the grid boxes Carbon dioxide(CO2) is one of the main greenhouse gases affected by human activities. A common experiment for comparing different climate model simulations of enhanced greenhouse conditions is an instantaneous doubling of the atmospheric carbon dioxide concentration(2x CO2). The timing of 2x COz depends critically on the growth rate of greenhouse gas emissions, and the rate of uptake of CO by the biosphere and oceans. The Intergovernmental Panel on Climate Change(IPCC: Houghton et al. 1996)has produced six emission scenarios which vary widely over the next century. For the mid-range scenario(Is92a) a doubling of the 1975 CO2 concentration occurs by the year 2100. When the effects of other greenhouse gases are included, the change in radiation equivalent to a doubling of CO2 alone occurs by the year 2060(Dix and Hunt, 1995) Over the ocean, most 2x CO2 experiments use a simple slab"of water at the lower boundary which represents the mixed-layer in the top 50 metres of ocean. Slab ocean experiments cannot take into account the potential climatic effect of changes in ocean circulation and the transfer of surf ace warming into the deep ocean. This is an important caveat Coupled ocean-atmosphere GCMs employ models of the full ocean (including the deep ocean). They can simulate the uptake of surface warming by the deep ocean and changes in ocean circulation, and the consequent effect this has on regional climate change. Some features of climate variability associated with the El Nino-Southem Oscillation(ENSO)are also captured by coupled models. In addition, coupled models are driven by a realistic IPCC scenario of steadily increasing( transient) concentrations of carbon dioxide when run under enhanced greenhouse conditions, rather than an instantaneous doubling of Co2
Global climate models A global climate model is a computer model representing the atmosphere, oceans, land and icecaps. By solving mathematical equations based upon the laws of physics, a GCM simulates the behaviour of the climate system. The model divides the planet into a number of vertical layers representing levels in the atmosphere and depths in the oceans, and divides the surface of the planet into a grid of horizontal boxes separated by lines similar to latitudes and longitudes. In this way, the planet is covered by a three-dimensional grid of boxes The horizontal size of a typical grid box in the CSIRO GCM is about 625 km by 350 km, limited largely by computer power. Inside each grid box, the mathematical equations are solved at model-timesteps of about an hour for many model-decades until a picture of the Earth’s climate is built up. Global climate models capture large scale features like the deserts and tropics very well, but have difficulty capturing smaller features like cyclones and thunderstorms because they occur at scales much smaller than the grid boxes. Carbon dioxide (CO2) is one of the main greenhouse gases affected by human activities. A common experiment for comparing different climate model simulations of enhanced greenhouse conditions is an instantaneous doubling of the atmospheric carbon dioxide concentration (2×CO2). The timing of 2×CO2 depends critically on the growth rate of greenhouse gas emissions, and the rate of uptake of CO2 by the biosphere and oceans. The Intergovernmental Panel on Climate Change (IPCC: Houghton et al., 1996) has produced six emission scenarios which vary widely over the next century. For the mid -range scenario (IS92a), a doubling of the 1975 CO2 concentration occurs by the year 2100. When the effects of other greenhouse gases are included, the change in radiation equivalent to a doubling of CO2 alone occurs by the year 2060 (Dix and Hunt, 1995). Over the ocean, most 2×CO2 experiments use a simple “slab” of water at the lower boundary which represents the mixed-layer in the top 50 metres of ocean. Slab ocean experiments cannot take into account the potential climatic effect of changes in ocean circulation and the transfer of surface warming into the deep ocean. This is an important caveat. Coupled ocean-atmosphere GCMs employ models of the full ocean (including the deep ocean). They can simulate the uptake of surface warming by the deep ocean and changes in ocean circulation, and the consequent effect this has on regional climate change. Some features of climate variability associated with the El Niño-Southern Oscillation (ENSO) are also captured by coupled models. In addition, coupled models are driven by a realistic IPCC scenario of steadily increasing (transient) concentrations of carbon dioxide when run under enhanced greenhouse conditions, rather than an instantaneous doubling of CO2
Coupled models are conceptually better than models with a slab ocean, but the choice of model for Australian studies is unfortunately not that simple. The discussion below lines why output from both slab and coupled models should be considered equally valid, at the present time In the northern hemisphere the pattems of simulated temperature and rainfall change are similar in slab and coupled models From the perspective of regional scenario development in the northen hemisphere, the move to using coupled models is not a big issue. However, the differences are large in the southen hemisphere. Coupled models simulate a strong uptake of heat into the deep ocean in high southern latitudes. leading to reduced surface warming relative to other latitudes, whereas slab models do not show this reduction in warming In particular, slab models simulate increased rainfall over northern and westem Australia in summer, but coupled models simulate decreased rainfall (CSIRO, 1996; Whetton et al., 1997b) There are two reasons why coupled models may be over-estimating the reduced warming in high southern latitudes. Oceanic observations suggest that the Southern Ocean is not mixed as actively as is typically simulated in coupled models(England, 1995), and observed temperature trends this century do not show a reduced warming in hig her latitudes of the southem hemisphere relative to other parts of the world (Kattenberg et al., 1996). However, slab models may be over-estimating the Southem Ocean warming because they do not include uptake of heat by the deep ocean Therefore, coupled models may be under-estimating the warming in the Southem Ocean and slab models may be over-estimating the warming. Until the problems associated with coupled models in the southen hemisphere are resolved or at least reduced, output derived from both slab and coupled models are worth analysing for the Australian region Regional climate models To improve regional detail in climate models, it is desirable to reduce the spacing between gridpoints However, due to the complexity of global climate modelling, computational requirements become prohibitive if the horizontal grid resolution is less than a few hundred kilometres. At this resolution, vitally important small-scale phenomena, like tropical cyclones and cold fronts, are poorly captured. This affects simulated patterns of temperature and rainf all, and hence the ability to realistically simulate observed regional climate features in GCM: A computationally feasible altemative to a coarse resolution global climate model is to use a finer resolution model over a small part of the globe. a regional climate model (RCM), with a horizontal resolution of about 100 km or less, is able to simulate regional weather patterns better than most GCMs(Mc Gregor et aL, 1993) Part of the reason for the improved climate simulation relative to gCms is the fact that coastlines and mountains are represented in more detail in RCMs. Since topographic features strongly influence regional temperature and rainf all, more detailed features are likely to give a better climate simulation
Coupled models are conceptually better than models with a slab ocean, but the choice of model for Australian studies is unfortunately not that simple. The discussion below outlines why output from both slab and coupled models should be considered equally valid, at the present time. In the northern hemisphere, the patterns of simulated temperature and rainfall change are similar in slab and coupled models. From the perspective of regional scenario development in the northern hemisphere, the move to using coupled models is not a big issue. However, the differences are large in the southern hemisphere. Coupled models simulate a strong uptake of heat into the deep ocean in high southern latitudes, leading to reduced surface warming relative to other latitudes, whereas slab models do not show this reduction in warming. In particular, slab models simulate increased rainfall over northern and western Australia in summer, but coupled models simulate decreased rainfall (CSIRO, 1996; Whetton et al., 1997b). There are two reasons why coupled models may be over-estimating the reduced warming in high southern latitudes. Oceanic observations suggest that the Southern Ocean is not mixed as actively as is typically simulated in coupled models (England, 1995), and observed temperature trends this century do not show a reduced warming in higher latitudes of the southern hemisphere relative to other parts of the world (Kattenberg et al., 1996). However, slab models may be over-estimating the Southern Ocean warming because they do not include uptake of heat by the deep ocean. Therefore, coupled models may be under-estimating the warming in the Southern Ocean and slab models may be over-estimating the warming. Until the problems associated with coupled models in the southern hemisphere are resolved or at least reduced, output derived from both slab and coupled models are worth analysing for the Australian region. Regional climate models To improve regional detail in climate models, it is desirable to reduce the spacing between gridpoints. However, due to the complexity of global climate modelling, computational requirements become prohibitive if the horizontal grid resolution is less than a few hundred kilometres. At this resolution, vitally important small-scale phenomena, like tropical cyclones and cold fronts, are poorly captured. This affects simulated patterns of temperature and rainfall, and hence the ability to realistically simulate observed regional climate features in GCMs. A computationally feasible alternative to a coarse resolution global climate model is to use a finer resolution model over a small part of the globe. A regional climate model (RCM), with a horizontal resolution of about 100 km or less, is able to simulate regional weather patterns better than most GCMs (McGrego r et al., 1993). Part of the reason for the improved climate simulation relative to GCMs is the fact that coastlines and mountains are represented in more detail in RCMs. Since topographic features strongly influence regional temperature and rainfall, more detailed features are likely to give a better climate simulation
A regional climate model requires weather inf ormation at its lateral boundaries in order to simulate weather within its boundaries For climate change studies, an RCM is typically driven at its bound aries by infomation from a coarser-scale GaM. This is commonly called nesting an RCM inside a GCM One-way nesting allows inf ormation to flow from the GCM to the RCM each simulated day, but the weather simulated by the RCM does not affect the GCM interactively. This means that the RCM can be run after the gCm experiment has been completed The application of RCMs to decadal-scale climate modelling is only recent, since RCMs have mainly been used in the past for short-term weather forecasting. Very few RCMs have been used for climate change experiments, and CSIRO is a leader in this field. Although the performance of an RCM is constrained by its reliance on GCM performance at the lateral boundares, RCMs offer detailed insight into regional climate change. The ability to use fine resolution RCM climate change output should be seen as a significant opportunity CsIRo climate models Overview This section describes the three csiro climate models used in enhanced greenhouse experiments. There are two coarse resolution global climate models and a fine resolution regional climate model. Since each model was developed at CSIRo, there are many similarities Each model uses the same basic equations which describe the laws of physics. Schemes for boundary layer mixing, moisture advection, radiation and cloud formation are also common to each model The simulation of average climate for selected variables has been validated against observed average climatic data as part of standard model testing procedures. Simulations described in this report are from models which have passed global and Australian climate validation, so that some confidence may be placed in output from enhanced greenhouse simulations, taking the following caveats into account The models do not (and cannot) take into account all processes (natural and anthropogenic)which affect climate variability and change. Some processes are not well understood and others must be represented in a simplified way in order to ensure computational efficiency. While continental-scale climatic features are well simulated for present conditions, regional features are captured with less accuracy None of the models includes the regional cooling effect of sulfate aerosol which has been identified by the IPCC(Houghton et aL., 1996)as an important element of anthropogenic climate change particularly in the northem hemisphere where aerosol are emitted in large quantities. While aerosol emissions in Australia are relatively small, northern hemisphere aerosol may influence the Australian climate indirectly, through
A regional climate model requires weather information at its lateral boundaries in order to simulate weather within its boundaries. For climate change studies, an RCM is typically driven at its boundaries by information from a coarser-scale GCM. This is commonly called nesting an RCM inside a GCM. One-way nesting allows information to flow from the GCM to the RCM each simulated day, but the weather simulated by the RCM does not affect the GCM interactively. This means that the RCM can be run after the GCM experiment has been completed. The application of RCMs to decadal-scale climate modelling is only recent, since RCMs have mainly been used in the past for short-term weather forecasting. Very few RCMs have been used for climate change experiments, and CSIRO is a leader in this field. Although the performance of an RCM is constrained by its reliance on GCM performance at the lateral boundaries, RCMs offer detailed insight into regional climate change. The ability to use fine resolution RCM climate change output should be seen as a significant opportunity. CSIRO climate models Overview This section describes the three CSIRO climate models used in enhanced greenhouse experiments. There are two coarse resolution global climate models and a fine resolution regional climate model. Since each model was developed at CSIRO, there are many similarities. Each model uses the same basic equations which describe the laws of physics. Schemes for boundary lay er mixing, moisture advection, radiation and cloud formation are also common to each model. The simulation of average climate for selected variables has been validated against observed average climatic data as part of standard model testing procedures. Simulations described in this report are from models which have passed global and Australian climate validation, so that some confidence may be placed in output from enhanced greenhouse simulations, taking the following caveats into account. The models do not (and cannot) take into account all processes (natural and anthropogenic) which affect climate variability and change. Some processes are not well understood and others must be represented in a simplified way in order to ensure computational efficiency. While continental-scale climatic features are well simulated for present conditions, regional features are captured with less accuracy. None of the models includes the regional cooling effect of sulfate aerosol which has been identified by the IPCC (Houghton et al., 1996) as an important element of anthropogenic climate change, particularly in the northern hemisphere where aerosol are emitted in large quantities. While aerosol emissions in Australia are relatively small, northern hemisphere aerosol may influence the Australian climate indirectly, through