WunderBlog Archive » Dr. Ricky Rood's Climate Change Blog
Category 6 has moved! See the latest from Dr. Jeff Masters and Bob Henson here.Preparing for the Next IPCC
Preparing for the Next IPCC: This blog continues the series (linked below) where I have tried to give some visibility into the management and politics within the climate community. This one is about how the community is preparing for the next Intergovernmental Panel on Climate Change (IPCC) Report … The next report for the IPCC Working Group I, who are the physical scientists, is scheduled for release in June of 2013. In climate centers around the world, they are already configuring the models that will be used so that they can undergo extensive evaluation before they are run in IPCC experiments.
For the most part, scientific development and the community of scientists are not strongly managed. One of the big changes in the climate community, as the results of the scientific investigation take on more and more importance in society as a whole, is the need to provide “products” for particular purposes, such as the IPCC assessments. In the beginning these assessments were treated like an “add on” to the research activities that had been funded for, more or less, basic research. Today, in the U.S. there is a sub-culture of the community that is directly interested in and funded to assure the U.S> participation in IPCC. There is a constant tension between the need for basic research and the requirement to produce the products necessary for the scientific assessment of climate change. (More on that, next time. Science is managed differently in other countries.))
As suggested in the previous blogs there are a variety of ways that the community organizes to meet the need for IPCC assessments. For the next assessment, named Assessment Report 5 (AR5), it is anticipated that new types of numerical simulations will be needed. Rather than running an array of scenarios to outline what will happen, there will be more consideration of what can and will be done to stabilize the climate.
One way that the community is organizing is through a program called the Climate Model Intercomparison Project. (CMIP) . This will be CMIP number 5; hence, CMIP5. The CMIP projects follow from the Atmospheric Model Intercomparison Problem which was started in 1990. There is also an even longer history of model intercomparison and assessments in the stratospheric ozone community.
These intercomparison projects are an important part of model evaluation, but they are just part of the testing and evaluation that is done in assessing the strengths and weaknesses of models. They all have basically the same steps. Observations are the foundation of any evaluation. Hence, there is the need to identify a set of observations that will be used in the evaluations. There are hundreds of possibilities, and over the community as a whole, virtually any credible observation set that provides useful information has been used. However, there are a few that rise to stop as standard. A couple of examples are the surface temperature observations as, for example, compiled and validated and maintained by the Hadley Center and the Goddard Institute for Space Studies. Another classic example are the cloud and radiation observations that come from the Clouds and the Earth’s Radiant Energy System (CERES) instruments that fly on several satellites. (Here’s where you can get some data.)
Observations sit at the foundation, but there are several other critical elements in model evaluation. One of those critical elements is to have at least one group of independent researchers mode up of members NOT responsible for the model development. This is a group that can look at models with objectivity. In the U.S. the Program for Climate Model Diagnosis and Intercomparison is such a group. (This group is sponsored by the Department of Energy’s Office Biological and Environmental Research.)
Also critical to the process is the design of numerical experiments. (Yes, some scientists argue that there is no such thing as a “numerical experiment,” but it is possible to set up robust scientific experimentation with numerical models.) For example, in the Atmospheric Model Intercomparison Project, all of the models simulate from 1979 – 2000 using observed monthly mean sea surface temperatures. This time span was chosen because of the presence of global satellite observations. There are several standard runs in the climate model intercomparisons. An example is the “modern industrial era,” approximately the past 150 years.
Another element of the evaluation is the selection of objective measures for the evaluation and intercomparison. One of the standard measures is called the Taylor Diagram, which is an accumulation of statistical information from many data sources and many models. Here is an example of a Taylor Diagram.
Figure 1: Taylor Diagram: (primer) The plot is constructed based on the Law of Cosines. The observed field is represented by a point at unit distance from the origin along the abscissa. All other points, which represent simulated fields, are positioned such that the variance is the radial distance from the origin, the correlation is the cosine of the azimuthal angle, and the normalized root mean square difference is the distance to the observed point. When the distance to the point representing the observed field is relatively short, good agreement is found between the simulated and observed fields. In the limit of perfect agreement (which is, however, generally not achievable because there are fundamental limits to the predictability of climate), the root mean square difference would approach zero, and and correlation would approach unity.
Finally, this is an example of organizing and planning in the climate community. The process works from both the bottom and the top. Some scientists see the need for both coordination and the need to have controlled experiments across many organizations. They self organize, then seek funding from the agencies. Sometimes the agencies see the need for organization, and then offer incentives and opportunities for scientists to organize. I want to point you to an interesting document for next major IPCC assessment. This is a strategy document developed by part of the modeling community. It is an example of scientists trying to take part in the definition of the best experiments to support the assessments. Here’s A Strategy for Climate Change Stabilization Experiments with Atmospheric Ocean General Circulation Models and Earth System Models. And here are the objectives as quoted from this document.
1. Identify new components that are currently under implementation or will be ready in the next six months for inclusion as first generation Earth System Models in Atmosphere-Ocean General Circulation Models (AOGCMs).
2. Establish communication through WCRP, IGBP, IPCC, the climate impacts community, and integrated assessment (IA) modeling teams to coordinate activities in preparation for climate change simulations that will be performed with this next generation of climate system models for a possible IPCC AR5.
3. Propose an experimental design for 21st century climate change experiments with these models (near term and longer term time frames).
4. Specify the requirements for these new models in terms of time series of constituents from new stabilization scenarios (particularly with regard to impacts, mitigation, and adaptation).
Links to relevant blogs.
Importance of Justification
Buying Big Computers
Fragmented Climate
Organizing the Fragments
This series of blogs collected.
For the most part, scientific development and the community of scientists are not strongly managed. One of the big changes in the climate community, as the results of the scientific investigation take on more and more importance in society as a whole, is the need to provide “products” for particular purposes, such as the IPCC assessments. In the beginning these assessments were treated like an “add on” to the research activities that had been funded for, more or less, basic research. Today, in the U.S. there is a sub-culture of the community that is directly interested in and funded to assure the U.S> participation in IPCC. There is a constant tension between the need for basic research and the requirement to produce the products necessary for the scientific assessment of climate change. (More on that, next time. Science is managed differently in other countries.))
As suggested in the previous blogs there are a variety of ways that the community organizes to meet the need for IPCC assessments. For the next assessment, named Assessment Report 5 (AR5), it is anticipated that new types of numerical simulations will be needed. Rather than running an array of scenarios to outline what will happen, there will be more consideration of what can and will be done to stabilize the climate.
One way that the community is organizing is through a program called the Climate Model Intercomparison Project. (CMIP) . This will be CMIP number 5; hence, CMIP5. The CMIP projects follow from the Atmospheric Model Intercomparison Problem which was started in 1990. There is also an even longer history of model intercomparison and assessments in the stratospheric ozone community.
These intercomparison projects are an important part of model evaluation, but they are just part of the testing and evaluation that is done in assessing the strengths and weaknesses of models. They all have basically the same steps. Observations are the foundation of any evaluation. Hence, there is the need to identify a set of observations that will be used in the evaluations. There are hundreds of possibilities, and over the community as a whole, virtually any credible observation set that provides useful information has been used. However, there are a few that rise to stop as standard. A couple of examples are the surface temperature observations as, for example, compiled and validated and maintained by the Hadley Center and the Goddard Institute for Space Studies. Another classic example are the cloud and radiation observations that come from the Clouds and the Earth’s Radiant Energy System (CERES) instruments that fly on several satellites. (Here’s where you can get some data.)
Observations sit at the foundation, but there are several other critical elements in model evaluation. One of those critical elements is to have at least one group of independent researchers mode up of members NOT responsible for the model development. This is a group that can look at models with objectivity. In the U.S. the Program for Climate Model Diagnosis and Intercomparison is such a group. (This group is sponsored by the Department of Energy’s Office Biological and Environmental Research.)
Also critical to the process is the design of numerical experiments. (Yes, some scientists argue that there is no such thing as a “numerical experiment,” but it is possible to set up robust scientific experimentation with numerical models.) For example, in the Atmospheric Model Intercomparison Project, all of the models simulate from 1979 – 2000 using observed monthly mean sea surface temperatures. This time span was chosen because of the presence of global satellite observations. There are several standard runs in the climate model intercomparisons. An example is the “modern industrial era,” approximately the past 150 years.
Another element of the evaluation is the selection of objective measures for the evaluation and intercomparison. One of the standard measures is called the Taylor Diagram, which is an accumulation of statistical information from many data sources and many models. Here is an example of a Taylor Diagram.
Figure 1: Taylor Diagram: (primer) The plot is constructed based on the Law of Cosines. The observed field is represented by a point at unit distance from the origin along the abscissa. All other points, which represent simulated fields, are positioned such that the variance is the radial distance from the origin, the correlation is the cosine of the azimuthal angle, and the normalized root mean square difference is the distance to the observed point. When the distance to the point representing the observed field is relatively short, good agreement is found between the simulated and observed fields. In the limit of perfect agreement (which is, however, generally not achievable because there are fundamental limits to the predictability of climate), the root mean square difference would approach zero, and and correlation would approach unity.
Finally, this is an example of organizing and planning in the climate community. The process works from both the bottom and the top. Some scientists see the need for both coordination and the need to have controlled experiments across many organizations. They self organize, then seek funding from the agencies. Sometimes the agencies see the need for organization, and then offer incentives and opportunities for scientists to organize. I want to point you to an interesting document for next major IPCC assessment. This is a strategy document developed by part of the modeling community. It is an example of scientists trying to take part in the definition of the best experiments to support the assessments. Here’s A Strategy for Climate Change Stabilization Experiments with Atmospheric Ocean General Circulation Models and Earth System Models. And here are the objectives as quoted from this document.
1. Identify new components that are currently under implementation or will be ready in the next six months for inclusion as first generation Earth System Models in Atmosphere-Ocean General Circulation Models (AOGCMs).
2. Establish communication through WCRP, IGBP, IPCC, the climate impacts community, and integrated assessment (IA) modeling teams to coordinate activities in preparation for climate change simulations that will be performed with this next generation of climate system models for a possible IPCC AR5.
3. Propose an experimental design for 21st century climate change experiments with these models (near term and longer term time frames).
4. Specify the requirements for these new models in terms of time series of constituents from new stabilization scenarios (particularly with regard to impacts, mitigation, and adaptation).
Links to relevant blogs.
Importance of Justification
Buying Big Computers
Fragmented Climate
Organizing the Fragments
This series of blogs collected.
The views of the author are his/her own and do not necessarily represent the position of The Weather Company or its parent, IBM.