There is a valuable new publication that has been introduced by the The Meteorological Society of Japan . It is called SOLA and information is available online as to how to submit papers (see).
As communicated me by Dr. Takehiko Satomura of the Climate Physics Lab., Division of Earth and Planetary Science at Kyoto University in Kyoto, Japan,
“SOLA (Scientific Online Letters on the Atmosphere) is a new electronic journal published by the Meteorological Society of Japan (MSJ) started from 1 January 2005. SOLA is a medium for the electronic publication of short letters in the atmospheric science and related interdisciplinary studies. It is an electronic Journal open to the public through the Internet and is aimed for rapid reporting of recent significant discoveries. The decision of acceptance or rejection of submitted articles is done within two moths after the submission. The Journal publishes research letters by members and nonmembers of the Society and is posted as soon as the paper is accepted.”
The value of this new journal is that it very effectively utilizes the current technology to provide rapid dissemination of new and important reserarch results, without compromising rigorous peer review. The availability of such a journal from such a prestigiouos professional society as the MSJ eliminates the seemingly arbitrary rejection of even reviewing research papers, as identified on James Annan’s website with respect to his submission of a paper to Nature. It will also eliminate unreasonable delay in the publication of papers (my 2005 paper with Christopher Davey entitled “Microclimate exposures of surface-based weather stations – implications for the assessment of long-term temperature trends” took over three years to publish in the Bulletin of the American Meteorological Society!).
I urge the climate community to ultilize this effective new resource, and look forward to alerting readers of the Climate Science weblog to research papers that are published in SOLA.
On the Climate Science weblog for May 25 2006, the subject of whether the multi-decadal global climate simulation are predictions or projections was presented (see), and a number of valuable comments on it are posted.
This weblog asks a related question. Are the multi-decadal global model simulations hypotheses?
“A tentative explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.”
The definition of a “model” as used in mathematics and physics include the following;
“Mathematical use of data to project experimental results. A small imitation of the real thing; a system of postulates, data, and inferences presented as a mathematical description of an entity or state of affairs.” (from)
‘In science, a representation such that knowledge concerning the model offers insight about the entity modeled. Whether models are heuristic devices or essential features of scientific explanation is a matter of debate. Mathematical models are interpretations of a formal system assigning truth values to the formulae of the system, thus testing the system for consistency.” (from)
The American Meteorological Society defines a “model” as
“modelâA tool for simulating or predicting the behavior of a dynamical system like the atmosphere.
Models can be based on subjective heuristic methods, statistics (see statistical dynamical model, model output statistics), numerical methods (see numerical forecasting), simplified physical systems (see dishpan experiments), analogy (see analogs), etc. The term is now most commonly applied to numerical models.”
‘Measurements in atmospheric science sometimes determine universal functions, but more commonly data are collected in the form of case studies. Models are conceptual constructs that can be used to make predictions about the outcomes of measurements. Hypotheses can be expressed in terms of model results, and the best use of measurements is to falsify such hypotheses. Tuning of models should be avoided because it interferes with falsification. Comparison of models with data would be easier if the minimum data requirements for testing some types of models could be standardized.”
Thus it is clear, that the multi-decadal global climate predictions are hypotheses. With this interpretation, the question is whether the testing of the models using observed surface and tropospheric temperature trends over the last several decades, as reported in the CCSP Report âTemperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differencesâ?, has resulted in a falsification of the following hypotheses from the model simulations in the CCSP Report;
1. Hypothesis #1: The multi-decadal global climate models predict a linear tropical (20N to 20S) zonally averaged surface and tropospheric temperature trend for the period 1979-1999 that is consistent with the available observations.
“Although the majority of observational data sets show more warming at the surface than in the troposphere, some observational data sets show the opposite behavior. Almost all model simulations show more warming in the troposphere than at the surface. This difference between models and observations may arise from errors that are common to all models, from errors in the observational data sets, or from a combination of these factors. The second explanation is favored, but the issue is still open.”
While the attribution of the difference to the observations is disingenuous, it is clear that the model results are falsified, thus far, with respect to the tropical zonally averaged surface and tropospheric trends.
2. Hypothesis #2 The multi-decadal global climate models predict a linear global averaged surface and tropospheric temperature trend for the period 1979-1999 that is consistent with the available observations.
“The most recent climate model simulations give a range of results for changes in global-average temperature. Some models show more warming in the troposphere than at the surface, while a slightly smaller number of simulations show the opposite behavior. There is no fundamental inconsistency among these model results and observations at the global scale.”
An obvious issue with this conclusion is that how can there be “no fundamental inconsistency among these model results and observations at the global scale” if the tropical zonal average surface and tropospheric temperature trends cannot be accurately simulated?
3. Hypothesis #3 The multi-decadal global climate models predict linear regional averaged surface and tropospheric temperature trends for the period 1979-1999 that are consistent with the available observations.
âOwing to natural internal variability, models cannot be expected to reproduce regional patterns of trend over a period as short as 20 years from changes of radiative forcings alone.â?
What this means is that even for the assessment of linear trends, the multi-decadal global climate models have not even been tested as a hypothesis. I urged that this be done in the original version of Chapter 6 of the CCSP Report entitled “What measures can be taken to improve our understanding of observed changes?” which was purged from the Report when I resigned.
Thus, the answers to the questions are as follows:
“Are Multi-Decadal Global Climate Simulations Hypotheses? ”
“Has the Hypothesis As Represented By the Models Been Falsified?”
The Report concludes that the linear trends of the global average surface and tropospheric temperatures are consistent with the observations (thus indicating that the hypothesis has not been falsified). However, the Report also concludes that the linear trends of the tropical (20N to 20S) average surface and tropospheric temperatures are not generally consistent with the observations. The claim of a consistency between the observations and the models in the linear global surface and troposphere temperature trends, but a lack of consistency for the tropics must mean that the global model average results fortuitously agree. At the very least, the testing of the linear global average surface and tropospheric temperature trends is inconclusive.
The broad conclusion is that the multi-decadal global climate models are unable to to accurately simulate the linear trends of surface and tropospheric temperatures for the 1979-1999 time period on the regional and tropical zonally-averaged spatial scale. Their ability to skillfully simulate the global averages surface and tropospheric temperature trend on this time scale is, at best, inconclusive.
This has major implications for the impacts community. Studies such as the U.S. National Assessment and Chapters and the IPCC which use regional results from the multi-decadal climate models are constructed on models which have been falsified in their ability to accurately simulate even the linear trend of the tropical zonally averaged surface and tropospheric temperature trends over the last several decades. Since almost all impact studies require regional and smaller scale resolution, the current generation of multi-decadal global climate prediction models is inappropriate to use for impact prediction for the coming decades.
A recommendation that results from this assessment of the models as hypotheses is that, while they are valuable tools to examine climate processes, we need to move to a new perspective based on the vulnerability framework advocated on this weblog, and discussed in detail in the paper
Pielke, R.A. Sr., 2004: Discussion Forum: A broader perspective on climate change is needed. IGBP Newsletter, 59, 16-19. http://www.igbp.kva.se//uploads/NL_59.pdf – Discussion Forum: How Good are Climate Projections?
This means that the funding of climate research should provide much better funding to vulnerability research than provided up to now.
An extract from his essay with respect to the terms “prediction” and ‘projection” state,
“2. Prediction versus Projection
Based on the failure to treat the various land cover processes that are suggested, Pielke (2002) also suggests that ‘[i]f climate prediction is not possible beyond some time scale, a focus on vulnerability is the preferred scientific approach to provide policymakers with useful information’. This statement seems to me to confound two issues that merit further attention. Regarding the first, both IPCC and the U.S. National Assessment are very careful in their usage of the word projection rather than prediction. For these groups, the distinction is meant to convey a very significant difference that is too often being ignored by critics of these reports. Acknowledging Pielke’s point that at least some dictionaries are not yet capturing these subtleties (although my 1999 Webster’s II New College Dictionary defines projection as a ‘plan for a future course of action’ rather than a prediction), I would argue that the differences in these two words are roughly as follows:
• A prediction is a probabilistic statement that something will happen in the future based on conditions that are known today and assumptions about the physical processes that will determine these changes. A prediction generally assumes that future changes in factors other than those being predicted will not have a significant influence on what is to happen. In this sense, a prediction is most influenced by the ‘initial conditions’, that is, predictions depend on the current conditions that are known through observations. Thus, a weather prediction indicating a major snowstorm will develop over the next few days is based on the state of the atmosphere today (and its conditions in the recent past) and not on unpredictable changes of other potentially influential factors that serve as ‘boundary conditions’, such as how ocean temperatures or human activities may change over the next few days. A prediction is made probabilistic by accounting for various types of uncertainties, for example, in
the accuracy of observations, in the chaotic state of the atmosphere, etc. For decision-makers, what is important is that a prediction is a statement about an event that is likely to occur no matter what they do (i.e., policymakers cannot change tomorrow’s weather).
• A projection is usually a probabilistic statement that it is possible that something will happen in the future if certain conditions develop. In contrast to a prediction, a projection specifically allows for significant changes in the set of ‘boundary conditions’ that might influence the prediction. As a result, what emerges are conclusions of the type ‘if this happens, then this is what is expected’. The simplest type of projection is to extrapolate into the future assuming all of the boundary conditions remain the same or that the same trends prevail. For projections extending well out into the future, however, this is often a poor assumption, so scenarios (or story-lines) are developed of what could happen given various assumptions and judgments. For example, IPCC (2001) projects a range of possible temperature increases for the 21st century that calculations indicate would result in the event that the world follows a number of plausible story-lines concerning population and economic growth, energy technologies and emissions, and demographics and international relationships (see IPCC, 2000) – but also assuming no agreements to
limit emissions due to concerns about climate change. By considering how the resulting changes in atmospheric composition would affect the climate using seven different climate models, each with its own particular climate sensitivity, the projections of climate change accounted, to a reasonable extent, for a wide range of possibilities of both societal development and climate behavior.
Given this approach, projections are clearly indications of what could happen if certain assumed conditions prevail in the future – they are neither a prediction nor a forecast of what will or is likely to happen. For decision-makers, a projection is thus an indication of a possibility, and normally of one that could be influenced by their actions.”
My reading of these definitions is that “a projection is a prediction if certain actions (e.g. CO2 reduction) are not undertaken. A “projection” is a “conditional prediction” (conditioned in that humans can alter the prediction based on specific actions). These are both predictions!
In the context of weather forecasting, a ‘weather projection’ would be one where we could, for example, alter a hurricane’s intensity and path by cloud seeding. This is still a prediction.
Process studies: The application of climate models to improve our understanding of how the system works is a valuable application of these tools. In my Climatic Change essay, I used the term sensitivity study to characterize a process study. In a sensitivity study, a subset of the forcings and/or feedback of the climate system may be perturbed to examine its response. The model of the climate system might be incomplete and not include each of the important feedbacks and forcings.
Diagnosis: The application of climate models, in which observed data is assimilated into the model, to produce an observational analysis that is consistent with our best understanding of the climate system as represented by the manner in which the fundamental concepts and parameterizations are represented. Although not yet applied to climate models, this procedure is used for weather reanalyses (see the NCEP/NCAR 40-Year Reanalysis Project).
Forecasting: The application of climate models to predict the future state of the climate system. Forecasts can be made from a single realization, or from an ensemble of forecasts which are produced by slightly perturbing the initial conditions and/or other aspects of the model.
Under what of these three types of climate modeling does the term “projection” best fit with respect to multi-decadal global climate simulations, such as used by the IPCC? “Forecasting” is clearly not the type as concluded by Mike MacCracken, and I assume also by James Annan based on his comment on the weblog. Obviously, they are not “diagnostic climate models”.
The multi-decadal global climate model simulations are process (sensitivity) studies. The use of the term “projection” is misleading the impacts community that uses the model results for their studies. Its use is confusing to the impacts community who almost all interpret (correctly) that the term “projection” means “prediction”.
This is a significant issue. The use of the term “projection” results in erroneous communication to policymakers on the accuracy of the multi-decadal global model simulations in being capable of accurately predicting the climate in the coming decades. The models cannot be skillful since they do not contain all of the important first order climate forcings, as identified in the 2005 National Research Council Report. Indeed, when a range of global averaged surface temperature increases for the coming decades are next presented, the question should be asked if this is a prediction, or just the result of a process modeling study with incomplete climate physics ? The honest answer will be the later.
The weblog RealClimate on May 18 2006 has a posting entitled “Thank you for emitting”. . In the post, which is written in response to an advertisement, there is text referring to CO2 as a pollutant; ;
” It contains the immortal lines ‘CO2: they call it pollution, we call it Life!’ – it is beyond parody and without content – and so you should definitely see it.”
Is CO2 a pollutant? This issue was discussed on the Climate Science weblog of August 9 2005 which included a constructive comment discussion on this question. The subject of whether CO2 is a pollutant is revisited here.
“The Clean Air Act established two types of National Ambient Air Quality Standards.
“Primary’ standards are designed to establish limits to protect public health, including the health of “sensitive” populations such as asthmatics, children, and the elderly.
‘Secondary’ standards set limits to protect public welfare, including protection against decreased visibility and damage to animals, crops, vegetation, and buildings”
The six criteria pollutants, as defined by the EPA, are ozone, particulate matter, carbon monoxide, nitrogen dioxide, sulfur dioxide and lead.
Having served two terms on the Colorado Air Quality Control Commission, published a number of papers on air quality modeling, and working with the EPA and other regulatory agencies, my understanding of when the term “pollution” should be used is based on the existing EPA context. The term “pollution” connotes an undesirable constituent. For example, ozone is undesirable at any concentration in the lower atmosphere where we can inhale it; O3 is a pollutant in the troposphere. In the stratosphere, however, its absence is undesirable! O3 is not a pollutant in the stratosphere.
Thus the referral to CO2 as a pollutant, in my view, is inaccurate. Indeed, one of the environmental successes was the development of vehicles which have very efficient combustion such that CO2 rather than CO is produced (see the National Research Council report where it is stated,
“The regulation of carbon monoxide has been one of the great success stories in air pollution control. While more than 90 percent of the locations with carbon monoxide monitors were in violation in 1971, today the number of monitors showing violations has fallen to only a few, on a small number of days and mainly in areas with unique meteorological and topographical conditions. ”
The reason that this is a success story is that vehicles have more efficient combustion today, so that more CO2 and less CO is produced!
Information on whether CO2 is a pollutant include a “Is CO2 a Pollutant?” Department of Energy Technical Report edited by B. R. Strain and J.D. Cure entitled “Direct effects of increasing carbon dioxide on vegetation”.
“CO2 is an essential environmental resource. It is required as a raw material of the orderly development of all green plants. As the availability of CO2 increases, perhaps reaching two or three times the concentration prevailing in preindustrial times, plants and all other organisms dependent on them for food will be affected. Humans are releasing a gaseous fertilizer into the global atmosphere in quantities sufficient to affect all life. This volume considers the direct effects of global CO2 fertilization on plants and thus on all other life. Separate abstracts have been prepared for individual papers.”
“In short-term experiments under productive laboratory conditions, native herbaceous plants differ widely in their potential to achieve higher yields at elevated concentrations of atmospheric carbon dioxide. The most responsive species appear to be large fast-growing perennials of recently disturbed fertile soils. These types of plants are currently increasing in abundance9 but it is not known whether this is an effect of rising carbon dioxide or is due to other factors. Doubts concerning the potential of natural vegetation for sustained response to rising carbon dioxide have arisen from experiments on infertile soils, where the stimulus to growth was curtailed by mineral nutrient limitations. Here we present evidence that mineral nutrient constraints on the fertilizer effect of elevated carbon dioxide can also occur on fertile soil and in the earliest stages of secondary succession. Our data indicate that there may be a feedback mechanism in which elevated carbon dioxide causes an increase in substrate release into the rhizosphere by non-mycorrhizal plants, leading to mineral nutrient sequestration by the expanded microflora and a consequent nutritional limitation on plant growth.”
We also know that atmospheric concentrations of CO2 routinely double everyday within tropical forests, as soils and plants respire at night releasing CO2, with vegetation assimilating CO2 during the day. For example, a study by Jenny Rissler, Erik Swietlicki, Anders Vestin and Jingchuan Zhou entitled ” Diurnal Aerosol patterns and nucleation in the Amazon Region” (see their Figures 2 and 3) show atmospheric CO2 concentrations reaching as high as 500 ppm in the Amazon. Clearly, this local level of 500 ppm is not a pollutant for the rain forest.
There are, therefore, several conclusions from such studies with respect to the question of whether CO2 is a pollutant.
1. Atmospheric CO2 is essential for vegetation growth, and is not an air quality pollutant in the same context as the EPA Criteria pollutants.
2. Elevated atmospheric concentrations of CO2 affect vegetation differentially, with the result that species compositions should be expected to change.
3. High (doubled from background free atmospheric concentrations) of CO2 are routine in forests.
4. We do not know what (or even if) there is an optimal level of CO2 in the atmosphere with respect to vegetation. It appears there are a wide diversity of optimal conditions for each vegetation (and perhaps even genotype), weather, latitude and soil conditions.
Focusing on CO2 as a pollutant is, therefore, counterproductive if the goal is to limit its increase by human activities. The added CO2 is a radiative and biogeochemical climate forcing, and it should be communicated to policymakers in this context. We do not use the term “pollutant” when referring to land use/land cover change yet this is just as much a climate forcing as CO2.
Dr. Colette L. Heald presented a seminar at Colorado State Univerisity on May 22, 2006 entitled “Observing Tropospheric Composition: Insights on Sources and Fate of Pollution”
The abstract of her talk is
“Understanding the composition of the troposphere is vital to issues of air quality and climate forcing. The suite of observations of tropospheric
composition from surface sites, aircraft campaigns and remote platforms provide a means of testing current knowledge, as represented by models, and investigating the links between air quality, chemistry and climate. This talk will focus on how we can use these observations to understand the sources and fate of pollution in the troposphere, highlighting the role of satellite observations. The integration of observations has been successfully applied to estimate emissions of carbon monoxide and observe the intercontinental transport of this pollution. Understanding the formation and transport of aerosols in the troposphere represents a greater challenge. The transpacific transport of Asian sulfate has important consequences for domestic air quality objectives. Space-based observations of aerosols are used here with in situ observations to examine the evolution and impact of this transport. Recent observations aboard aircraft off of Asia show a large burden of organic carbon aerosol in the free troposphere. The inability of current models to explain this aerosol suggests an incomplete understanding of secondary organic aerosol formation, with significant implications for both air quality and climate forcing.”
A key statement in this abstract is the recognition that
“Recent observations aboard aircraft off of Asia show a large burden of organic carbon aerosol in the free troposphere. The inability of current models to explain this aerosol suggests an incomplete understanding of secondary organic aerosol formation, with significant implications for both air quality and climate forcing”.
A new paper that she has in press in the Journal of Geophysical Research provides an in depth report on her research on aerosols. The paper is
“We use satellite (MODIS) observations of aerosol optical depths (AODs) over the North Pacific, together with surface aerosol measurements at a network of remote U.S. sites (IMPROVE), to improve understanding of the transpacific transport of Asian aerosol pollution and assess the ability of a global 3-D chemical transport model (GEOS-Chem CTM) to quantify Asian aerosol enhancements in U.S. surface air. The MODIS observations show the strongest transpacific transport occurring in spring at 40-55oN. This transport in the model takes place mainly in the lower free troposphere (900-700 hPa) because of scavenging during transport either in the boundary layer or during lifting to the upper troposphere. The preferential altitude of aerosol transpacific transport results in direct impact on the elevated terrain of the NW United States. Sulfate observations in the NW United States in spring 2001 show higher concentrations on the days of model predicted maximum Asian influence (1.04 μg m-3) than seasonal mean values (0.69 μg m-3). No such Asian enhancements are observed for nitrate or for organic carbon (OC) aerosol. Distinct Asian sulfate episodes correlated with dust events are observed in the NW United States and simulated with the model. The mean Asian pollution enhancement in that region in spring is 0.16 μg m-3 with a 50% estimated uncertainty. This is higher than the estimated natural concentration of 0.09 μg m-3 presently used as objective for regulation of visibility in U.S. wilderness areas.”
This research clearly documents the importance of the long range transport of aerosols in the climate system, as also identified in the 2005 National Research Council report in a section entitled “TELECONNECTIONS AND RADIATIVE FORCING”. This type of “teleconnection” over long distances is a first order climate effect which alters the diabatic heating of the troposphere significantly. The result of this alteration in diabatic heating are changes in large scale weather patterns (e.g. see).
A focus on the importance of these types of heterogeneous climate forcing should be a major focus of the international climate assessments (e.g.see), but unfortunately, so far has been mostly ignored since the IPCC and other assessments have made global average surface temperature the icon of climate change. Clearly based on research such as presented in the Heald et al study, the assessments are overlooking critical climate science.
Two new papers have appeared in the peer reviewed literature on recent trends in major hurricanes. It will be informative to see if the media include these studies in their news on the upcoming hurricane season.
“The recent destructive Atlantic hurricane seasons and several recent publications have sparked debate over whether warming tropical sea surface temperatures (SSTs) are causing more intense, longer-lived tropical cyclones. This paper investigates worldwide tropical cyclone frequency and intensity to determine trends in activity over the past twenty years during which there has been an approximate 0.2°–0.4°C warming of SSTs. The data indicate a large increasing trend in tropical cyclone intensity and longevity for the North Atlantic basin and a considerable decreasing trend for the Northeast Pacific. All other basins showed small trends, and there has been no significant change in global net tropical cyclone activity. There has been a small increase in global Category 4–5 hurricanes from the period 1986–1995 to the period 1996–2005. Most of this increase is likely due to improved observational technology. These findings indicate that other important factors govern intensity and frequency of tropical cyclones besides SSTs.”
The text included the statement,
“These findings are contradictory to the conclusions drawn by Emanuel  and Webster et al. . They do not support the argument that global TC frequency, intensity and longevity have undergone increases in recent years. Utilizing global ‘‘best track’’ data, there has been no significant increasing trend in ACE and only a small increase (~10%) in Category 4–5 hurricanes over the past twenty years, despite an increase in the trend of warming sea surface temperatures during this time period.”
“Whereas there is a significant relationship between overall sea-surface temperature (SST) and tropical cyclone intensity, the relationship is much less clear in the upper range of SST normally associated with these storms. There, we find a step-like, rather than a continuous, influence of SST on cyclone strength, suggesting that there exists a SST threshold that must be exceeded before tropical cyclones develop into major hurricanes. Further, we show that the SST influence varies markedly over time, thereby indicating that other aspects of the tropical environment are also critically important for tropical cyclone intensification. These findings highlight the complex nature of hurricane development and weaken the notion of a simple cause-and-effect relationship between rising SST and stronger Atlantic hurricanes. ”
The text of the article includes the statement,
“Our results show that SST plays a relatively minor role in the observed characteristics of tropical storms and hurricanes in the North Atlantic Basin. As such, other factors must be involved in the increase in tropical cyclone activity recorded during the post-1994 Atlantic hurricane seasons. The full reason behind these observed changes remain an area of active scientific inquiry. We therefore recommend a cautious approach to assigning an underlying cause in this complex system.”
The criteria for tropical cyclone development and intensification were summarized in the following books:
Pielke, R.A., 1990: The hurricane. Routledge Press, London, England, 228 pp.
Pielke, R.A., Jr. and R.A. Pielke, Sr., 1997: Hurricanes: Their nature and impacts on society. John Wiley and Sons, England, 279 pp.
Chapter 3 of the second book discusses the following topics;
CHAPTER 3 Tropical Cyclones on Planet Earth 3.1 Life of a Hurricane 3.1.1 Birth and growth 3.1.2 Maturity 3.1.3 Decay 3.1.4 Criteria for development and intensification of a tropical cyclone 3.2 Special Cases of Development and Intensification 3.3 Geographic and Seasonal Distribution 3.3.1 Origin 3.3.2 Movement 3.3.3 Tropical cyclones in the Atlantic Ocean Basin.
A major conclusion from the analysis of major hurricanes that are summarized in these books is that vertical wind shear is the critical requirement to permit hurricanes to reach their maximum possible intensity for a given sea surface temperature. As easily seen on any analysis of tropical sea surface temperatures (e.g.see) very warm temperatures that permit major hurricanes are common over vast areas of the coean. That we seldom achieve such intensity is a result of the need for an optimal connection between low level moist inflow and the anticyclonic outward aloft. Even relatively weak vertical wind shear can disrupt this connection.
To focus on sea surface temperatures, rather then the entire synoptic environment of the tropical cyclone in multi-decadal trend assessments is another example of where the icon of the surface temperature as THE climate metric, unfortunately, persists.