Climate Science: Roger Pielke Sr. Research Group News

There is  a very important new weblog on water vapor and cloud feedbacks within the climate system as represented by the models used to project multi-decadal climate change. The paper is

 Sun, D.-Z., Y. Yu, and T. Zhang, 2007: Tropical Water Vapor and Cloud Feedbacks in Climate Models: A Further Assessment Using Coupled Simulations. J. Climate, Submitted. [a powerpoint talk of this research was completed for my class last spring (see Validating and Understanding Feedbacks in Climate Models ).

The abstract reads,

By comparing the response of clouds and water vapor to ENSO forcing in nature with that in AMIP simulations by some leading climate models, an earlier evaluation of tropical cloud and water vapor feedbacks has revealed two common biases in the models: (1) an underestimate of the strength of the negative cloud albedo feedback and (2) an overestimate of the positive feedback from the greenhouse effect of water vapor. Extending the same analysis to the fully coupled simulations of these models as well as to other IPCC coupled models, we find that these two common biases persist. Relative to the earlier estimates, the overestimate of the positive feedback from water vapor is alleviated somewhat for most of the models. Improvements in the simulation of the cloud albedo feedback are only found in the models whose AMIP runs suggest a positive or nearly positive cloud albedo feedback. The strength of the negative cloud albedo feedback in all other models is found to be substantially weaker than that estimated from the corresponding AMIP simulations. Consequently, all models analyzed in this study are found to have a weaker negative feedback from the net surface heating over the ocean than that indicated in observations. The weakening in the cloud albedo feedback is linked to a reduced response of deep convection over the equatorial Pacific which is in turn linked to the excessive cold-tongue in the mean climate of these models. The results highlight that the feedbacks of water vapor and clouds—the cloud albedo feedback in particular—depend on the mean intensity of the hydrological cycle. We have also examined whether the variations among models of the feedback from cloud albedo (water vapor) in the ENSO variability are correlated with the variations among models of the feedback from cloud albedo (water vapor) in global warming. While we find a weak positive correlation between the variations among models in the feedback of water vapor during ENSO and the variations among models in the water vapor feedback during global warming, we find no significant correlation between the variations among models in the cloud albedo feedback during ENSO and the variations among models in the cloud albedo feedback during global warming. We thereby suggest that the two common biases revealed in the simulated ENSO variability may not be carried over to the simulated global warming, though these biases highlight the continuing difficulty that models have to simulate accurately the feedbacks of water vapor and clouds on a time-scale we have observations.

The conclusion the paper has the text,

“The extended calculation using coupled runs confirms the earlier inference from the AMIP runs that underestimating the negative feedback from cloud albedo and overestimating the positive feedback from the greenhouse effect of water vapor over the tropical Pacific during ENSO is a prevalent problem of climate models. The estimates from the coupled simulations of both the cloud albedo feedback and the water vapor feedback differ from the estimates from the corresponding AMIP simulations. The changes in the cloud albedo feedback are particularly significant. The previous analysis of Sun et al. (2006) has suggested that the GFDL CM2 may have a cloud albedo feedback that is as strong as observations. The new estimate with the coupled runs puts this suggestion in doubt as the new estimate is significantly weaker than the previous estimate. All models we have examined in this analysis are found to have a weaker negative feedback from the net surface heating than that from observations, indicating that deep convection over the equatorial Pacific in the models has a weaker regulatory effect over the SST in that region. The differences between the values estimated from the coupled runs and the values estimated from the corresponding AMIP runs are shown to be linked to the excessive cold-tongue in the climatology in the coupled models.

The two common biases, shown in the ENSO cycle, however, do not appear to be carried over the global warming simulations. The variations in the cloud albedo feedback among different models are not correlated with the variations in the same feedback in the global warming simulations among different models. The variations in the water vapor feedback among different models during ENSO over the cold-tongue are positively correlated with the variations in the water vapor feedback during global warming, but the correlation is weak. There is no correlation between the feedbacks over the cold-tongue region during ENSO and the globally averaged feedbacks during global warming. Therefore, the overestimate of the water vapor feedback and the underestimate of the cloud albedo feedback during the ENSO cycle in the models do not necessarily imply that the sensitivity of the mean tropical climate to anthropogenic forcing is overestimated by the models. On the other hand, we are not suggesting that the prevalence of these two biases in the models during ENSO should not be of concern for the accuracy of global warming simulated by the models. This is because the lack of correlation in the models between the feedbacks on these two time-scales could be due to error cancellations in the models. In any case, the present results highlight the continuing difficulty that models have in simulating accurately the water vapor and cloud feedbacks in the deep tropics on the time-scale over which we have observations to compare with model simulations. The results should also be of value to the diagnosis of the causes of the biases in the ENSO amplitude in the models.”

An important conclusion from the Sun et al study is that “all models analyzed in this study are found to have a weaker negative feedback from the net surface heating over the ocean than that indicated in observations.”

The authors further state that

“We thereby suggest that the two common biases revealed in the simulated ENSO variability may not be carried over to the simulated global warming, though these biases highlight the continuing difficulty that models have to simulate accurately the feedbacks of water vapor and clouds on a time-scale we have observations”.

However it is not clear how such a bias could be removed when the models are applied in longer term model projections. Indeed, what is the data which says that the biases are removed?

FOLLOW UP

In order to obtain an answer to the above question, I contacted Dr. Sun with the following
 ”I have set for your paper to be weblogged on in a couple of weeks. However, I have a question on your conclusion that ‘We thereby suggest that the two common biases revealed in the simulated ENSO variability may not be carried over to the simulated global warming, though these biases highlight the continuing difficulty that models have to simulate accurately the feedbacks of water vapor and clouds on a time-scale we have observations’, however it is not clear how such a bias could be removed when the models are applied in longer term model projections. Indeed, what is the data which says that the biases are removed?

Please clarify and I can add to the weblog.”

REPLY FROM DR. SUN

“You are right that no data have shown that those biases will not be removed. We are just mentioning the possibility that there could be error cancellation as global warming may involve more processes that those in ENSO, and the errors may cancel in such a way that prediction of global warming by these models that have these errors may actually get the answer right.  It is just a possibility worth mentioning.”

The message from the Sun et al study, therefore, is that the models used to make the multi-decadal global climate projections that are reported in the IPCC report are “…that underestimating the negative feedback from cloud albedo and overestimating the positive feedback from the greenhouse effect of water vapor over the tropical Pacific during ENSO is a prevalent problem of climate models.” 

This study indicates that the IPCC models are overpredicting global warming in response to positive radiative forcing.

There is an important new paper on the role of landscape processes within the climate system [and thanks to Tobis Rothenberger at the University of St. Gallen for alerting us to it!].  The article is

Barnes, C. A., and D. P. Roy (2008), Radiative forcing over the conterminous United States due to contemporary land cover land use albedo change, Geophys. Res. Lett., 35, L09706, doi:10.1029/2008GL033567.

The abstract reads

“Recently available satellite land cover land use (LCLU) and albedo data are used to study the impact of LCLU change from 1973 to 2000 on surface albedo and radiative forcing for 36 ecoregions covering 43% of the conterminous United States (CONUS). Moderate Resolution Imaging Spectroradiometer (MODIS) snow-free broadband albedo values are derived from Landsat LCLU classification maps located using a stratified random sampling methodology to estimate ecoregion estimates of LCLU induced albedo change and surface radiative forcing. The results illustrate that radiative forcing due to LCLU change may be disguised when spatially and temporally explicit data sets are not used. The radiative forcing due to contemporary LCLU albedo change varies geographically in sign and magnitude, with the most positive forcings (up to 0.284 Wm⁻²) due to conversion of agriculture to other LCLU types, and the most negative forcings (as low as −0.247 Wm⁻²) due to forest loss. For the 36 ecoregions considered a small net positive forcing (i.e., warming) of 0.012 Wm⁻² is estimated.”

The conclusion includes the text

“ Loss of agricultural and forested lands were observed to be the LCLU changes that caused the greatest absolute albedo induced forcing. Across the CONUS however there is no single profile of LCLU change, rather, there are varying pulses affected by clusters of change agents [Loveland et al., 2002]. This argues strongly for the ecoregion based analysis we have described, as continental averages may mask regional differences; indeed, because of the variability in magnitude and sign of forcing, we estimate only a small, 0.012 Wm⁻², net CONUS forcing due to contemporary LCLU albedo change. This work did not consider snow, which may have a significant land cover dependent albedo effect [Jin et al., 2002] and so may impact the forcing associated with actual albedo change [Betts, 2000]; however, only about one eighth of the CONUS ecoregions considered in this study have significant annual snow cover. Further research will be undertaken to address these impacts for a larger number of ecoregions as more LCLU change data become available.”

This study is yet another example of why we need to include the assessment of landscape on the regional scale, as altered by humans, in terms of how our climate is being changed.

There is another paper on the role of landscape processes within the climate system; it is

van der Molen, M.K., H.F. Vugts, L.A. Vruijnzeel, F.N. Scatena, R.A. Pielke, and L.J.M. Kroon, 2007: Mesoscale climate change due to lowland deforestation in the maritime tropics. In: Mountains in the Mist, Science for conserving and managing Tropical Montane Cloud Forest. L.A. Bruijnzeel, J. Juvik, F.N. Scatena, L.S. Hamilton and P. Bubb (Eds.). University of Hawaii Press, in press.

The abstract reads

“Annual precipitation on the Caribbean island of Puerto Rico decreased steadily during the 20th century, on average by 16 %. The reduced rainfall manifested itself in the form of regular water rationings during the 1990s which hit millions of inhabitants. Simultaneous with the reduction in rainfall there was widespread deforestation, notably in the coastal lowlands. This paper examines the link between the reduction in precipitation and the land cover change using a combination of energy balance measurements and mesoscale atmospheric modelling.

The explanation of the reduction in precipitation appears to be quite different than expected. Based on measurements made earlier over rainforest and pasture in the Amazon, a forest covered island would be expected to be cooler because the higher transpiration -of the forest compared to grassland- tends to cool the surface. During an intensive measurement campaign on Puerto Rico, the opposite appeared to be the case: transpiration by a coastal wetland forest proved to be less than that for a grassland. In addition, the forest albedo was 8 % lower than that for grassland. Together, these two factors caused the sensible heat flux over the forest to be twice as high as that over the grassland, whereas forest evaporation was lower.

The surface energy balance observations over forest and grassland were used to derive proper land surface parameterizations, which were implemented in a mesoscale atmospheric circulation model (RAMS) to simulate the meteorological effects of island wide deforestation. The model simulations indicated that the development of a sea breeze during the day dominates climate on the island. Sea breezes develop when the land surface is warmer than the surrounding ocean. In model runs, where the island was assumed to be completely covered with forest, the sea breeze was considerably stronger than in model runs where the vegetation had been transformed to grassland. Along the sea breeze front, convergence caused upward air motions. As this happens more strongly over a forested island, more clouds are formed but at a higher elevation, with an estimated 10-20 % enhancement of precipitation compared to a deforested island. In the deforested scenario the cloud base was typically lowered by 200 m.

Refinement of the model is required to obtain more accurate estimates of the changes in precipitation, although most likely the relevant processes have been determined. This project has offered new insights into the effects of climate change and may contribute to improved land use and water resources policies on Puerto Rico.”

Everywhere that model simulations of landscape change are completed, we are finding significant effects on the climate of the region. The 2007 IPCC failed to adequately communicate to policymakers this important component of human caused climate change.

Professor Chris Castro alerted us to the following paper;

Barnett, T. P, and D. W. Pierce, 2008: When will Lake Mead go dry? Water Resour. Res., 44, W03201, doi:10.1029/2007WR006704.

The abstract reads

“A water budget analysis shows that under current conditions there is a 10% chance that live storage in Lakes Mead and Powell will be gone by about 2013 and a 50% chance that it will be gone by 2021 if no changes in water allocation from the Colorado River system are made. This startling result is driven by climate change associated with global warming, the effects of natural climate variability, and the current operating status of the reservoir system. Minimum power pool levels in both Lake Mead and Lake Powell will be reached under current conditions by 2017 with 50% probability. While these dates are subject to some uncertainty, they all point to a major and immediate water supply problem on the Colorado system. The solutions to this water shortage problem must be time-dependent to match the time-varying, human-induced decreases in future river flow.”

The text includes the statements

“We consider human-induced reductions in runoff of 10 to 30%, in accordance with estimates from global climate models and statistical analysis, and take these reductions to be linear in time over the next 50 years (i.e., runoff slowly decreases until it reaches a total reduction of, say, 10% below current levels in 2057)”;

“….we begin with deterministic estimates of when the live storage will be depleted by global warming-driven runoff reductions alone, without the outside impacts of evaporation and natural variability in the river flow”;

“The climate models which have produced estimates of decreasing runoff have a host of problems of their own in handling the water budget from coarse resolution (little in the way of Rocky Mountains) to the variety of ways they handle soil processes and vegetation representations. However, a recent study of changes in hydrology of the western U.S. over that last 50 years shows several of the models, when run with observed anthropogenic forcings, reproduce extremely well the observed changes in river flow timing, snow pack decline and increasing air temperatures in the western United States [Barnett et al., 2008]. So these models, while not perfect, have a message to tell; a message supported by their ability to reproduce well the last 50 years of multivariate hydrological observations“;

and 

“…..the Colorado River will continue to lose water in the future, if the global climate models are correct.”

This paper correctly identifies that there is risk associated with the limited water available from the Colorado River. Indeed their statement that

“Tree ring data suggest the long term flow of the Colorado experiences more variability than has been observed over the last century [NAS, 2007]. These data also suggest prolonged droughts far worse and more extensive than seen in the last 100 years of flow record on the River are possible”

shows that the water resource is at risk regardless of how humans have altered the system. This is a conclusion we also reached in our paper

 Pielke Sr., R.A., N. Doesken, O. Bliss, T. Green, C. Chaffin, J.D. Salas, C. Woodhouse, J.L. Lukas, and K. Wolter, 2005: Drought 2002 in Colorado - An unprecedented drought or a routine drought?Pure Appl. Geophys., Special Issue in honor of Prof. Singh, 162, 1455-1479, doi:10.1007/200024-005-2679-6.

However, the paper suffers from their reliance on the multi-decadal global models as quantitative predictions of what will happen in terms of climate in the coming years. They even recognize this in their text “…..the Colorado River will continue to lose water in the future, if the global climate models are correct.” 

Thus while Climate Science agrees that there is a significant concern on water available from the Colorado River, and planning should be a major priority with respect to long-term drought, the multi-decadal global model predictions are just hypotheses and their use as part of the computation as definitive, skillful predictions to present quantitative probabilities of Lake Mead drying out is misleading to the policymakers. This is yet another example of overselling the skill that exists in using these models as predictions. The large amounts of precipitation this past winter (2007-2008) in large areas of the West should be a wake-up call on the serious limitations of the IPCC models.

We have a new paper that has appeared which reports on the role of an urban area (Mumbai, India) in a heavy rainfall event. The paper is

Lei, M., D. Niyogi, C. Kishtawal, R. Pielke Sr., A. Beltrán-Przekurat, T. Nobis, and S. Vaidya, 2008: Effect of explicit urban land surface representation on the simulation of the 26 July 2005 heavy rain event over Mumbai, India. Atmos. Chem. Phys., accepted.

The abstract reads

“We investigate whether explicit representation of the urban land surface improves the simulation of the record-breaking 24-h heavy rain event that occurred over Mumbai, India on 26 July 2005 as the event has been poorly simulated by operational weather forecasting models. We coupled and conducted experiments using the Regional Atmosphere modeling system (RAMS 4.3), with and without an explicit urban energy balance model-town energy budget (TEB) to study the role of urban land – atmosphere interactions in modulating the heavy rain event over the Indian monsoon region. The impact of including an explicit urban energy balance on surface thermodynamic, boundary layer, and circulation changes are analyzed. The results indicate that even for this synoptically active rainfall event, the vertical wind and precipitation are significantly influenced by urbanization, and the effect is more significant during the storm initiation. Interestingly, precipitation in the upwind region of Mumbai city is increased in the simulation, possibly as a feedback from the sea breeze – urban landscape convergence. We find that even with the active monsoon, the representation of urbanization contributes to local heavy precipitation and mesoscale precipitation distribution over the Indian monsoon region. Additional experiments within a statistical dynamical framework show that an urban model by itself is not the dominant factor for the enhanced rainfall for Mumbai heavy rain event; the combination of updated SST fields using Tropical Rainfall Measurement Mission (TRMM) data with the detailed representation of urban heat island (UHI) simulated by the TEB/urban model created realistic gradients that successfully maintained the convergence zone over Mumbai. Further research will require more detailed morphology data for simulating weather events in such urban regions. The results suggest that urbanization can significantly contribute to extremes in monsoonal rain events that have been reported to be on the rise.”

This new research provides even more demostration of the important role of urban effects on the climate system.

There is an excellent Newsletter series published by the International Global Chemistry Project (IGAC). The latest issue has a very important article entitled

“Comparison of Air Pollutant Emissions among Mega-Cities”by Parish et al. The article starts with the paragraph

“The world’s mega-cities represent a wide diversity of cultures and histories, with examples of mega-cities on all of the five major continents. This diversity might be expected to lead to very different patterns of air pollutant emissions. However, as mega-cities develop economically, a convergence of cultures occurs in the sense that automobile fleets and industrial processes develop in similar modes across all cultures. Our goal in this article is to compare and contrast mega-city air pollutant emissions as reflected in measured ambient concentrations of those pollutants.”

Figure 4 in their article shows the major improvement in the concentration of several important pollutants in recent years, as well as the difference among large cities. It viewing this figure, note that the left axis in is units of the logarithm of concentration such that the spread is in units of concentration are, of course, much larger.

The conclusion of the paper has the text

“The speciation of ambient hydrocarbon concentrations in the mega-cities and other U.S. cities examined here (Figures 1-4) reveal a large degree of similarity. This similarity spans the cities in North America and Asia, has remained nearly constant over the past 2 decades in the U.S., and persists over wide ranges of absolute concentrations. A two-part hypothesis most likely explains this similarity: First, on-road vehicle exhaust and the associated evaporative gasoline emissions dominate the ambient hydrocarbon concentrations in all of these urban areas. Second, there is no large difference in the hydrocarbon composition of gasoline between these urban areas.

Comparison of data sets collected in U.S. cities over the past three decades indicate that a substantial decrease in hydrocarbon emissions has occurred even while total vehicle usage has more than doubled. The ambient concentration data suggest that the emission decrease has been larger than indicated by U.S. emission inventories. Thus, U.S. strategies aimed toward controlling hydrocarbon emissions, based upon automobile catalytic converters and minimization of gasoline evaporation, have been quite successful - indeed more successful than indicated by emission inventories.”

This study documents an environmental success story in the United States (from the period 1988-1984 to the period 2005 to 1999) as well as that the United States, despite similarities around the world, has significantly lower atmospheric concentrations at present than found in Mexico City, Tokyo and Beijing. With the introduction of biofuels, there needs to be continued monitoring of a possible rise in these concentrations due to their particular emissions (e.g see

Evidence Of Health Problems With Ethanol Fuels

Will Climate Effects Trump Health Effects In Air Quality Regulations?

Readers of Climate Science are urged to read past and upcoming issues of the IGAC Newsletter for other excellent research contributions, which are expanding our understanding of the climate system. 

We have published a new research paper, which while not directly on the climate science issue, may be of interest to many Climate Science readers. The paper is

Schecter, D.A., M.E. Nicholls, J. Persing, A.J. Bedard Jr., and R.A. Pielke Sr., 2008: Infrasound emitted by tornado-like vortices: Basic theory and a numerical comparison to the acoustic radiation of a single-cell thunderstorm. J. Atmos. Sci., 65, 685-713.

The abstract reads,

“This paper addresses the physics and numerical simulation of the adiabatic generation of infrasound by tornadoes. Classical analytical results regarding the production of infrasound by vortex Rossby waves and by corotating ’suction vortices’ are reviewed. Conditions are derived for which critical layers damp vortex Rossby waves that would otherwise grow and continually produce acoustic radiation. These conditions are similar to those that theoretically suppress gravity wave radiation from larger mesoscale cyclones, such as hurricanes. To gain perspective, the Regional Atmospheric Modeling System (RAMS) is used to simulate the infrasound that radiates from a single-cell thunderstorm in a shear-free environment. In this simulation, the dominant infrasound in the 0.1–10-Hz frequency band appears to radiate from the vicinity of the melting level, where diabatic processes involving hail are active. It is shown that the 3D Rossby waves of a tornado-like vortex (simulated with RAMS) can generate stronger infrasound if the maximum wind speed of the vortex exceeds a modest threshold. Technical issues regarding the numerical simulation of tornado infrasound are also addressed. Most importantly, it is shown that simulating tornado infrasound likely requires a spatial resolution that is an order of magnitude finer than the current practical limit (10-m grid spacing) for modeling thunderstorms.”

This research builds on our studies

Nicholls, M.E. and R.A. Pielke, 1994: Thermal compression waves. I: Total energy transfer. Quart. J. Roy. Meteor. Soc., 120, 305-332.

Nicholls, M.E. and R.A. Pielke, 1994: Thermal compression waves. II: Mass adjustment and vertical transfer of total energy. Quart. J. Roy. Meteor. Soc., 120, 333-359

Pielke, R.A., M.E. Nicholls, and A.J. Bedard, 1993: Using thermal compression waves to assess latent heating from clouds. EOS, 74, 493.

Nicholls, M.E. and R.A. Pielke Sr., 2000: Thermally-induced compression waves and gravity waves generated by convective storms. J. Atmos. Sci., 57, 3251-3271

where

we show the diagnostic value of using sound wave information to assess meteorological dynamics. We have shown that this approach works for thunderstorms including tornadoes, and would be a very effective monitoring approach to add to the arsenal of hurricane intensity change monitoring by agencies such as the USA National Severe Storms Forecast Center and the National Hurricane Center.

The climate issue, with respect to how humans are influencing the climate system, can be segmented into three distinct hypotheses. These are:

• The human influence is minimal and natural variations dominate climate variations on all time scale;
• While natural variations are important, the human influence is significant and involves a diverse range of first-order climate forcings (including, but not limited to the human input of CO₂);
• The human influence is dominated by the emissions into the atmosphere of greenhouse gases, particularly carbon dioxide.

The third hypothesis, of course, is the IPCC perspective.

The challenge to the scientific community, using the scientific method, is to present observational evidence that refutes one or more of these hypotheses.

Climate Science’s perspective is that the second hypotheses is correct, which has support from the

National Research Council, 2005: Radiative forcing of climate change: Expanding the concept and addressing uncertainties. Committee on Radiative Forcing Effects on Climate Change, Climate Research Committee, Board on Atmospheric Sciences and Climate, Division on Earth and Life Studies, The National Academies Press, Washington, D.C., 208 pp.

A new Nature paper by Keenlyside et al. entitled “Advancing decadal-scale climate prediction in the North Atlantic sector” provides evidence that is inconsistent with the third hypothesis. This paper writes in the abstract

“The climate of the North Atlantic region exhibits fluctuations on decadal timescales that have large societal consequences. Prominent examples include hurricane activity in the Atlantic, and surface-temperature and rainfall variations over North America, Europe and northern Africa……Our results suggest that global surface temperature may not increase over the next decade, as natural climate variations in the North Atlantic and tropical Pacific temporarily offset the projected anthropogenic warming.”

There are several important messages from this paper:

• While this Nature paper claims that this lack of global warming is temporary due to “natural climate variations“, unless the first hypothesis is true, there are NO climate variations that are not affected by humans (i.e., the term “natural climate variations” is therefore a misnomer).  
• This new paper supports the perspective that climate variations and change (even the global average radiative imbalance) are dominated by regional alterations in circulations [as summarized in the 2005 National Research Council Report, and emphasized on Climate Science and associated papers (e.g. see) including the very important guest weblog on Climate Science by Roy Spencer (see) on this subject].
• Since the multi-decadal global climate model predictions used for the 2007 IPCC report are failing to skillfully predict these “fluctuations on decadal time scales”, there is no credible reason to accept the claim in the Nature paper that the “projected anthropogenic warming” will be accurately predicted after the next decade.

There is a remarkable quote on the Nature.com blog website . On that website it is written

“The NY Times wraps up its main piece [by Andy Revkin] with a useful quote from Kevin Trenberth, of the US National Center for Atmospheric Research: ‘Too many think global warming means monotonic relentless warming everywhere year after year. It does not happen that way.’”

This is an amazing error.  Global warming does require a more-or-less monotonic increase in warming (in the absence of a  major volcanic eruption) as illustrated in all available multi-decadal global model runs (e.g. see the Figure in this post on Climate Science ; and see Figure 1 in Barnett et al, 2001). This essentially monotonic report is even emphasized in the 2007 IPCC Summary for Policymakers (see Figure SPM.4)!

Climate Science published a proposed test of the multi-decadal global model predictions (see A Litmus Test For Global Warming - A Much Overdue Requirement).  Clearly, so far, the models are failing to skillfully predict the rate (and even the sign for the most recent years) of global warming. Andy Revkin should follow up his article to document what the models predict in terms of global warming (in Joules) over different time periods, and what do the observations actually show. This would be excellent investigative (much needed) journalism.

In our papers

Pielke Sr., R.A., C. Davey, and J. Morgan, 2004: Assessing “global warming” with surface heat content. Eos, 85, No. 21, 210-211

and 

Davey, C.A., R.A. Pielke Sr., and K.P. Gallo, 2006: Differences between near-surface equivalent temperature and temperature trends for the eastern United States - Equivalent temperature as an alternative measure of heat content. Global and Planetary Change, 54, 19–32

we urged the adoption of a more complete measure of heat content trends in the near-surface atmosphere (i.e. moist enthalpy).

 Thanks to Souleymane Fall of Purdue for alerting us to a new paper which has built on this idea with important new insight into this climate metric.

The paper is

Rogers, J.C., S.H. Wang, and J.S.M. Coleman, 2007: Evaluation of a Long-Term (1882–2005) Equivalent Temperature Time Series. J. Climate, 20, 4476–4485.

The abstract reads

“A 124 (1882-2005) summer record of total surface energy content consisting of time series of surface equivalent temperature (T_E) and its components T (mean air temperature) and Lq/c_p(moist enthalpy, denoted Lq) is developed, quality controlled, and analyzed for Columbus, Ohio, where long records of monthly dewpoint temperature are available. The analysis shows that the highest T_Eoccurs during the summer of 1995 when both T and Lq were very high, associated with a severe midwestern heat wave. That year contrasts with the hot summers of 1930-36, when Lq and T_Ehad relatively low or negative anomalies (low humidity) compared to those of T. Following the 1930-36 summers, T and Lq departures are much more typically the same sign in individual summers, and the two parameters develop a statistically significant high positive correlation into the twenty-first century. Mean T and Lq departures from the long-term normal have opposite signs, however, when summers are stratified either by seasonal total rainfall amounts or by the Palmer drought severity soil moisture index. Normalized trends of T, Lq, and T_E are downward from 1940 to 1964 with those of T_E exceeding T. Since 1965, however, significant positive T trends slightly exceed T_Ein magnitude and those of dewpoint temperature and Lq are comparatively lower. A highly significant upward trend in minimum temperatures especially dominates the T variability, creating a significant downward trend in the temperature range that dominates recent summer climate variability more than moisture trends. Regional moisture flux variations are largest away from Columbus, over the upper Midwest and western Atlantic Ocean, during its seasonal extremes in total surface energy.”

In the assessment of global warming (and global cooling), this research further shows that unless the role of near surface vapor trends are included, a quantitatively erroneous assessment will necessarily result. Thus, when a media report or scientific paper claims that a certain increase (or decrease) in temperatures have occurred over a period of years, this cannot by itself, be used to say this is warming or cooling (in terms of heat), unless the changes in water vapor concentrations are simultaneously assessed so that moist enthalpy changes are computed.