Category Archives: Climate Change Forcings & Feedbacks

Two New Articles On The Role Of Land Manangement On The Climate System: Hossain Et Al 2009a,b

We have two new papers that document a role of land management (in this case the effect of reservoirs and changes in landscape around a large dam) on extreme rainfall.

The papers are:

 Hossain, F., I. Jeyachandran, and R.A. Pielke Sr., 2009: Have large dams altered extreme precipitation patterns during the last Century? Eos, Vol. 90, No. 48, 453-454. Copyright (2009) American Geophysical Union.

Hossain, F., I. Jeyachandran, and R.A. Pielke Sr., 2009: Dam safety effects due to human alteration of extreme precipitation. Water Resources Research, doi:10.1029/2009WR007704, in press.

The conclusion of the second paper reads

“Today, we know little about the impact of dams and reservoirs on the alteration in precipitation patterns as we step into the 21st century. Dam design protocol in civil engineering continues to assume as ‘static’ the statistical parameters of a low exceedance probability precipitation event during the life-span of the dam. Our study seems to indicate that the impact of large dams on extreme precipitation is clearly a function of surrounding meso-scale and land-use conditions (e.g., see Pielke et al., 2007; Douglas et al 2009), and that more research is necessary to gain insights on the physical mechanisms of extreme precipitation alteration by dams. The changes in land-use, for example from added irrigation, add a significant amount of water vapor into the atmosphere in the growing season, thereby fueling showers and thunderstorms (e.g. see Pielke and Zeng, 1989; Pielke et al 1997; Pielke 2001). Such landscape changes can even alter large scale precipitation patterns such as the Asian monsoon (e.g. see Takata et al, 2009).

Although, the focus of our paper is primarily on how dams may alter extreme precipitation patterns and consequentially the flood frequency relationship, we should also recognize that there are other direct ways that the discharge into a reservoir may increase in frequency and magnitude (such as urbanization and other changes in land cover). Whatever the possible causes might be, it is timely for the civil engineering profession to change perceptions and embrace an interactive hydrology/atmospheric science approach to safe dam design and operations for the 21st century.

There has been news coverage of our articles, including,2933,579087,00.html

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Comment On The Inaccurate Response By Gavin Schmidt Of Real Climate On The Role of Land Use Change On Temperature Trends

UPDATE: December 1 2009

Gavin Schmidt  responded to this post with the following [thanks to Bob Thompson for alerting us to this!]

From Real Climate

990 whatAboutBob says:> 30 November 2009 at 8:21 AM


Your response in comment #289 is incorrect (at best uninformed) please see


Gavin’ response

[ Response: Not sure what you are pointing to specifically, but I stand = by that statement. The relevant IPCC summary (Chp 2. p185) is as follows:

Since the dominant aspect of land cover change since 1750 has been deforestation in temperate regions, the overall effect of anthropogenic land cover change on global temperature will depend largely on the relative
importance of increased surface albedo in winter and spring (exerting a cooling) and reduced evaporation in summer and in the tropics (exerting a warming) (Bounoua et al., 2002). Estimates of global temperature =
responses from past deforestation vary from 0.01=B0C (Zhao et al., 2001) to = =960.25=B0C
(Govindasamy et al., 2001a; Brovkin et al., 2006). If cooling by = increased surface albedo dominates, then the historical effect of land cover = change may still be adequately represented by RF. With tropical deforestation becoming more significant in recent decades, warming due to reduced evaporation may become more significant globally than increased surface albedo. Radiative forcing would then be less useful as a metric of climate change induced by land cover change recently and in the future.

and (p184)

On the basis of the studies assessed here, including a number of new estimates since the TAR, the assessment is that the best estimate of RF relative to 1750 due to land-use related surface albedo change should =
remain at =960.2 =B1 0.2 W m=962.

Thus while there are complexities and uncertainties involved, the best estimate is that LCC has been a cooling effect historically. I still don’tknow where the US statistic that was quoted in #289 comes from. – gavin]

My Reply

Gavin is using old information. New research has shown a significant warming effect for a number of landscape conversions; e.g. see

 Fall, S., D. Niyogi, A. Gluhovsky, R. A. Pielke Sr., E. Kalnay, and G. Rochon, 2009: Impacts of land use land cover on temperature trends over the continental United States: Assessment using the North American Regional Reanalysis. Int. J. Climatol., DOI: 10.1002/joc.1996.

from the abstract

“….most of the warmingtrends that we identify can be explained on the basis of LULC changes, we suggest that in addition to considering the greenhouse gases–driven radiative forcings, multi-decadal and longer climate models simulations must further include LULC changes.”


New Idea offered to fight climate change  from Georgia Tech which has 6 links (under the author’s name) in google news where the press release has the text

“Across the (United States) as a whole, approximately 50 percent of the warming that has occurred since 1950 is due to land use changes (usually in the form of clearing forest for crops or cities) rather than to the emission of greenhouse gases,” Stone said. “Most large U.S. cities … are warming at more than twice the rate of the planet as a whole — a rate that is mostly attributable to land use change.”

******END OF UPDATE****

There is a response by Gavin Schmidt on Real Climate with respect to the role of land use change on the attribution of surface air temperature trends [thanks to Charlie Allen for alerting us to it!]. While Gavin has expertise in global climate modeling, his reply illustrates his lack of expertise on the role of landscape processes within the climate system, and, in this example, with respect to the role of land use/land cover change on long temperature trends.

The text from Real Climate is

  1. 1.       CCPO @258 – you quoted Gavin as saying “Note. global land use effects result in a cooling because the biggest issue is the chopping down of forest (dark) to make cropland (bright)”

Well, that’s not actually true. Here’s a press release for a new paper from Georgia Tech, showing how 50% of the warming across the US is due to land use changes.

Original reference for Gavin’s comment was from Edward’s post @95.


[Response: A statement in a press release is not a scientific result and the paper referred to does not show this to be true (and in fact I doubt very much that it is true). There are many papers on the global impacts of land cover change – Pondgratz et al is good, and all such papers show that land use at the global scale drives a cooling. – gavin]

The person who prepared the comment (CCPO CORRECTED Dec 1 2009 – Thanks to Michael Lenaghan who let me know the correct person to credit was Ted) clearly better understands the science issue  better than Gavin Schmidt. 

 I have already documented his lack of expertise in research topics that he comments on at Real Climate and elsewhere in my post

Does Gavin Schmidt Understand Boundary Layer Physics?

A Recent paper of ours which document an increase in surface temperatures due to landscape change include

Fall, S., D. Niyogi, A. Gluhovsky, R. A. Pielke Sr., E. Kalnay, and G. Rochon, 2009: Impacts of land use land cover on temperature trends over the continental United States: Assessment using the North American Regional Reanalysis. Int. J. Climatol., DOI: 10.1002/joc.1996

With respect to the study by Stone Jr, Gavin apparently did not even read it before he commented!

 In the paper

Stone Jr., Brian, 2009: Land Use As Climate Change Mitigation,  Environmental Science and Technology (in press).

 it is written [emphasis added in bold face font]

“….the mean decadal rate of warming across the urban stations is significantly higher than that of rural stations. Averaged over the full period, the mean decadal rate of warming for urban stations was found to be 0.08 °C higher than that of rural stations. This average rate of heat island growths i.e., urban warming in excess of the rural trends rises to 0.20 °C/decade over the most recent 20 years of observation.”


“The increasing divergence between rural and urban temperature trends in U.S. cities highlights the limitationsof a climate policy framework focused on emissions reductions alone. If land use change is the dominant agent of climate forcing at the urban scale, Kyoto-based emissions trading schemes may fail to sufficiently safeguard human health in the most heavily populated regions of the planet. It is important to emphasize, however, that the phrase “urban heat island effect,”muchlike the phrase “greenhouse effect,” is a misnomer…The physical mechanisms underlying warming trends in cities are limited neither to urban areas nor to small geographic regions. Rather, changes in surface moisture and energy balances accompanying land conversion processes across large swaths of the planet’s land area are giving rise to changes in climate that may be of the same order of magnitude as changes brought about through the emission of GHGs. As such, the urban heat island effect should be understood to be only the most visible manifestation of a larger phenomenon occurring across multiple geographic scaless a phenomenon better characterized as a “green loss effect” than as something unique to urban areas.”

This reply by Gavin, besides ignoring (e.g. Fall et al 2009) and his trivializing (e.g. Stone Jr 2009)  peer reviewed papers that disagree with his perspective,  his comment also shows that he has learned little from the exposure of the inappropriate attempt by Phil Jones and colleagues to serve as gatekeepers to climate science issues.

Since Gavin Schmidt is not a recognized expert on the role of land use/land cover change, he should have sought a qualified climate scientist to address the comment by CCPO. Instead, he perpetuates the biased and often inaccurate presentation of climate views on Real Climate.

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New Paper “Global Urban Land-Use Trends And Climate Impacts” By Seto and Marshall 2009

Seto, Karen C and J Marshall Shepherd, 2009: Global urban land-use trends and climate impacts. Current Opinion in Environmental Sustainability 2009, 1:89–95 DOI 10.1016/j.cosust.2009.07.012.

The abstract reads

“In 2008, the global urban population exceeded the nonrural population for the first time in history, and it is estimated that by 2050, 70% of the world population will live in urban areas, with more than half of them concentrated in Asia. Although there are projections of future urban population growth, there is significantly less information about how these changes in demographics correspond with changes in urban extent. Urban land-use and land-cover changes have considerable impacts on climate. It has been well established that the urban heat island effect is more significant during the night than day and that it is affected by the shape, size, and geometry of buildings as well as the differences in urban and rural gradients. Recent research points to mounting evidence that urbanization also affects cycling of water, carbon, aerosols, and nitrogen in the climate system. This review highlights advances in the understanding of urban land-use trends and associated climate impacts, concentrating on peer-reviewed papers that have been published over the last two years.”

The conclusion includes the text

“Clearly, the footprint of urban land-use is apparent in Earth’s climate system and must be accounted for in emerging climate modeling systems…. Huge uncertainties remain about the rate and magnitude of urban expansion: which ecosystems are most at risk to urban development, what are the emerging patterns of urban land-use, and how will extensive and expansive urban land-use change drive affect regional and global climate? As area estimates and mapping of global urban land-use improve and converge with ever-increasing spatial resolution of climate models (i.e. as grid cells cover smaller surface areas), the aforementioned urban forcing on atmospheric thermodynamics, dynamics, energy balance, microphysics, and composition must be explicitly represented. Only then will the climate science community make the necessary progress to understand the integrated effects of urban land-use, urban land-use change, and associated aerosol processes on climate.”

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“Are The Operational Weather Models Creating Too Much Moisture In The Upper Troposphere? If So, Does This Suggest Too High Moisture Feedback To The Climate Change Models?” By William Nichols

Guest Weblog:

Bill Nichols is a 35 year Atmospheric Physicist, spending over 7 years in the Climate Change arena.  Working projects ranging from Nuclear Winter to Global Warming for future weapon systems (e.g. B-2, F-117A) in the USAF starting in 1987 before retiring from the military in August 1994.   Since September 1994, he’s been employed by NOAA NWS, first as a Science and Operations Officer (SOO), and currently as a Senior Forecaster.   He can be contacted at

“Are The Operational Weather Models Creating Too Much Moisture In The Upper Troposphere?  If So, Does This Suggest Too High Moisture Feedback To The Climate Change Models?”

Over the past several years, there has been considerable discussion about the amount of radiative feedback related to changes in moisture due to increasing greenhouse gases, most notably CO2.    One important research question is if the magnitude used by the Intergovernmental Panel on Climate Change (IPCC) of a significant positive forcing is accurate.  A central issue is the climate models distribution of moisture at higher levels, suggesting a higher positive radiative feedback, versus the lower levels where less positive feedback is suggested, such as discussed in Tropical Water Vapor and Cloud Feedbacks in Climate Models: A Further Assessment Using Coupled Simulations by De-Zheng Sun,  Yongqiang Yu, and Tao Zhang in Journal of Climate,  Volume 22, Issue 5 (March 2009) pp. 1287–1304. 

 A figure of this suggested warming, roughly centered near 300 mb by the models in the upper levels of the troposphere can be found at the IPCC.    Operational Weather Models and Climate Models share very similar moisture and physics packages, so if a discrepancy is noticed in the operational weather models, closer investigation to answering this question in climate models is valid.

In operational weather forecasting, meteorologists have the capability of comparing upper air observational data to various model solutions.  This is a critical first step, as ensuring the models are accurately portraying the real atmosphere must be assessed in the forecast process.   This is called model initialization, where the models start from.  The next step in the forecast process is verifying the model output in real time at a future time period to again observational data.   Since these two steps determine when and if a model can be used in forecasting, we have several tools to accomplish this task.

The two figures below compare observations and model temperature dewpoint depression at 300 mb, or roughly near 40,000 feet.  The first figure (Fig 1) is for the Western Pacific with a graphic image of the Hi-Res ECMWF verifying at 12 hours.  The second image (Fig 2) is the initialization at zero hours of the 90 km GFS with North American observations.  Both graphic images are customized to show areas where the model dewpoint depression is less than or equal to 5 degrees celsius in purple.  The moderate purple frost is for dewpoint depression values of 2 to 4 with values less than 1 a near white frost, which is over 50 percent purple coverage in both images. Rawinsonde observations (Raobs) are plotted as filled circles whenever the dewpoint depression  values are less than or equal to 5 degrees Celsius.   Note the discrepancies below of a significant number of sites showing open circles in purple areas with actual dewpoint depression value (lower left) often in double digits.  Almost none of the reporting sites have a dewpoint depression value of 1 or less.

Personal observations, now for over a year, in the forecast process has noted this discrepancy in all seasons in the Northern Hemisphere, and for all model solutions with the two figures below representative both at model initialization and verification.  The images are reasonable examples of what occurs with each forecast and raob cycle.

nichols-fig-1Figure 1: Comparison of 12 hour forecast of the Hi-Res ECMWF with actual Western Pacific Observations.    

nichols-fig-2Figure 2:  Comparison of 90 KM GFS initialization with North American Observations.

In the tables below, a mean comparison was done for dewpoint depression in the above images (Fig 1 & 2).  Note the several degree Celsius model too moist bias for both moist and dry environments (fourth column higher value to the third column).    The numbers of data points are large enough to suggest this may be statistically significant.  In addition, it encapsulates numerous countries, different parts of the world and multiple model.

Comparison Dewpoint Departure – North America – 300MB – 90KM GFS versus RAOBS

GFS Dewpoint Depression Number Observations Mean GFS Value (Co) Mean Raob Value (Co) Number Obs Drier Than GFS
LTE 5C 50 2.4 9.9 50/50
GT 5C 21 9.0 21.1 21/21

Comparison Dewpoint Departure – Western Pacific – Hi-Res ECMWF (EMF) versus RAOBS

 Dewpoint Depression Number Observations Mean EMF Value (Co) Mean Raob Value (Co) Number Obs Drier Than EMF
LTE 5C 22 3.0 7.1 19/22
GT 5C 18 11.6 18.7 14/18

Another method of displaying this discrepancy is through a vertical slice in the atmosphere by the Skew-T Log P diagram (Fig 3). Note the actual dew point values (far left set) of the observations are drier than all 3 model solutions at the 12 hour forecast point above 400 mb.

nichols-fig-3Figure 3:  Typical Skew-T from DVN of RAOB Temperature and Dewpoint (Solid Yellow) and Various Models (Dashed) of 80km NAM (Green), 90 km GFS (Rust), and ECMWF-Hi-Resolution (Blue).

The 3 images above all illustrate a model moist tendency both at model initialization and verification in a future time period.

Therefore, an explanation of this discrepancy of model output to observational data is warranted since these models have similar physics with Climate Change Models.  With this apparent discrepancy, and the importance of how vertical moisture distribution impacts radiative forcing with increased greenhouse gases, it is proposed this should be looked into.

It is believed further investigation is needed to answer the following:

1.)    Is this apparent moist bias legitimate?

2.)    If this bias is real, what tests should be done to gain further insight on the impacts and reliability of current climate change models?

3.)    If this does impact climate change models, how can this be effectively communicated to key decision makers toward Climate Change mitigation decisions?

One specific suggestion toward determining if this discrepancy is valid pertains towards question 2.   Rerun the models with the more accurate, drier observational data.  Then compare and assess the magnitude of any changes in the output of both temperature and moisture, this could provide insight to our understanding of the energy and hydrologic budget (conservation of energy) in the models. 

Note:  This post does not necessarily reflect in any way, or is associated with, the position of NOAA on Climate Change.

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Comments On Roy Spencer’s Excellent Post “IPCC Crushes Scientific Objectivity, 91-0”

Roy Spencer published an excellent post on October 18 2009 titled “IPCC Crushes Scientific Objectivity, 91-0”.

He post includes the statements

“The most glaring example of this bias [that of the IPCC] has been the lack of interest on the IPCC’s part in figuring out to what extent climate change is simply the result of natural, internal cycles in the climate system…….”

“The IPCC is totally obsessed with external forcing, that is, energy imbalances imposed upon the climate system that are NOT the result of the natural, internal workings of the system…”

“Admittedly, we really do not understand internal sources of climate change. Weather AND climate involves chaotic processes, most of which we may never understand, let alone predict. While chaos in weather is exhibited on time scales of days to weeks, chaotic changes in the ocean circulation could have time scales as long as hundreds of years, and we know that cloud formation – providing the Earth’s natural sun shade – is strongly influenced by the ocean….”

“Thus, small changes in ocean circulation can lead to small changes in the Earth’s albedo (how much sunlight is reflected back to space), which in turn can lead to global warming or cooling. The IPCC’s view (which is never explicitly stated) that such changes in the climate system do not occur is little more than faith on their part….”

The identification by Roy of a much more significant role for internal climate variability in altering even the global average radiative heating over multi-year and longer time scales is a major research finding. This hypothesis was not tested by the IPCC. Of course, none of the IPCC models can skillfully predict, even in retrospect, the multi-year variations that Roy has identified. Thus the IPCC simply chose to essentially ignore this issue.

We presented this perspective of the climate system as a chaotic system in our papers; e.g. see

Pielke, R.A., 1998: Climate prediction as an initial value problem. Bull. Amer. Meteor. Soc., 79, 2743-2746

Rial, J., R.A. Pielke Sr., M. Beniston, M. Claussen, J. Canadell, P. Cox, H. Held, N. de Noblet-Ducoudre, R. Prinn, J. Reynolds, and J.D. Salas, 2004: Nonlinearities, feedbacks and critical thresholds within the Earth’s climate system. Climatic Change, 65, 11-38,

but these also were ignored by the IPCC.

We look forward to Roy’s  seminal publication of  “On the Diagnosis of Radiative Feedback in the Presence of Unknown Radiative Forcing”.  Of course, it needs to first hurdle the inappropriate role of some reviewers and even editors as gatekeepers of the IPCC dogma.

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E-Mail Communication Between Josh Willis and Roger A. Pielke Sr. on the Murphy et al. 2009 Paper

The Journal of Geophysical Research has published the paper

Murphy, D. M., S. Solomon, R. W., Portmann, K. H. Rosenlof, P. M. Forster, and T. Wong (2009), An observationally based energy balance for the Earth since 1950, J. Geophys. Res., 114, D17107, doi:10.1029/2009JD012105.

Their abstract reads

“We examine the Earth’s energy balance since 1950, identifying results that can be obtained without using global climate models. Important terms that can be constrained using only measurements and radiative transfer models are ocean heat content, radiative forcing by long-lived trace gases, and radiative forcing from volcanic eruptions. We explicitly consider the emission of energy by a warming Earth by using correlations between surface temperature and satellite radiant flux data and show that this term is already quite significant. About 20% of the integrated positive forcing by greenhouse gases and solar radiation since 1950 has been radiated to space. Only about 10% of the positive forcing (about 1/3 of the net forcing) has gone into heating the Earth, almost all into the oceans. About 20% of the positive forcing has been balanced by volcanic aerosols, and the remaining 50% is mainly attributable to tropospheric aerosols. After accounting for the measured terms, the residual forcing between 1970 and 2000 due to direct and indirect forcing by aerosols as well as semidirect forcing from greenhouse gases and any unknown mechanism can be estimated as 1.1 ± 0.4 W m2 (1s). This is consistent with the Intergovernmental Panel on Climate Change’s best estimates but rules out very large negative forcings from aerosol indirect effects. Further, the data imply an increase from the 1950s to the 1980s followed by constant or slightly declining aerosol forcing into the 1990s, consistent with estimates of trends in global sulfate emissions. An apparent increase in residual forcing in the late 1990s is discussed.”

On the topic of this paper, I recommend Bob Tisdale’s excellent weblog on an update on the Levitus et al ocean heat data. In terms of missing forcings and feedbacks in the Murphy et al paper, I recommend readers read Roy Spencer’s informative discussion of this issue at his weblog.

On the Murphy et al article, I e-mailed to Josh Wills and asked him a set of questions as well as made comments. These are written below with my text in bold face and his in italics. In the first e-mail we wrote to each other

 Hi Josh

 What is your view on this new analysis? Have you been able to update your assessment? I plan to post on this next week, but would value your feedback and comments first.

 Best Regards


Hi Roger,

Well, at first I was pretty skeptical about those results because the cooling in the Atlantic brings back bad memories of Argo floats that were biased cold there.  In addition, I think we have to be very careful about any results that span the transition from the XBT network to Argo because I know that there are still systematic errors in the XBT dataset. Although we have all made attempts to reduce these errors, I don’t think anyone can claim to have eliminated all of them.  So, we need to be cautious here.

That said, I also see a sort of transition in the North Atlantic from a period of rapid warming from the mid-1990s through about 2004, followed by a slight cooling during 2005 and 2006 and it has pretty much been level since then. This seems to agree well with the average over the altimeter data for the North Atlantic.  So, perhaps the recent cooling of the North Atlantic is real.



The following set of e-mails are extracted and rewritten below:

1. The assumption that

“For the purposes of this paper we estimate that from 1950 to 2003 the increase in the heat content of the ocean deeper than 700 m was 40 +/- 15% of the increase from 0 to 700 m”

is rather cavalier, and this arbitrariness is compounded by their claim that

“For a given year, the deep ocean heat content is scaled to the heat content above 700 m averaged over the preceding 10 years.”

If the deeper ocean is actually such a large store of heat, this presumably is a sink that is not readily (or quickly) available to the atmospheric part of the climate system including the surface land temperatures.

Well there are regions such as the North Atlantic where convection occurs to depths of 2000 m or so most every year.  Over longer time scales, these waters are advected away and become detached from the atmospheric connection, but I think that using the 10 year average rate of warming in the surface waters and scaling it down is a very reasonable assumption in lieu of actual data there.

Well, the rate of deep heating is really not known, and some assumption must be made.  The long term trends in the deep ocean from Levitus suggest that the 700 m to 3000 m heat content is a small fraction of the 0 to 700 m rate.  So I think this is not unreasonable.

2. They also claim that their data is corrected adequately

“There are several recent calculations of observed ocean heat contents from the surface to 700 m depth [Domingues et al., 2008; Ishii and Kimoto, 2009; Levitus et al., 2009]. In each study, temperature profiles were converted to estimates of the ocean heat content. Each study also corrects expendable bathy-thermograph (XBT) measurements using fall rate or empirical corrections. These corrections make the heat content estimates more accurate than previous estimates using similar data [Wijffels et al., 2008].”

This claim ignores your concerns on the remaining uncertainties in the data.

They also ignore the puzzling sudden jump in the Levitus et al data just prior to 2003, which, to my knowledge is not supported by other data analyses. It certainly cannot be due to one of the longer term climate forcings, even if it were true.

Well, I think that their comment is correct.  These estimates ARE more accurate than previous estimates because they at least attempt to address the known errors.  I think there is more work to do and that the biases in XBT data can be further reduced, but for the time being, those are the best estimates.  I have seen plots overlaying all of the recent estimates and although the Levitus et al jump in 2003 seems a bit large to me, it is not WAY outside the scatter of all the estimates of recent ocean heat content change.

 3. Their acceptance of the surface temperature trend as quantitatively  robust is flawed, where they write

 “First, we use lamda to predict net outgoing radiation from observed temperature changes and ordinary regression against temperature matches this use”

 This ignores the major unresolved issues that we have found with this surface temperature metric: e.g.,

 Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2009: An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J. Geophys. Res., in press. [the final published version will have a few additional edits with respect to the conclusion we have in this version on the Lin et al. paper]


 Pielke Sr., R.A., C. Davey, D. Niyogi, S. Fall, J. Steinweg-Woods, K. Hubbard, X. Lin, M. Cai, Y.-K. Lim, H. Li, J. Nielsen-Gammon, K. Gallo, R. Hale, R. Mahmood, S. Foster, R.T. McNider, and P. Blanken, 2007: Unresolved issues with the assessment of multi-decadal global land surface temperature trends. J. Geophys. Res., 112, D24S08, doi:10.1029/2006JD008229.


 There clearly is a warm bias in the surface temperature data as we have shown in Klotzbach et al.

 4. Rather than cite and discuss peer-reviewed papers that conflict with their paper; e.g., see their text

 “Questions have been raised in the popular media about the reduced rate of warming since 1998 (e.g., http://;


 cnn-is-spun-right-round-baby-right-round/langswitch_lang/ in#more-640)”

 they use the popular media to make their point.

 The available peer reviewed papers includes most recently

 Douglass, D.H. and R. Knox, 2009: Ocean heat content and Earth’s radiation imbalance. Physics letters A.

 5. Their Figure 6 looks like an example of knowing the answer (e.g. the ocean heat storage change) and then making the different forcings to fit. Their units are not even correct; 10** 21 Joules on their axes is not a forcing but what they claim to be the accumulation of heat over time. An appropriate figure for them to show would be the forcing of each term as the global average watts per meter squared. Converting Figure 6 to this units would be informative.

6.  There is another problem with their Figure 6. In the right hand figure, they mix what they label as forcings with feedbacks. The outgoing radiation is a feedback.

I am not really familiar enough with the surface temperature data or the attribution of various forcings to feel comfortable commenting on your blog. However, I think their use of the ocean heat content data was reasonable.  I also think that it makes sense to look at things in terms of their time-integrated values in order to make comparisons with ocean heat content. This is the part of the reason that ocean heat content estimates are so valuable–because the ocean accumulates the net radiative imbalance over time.

As always, you are more than welcome to use my emailed comments on your blog.

I want to thank Josh for engaging in a constructive discussion even though we disagree on the merits of the Murphy et al paper. As another issue with the Murphy et al. paper that I did not present in my e-mails, note that Figure 6 has exponentially increasing positive and negative radiative forcings.  This behavoir conflicts for what we know about the radiative forcings of CO2 and other well-mixed greenhouse gas forcings. In the real world, they are logarithmic with increasing atmospheric concentration (due to the approach to saturation of the absorption lines in the long wave radiative spectrum) . They actually behave as Murphy et al. presented in Figure 1. Apparently, the authors ignored this in order to create Figure 6.

With respect to Figure 6, as was shown in

Ellis et al. 1978: The annual variation in the global heat balance of the Earth. J. Climate. 83, 1958-1962

Pielke Sr., R.A., 2003: Heat storage within the Earth system. Bull. Amer. Meteor. Soc., 84, 331-335


Pielke Sr., R.A., 2008: A broader view of the role of humans in the climate system. Physics Today, 61, Vol. 11, 54-55

it is the heat storage change that is really global warming. Their plot of the ocean heating concludes that there was a change of heat of 200 * 10**21 Joules over a period of  54 years. This corresponds to 0.37 x 10**22 Joules per year which yields a radiative imbalance (i.e. global warming rate averaged over the 54 years) of 0.23 Watts per meter squared.  The authors also (conveniently) end their analysis in 2004. Since 2003, as presented in the figure in my Physics Today article from the data analysis provided by Josh Willis, the  global warming rate (their ocean heating term) up to at least the end of 2008 was essentially zero.

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Recent Paper “Influence Of Cloud Condensation And Giant Cloud Condensation Nuclei” By Cheng Et Al 2009

Cheng, W. Y. Y., G. G. Carrió, W. R. Cotton, and S. M. Saleeby (2009), Influence of cloud condensation and giant cloud condensation nuclei on the development of precipitating trade wind cumuli in a large eddy simulation, J. Geophys. Res., 114, D08201, doi:10.1029/2008JD011011.

“To investigate the effects of both cloud condensational nuclei (CCN) and giant CCN (GCCN), the Regional Atmospheric Modeling System was used to investigate the effects of various CCN and GCCN concentrations on the development of precipitating trade wind cumuli in a large eddy simulation (LES) framework. The sounding to initialize the LES was taken from the Rain in Cumulus over the Ocean Experiment archive for 11 January 2005. Several sensitivity experiments were performed in which two levels of CCN (GCCN) concentrations were used: 100 (0.01) and 1000 (0.1) per [centimeter cubed] corresponding to low and high values, respectively. Both CCN and GCCN can affect the precipitation processes. With low GCCN concentration, raising the CCN concentration from low to high reduced the precipitation rate as well as the accumulated precipitation due to the presence of a large number of small cloud droplets that are inefficient in forming drizzle. However, GCCN can have a greater response in increasing the precipitation rate and accumulation when the cloud system has a high CCN concentration. The total cloud coverage (TCC) was reduced for the higher CCN concentration experiments because of the susceptibility of evaporation of cloud droplets in the upper parts of the cloud as a result of entrainment. On the other hand, the TCC was increased for the higher GCCN concentration experiments. For this trade wind cumuli case, the time‐ and domain‐averaged albedo changed very slightly with increased [CCN] and/or [GCCN] because of a compensating increase/decrease among the optical depth, liquid water path, cloud coverage, and cloud droplet concentration.”

The conclusions include the text

“Entrainment played a role in affecting the cloud properties and dynamics contrary to Albrecht’s second indirect effect in this case as a result of the different cloud droplet concentrations. The results further illustrate the nonlinear response of clouds to perturbations in aerosol concentrations and that changes in cloud dynamics are just as important as changes in cloud microphysics when examining the radiative responses of clouds to air pollution aerosols.”

This paper provides new insight into one of the complex roles of clouds within the climate system as affected by aerosols.  The indirect effect of aerosols was highlighted as a still very incompletely understood major climate forcing in NRC (2005); see page 40.

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New Paper “Impacts Of Land Use Land Cover Change On Climate And Future Research Priorities” By Mahmood Et Al 2009

We have a new multi-authored paper that has been accepted.  This paper illustrates the breadth and diversity of scientists who have concluded that land use/land cover change is a first order climate forcing.

The paper is

Mahmood, R., R.A. Pielke Sr., K.G. Hubbard, D. Niyogi, G. Bonan, P. Lawrence, B. Baker, R. McNider, C. McAlpine, A. Etter, S. Gameda, B. Qian, A. Carleton, A. Beltran-Przekurat, T. Chase, A.I. Quintanar, J.O. Adegoke, S. Vezhapparambu, G. Conner, S. Asefi, E. Sertel, D.R. Legates, Y. Wu, R. Hale, O.W. Frauenfeld, A. Watts, M. Shepherd, C. Mitra, V.G. Anantharaj, S. Fall,R. Lund, A. Nordfelt, P. Blanken, J. Du, H.-I. Chang, R. Leeper, U.S. Nair, S. Dobler, R. Deo, and J. Syktus, 2009: Impacts of land use land cover change on climate and future research priorities. Bull. Amer. Meteor. Soc., accepted.

The paper starts with the text

“Human activities have modified the environment for thousands of years. Significant population increase, migration, and accelerated socio-economic activities have intensified these environmental changes over the last several centuries. The climate impacts of these changes have been found in local, regional, and global trends in modern atmospheric temperature records and other relevant climatic indicators.”

In our conclusions, we write

“It is the regional responses, not a global average, that produce drought, floods and other societally important climate impacts.”

as well as make the following recommendations

“we recommend, as a start, to assess three new climate metrics:

1. The magnitude of the spatial redistribution of land surface latent and sensible heating (e.g., see Chase et al. 2000; Pielke et al. 2002). The change in these fluxes into the atmosphere will result in the alteration of a wide variety of climate variables including the locations of major weather features. For example, Takata et al. (2009) demonstrated the major effect of land use change during the period 1700-1850 on the Asian monsoon. As land cover change accelerated after 1850 and continues into the future, LULCC promises to continue to alter the surface pattern of sensible and latent heat input to the atmosphere.

2. The magnitude of the spatial redistribution of precipitation and moisture convergence (e.g., Pielke and Chase 2003). In response to LULCC, the boundaries of regions of wet and dry climates can change, thereby affecting the likelihood for floods and drought. This redistribution can occur not only from the alterations in the patterns of surface sensible and latent heat, but also due to changes in surface albedo and aerodynamic roughness (e.g., see Pitman et al. 2004; Nair et al. 2007).

3. The normalized gradient of regional radiative heating changes. Since it is the horizontal gradient of layer-averaged temperatures that force wind circulations, the alteration in these temperatures from any human climate forcing will necessarily alter these circulations. In the evaluation of the human climate effect from aerosols, for example, Matsui and Pielke (2006) found that, in terms of the gradient of atmospheric radiative heating, the role of human inputs was 60 times greater than the role of the human increase in the well-mixed greenhouse gases. Thus, this aerosol effect has a much more significant role on the climate than is inferred when using global average metrics. We anticipate a similar large effect from LULCC. Feddema et al. (2005), for example, have shown that global averages mask the impacts on regional temperature and precipitation changes. The above climate metrics can be monitored using observed data within model calculations such as completed by Matsui and Pielke (2006) for aerosols, as well as by using reanalyses products, such as performed by Chase et al (2000) with respect to the spatial pattern of lower tropospheric heating and cooling. They should also be calculated as part of future IPCC and other climate assessment multi-decadal climate model simulations.”

We also write

“With respect to surface air temperatures, for example, there needs to be an improved quantification of the biases and uncertainties in multi-decadal temperature trends, which remain inadequately evaluated in assessment reports such as from the Climate Change Science Program (CCSP 2006). We also recommend that independent committees (perhaps sponsored by the National Science Foundation) conduct these assessments.”

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New Paper “Increase In Background Stratospheric Aerosol Observed With Lidar” By Hofmann Et Al 2009

There is a new paper which has appeared that demonstrates that geoengineering, although inadvertent, is already occurring (thanks to Kiminori Itoh for alerting us to it!).

The paper is

Hofmann, D., J. Barnes, M. O’Neill, M. Trudeau, and R. Neely (2009), Increase in background stratospheric aerosol observed with lidar at Mauna Loa Observatory and Boulder, Colorado, Geophys. Res. Lett., 36, L15808, doi:10.1029/2009GL039008.

The abstract reads

“The stratospheric aerosol layer has been monitored with lidars at Mauna Loa Observatory in Hawaii and Boulder in Colorado since 1975 and 2000, respectively. Following the Pinatubo volcanic eruption in June 1991, the global stratosphere has not been perturbed by a major volcanic eruption providing an unprecedented opportunity to study the background aerosol. Since about 2000, an increase of 4–7% per year in the aerosol backscatter in the altitude range 20–30 km has been detected at both Mauna Loa and Boulder. This increase is superimposed on a seasonal cycle with a winter maximum that is modulated by the quasi-biennial oscillation (QBO) in tropical winds. Of the three major causes for a stratospheric aerosol increase: volcanic emissions to the stratosphere, increased tropical upwelling, and an increase in anthropogenic sulfur gas emissions in the troposphere, it appears that a large increase in coal burning since 2002, mainly in China, is the likely source of sulfur dioxide that ultimately ends up as the sulfate aerosol responsible for the increased backscatter from the stratospheric aerosol layer. The results are consistent with 0.6–0.8% of tropospheric sulfur entering the stratosphere.”

Among the conclusions in the paper are

  • “Background stratospheric aerosol conditions have existed since about 1996 (12 years).
  • There is an increasing average trend in aerosol backscatter above 20 km after 2000 of about 4–7% per year (0.015–0.02 TgS per yr).
  • China’s estimates of future coal use without removal of SO2 could result in a doubling of the ‘‘normal’’ 2000 level of background stratospheric aerosol by about 2022, resulting in a small perturbation to tropospheric temperatures and stratospheric ozone with a stratospheric background aerosol level comparable to about 5% of the Pinatubo volcanic aerosol maximum.”

This study further highlights the diverse ways that humans are altering the climate, as was summarized in NRC (2005). Proposals to deliberately geoengineer the climate system could learn from these inadvertent climate modifications. Predicting the consequences of the human alteration of the climate is much more complicated, and has a wider range of consequences, than has been claimed in the existing ideas to influence the global climate heating and cooling.


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New Paper “Impact Of Land Surface Heterogeneity On Mesoscale Atmospheric Dispersion” By Wu Et Al 2009

We have a new paper that has been accepted for publication. It is

Wu., Y., U.S. Nair, R.A. Pielke Sr., R.T. McNider, S.A. Christopher, and V. Anantharaj, 2009: Impact of land surface heterogeneity on mesoscale atmospheric dispersion. Bound.-Layer Meteor., accepted.

The abstract reads

“Prior numerical modelling studies show that atmospheric dispersion is sensitive to surface heterogeneities. However, past studies do not consider the impact of realistic distribution of surface heterogeneities on mesoscale atmospheric dispersion. While past studies focused on dispersion in the convective boundary layer, the present work also considers dispersion in the nocturnal boundary layer and above. Using a Lagrangian Particle Dispersion Model (LPDM) coupled to the Eulerian Regional Atmospheric Modeling System (RAMS), the impact of topographic, vegetation, and soil moisture heterogeneities on daytime and nighttime atmospheric dispersion is examined in the present study. In addition, sensitivity to the use of satellite-derived, realistic spatial distribution of vegetation characteristics on atmospheric dispersion is also

The impact of vegetation and terrain heterogeneities on atmospheric dispersion is strongly modulated by soil moisture, with the nature of dispersion switching from non-Gaussian to near-Gaussian behaviour for wetter soils (fraction of saturation soil moisture content exceeding 40%). At drier soil moisture conditions, vegetation heterogeneity causes differential heating and formation of mesoscale circulation patterns that are primarily responsible for non- Gaussian dispersion patterns. Nighttime dispersion is very sensitive to topographic, vegetation, soil moisture, and soil type heterogeneity and is distinctly non-Gaussian for heterogeneous land surface conditions. Sensitivity studies show that soil type and vegetation heterogeneities have the most dramatic impact on atmospheric dispersion. To provide more skilful dispersion calculations, we recommend the utilisation of satellite-derived vegetation characteristics coupled with data assimilation techniques that constrain soil-vegetation-atmosphere transfer (SVAT) models to generate realistic spatial distributions of surface energy fluxes.”

This is another research study that documents why landscape heterogeneity matter in weather and climate.

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