Monthly Archives: September 2008

Uncertainty In Multi-Decadal Global Climate Model Predictions Associated With Snow Albedo Feedbacks

There is a paper which documents a large uncertainty of the feedback of snow albedo on the climate system. It is

Hall A., X. Qu (2006), Using the current seasonal cycle to constrain snow albedo feedback in future climate change, Geophys. Res. Lett., 33, L03502, doi:10.1029/2005GL025127.

The abstract reads

“Differences in simulations of climate feedbacks are sources of significant divergence in climate models’ temperature response to anthropogenic forcing. Snow albedo feedback is particularly critical for climate change prediction in heavily-populated northern hemisphere land masses. Here we show its strength in current models exhibits a factor-of-three spread. These large intermodel variations in feedback strength in climate change are nearly perfectly correlated with comparably large intermodel variations in feedback strength in the context of the seasonal cycle. Moreover, the feedback strength in the real seasonal cycle can be measured and compared to simulated values. These mostly fall outside the range of the observed estimate, suggesting many models have an unrealistic snow albedo feedback in the seasonal cycle context. Because of the tight correlation between simulated feedback strength in the seasonal cycle and climate change, eliminating the model errors in the seasonal cycle will lead directly to a reduction in the spread of feedback strength in climate change. Though this comparison to observations may put the models in an unduly harsh light because of uncertainties in the observed estimate that are difficult to quantify, our results map out a clear strategy for targeted observation of the seasonal cycle to reduce divergence in simulations of climate sensitivity.”

This paper reinforces the conclusions we reached in our papers

Strack, J.E., R.A. Pielke Sr., and J. Adegoke, 2003: Sensitivity of model-generated daytime surface heat fluxes over snow to land-cover changes. J. Hydrometeor., 4, 24-42

with the abstract

“Snow cover can significantly suppress daytime temperatures by increasing the surface albedo and limiting the surface temperature to 0C. The strength of this effect is dependent upon how well the snow can cover, or mask, the underlying surface. In regions where tall vegetation protrudes through a shallow layer of snow, the temperature-reducing effects of the snow will be suppressed since the protruding vegetation will absorb solar radiation and emit an upward turbulent heat flux. This means that an atmospheric model must have a reasonable representation of the land cover, as well as be able to correctly calculate snow depth, if an accurate simulation of surface heat fluxes, air temperatures, and boundary layer structure is to be made. If too much vegetation protrudes through the snow, then the surface sensible heat flux will be too large and the air temperatures will be too high.

In this study four simulations are run with the Regional Atmospheric Modeling System (RAMS 4.30) for a snow event that occurred in 1988 over the Texas Panhandle. The first simulation, called the control, is run with the most realistic version of the current land cover and the results verified against both ground stations and aircraft data. Simulations 2 and 3 use the default methods of specifying land cover in RAMS 4.29 and RAMS 4.30, respectively. The significance of these variations in land-cover definition is then examined by comparing with the control run. Finally, the last simulation is run with the land cover defined as all short grass, the natural cover for the region. The results of this study indicate that variations in the land-cover specification can lead to differences in sensible heat flux over snow as large as 80 W m2. These differences in sensible heat flux can then lead to differences in daytime temperatures of as much as 6C. Also, the height of the afternoon boundary layer can vary by as much as 200–300 m. In addition, the results suggest that daytime temperatures are cooler over snow in the regions where short grass has been converted to cropland, while they appear to be warmer over regions where shrubs have increased.”


Strack, J., R.A. Pielke Sr., and G. Liston, 2007: Arctic tundra shrub invasion and soot deposition: Consequences for spring snowmelt and near-surface air temperatures. J. Geophys. Res., 112, G04S44, doi:10.1029/2006JG000297

with the abstract

“Invasive shrubs and soot pollution both have the potential to alter the surface energy balance and timing of snow melt in the Arctic. Shrubs reduce the amount of snow lost to sublimation on the tundra during the winter leading to a deeper end-of-winter snowpack. The shrubs also enhance the absorption of energy by the snowpack during the melt season by converting incoming solar radiation to longwave radiation and sensible heat. Soot deposition lowers the albedo of the snow, allowing it to more effectively absorb incoming solar radiation and thus melt faster. This study uses the Colorado State University Regional Atmospheric Modeling System version 4.4 (CSU-RAMS 4.4), equipped with an enhanced snow model, to investigate the effects of shrub encroachment and soot deposition on the atmosphere and snowpack in the Kuparuk Basin of Alaska during the May–June melt period. The results of the simulations suggest that a complete invasion of the tundra by shrubs leads to a 2.2C warming of 3 m air temperatures and a 108 m increase in boundary layer depth during the melt period. The snow-free date also occurred 11 d earlier despite having a larger initial snowpack. The results also show that a decrease in the snow albedo of 0.1, owing to soot pollution, caused the snow-free date to occur 5 d earlier. The soot pollution caused a 1.0C warming of 3 m air temperatures and a 25 m average deepening of the boundary layer.”

There is very significant (and difficult) challenge of accurately representing the role of snow albedo effects on climate, as well as the role of human activity in altering this albedo over time and space.

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Increasing Eolian Dust Deposition in the Western United States Linked to Human Activity by Neff et al 2008

There is an important new paper that presents further evidence of the complexity of the climate system. It is

Neff, J.C., Ballantyne, A.P., Famer, G.L., Mahowald, N.M., Conroy, J.L., Landry, C.C., Overpeck, J.T., Painter, T.H., Lawrence, C.R., and Reynolds R.L., 2008, Increasing eolian dust deposition in the western United States linked to human activity.Nature – Geosciences. doi:10.1038/ngeo133

The abstract reads

“Mineral aerosols from dust are an important influence on climate and on marine and terrestrial biogeochemical cycles. These aerosols are generated from wind erosion of surface soils. The amount of dust emission can therefore be affected by human activities that alter surface sediments. However, changes in regional- and global-scale dust fluxes following the rapid expansion of human populations and settlements over the past two centuries are not well understood. Here we determine the accumulation rates and geochemical properties of alpine lake sediments from the western interior United States for the past 5,000 years.We find that dust load levels increased by 500% above the late Holocene average following the increased western settlement of the United States during the nineteenth century.We suggest that the increased dust deposition is caused by the expansion of livestock grazing in the early twentieth century. The larger dust flux, which persists into the early twenty-first century, results in a more than fivefold increase in inputs of K, Mg, Ca, N and P to the alpine ecosystems, with implications for surface-water alkalinity, aquatic productivity and terrestrial nutrient cycling.”

This effect is a consequence of human landscape change, which, as Climate Science has repeatedly emphasized, is at least as important as the radiative effect of CO2 in altering the climate system.

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Comprehensive Data Set of Global Land Cover Change for Land Surface Model Applications by Sterling and Ducharne (2008)

There is yet another paper that documents the very important role of land cover change as a component of the climate system [and thanks to Laure M. Montandon for alerting us to this article!]. The paper is

Sterling, S., and A. Ducharne (2008), Comprehensive data set of global land cover change for land surface model applications, Global Biogeochem. Cycles, 22, GB3017, doi:10.1029/2007GB002959.

The abstract reads

“To increase our understanding of how humans have altered the Earth’s surface and to facilitate land surface modeling experiments aimed to elucidate the direct impact of land cover change on the Earth system, we create and analyze a database of global land use/cover change (LUCC). From a combination of sources including satellite imagery and other remote sensing, ecological modeling, and country surveys, we adapt and synthesize existing maps of potential land cover and layers of the major anthropogenic land covers, including a layer of wetland loss, that are then tailored for land surface modeling studies. Our map database shows that anthropogenic land cover totals to approximately 40% of the Earth’s surface, consistent with literature estimates. Almost all (92%) of the natural grassland on the Earth has been converted to human use, mostly grazing land, and the natural temperate savanna with mixed C3/C4 is almost completely lost (~90%), due mostly to conversion to cropland. Yet the resultant change in functioning, in terms of plant functional types, of the Earth system from land cover change is dominated by a loss of tree cover. Finally, we identify need for standardization of percent bare soil for global land covers and for a global map of tree plantations. Estimates of land cover change are inherently uncertain, and these uncertainties propagate into modeling studies of the impact of land cover change on the Earth system; to begin to address this problem, modelers need to document fully areas of land cover change used in their studies.”

Since, as we have shown in

Strack, J.E., R.A. Pielke Sr, L.T. Steyaert, and R.G. Knox, 2008: Sensitivity of summer near-surface temperatures and precipitation in the eastern United States to historical land cover changes since European settlement. Water Resources Research, accepted,

long term temperature and precipitation variations and trends do strongly depend on the time evolution of the landscape in the eastern United States, the same effect must also be true wherever humans have altered the landscape. Based on the Sterling and Ducharne article, this corresponds to directly to about 40% of the Earth’s land surface, and from teleconnections (i.e. advection by winds, alteration of atmospheric pressure fields) to effecting the weather throughout large areas of the rest of the Earth, as shown, for example, by

Chase, T.N., R.A. Pielke, T.G.F. Kittel, R.R. Nemani, and S.W. Running, 2000: Simulated impacts of historical land cover changes on global climate in northern winter. Climate Dynamics, 16, 93-105 [in which only about 15% of the Earth’s land surface was modified by humans in the model].

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Conference Marie Curie-iLEAPS – Feedbacks-Land-Climate Dynamics – Key Gaps

There is an upcoming meeting that will inform us further on the role of landascape proceeses within the climate system. It is the Marie Curie – iLEAPS conference
Date: 17-21 November 2008  to be hel at the Hotel Club “Le Continental” Hyeres, France

The contact is Dr. Nathalie de Noblet-Ducoudré

 Conference Marie Curie-iLEAPS – Feedbacks-Land-Climate Dynamics – Key Gaps

The objective …. is to bring together most scientists (young and senior) involved in the field of understanding the role terrestrial biosphere plays in the climate system (changes, transitions, extremes) at the regional to global scale, and to make a firm status on the present knowledge of these interactions and the remaining parts to be explored. Talks and posters will initiate discussions that should lead to a synthesis paper on the state-of-the-art knowledge on this topic. Actions to carry out in the next 5 years should emerge from these discussions. These actions will include coordinated modelling experiments as well as synthesis of surface data at the regional to global scales. At the end of the workshop will set up a web site with the main papers, overheads, and reports on discussions to help the dissemination of the knowledge gained, and to help the writing up of the synthesis paper.

Call for abstracts and application for this International Conference on Biosphere-Atmosphere Interactions is open. The deadline for sending abstracts and application is 12 September.

On-line registration and submission of abstracts is now available.

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A Geophysical Research Letter Article by Lobell, D. B., G. Bala, and P. B. Duffy (2006): Biogeophysical Impacts Of Cropland Management Changes On Climate

Recently, I came across an interesting paper that is another valuable resource that documents the first order role of landscape processes as part of climate variability and change. The paper is

Lobell, D. B., G. Bala, and P. B. Duffy (2006), Biogeophysical impacts of cropland management changes on climate, Geophys. Res. Lett. L06708, doi:10.1029/2005GL025492.

The abstract reads

“It is well known that expansion of agriculture into natural ecosystems can have important climatic consequences, but changes occurring within existing croplands also have the potential to effect local and global climate. To better understand the impacts of cropland management practices, we used the NCAR CAM3 general circulation model coupled to a slab-ocean model to simulate climate change under extreme scenarios of irrigation, tillage, and crop productivity. Compared to a control scenario, increases in irrigation and leaf area index and reductions in tillage all have a physical cooling effect by causing increases in planetary albedo. The cooling is most pronounced for irrigation, with simulated local cooling up to 8°C and global land surface cooling of 1.3°C. Increases in soil albedo through reduced tillage are found to have a global cooling effect (0.2°C) comparable to the biogeochemical cooling from reported carbon sequestration potentials. By identifying the impacts of extreme scenarios at local and global scales, this study effectively shows the importance of considering different aspects of crop management in the development of climate models, analysis of observed climate trends, and design of policy intended to mitigate climate change. “

The paper includes the statement that

“… land cover change impacts can complicate detection and attribution of recent anthropogenic greenhouse warming [Chase et al., 2001], and may play a significant role in driving future climate change [DeFries et al., 2002; Feddema et al., 2005; Sitch et al., 2005].”

“Despite the focus of past modeling efforts on land cover changes, there are many other land use changes not reflected in land cover that can potentially influence climate. (Land use change includes both conversion and other modifications [Meyer and Turner, 1992]). In particular, over the last 50 years, the net increase in global cropland area of ~10% has been relatively minor on a percentage basis compared to land use changes occurring within croplands, such as a doubling of irrigation extent, more than doubling of crop yields, and rapid regional increases in cropping intensity (# crops grown in a field per year) (Food and Agricultural Organization, FAO statistical databases, available at, 2004). Similarly, future changes of land use within existing croplands will likely be substantial as society strives to meet growing food demands.”

“In this paper, we evaluate the potential biogeophysical effects of various cropland changes using an atmospheric general circulation model (GCM) coupled to a mixed-layer ocean model. We find that current trends in crop management toward more irrigation, higher crop leaf area index (LAI), and reduced tillage all can have substantial cooling effects on local and, in some cases, global climate.”

The conclusions include the text

The cooling from irrigation and marked decrease in diurnal temperature range is consistent with previous modeling and observational studies of irrigation’s impact in specific regions [Adegoke et al., 2003; de Ridder and Gallee, 1998]. For example, Mahmood et al. [2004] found reductions in diurnal temperature range in irrigated regions of Nebraska relative to adjacent non-irrigated regions. The results presented here demonstrate that irrigation’s impact on climate will vary temporally (day vs. night), vertically (surface vs. 350mb), seasonally, and spatially, and therefore that a unique footprint associated with irrigation changes should be discernible in the observational records, as other drivers of climate change will likely have different patterns of temperature impacts.

The substantial increase in cloud cover also indicates that irrigation can indirectly raise the planetary albedo. While this study considered only the CAM model, several climate models (including CAM) as well as available observations show an inverse relationship between soil moisture and cloud base height [Dirmeyer et al., 2005], which presumably reflects a positive correlation between soil moisture and cloud cover. This suggests that a significant feedback between irrigation and incident surface radiation is not an artifact of the particular model we used; however, further study would be needed to confirm this.

The simulated effect of reduced tillage showed that widespread adoption of no-till practices is likely to have a substantial cooling effect because of increased albedo, with a possible negative precipitation response in India. Most work on tillage has considered only the biogeochemical effect on climate, with estimates of global sequestration potential ranging from 25–50 Gt C globally [Lal, 2004]. If one assumes a radiative forcing for doubled CO2 of 3.5 W m−2 [IPCC, 2001], a model sensitivity of 2.2°C for doubled CO2 [Gibbard et al., 2005], and an atmospheric CO2reduction of 12–25 ppm corresponding to a sink of this strength, then the potential biogeochemical cooling effect of reduced tillage is 0.11–0.21°C. The biogeophysical cooling effect estimated here (~0.2°C) is therefore comparable in magnitude and in the same direction as the potential biogeochemical effect. Moreover, the biogeochemical effect is likely to diminish with time as the atmosphere equilibrates with the ocean [Maier-Reimer and Hasselmann, 1987], while the biogeophysical effect will be permanent.

Overall, this study makes clear that while land cover change is an important aspect of human land use, changes occurring within existing agricultural lands can also have important consequences for climate. Interpretation of climate records in agricultural regions that fail to consider these changes may incur significant errors. For example, the cooling trends simulated here may mask any warming effect of rising carbon dioxide levels, especially at local scales. To better understand the role of crop management in climate, more realistic data sets on irrigation, productivity, and tillage changes should be developed and used to drive additional climate simulations.

Finally, policies that promote management changes such as reduced tillage or increased irrigation may need to consider their climate consequences and possible feedbacks onto crop production. Efforts to incorporate crop management practices such as tillage into international carbon trading programs, which inherently focus on biogeochemical effects, may also wish to consider the potentially significant biogeophysical impacts on climate.”

This paper yields clear further evidence that multi-decadal global climate model simulations that do not include the human management of agriculture as a first order climate forcing will necessarily be inaccurate.

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Spencer R. Weart On The Weblog Real Climate Makes A Confession

Spencer R. Weart posts a remarkable weblog on Real Climate titled “Simple Question, Simple Answer… Not“. He writes

“I often get emails from scientifically trained people who are looking for a straightforward calculation of the global warming that greenhouse gas emissions will bring.”


“I’m not saying we don’t understand the greenhouse effect. We understand the basic physics just fine, and can explain it in a minute to a curious non-scientist. (Like this: greenhouse gases let sunlight through to the Earth’s surface, which gets warm; the surface sends infrared radiation back up, which is absorbed by the gases at various levels and warms up the air; the air radiates some of this energy back to the surface, keeping it warmer than it would be without the gases.) For a scientist, you can give a technical explanation in a few paragraphs. But if you want to get reliable numbers – if you want to know whether raising the level of greenhouse gases will bring a trivial warming or a catastrophe – you have to figure in humidity, convection, aerosol pollution, and a pile of other features of the climate system, all fitted together in lengthy computer runs.

Physics is rich in phenomena that are simple in appearance but cannot be calculated in simple terms. Global warming is like that. People may yearn for a short, clear way to predict how much warming we are likely to face. Alas, no such simple calculation exists. The actual temperature rise is an emergent property resulting from interactions among hundreds of factors. People who refuse to acknowledge that complexity should not be surprised when their demands for an easy calculation go unanswered.”

This is a clear admission of the complexity of the climate system which Climate Science has been emphasizing since it was initiated!

Indeed, since Spencer accepts that “The actual temperature rise is an emergent property resulting from interactions among hundreds of factors”, it also follows that we do not know even if the actual temperature will rise, since there are a variety of human cooling climate forcings, including from several of the aerosol effects (see), as well as natural cooling effects including atmospheric circulation changes, decreases in solar irradiance, and volcanic emissions.  

We recognized this complexity in several of our papers; for example,

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,

where we write

 “The Earth’s climate system is highly nonlinear: inputs and outputs are not proportional,
change is often episodic and abrupt, rather than slow and gradual…..It is imperative that the Earth’s climate system research community embraces this nonlinear paradigm if we are to move forward in the assessment of the human influence on climate.”


Pielke, R.A. Sr., H.J. Schellnhuber, and D. Sahagian, 2003: Non-linearities in the Earth system. Global Change Newsletter, No. 55, 11-15

we wrote

“The complex non-linear physical, chemical, and biological interactions among the components of the Earth System are becoming an increasingly important focus in global change research …. These interactions between atmosphere, oceans, ice, and land are driven externally by the solar input of heat, and internally by geologic activity and the myriad processes that control the behaviour of each sub-system….Human activity is an integral component of these interactions…”


“The complexity of the Earth System’s behaviour makes it extremely difficult to accurately
forecast the future of the Earth System, and presents a major challenge to the global change research community.”


 Skillful multi-decadal global climate predictions (and, thus also multi-decadal regional climate predictions) are not yet possible. Spencer R. Weart’s weblog is a step forward in the wider recognition of the actual complexity of the climate system.


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Further Evidence Of The Serious Limitiations Of Using Regional Climate Models For Multi-Decadal Predictions

Regional Climate Models (RCMs) are used extensively to provide regional and local weather, water resource and other predictions, decades into the future, to planners and policymakers.  The RCMs use lateral boundary conditions and interior domain nudging from the multi-decadal global climate model predictions (e.g. see Chapter 7 in the 2007 IPCC report). 

As concluded in our previous papers, however, the presentation of regional forecast skill is an illusion based on the finer scale appearing results produced by the RCMs, as a consequence of their ability to map their output onto more detailed resolution terrain and landscape. The RCMs, however, are just sophsiticated interpolations of the output from the global climate models, and cannot correct biases that are already present in these models. Our past papers that discuss this issue include

Castro, C.L., R.A. Pielke Sr., and G. Leoncini, 2005: Dynamical downscaling: Assessment of value retained and added using the Regional Atmospheric Modeling System (RAMS). J. Geophys. Res. – Atmospheres, 110, No. D5, D05108, doi:10.1029/2004JD004721

Castro, C.L., R.A. Pielke Sr., J. Adegoke, S.D. Schubert, and P.J. Pegion, 2007: Investigation of the summer climate of the contiguous U.S. and Mexico using the Regional Atmospheric Modeling System (RAMS). Part II: Model climate variability. J. Climate, 20, 3866-3887.

Lo, J.C.-F., Z.-L. Yang, and R.A. Pielke Sr., 2008: Assessment of three dynamical climate downscaling methods using the Weather Research and Forecasting (WRF) Model. J. Geophys. Res., 113, D09112, doi:10.1029/2007JD009216.

We now have another paper which is “in press” that further documents the limitations of regional climate modeling. The paper is

Rockel, B., C. L. Castro, R. A. Pielke Sr., H. von Storch, and G. Leoncini (2008), Dynamical Downscaling: Assessment of Model System Dependent Retained and Added Variability for two Different Regional Climate Models, J. Geophys. Res., doi:10.1029/2007JD009461, in press.

The abstract reads

“In this paper, we compare the retained and added variability obtained using the regional climate model CLM (Climate version of the Local Model of the German Weather Service) to an earlier study using the RAMS (Regional Atmospheric Modeling System) model. Both models yield similar results for their standard configurations with a commonly used nudging technique applied to the driving model fields. Signicantly both models do not adequately retain the large-scale variability in total kinetic energy with results poorer on a larger grid domain. Additional experiments with interior nudging, however, permit the retention of large-scale values for both models. The spectral nudging technique permits more added variability at smaller scales than a four dimensional internal grid nudging on large domains. We also confirmed that dynamic downscaling does not retain (or increase) simulation skill of the large-scale fields over and beyond that which exists in the larger-scale model or reanalysis. Our conclusions should be relevant to all applications of dynamic downscaling for regional climate simulations.”

Our conclusions support the statement that

“….dynamical downscaling .. does not retain value of the large-scale over and above that which exists in the larger global reanalysis. If the variability of synoptic features is underestimated or there is a consistent bias in the larger model, no increased skill would be gained by dynamical downscaling”

What this means is that claims of regional forecast skill for decades into the future (such as changes in drought frequency, etc) represent an overselling of the capabilities of the RCMs since the global climate models not have all of the first order climate forcings and feedbacks (e.g. see), which necessarily is a prerequisite for skillful forecasts. Media articles and published papers that claim otherwise are ignoring scientific evidence that shows that such regional forecast ability does not yet exist.

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New Evidence For The Complex Role Of Aerosols On The Climate System By Rosenfeld et al 2008

There is an important new paper in Science magazine that sheds new insight into the complex role that aerosols play within the climate system.  Since aerosols are input into the atmosphere through a variety of human activities (e.g. industrial and vehicular emissions, biomass burning, blowing dust from landscape degradation), this means that the human aerosol effect on climate is not only very significant but also quite complicated in how it affects weather.

The paper is Flood or Drought: How Do Aerosols Affect Precipitation?by Daniel Rosenfeld, Ulrike Lohmann, Graciela B. Raga, Colin D. O’Dowd, Markku Kulmala, Sandro Fuzzi, Anni Reissell, Meinrat O. Andreae, Science 5 September 2008: Vol. 321. no. 5894, pp. 1309 – 1313 DOI: 10.1126/science.1160606.

The abstract reads

“Aerosols serve as cloud condensation nuclei (CCN) and thus have a substantial effect on cloud properties and the initiation of precipitation. Large concentrations of human-made aerosols have been reported to both decrease and increase rainfall as a result of their radiative and CCN activities. At one extreme, pristine tropical clouds with low CCN concentrations rain out too quickly to mature into long-lived clouds. On the other hand, heavily polluted clouds evaporate much of their water before precipitation can occur, if they can form at all given the reduced surface heating resulting from the aerosol haze layer. We propose a conceptual model
that explains this apparent dichotomy.”

An excerpt from the text of the paper reads

“….before humankind started to change the environment, aerosol concentrations were not much greater (up to double) over land than over the oceans… Anthropogenic aerosols alter Earth’s energy budget by scattering and absorbing the solar radiation that energizes the formation of clouds…Because all cloud
droplets must form on preexisting aerosol particles that act as cloud condensation nuclei (CCN), increased aerosols also change the composition of clouds (i.e., the size distribution of cloud droplets). This, in turn, determines to a large extent the precipitation-forming processes.”

The excellent Rosenfeld et al paper is an important new contribution that describes the complexity of how aerosols affect the climate system. Since the multi-decadal global models used to create the 2007 IPCC report did not properly represent these effects, their projections of how precipitation (and thus all other climate variables) are expected to change in the future are clearly inadequate scientifically.

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Another Example of Bias – This Time By The Weblog

In response to the Climate Science weblog

Hurricanes And Global Warming – A Scientific Disconnect

the website published an attack titled “Roger Pielke Sr. Attacks Messenger, Injures Self“.  This ad hominem Desmog weblog is a clear example of the bias that has permeated the climate science issue. The article fails to comment on the science that is presented [which implicitly means the perspective presented by Climate Science on this issue is correct].

If the Desmogblog were interested in the science, it would present counter arguments to the statements they quote from Climate Science; i.e.

  • Hurricanes respond to their immediate environment, not a global average increase in heat!
  • The focusing on global warming as the reason for any hurricane (or making it more likely to occur or become more intense) ignores that natural variations are not only more important than indicated by the AP news story, but also that the human influence  involves a diverse range of first-order climate forcings, including, but not limited global warming [which, of course, has not occurred since at least mid-2004!].

Except for erroneously claiming that the last 10 years included the warmest nine in recorded history [which is easy to refute with data; see Figure 7], the DeSmog weblog is nothing more than the continuation of personal attacks at those who seek to broaden the discussion of the role of humans within the climate system. Hopefully, DeSmog will take this opportunity to present coherent, scientifically defensible comments on the weblog presented at Climate Science.

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Recent Presentation By Roger A. Pielke Sr. – “Human Impacts on Weather and Climate – Recent Research Results Require That We Adopt A Broader Assessment”

I recently gave the following recent invited talk at the 2008 American Association of Wind Engineering meeting;

Pielke Sr., R.A., 2008: Human Impacts on Weather and Climate – Recent Research Results Require That We Adopt A Broader Assessment. AAWE Keynote Lecture, August 21, 2008, Vail, CO.

Included in the talk were examples of climate data which should be routinely monitored in order to accurately communicate climate variability and trends.

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