Climate Science: Roger Pielke Sr. Research Group News

There has been a development over the last 10-15 years or so in the scientific peer reviewed literature that is short circuiting the scientific method.

The scientific method involves developing a hypothesis and then seeking to refute it. If all attempts to discredit the hypothesis fails, we start to accept the proposed theory as being an accurate description of how the real world works.

A useful summary of the scientific method is given on the website sciencebuddies.org.where they list six steps

• Ask a Question
• Do Background Research
• Construct a Hypothesis
• Test Your Hypothesis by Doing an Experiment
• Analyze Your Data and Draw a Conclusion
• Communicate Your Results

Unfortunately, in recent years papers have been published in the peer reviewed literature that fail to follow these proper steps of scientific investigation. These papers are short circuiting the scientific method.

Specifically, papers that present predictions of the climate decades into the future have proliferated. Just a two recent examples (and there are many others) are

Hu, A., G. A. Meehl, W. Han, and J. Yin (2009), Transient response of the MOC and climate to potential melting of the Greenland Ice Sheet in the 21st century, Geophys. Res. Lett., 36, L10707, doi:10.1029/2009GL037998.

Solomon, S. 2009: Irreversible climate change due to carbon dioxide emissions. The Proceedings of the National Academy of Sciences. Published online before print January 28, 2009, doi: 10.1073/pnas.0812721106

Such studies are even reported in the media before the peer reviewed process is completed; e.g. see in the article by Hannad Hoag in the May 27 2009 issue of Nature News Hot times ahead for the Wild West.

These studies are based on models, of which only a portion of which represent basic physics (e.g. the pressure gradient force, advection and the universal gravitational constant), with the remainder of the physics parameterized with tuned engineering code (e.g see).
 

When I served as Chief Editor of the Monthly Weather Reviews (1981-1985), The Co-Chief Editor of the Journal of Atmospheric Sciences (1996-2000), and as Editor-in-Chief of the US National Science Report to the IUGG  for the American Geophysical Union (1993-1996), such papers would never have been accepted.

What the current publication process has evolved into, at the detriment of proper scientific investigation, are the publication of untested (and often untestable) hypotheses.  The fourth step in the scientific method “Test Your Hypothesis by Doing an Experiment” is bypassed.

This is a main reason that the policy community is being significantly misinformed about the actual status of our understanding of the climate system and the role of humans within it.

There is a new paper which presents forecasts of regional climate decades into the future. Climate Science has been very critical of such papers since i) we have wait decades to validate the skill of the predictions, and ii) the multi-decadal global climate models have shown no skill in predicting regional climate events (such as drought) in the 20th century up to the present (e.g. see

On the Credibility of Climate Predictions by Koutsoyiannis et al. 2008).

However, in contrast to many other such papers, this paper does recognize the serious limitations of this approach.

The paper is

Harmsen, E.W., Miller, N.L., Schlegel, N.J., Gonzalez, J.E., 2009: Seasonal climate change impacts on evapotranspiration, precipitation deficit and crop yield in Puerto Rico. Agricultural Water Management, 96, issue 7, 1085 - 1095,

with the abstract

“The purpose of this study was to estimate precipitation (P), reference evapotranspiration (ET_o), precipitation deficit (PD = P − ET_o) and relative crop yield reduction (YR) for a generic crop under climate change conditions for three locations in Puerto Rico: Adjuntas, Mayaguëz, and Lajas. Reference evapotranspiration was estimated by the Penman-Monteith method. Precipitation and temperature data were statistically downscaled and evaluated using the DOE/NCAR PCM global circulation model projections for the B1 (low), A2 (mid-high) and A1fi (high) emission scenarios of the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios. Relative crop yield reduction was estimated from a water stress factor, which is a function of soil moisture content. Average soil moisture content for the three locations was determined by means of a simple water balance approach.

Results from the analysis indicate that the rainy season will become wetter and the dry season will become drier. The 20-year average September precipitation excess (i.e., PD > 0) increased for all scenarios and locations from 121 to 321 mm between 2000 and 2090. Conversely, the 20-year average February precipitation deficit (i.e., PD < 0) changed from —27 to —77 mm between 2000 and 2090. The results suggest that additional water could be saved during the wet months to offset increased irrigation requirements during the dry months. The 20-year average relative crop yield reduction for all scenarios decreased on average from 12% to 6% between 2000 and 2090 during September, but increased on average from 51% to 64% during February. Information related to the components of the hydrologic water budget(i.e., actual evapotranspiration, surface runoff, aquifer recharge and soil moisture storage) is also presented. This study provides important information that may be useful for future water resource planning in Puerto Rico.”

The cavaets to this study are given in the section “Limitations in results presented”, where they write

“The results presented in this paper should necessarily be viewed with caution since they are based in part on coarse resolution GCM data downscaled to single sites. As Pielke et al. (2007) rightly point out, future ‘‘agricultural impacts extend far beyond a global mean temperature and include other anthropogenic climate forcings.’’ Some of these forcings include land-use change, atmospheric aerosols, and complex nonlinear feedbacks, not accounted for in present-day, and likely next-generation, GCMs. Statistical downscaling itself assumes that the predictor– predictand relationship remains constant in time with stationary dynamic conditions under future climate change (Mearns et al., 2003). Furthermore, this study was based on only one GCM and since many uncertainties still exist among different models, the results need to be used with caution (Bouraoui et al., 1997).”

A section in every paper of this type titled  “Limitations in results presented”, should be a requirement so that readers can more appropriately place such studies in ther proper perspective as “sensitivity studies”.

There is a new paper that is in press in the Proceedings of the National Academy of Sciences. It is

“Amplification of the North American ‘Dust Bowl’ drought through human induced land degradation By B. I. Cook, R. L. Miller and R. Seager.

This paper was also presented on Monday, March 9 2009 at the Univeristy of Colorado in Boulder at INSTARR.

The abstract reads

“The ‘Dust Bowl’ drought of the 1930s was highly unusual for North America, deviating from the typical pattern forced by ‘La Nina’ with the maximum drying in the central and northern Plains, warm temperature anomalies across almost the entire continent, and widespread dust storms. General circulation models (GCMs), forced by sea surface temperatures (SSTs) from the 1930s, produce a serious drought, but one that is centered in southwestern North America and without the warming centered in the middle of the continent. Here we show that the inclusion of forcing from human land degradation during the period, in addition to the anomalous SSTs, is necessary to reproduce the anomalous features of the Dust Bowl drought. The degradation over the Great Plains is represented in the GCM as a reduction in vegetation cover and the addition of a soil dust aerosol source, both a consequence of crop failure. As a result of land surface feedbacks, the simulation of the drought is much improved when the new dust aerosol and vegetation boundary conditions are included. Vegetation reductions explain the high temperature anomaly over the northern U.S. and the dust aerosols intensify the drought and move it northward of the purely ocean-forced drought pattern. When both factors are included in the model simulations, the precipitation and temperature anomalies are of similar magnitude and in a similar location compared to the observations. Human-induced land degradation is likely to have not only contributed to the dust storms of the 1930s, but also amplified the drought and these together turned a modest SST-forced drought into one of the worst environmental disasters the U.S. has experienced.”

The conclusion has the text

“The results from this study suggest a mechanism that could explain some of the anomalous drought patterns during the last thousand years, as seen in proxy reconstructions from tree ring records (20, 21). The ‘Dust Bowl’ drought was likely unique during the instrumental era, but similar drought patterns can be found during the Medieval Climate Anomaly (MCA) (4). Typical North American droughts during the MCA were longer lasting (on the order of decades) and more intense (21), and were accompanied by large scale dune mobilization over parts of the Great Plains (22). This movement of dunes implies a near-complete loss of vegetation cover (in this case induced naturally by an intense and persistent drought), and the possibility of a productive dust source and subsequent aerosol and vegetation feedbacks. Additionally, we note there are several areas in the world today where human land degradation (manifesting as loss of vegetation cover and increased vulnerability to wind erosion) and drought, potentially worsened by the subtropical drying that is projected to occur as a consequence of global warming (23, 24), have the potential to interact, leading to future ‘Dust Bowl’ droughts in some
developing regions (14). Both issues will require an integrated modeling approach, similar to the current study.”

The full paper will appear soon in the PNAS.

This excellent study highlights that land surface processes represent a first order climate forcing that must be included as a necessary condition to obtain realistic simulations of climate processes. This is a finding recommended in the 2005 NRC report

Radiative forcing of climate change: Expanding the concept and addressing uncertainties.

and in our published papers e.g. see

Pielke Sr., R.A., G. Marland, R.A. Betts, T.N. Chase, J.L. Eastman, J.O. Niles, D. Niyogi, and S. Running, 2002: The influence of land-use change and landscape dynamics on the climate system- relevance to climate change policy beyond the radiative effect of greenhouse gases. Phil. Trans. A. Special Theme Issue, 360, 1705-1719.

Pielke Sr., R.A., 2005: Land use and climate change. Science, 310, 1625-1626

There is an excellent and very informative weblog at the website The Blackboard: Where Climate Talk Gets Hot!

It is Fact 6A: Model Simulations Don’t Match the Average Surface Temperature of the Earth.

There is a figure titled “Figure 1: IPCC Model Simulations Prediction of Earth Surface Temperature” which documents the large variations of the IPCC model predicted surface temperatures. This weblog clearly documents an issue with the use of the global average surface temperature as the primary metric to diagnose and predict climate change. We discussed the definition of a global average surface temperature  (see Section 2) and other issues in our 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.

The differences in the model results are several degrees Celsius as presented in the figure presented on The Blackboard. Since the outgoing long wave radiation to space is proportional to T**4, these differences among the models is significant.  These differences from the observations cannot be ignored, even though the IPCC focuses on the changes (trends) of these temperatures over time.

We  look forward to the appearance of Lucia’s outstanding evaluations of the IPCC model skill in the peer reviewed literature, and will report on Climate Science when it does.

We have in press another peer reviewed paper that demonstrates the role of land surface processes as a first order climate forcing as well as an integral component of any assessment of climate variability and change [our study complements the peer reviewed paper by Lee et al which was weblogged on Climate Science on January 30 2009].

The paper is

Douglas, E.M., A. Beltrán-Przekurat, D. Niyogi, R.A. Pielke, Sr., and C. J. Vörösmarty, 2009: The impact of agricultural intensification and irrigation on land–atmosphere interactions and Indian monsoon precipitation —A mesoscale modeling perspective, Glob. Planet. Change, doi:10.1016/j.gloplacha.2008.12.007 [see this link also for the paper].

The abstract reads 

“Using the Regional Atmospheric Modeling System (RAMS) we show that agricultural intensification and irrigation can modify the surface moisture and energy distribution, which alters the boundary layer and regional convergence, mesoscale convection, and precipitation patterns over the Indian monsoon region. Four experiments were conducted to simulate a rain event from 16 to 20 July 2002 over the Indian region: (i) a control with Global Land Cover land use and observed Normalized Difference Vegetation Index, (ii) an irrigated crop scenario, (iii) a non-irrigated crop scenario, and (iv) a scenario for potential (natural) vegetation. Results indicate that even under active monsoon conditions, the simulated surface energy and moisture flux over the Indian monsoon region are sensitive to the irrigation intensity and this effect is more pronounced than the impact of land use change from the potential vegetation to the agricultural landscape. When model outputs were averaged over the south Asia model domain, a statistically significant decrease in mean sensible heat flux between the potential vegetation and the irrigated agriculture scenarios of 11.7 W m^-2 was found. Changes in latent heat fluxes ranging from -20.6 to +37.2 W m^-2 (-26% to +24%) and sensible heat fluxes ranging -87.5 to +4.4 W m^-2 (-77% to +8%) fluxes were found when model outputs were averaged over Indian states. Decreases in sensible heat in the states of Punjab (87.5 W m^-2 or 77%) and Haryana (65.3 W m^-2 or 85%) were found to be statistically significant at the 95% confidence level. Irrigation increased the regional moisture flux which in turn modified the convective available potential energy. This caused a reduction in the surface temperature and led to a modified regional circulation pattern and changes in mesoscale precipitation. These agricultural changes, including irrigation modify the mesoscale convection and rain patterns in the Indian monsoon region. These regional changes in land use need to be considered in improved weather forecasting as well as multi-decadal climate variability and change assessments.”

An excerpt from the Summary and Conclusions reads

“The growth in human population has increased the demand food supplies leading to intensified agriculture worldwide. The consequent changes in agricultural practices can lead to alterations in the landscape via changes in the land-use land-cover including irrigation……Irrigation increased the regional moisture flux which in turn modified the convective available potential energy (CAPE), caused reduction in the surface temperature and led to a modified regional circulation pattern and changes in mesoscale precipitation. It is anticipated that agricultural changes, and irrigation impacts, can modify the regional climate and the mesoscale convection and rain patterns in the Indian monsoon region and need to be considered in multi-decadal climate variability and change assessments.”

We have another paper accepted for publication which examines the importance of land use and of atmospheric information with respect to mesoscale and regional weather and climate predictions. It is

Ray, D. K., R. A. Pielke Sr., U. S. Nair, R. M. Welch, and R. O. Lawton (2009). Importance of land use versus atmospheric information verified from cloud simulations from a frontier region in Costa Rica, J. Geophys. Res., doi:10.1029/2007JD009565, in press

The abstract reads

“Land-use/land-cover (LULC) change has been recognized as a key component in global climate change and numerous climate modeling studies at regional to global scales document this. The research strategies have invariably been to first conduct baseline simulations of current conditions to evaluate model performance. Then simulation of regional climate with land cover changes (LCC) implemented within the model allows differences with the baseline simulation to be used as evidence of global to regional-scale climate impacts of LCC.

However, even state-of-the-art regional climate models require two datasets to conduct reasonable baseline simulations. These are representative current land cover and atmospheric information over the study region. In frontier and developing areas (where most of the rapid land-use conversion is taking place), these datasets are frequently unavailable and the errors in simulations are either due to inaccurate land cover, insufficient atmospheric information, non-representative model physics, or a combination of one or more of the above. This study shows that in one frontier region, that surrounding the Cordillera de Tilarán of Costa Rica, the accuracy of simulating clouds decreases by 1% to 3% if default model land cover information is used. If the atmospheric datasets used are the ones usually available to researchers (with land cover information held constant), then the model accuracy is reduced by 21% to 25%. Model runs without updated land cover or atmospheric information reduces model accuracy slightly further. Precipitation comparisons also provided similar results.

This study thus shows that the critically important dataset for conducting accurate simulations is not land cover information but atmospheric information. Researchers may similarly get significant increase in the accuracy of their baseline simulations elsewhere by using radiosondes/rawinsondes over their study region. Finally, since atmospheric information is not available for different landscape scenarios, assessments of the relative role of LULC change will have to continue to rely on using the standard atmospheric data set and the acceptance that the use of more detailed atmospheric data to initialize and provide lateral boundary conditions would have reduced the uncertainties in such landscape sensitivity studies.”

An excerpt from the paper reads

“From this study, however, it is quite clear that changes in land cover and atmospheric information will result in changes in simulation accuracy……..With respect to assessing the relative role of land-use change on the climate system, the improved simulation accuracy with better atmospheric structure information has an important implication. Since atmospheric information, of course, is not available for different landscape scenarios, (i.e. simulations are one-way nested regional model integrations in which there is no interaction from the regional to the large scales through the lateral boundaries) assessments of the relative role of LULC change will still have to rely on either using the standard atmospheric data set or on the use of more detailed atmospheric data over the current landscape even though it is affected by the current landscape for initial and lateral boundary conditions. The latter approach will reduce the simulation differences expected in such landscape sensitivity studies since the initial atmospheric conditions with a different landscape would in reality, of course, be different.”

This study is relevant to dynamic regional downscaling from global models, which a technique used to obtain local climate change impact information (see). What is can be concluded from this study is that even with the best land surface information, if the atmospheric information being transmitted into the regional model through lateral boundary conditions is not accurate, the impact assessment will, necessarily, be erroneous. 

On April 4 2007 Climate Science published the following weblog

A Litmus Test For Global Warming - A Much Overdue Requirement

In that weblog, I wrote

“A figure, such as Figure 8 in Willis, J.K., D. Roemmich, and B. Cornuelle, 2004: Interannual variability in upper ocean heat content, temperature, and thermosteric expansion on global scales. J. Geophys. Res., 109, C12036, doi: 10.1029/2003JC002260.

should be widely communicated each year (or more frequently). For example, as a requirement to NOT reject the IPCC claim for global warming, Climate Science proposes that on the scale presented in Figure 3 in Willis et al, the left axis in their Figure 8 must exceed the following values in each year

2003 8*10**22 Joules
2004 9*10**22 Joules
2005 10*10**22 Joules
2006 11*10**22 Joules
2007 12*10**22 Joules
2008 13*10**22 Joules
2009 14*10**22 Joules
2010 15*10**22 Joules
2011 16*10**22 Joules
2012 17*10**22 Joules”

This is an accumulation of heat of 1 * 10**22 Joules per year. We now have data to assess what actually occurred in terms of this metric of global warming up through the end of 2008 (i.e. see the Figure in Pielke (2008),  Figure 1 in Willis et al (2008) and personal communication from Josh Willis to extend the data to the end of 2008).

The use of the ocean  heat content change as the most appropriate metric to diagnose global warming was reported in

Levitus, S., J.I. Antonov, J. Wang, T.L. Delworth, K.W. Dixon, and A.J. Broccoli, 2001: Anthropogenic warming of Earth’s climate system. Science, 292, 267-269

and

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

In a 2008 Climate Science weblog

Comparison of Model and Observations Of Upper Ocean Heat Content,

I wrote

“The conclusion in Hansen et al. 2005 that the “Earth is now absorbing 0.85 ± Watts per meter squared more energy from the Sun than it is emitting to space” is well supported by their modeling results for the ten years or so ending in 2003.”

With respect to the heating rate, in the paper

Hansen, J., L. Nazarenko, R. Ruedy, Mki. Sato, J. Willis, A. Del Genio, D. Koch, A. Lacis, K. Lo, S. Menon, T. Novakov, Ju. Perlwitz, G. Russell, G.A. Schmidt, and N. Tausnev, 2005: Earth’s energy imbalance: Confirmation and implications. Science, 308, 1431-1435, doi:10.1126/science.1110252,

they wrote

“Our climate model, driven mainly by increasing human-made greenhouse gases and aerosols among other forcings, calculates that Earth is now absorbing 0.85±0.15 W/m² more energy from the Sun than it is emitting to space. This imbalance is confirmed by precise measurements of increasing ocean heat content over the past 10 years.” 

See also the response by Jim Hansen to a comment by Christy and Pielke Sr [which Science refused to publish], where Hansen wrote me with respect to their GISS model predictions that

“Our simulated 1993-2003 heat storage rate was 0.6 W/m2 in the upper 750 m of the ocean.”

He further writes

“The decadal mean planetary energy imbalance, 0.75 W/m2, includes heat storage in the deeper ocean and energy used to melt ice and warm the air and land. 0.85 W/m2 is the imbalance at the end of the decade.”

Thus, the best estimate value of 0.60 Watts per meter squared given in Hansen et al can be used, as a conservative value, to calculate the heat change in Joules that should be expected in the upper ocean data from 2003 to the present, as an update to results reported on Climate Science on June 5 2008.

The observed best estimates of the observed heating and the Hansen et al prediction in Joules in the upper 700m of the ocean are given below:

OBSERVED BEST ESTIMATE OF ACCUMULATION Of JOULES [assuming a baseline of zero at the end of 2002].

2003 ~0 Joules
2004 ~0 Joules
2005 ~0 Joules
2006 ~0 Joules
2007 ~0 Joules
2008 ~0 Joules
2009 —— 
2010 —— 
2011 —— 
2012 ——     

HANSEN PREDICTION OF The ACCUMULATION OF JOULES [ at a rate of 0.60 Watts per meter squared] assuming a baseline of zero at the end of 2002].

2003 ~0.98 * 10** 22 Joules
2004 ~1.96 * 10** 22 Joules
2005 ~2.94 * 10** 22 Joules
2006 ~3.92 * 10** 22 Joules
2007 ~4.90 * 10** 22 Joules
2008 ~5.88 * 10** 22 Joules
2009 ~6.86 * 10** 22 Joules
2010 ~7.84 * 10** 22 Joules
2011 ~8.82 * 10** 22 Joules
2012 ~9.80 * 10** 22 Joules

Thus, according to the GISS model predictions, there should be approximately 5.88 * 10**22 Joules more heat in the upper 700 meters of the global ocean at the end of 2008 than were present at the beginning of 2003.

For the observations to come into agreement with the GISS model prediction by the end of 2012, for example, there would have to be an accumulation 9.8 * 10** 22 Joules of heat over just the next four years. This requires a heating rate over the next 4 years into the upper 700 meters of the ocean of 2.45 * 10**22 Joules per year, which corresponds to a radiative imbalance of ~1.50 Watts per square meter.

This rate of heating would have to be about 2 1/2 times higher than the 0.60 Watts per meter squared that Jim Hansen reported for the period 1993 to 2003.

While the time period for this descrepancy with the GISS model is relatively short, the question should be asked as to the number of years required to reject this model as having global warming predictive skill, if this large difference between the observations and the GISS model persists.

Professor George Kallos has contributed very significantly to atmospheric and climate sciences. He is an internationally well respected colleague. Below are additional results from his important studies.

Mitsakou, C., G. Kallos, N. Papantoniou, C. Spyrou, S. Solomo,s M. Astitha, and C. Housiadas, 2008:: Saharan dust levels in Greece and received inhalation doses, Atmos. Chem. Phys., 8, 7181-7192.

The abstract reads

“The desert of Sahara is one of the major sources of mineral dust on Earth, producing around 2×108 tons/yr. Under certain weather conditions, dust particles from Saharan desert get transported over the Mediterranean Sea and most of Europe. The limiting values set by the directive EC/30/1999 of European Union can easily be exceeded by the transport of desert dust particles in the south European Region and especially in urban areas, where there is also significant contribution from anthropogenic sources. In this study, the effects of dust transport on air quality in several Greek urban areas are quantified. PM10 concentration values from stationary monitoring stations are compared to dust concentrations for the 4-year period 2003-2006. The dust concentration values in the Greek areas were estimated by the SKIRON modelling system coupled with embedded algorithms describing the dust cycle. The mean annual dust contribution to daily-averaged PM10 concentration values was found to be around or even greater than 10% in the urban areas throughout the years examined. Natural dust transport may contribute by more than 20% to the annual number of exceedances - PM10 values greater than EU limits - depending on the specific monitoring location. In a second stage of the study, the inhaled lung dose received by the residents in various Greek locations is calculated. The particle deposition efficiency of mineral dust at the different parts of the human respiratory tract is determined by applying a lung dosimetry numerical model, which incorporates inhalation dynamics and aerosol physical processes. The inhalation dose from mineral dust particles was greater in the upper respiratory system (extrathoracic region) and less significant in the lungs, especially in the sensitive alveolar region. However, in cases of dust episodes, the amounts of mineral dust deposited along the human lung are comparable to those received during exposure in heavily polluted urban or smoking areas.”

Astitha, M., and G. Kallos, 2008: Gas-phase and aerosol chemistry interactions in South Europe and the Mediterranean Region. Special Issue on “Physics-Chemistry Interactions from the Air Quality Perspective” Env. Fluid Mechanics, DOI 10.1007/s10652-008-9110-7

The abstract reads

“The atmospheric chemical composition is affected by the interactionmechanisms among gases and particulate matter through a wide range of chemical reactions that can occur with the aid of particulate matter (e.g. particles act as reacting or absorbing surfaces) or be influenced by the presence of particulate matter in the atmosphere (photochemical reactions). Physical and chemical processes are also bonded in an interactive way that often leads to the influence of the radiation budget, cloud physics and the warming or cooling of the lower atmospheric levels. The Euro-Mediterranean region is a key-sensitive area due to the unique climatic and air quality characteristics associated with the regional climatic patterns, geomorphology (land and water contrast) and coexistence of pollutants from different origin. Focusing on this region, the gas-aerosol interactions are studied using state-of-the-art atmospheric and chemical transport modeling tools following the necessary development in the chemical transport model CAMx. Sensitivity and large-scale simulations have shown significant responses of the modeling system to the inclusion of natural species emissions, the direct shading effect of dust particles on photochemical processes and the formation of new types of aerosols through heterogeneous uptake of gases on dust particles. Including such interactions in the chemical transport model often led to the improvement of the model performance compared with available measurements in the region.”

Louka, P., G. Galanis, N. Siebert, G. Kariniotakis, P. Katsafados, G. Kallos, and I. Pytharoulis, 2007: Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering. Journal of Wind Engineering and Industrial Aerodynamics- Elsevier. 96, 2348– 2362.

The abstract reads

“This paper studies the application of Kalman filtering as a postprocessing method in numerical predictions of wind speed. Two limited-area atmospheric models have been employed, with different options/capabilities of horizontal resolution, to provide wind speed forecasts. The application of Kalman filter to these data leads to the elimination of any possible systematic errors, even in the lower resolution cases, contributing further to the significant reduction of the required CPU time. The potential of this method in wind power applications is also exploited. In particular, in the case of wind power prediction, the results obtained showed a remarkable improvement in the model forecasting skill.”

Also view the following posters:

Kallos et al, 2008: THE NEW SURFACE AND RADIATIVE TRANSFER PARAMETERIZATION IN THE SKIRON/DUST MODELING SYSTEM, AGU.

and

Solomos et al., 2008: A NEW MODELING SYSTEM FOR STUDYING AEROSOL-CLOUD-RADIATION PROCESSES. AGU.

Our research has shown that the forcing of weather systems from diabatic heating by the human input of aerosols is on the order of 60 times that of the forcing from the diabatic heating due to the human addition of well-mixed greenhouse gases (with the dominate gas being CO2); i.e. see

Matsui, T., and R.A. Pielke Sr., 2006: Measurement-based estimation of the spatial gradient of aerosol radiative forcing. Geophys. Res. Letts., 33, L11813, doi:10.1029/2006GL025974.

We now have a new paper that presents a quantitative methodology to assess the importance of this type of climate forcing. It is

Vukicevic, T., R. A. Pielke Sr., and A. Beltran-Przekurat, 2009: New Method For Estimating The Impact Of Heterogeneous Forcing On Atmospheric Circulations. J. Geophys. Res., doi:10.1029/2008JD010418, in press.

The abstract reads

“In this study a new method for estimating the impact of heterogeneous forcing on atmospheric circulations is discussed. This new method is similar to the commonly used model-based sensitivity studies in that the impact of forcing is diagnosed by a suitable measure of differences between atmospheric states with and without forcing, but differs in the way the atmospheric states are evaluated: by combining standard atmospheric data analysis, observationally-based estimates of the forcing, atmospheric observations and general circulation model (GCM) ensemble simulations. A new numerical technique, derived from the Ensemble Kalman Filter data assimilation approach, is used for
objective estimation of the atmospheric state not affected by the forcing. Using a tutorial example, numerical experiments were conducted varying an asymmetric thermal forcing as a proxy for the heterogeneous forcing. Results show that the method is capable of producing skilled estimates of the impact of the forcing. Strategies for application of the method with real-world data and GCMs are discussed. This new method is expected to produce more realistic estimates of the forcing impact than the standard model sensitivity approach because of the explicit use of the observationally-based estimates of atmospheric states and forcing.”

The importance of this study is that assessment groups, such as the IPCC, have a new tool with which to broaden their evaluations of the role of humans within the climate system. Climate modeling groups are urged to adopt this tool, or a similar approach, to better quantify the role of spatial variations in human climate forcings on weather and climate.

We have a new research paper that has been published. This paper applies a new methodology that we reported on in

Pielke Sr., R.A., T. Matsui, G. Leoncini, T. Nobis, U. Nair, E. Lu, J. Eastman, S. Kumar, C. Peters-Lidard, Y. Tian, and R. Walko, 2006: A new paradigm for parameterizations in numerical weather prediction and other atmospheric models. National Wea. Digest, 30, 93-99.

In that paper, we wrote

“Superparameterization embedded, Multi-Modeling Frameworks (MMF) are ….under development at several institutions, and there are plans to create global cloud libraries which includes detailed mass and energy output from cloud resolving models. With the LUT-based approach, the superparameterization approach could be used much more efficiently since the simulations (e.g., the 3-D cloud model) are integrated oflline, and the results are archived in a database for future retrieval.”

In our new paper, we demonstrate, using a radiation parameterization, that the LUT-based aproach is a computationally efficient method to replace existing parameterization approaches and as an effective alternative to the MMF approach.

Our new 2008 paper also further demonstrates that the answers provided on Real Climate by Gavin Schmidt with respect to parameterizations (see) do not adequately recognize that parameterizations in weather and climate models are engineering code. They are not basic physics.

Our paper is

 Leoncini, G., R.A. Pielke Sr., and P. Gabriel, 2008: From model based parameterizations to Lookup Tables: An EOF approach. Wea. Forecasting, 23, 1127.1145.

The abstract reads

“The goal of this study is to transform the Harrington radiation parameterization into a transfer scheme
or lookup table, which provides essentially the same output (heating rate profile and short- and longwave
fluxes at the surface) at a fraction of the computational cost. The methodology put forth here does not
introduce a new parameterization simply derived from the Harrington scheme but, rather, shows that given
a generic parameterization it is possible to build an algorithm, largely not based on the physics, that mimics
the outcome of the parent parameterization. The core concept is to compute the empiricalorthogonal
functions (EOFs) of all of the input variables of the parent scheme, run the scheme on the EOFs, and
express the output of a generic input sounding exploiting the input–output pairs associated with the EOFs.
The weights are based on the difference between the input and EOFs water vapor mixing ratios. A detailed
overview of the algorithm and the development of a few transfer schemes are also presented. Results show
very good agreement (r > 0.91) between the different transfer schemes and the Harrington radiation
parameterization with a very significant reduction in computational cost (at least 95%).”

The conclusion ends with

“While this study is limited to the Harrington radiation parameterization, it is reasonable to believe that the same methodology can be extended to a cloudy sky and applied to other parameterizations with similar results, as first envisioned in Pielke et al. (2006).”