Monthly Archives: January 2011

An Article On The Skill Of Seasonal Predictions of Arctic Sea By Ron Lindsay

There is an excellent article in the November 2010 issue of U.S. CLIVAR VARIATIONS by Ron Lindsay of the University of Washington titled

Seasonal Predictions of Arctic Sea Ice Coverage.

It is an informative article on the ability to produce  seasonal ice coverage predictions.

The article contains asks the questions

“What are the prospects for sea ice prediction on seasonal to decadal time scales? What seasons and regions show the most promise for accurate predictions?”

Excerpts from the author on the answers include

“On monthly to seasonal time scales, accurate weather predictions are challenging, and the initial ice concentration and thickness are most important.”

“The inherent predictability of Arctic sea ice on seasonal time scales was investigated by Holland et al. (2010). Running a series of ensemble experiments using the Community Climate System Model (CCSM) with identical initial ice conditions they determined that sea ice area exhibits predictability from January for the first summer and for winter conditions in the next year. Comparing experiments initialized with
different mean ice conditions indicates that ice area in a thicker sea ice regime generally exhibits higher predictability for a longer period of time. In a thinner sea ice regime, winter ice conditions provide little ice area predictive capability after approximately 1 year. In all regimes, ice thickness (as opposed to area) has high predictability for at least 2 years.”

“…the NCEP Climate Forecast System (CFS) is used to make ensemble forecasts of the global climate out nine months or more…. it has not been tested and improved for polar conditions and the simulated sea ice is not yet a good representation of the observed ice. CFS predictive skill in the Arctic is not great. More work needs to be done to know how to best initialize a global model with observed ice thickness data or ice thickness data from a high-resolution retrospective ice–ocean model.”

“Ice thickness observations suitable for evaluating model performance and eventually to initialize model forecasts are not yet readily available.”

“Because the ice is pushed by unpredictable winds, the prediction of regional ice area, extent, or thickness is much less skillful than for the basin-wide total extent, which is less sensitive to ice moving from one part of the basin to another. Yet for field operations a prediction for a particular place or region is much more useful than one for the entire basin. The prediction uncertainty principle applies here: the smaller the region the greater the uncertainty. It will be an additional challenge to develop skillful regional forecasts.”

The bottom line message from this article is that there is some prediction skill out to at least two years, but regional skill is still quite limited. For longer time periods, this indicates that skill will be even less.  This article further supports the conclusions in my posts

Dynamic Downscaling From Multi-Decadal Global Model Projections Does Not Add Spatial and Temporal Accuracy Of Value To The Impacts Community

Statistical Downscaling From Multi-Decadal Global Model Projections Does Not Add Spatial and Temporal Accuracy Of Value To The Impacts Community

The article by Ron Lindsay, however, is an excellent example of assessing predictability, as I discussed in the post

The Difference Between Prediction and Predictability – Recommendations For Research Funding Related to These Distinctly Different Concepts

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The Westerlies Explain The Recent Extreme Winter Weather, Not “Global Warming”

 There have been a number of news articles that claim that a global average surface temperature trend (i.e. “global warming) explains the extreme cold weather and snow that has occurred recently; e.g. see

Comment On The CBS News Article “Is Extreme Weather a Result of Global Warming?”

NBC Global Warming Nonsense

In this post I want to illustrate why it is the location of the westerlies that determine areas that have extreme cold weather and snowstorms.

The first image below presents the heights of the 500mb pressure surface and the temperatures at 850mb from the ECMWF analysis for January 28 2011 at noon GMT.

The 500mb level is used as it is about halfway through the depth of the atmosphere. The distances between the lines of equal height are proportional to the speed of the winds at that level. Since, in the Northern Hemisphere, winds blow counterclockwise around regions of lower heights, the wind field (not shown) is predominately westerly. This is why the middle and higher latitudes are often referred to as the “westerlies”.  Winds at this spatial scale blow almost parallel to lines of constant height. When the height contours are close together, we refer to the higher winds that result as the “polar jet stream”.

Clearly evident in the example below is the progressively cooler 850mb temperatures and lower 500mb heights as one progresses to higher latitudes. Also, clearly seen are the regions of colder air (and corresponding lower heights) that extend towards lower latitudes. When these large equatorward excursions of the westerlies occur, extreme cold weather often happens. On the east side of these cold pockets, where there is a strong contrast with warmer air to the east, winter storms occur. If the temperatures are cold enough, precipitation can fall as heavy snow. These large excursions of the westerlies explains why there have been several extreme snowstorms in the eastern USA and western Europe in recent months.

To illustrate the dynamic character of the westerlies, I have presented below the ECMWF 500mb height and 850mb temperature forecast for next Friday [February 7 2011]. Compare the above figure with the one below. Note, for example, the large excursion of cold air and, therefore, westerlies southward to over the central USA. If this forecast verifies, it will be an extreme cold outbreak  with considerable snow (and ice storms) on the southeast flank of this cold region.


It is not scientifically accurate to attribute “global warming” of a few tenths of a degree to explain these extreme weather events. 

 Moreover, in the latest measurements,  the lower tropospheric temperatures are actually cooler than the long-term average! [e.g. see

UAH prelim – January temp may be below normal globally.

For other excellent discussions of the recent extreme winter weather, see the posts by Joe Daleo; e.g.

Another Eastern Snow – Brutal Winter Assault continues

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James Annan Misses The Point (Again!)

There is a post on James Empty Blog titled

Pielkes all the way down, revisited

that continues to misrepresent the scientific findings we have published on with respect to the science of multi-decadal surface and lower tropospheric temperature trends. Moreover, he presents his views in a weblog post, but does not follow up in the peer reviewed literature.

The fundamental scientific question that my colleagues and I are asking is whether multi-decadal temperature trends are invariant with height, winds and surface landscape in the lower troposphere including the surface layer.

We have shown observationally that this is not correct with respect to height; e.g. see

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., 114, D21102, doi:10.1029/2009JD011841.

Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2010: Correction to: “An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J. Geophys. Res., 114, D21102, doi:10.1029/2009JD011841″, J. Geophys. Res., 115, D1, doi:10.1029/2009JD013655.

Our new paper

G. J. Steeneveld, A. A. M. Holtslag, R. T. McNider, and R. A. Pielke, 2011. Screen level temperature increase due to higher atmospheric carbon dioxide in calm and windy nights revisited. J. Geophys. Res., 116, D02122, doi:10.1029/2010JD014612, 2011

explores this issue further with a model for one particular land surface type (with a single specified value of aerodynamic roughness) with a focus on just the wind speed issue . As we wrote

“…..the parameter spaces investigated in this paper are limited….It is possible that larger roughnesses might provide more sensitivity to wind speed..”

Even for our limited staudy, Figure 3 in our paper illustrates that while the trends are quite similar in the wind speed range of 5 to 15 meter per second, there are larger differences with winds less than those speeds as well as a significant function of height.

We conclude

“…. that the temperature increase close to the surface is much less sensitive to wind speed than suggested by PM05 when the long wave radiative forcing change is from increases in the atmospheric concentration of CO2. However, the temperature changes do depend on height as also suggested by PM05.”

When James wrote in his weblog post that

“….the central claim of PM05, which underpinned this entire edifice, is refuted”

this is a completely inaccurate characterization of the Steenveld et al paper.

Our paper is also discussed in my post of November 19 2010 (which James does not seem to have read)

New Paper “Screen Level Temperature Increase Due To Higher Atmospheric Carbon Dioxide In Calm And Windy nights Revisited’ By Steeneveld Et Al 2010

See also

In the Dark of the Night – the Problem with the Diurnal Temperature Range and Climate Change by Richard T. McNider


Comments #55 in

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Excellent Interview Of Peter S. Eagleston By C. Schultz On The EOS AGU Bookshelf “On Range And Richness Of Vascular Land Plants: The Role Of Variable Light”

The AGU Bookshelf which appears on EOS is an excellent source of perspective on climate and other geophysical issues. In the December 21 2010 issue there is an interview of Peter S. Eagleston By C. Schultz titlled

Schultz, C. (2010), Range and Richness of Vascular Land Plants: The Role of Variable Light, Eos Trans. AGU, 91(51), doi:10.1029/2010EO510015.

The abstract summary of the interview

“The observation that the number of species decreases—while at the same time the average range of local species increases—with increasing latitude is known within ecological circles as Rapoport’s rule. In the AGU monograph Range and Richness of Vascular Land Plants: The Role of Variable Light, former AGU president Peter S. Eagleson seeks a cause for Rapoport’s rule. Using a tightly focused analysis, Eagleson delves into the complex interactions that govern ecosystems to propose the primary importance to range and richness of one key variable, the locally incident shortwave radiation. In this interview, Eos talks with Eagleson.”

The key finding of the importance of short wave radiation with respect to the range, richness and latitude of vascular land plants (which make up about 98% of all land plants) is summarized in this interview. Excerpts include the answers from Eagleston

“One of the troubles that I have with more complicated models is the extent to which they are made to fit the data. In hydrology, for example, there is a need to go from point behavior to that of the full-scale watershed. With the computer, there is the possibility of aggregating millions and millions of little pieces into a whole. But with those millions and millions of little pieces go many more millions of parameters, and to me it seems like it becomes an exercise simply to find the best fit, where you’re not sure if you’ve really represented the physics in a meaningful way. At least for the data set that you have you can show that the model represents what happened, but I’m not sure you can prove that it’s going to do what happens tomorrow in many cases.”

“…..each species has its own maximally productive shortwave flux,[thus] selection of local species should be, approximately, a function solely of the shortwave flux. Because there are good statistics for the shortwave flux, I can say I have good statistics for the species. I don’t know what the species are, and I can’t name them. I can’t tell you whether that’s a maple or a bush of some kind, but I can tell you the average and the variance of the local species distribution. So that allows me to make the transfer from what I have, the local shortwave flux statistics, to what I need, the statistics of local species. With this, I can get an idea of the range.”

“I remember reading that the variance in shortwave flux will likely be the first thing to change as our atmosphere warms. We won’t see that much of a change in the average value of the shortwave flux, but we will see more of a change in frequencies of cloudiness and precipitation. These changes will have some effect on species range and richness, but all I can really say is that according to my model the local range of species will increase and local richness of species will decrease if the variance of the shortwave flux
increases. That’s assuming that the average shortwave flux stays roughly the same at a given latitude.”

This interview indicates that skillful prediction of local short wave fluxes is a necessary requirement to accurately predict how the distribution of plants could change in the future (it is not a sufficient condition since we also need to predict changes in landscape by human activities, nitrogen deposition, and increased biogeochemical effects from added CO2, as well as alteration as exotic plant species, insect infestations, etc alter the natural biodiversity. Surface air temperature, apparently, is not a good indicator, except to the extent it is correlated with the short wave radiation.

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Article “Mesoscale Climate Change Due To Lowland Deforestation In The Maritime Tropics” By van der Molen Et Al 2011

An article that we worked on several years ago has finally appeared in a publication from Cambridge University Press. It is

van der Molen, M.K., H.F. Vugts, L.A. Bruijnzeel, F.N. Scatena, R.A. Pielke Sr, and L.J.M. Kroon, 2011: Mesoscale climate change due to lowland deforestation in the maritime tropics. p 527-537 in: L.A. Bruijnzeel, F.N. Scatena and L.S. Hamilton (Eds) Tropical Montane Cloud Forests: Science for conservation and management, 768 pp.International hydrology series, Cambridge University Press, New York. ISBN: 978-0-521-76035-5.

The abstract reads

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

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

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

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

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Comment On The CBS News Article “Is Extreme Weather a Result of Global Warming?”

Update: January 27 2011 – Mike Smith also has an excellent discussion of media misinformation regarding recent extreme weather in his post on his weblog Meterological Musings

NBC Global Warming Nonsense


There is a news article by CBS titled (h/t to Marc Morano)

Is Extreme Weather a Result of Global Warming?

Excerpts read

In the past year, every continent except Antarctica has seen record-breaking floods. Rains submerged one-fifth of Pakistan, a thousand-year deluge swamped Nashville and storms just north of Rio caused the deadliest landslides Brazil has ever seen.

 Southern France and northern Australia had floods, too. Sri Lanka, South Africa, the list goes on.

 And while no single weather event can be linked definitively to global climate change, a growing number of scientists say these extreme events represent the face of a warming world.

 “Any one of these events is remarkable,” said Jay Gulledge, senior scientist for the Pew Center on Global Climate Change. “But all of this taken together could not happen without the extra heat that’s in the ocean. It defies common sense to overlook that link.”

That link works more or less like this. Concentrations of greenhouse gases are the highest the earth has seen in 15 million years. These gases trap heat, warming both the air and the oceans. Warmer oceans give off more moisture, and a warmer atmosphere can hold more of it in suspension. The more moisture in the air, the more powerful storms tend to grow. When these supercharged weather systems hit land, they don’t just turn into rain or snow, they become cyclones, blizzards and floods.

 “There is a lot of tropical moisture in the atmosphere that is getting transported over very long distances and is dropping out in various places around the world in dramatic fashion,” Gulledge said.


“Weather like this matches the predictions of numerous recent climate studies. In 2007, the Intergovernmental Panel on Climate Change noted that severe droughts and heavy rains were already on the rise in many parts of the world, and linked them to the surge in greenhouse gases. A study published last year by the National Academy of Sciences predicted an increase in heavy rainfall of somewhere between 3 and 10 percent for every Celsius degree of warming. Each additional degree would also cause the amount of area burned by wildfires in North America to double or quadruple, according to the same report.”

What does the actual data say.

The current sea surface temperature anomaly (which is the interface where ocean heat interfaces with the atmosphere) is presented below [from].

The most recent global average lower tropospheric temperature anomaly is given below [from]

Channel TLT Trend Comparison Ch

From University of Alabama at Huntsville Lower Tropospheric Temperatures for 2010 and December 2010

The water vapor anomalies, unfortunately, are not routinely, updated and made available to us. Nevertheless, papers such as

Randel, B. et al, 2004: Interannual Changes of Stratospheric Water Vapor and Correlations with Tropical Tropopause Temperatures. Journal of Atmospheric Sciences. 2133-2148

where the abstract reads [highlight added]

“Interannual variations of stratospheric water vapor over 1992–2003 are studied using Halogen Occultation Experiment (HALOE) satellite measurements. Interannual anomalies in water vapor with an approximate 2-yr periodicity are evident near the tropical tropopause, and these propagate vertically and latitudinally with the mean stratospheric transport circulation (in a manner analogous to the seasonal ‘‘tape recorder’’). Unusually low water vapor anomalies are observed in the lower stratosphere for 2001–03. These interannual anomalies are also observed in Arctic lower-stratospheric water vapor measurements by the Polar Ozone and Aerosol Measurement (POAM) satellite instrument during 1998–2003. Comparisons of the HALOE data with balloon measurements of lower-stratospheric water vapor at Boulder, Colorado (408N), show partial agreement for seasonal and interannual changes during 1992–2002, but decadal increases observed in the balloon measurements for this period are not observed in HALOE data. Interannual changes in HALOE water vapor are well correlated with anomalies in tropical tropopause temperatures. The approximate 2-yr periodicity is attributable to tropopause temperature changes associated with the quasi-biennial oscillation and El Niño–Southern Oscillation.”


Susan Solomon, Karen Rosenlof, Robert Portmann, John Daniel, Sean Davis, Todd Sanford, Gian-Kasper Plattner, 2010: Contributions of Stratospheric Water Vapor to Decadal Changes in the Rate of
Global Warming. / 28 January 2010 / Page 1 / 10.1126/science.1182488 (see)

where the abstract reads [highlighting added]

Stratospheric water vapor concentrations decreased by about 10% after the year 2000. Here we show that this acted to slow the rate of increase in global surface temperature over 2000-2009 by about 25% compared to that which would have occurred due only to carbon dioxide and other greenhouse gases. More limited data suggest that stratospheric water vapor probably increased between 1980 and 2000, which would have enhanced the decadal rate of surface warming during the 1990s by about 30% compared to estimates neglecting this change. These findings show that stratospheric water vapor represents an important driver of decadal global surface climate change.”

The NASA water vapor dataset would help further diagnose the global atmospheric water vapor issue, but, as discussed in

Statement By Vonder Haar Et Al 2010 on Using Existing [NASA Water Vapor] NVAP Dataset (1988 – 2001) for Trends,

while a preliminary study showed a  (1988-1999) decrease in global atmospheric water vapor (see), an updated accurate NVAP data analysis will only be available in 2012 or 2013!

The available data shows that sea surface temperature anomalies show large spatial variations, including large areas of cooler than average conditions, the lower tropospheric temperature anomaly is only slightly warmer than the long-term average (and shows no statistically significant trend since 1998), and the global water vapor anomalies, to the extent we can determine from recent data, shows that it has not increased significantly in recent years. The tropical sea surface temperatures also show large areas of cooler than average conditions.

The conclusions in the CBS news article and the statements by those interviewed failed to examine the actual current values of key climate metrics.

My Recommendations are:

1. Make the latest global average sea surface temperature anomalies available along with the spatial map.

2. Make the latest global average sea surface temperature anomalies available along with the spatial map.

3. Make the latest global tropospheric and lower stratospheric water vapor anomalies available along with the spatial map.

With this information, claims such as made by CBS, and those who were interviewed, could be quickly confirmed or refuted.

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Comment On Gavin Schmidt’s Statement of Jan 21 On Real Climate Regarding Upper Ocean Heat Content

In the Real Climate post

2010 updates to model-data comparisons

in answer to the question by Dan H.

“……any comment as to why the ocean heat content has appeared to level off during the post 2003 period?”

Gavin replies

“As for OHC, it is likely to be a combination of internal variability, not accounting for heat increases below 700m, and issues with the observing system – compare to the Lyman et al analysis. More time is required for that to become clear.”

Gavin, unfortunately, too cavalierly dismisses this issue.  First, if the leveling off of OHC is due to internal variability, than the GISS, and other models have failed to skillfully simulate this behavior.  Where have the models predicted this muting of  upper ocean heating over a six year time scale (and counting).

Second, if the heating has increased below 700m, why was the transfer of this heat through the 0-700m depths not  seen in the Argo data?

Finally, perhaps there are remaining problems with the observing system. Neither Gavin or I are an expert on this subject. However, I do have expertise in the assessment in the long term monitoring of surface air temperature trends; e.g. see

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.

 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., 114, D21102, doi:10.1029/2009JD011841.

Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2010: Correction to: “An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J. Geophys. Res., 114, D21102, doi:10.1029/2009JD011841″, J. Geophys. Res., 115, D1, doi:10.1029/2009JD013655.

Gavin is selective in the validation information he uses to compare with the GISS model results.  He used the surface temperature trend data since it bolsters his conclusions, but fails to discuss the systematic warm bias that has been found in that data.

What is needed are independent assessments of the skill at these models at predicting climate metrics including upper ocean heat content . 

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