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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Filed under Climate Models, Research Papers

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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Filed under Climate Science Misconceptions, Climate Science Reporting, Extreme Weather

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

and

Comments #55 in http://rogerpielkejr.blogspot.com/2009/08/evidence-that-global-temperature-trends.html#c6757055539660809722

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Filed under Climate Change Metrics

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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Filed under Climate Change Forcings & Feedbacks, Climate Science Reporting

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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Filed under Climate Change Forcings & Feedbacks, Research Papers

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.

and

“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 http://www.osdpd.noaa.gov/data/sst/anomaly/2011/anomnight.1.24.2011.gif].

The most recent global average lower tropospheric temperature anomaly is given below [from http://www.remss.com/msu/msu_data_description.html]

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.”

and

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. http://www.sciencexpress.org / 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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Filed under Bias In News Media Reports, Climate Science Misconceptions, Climate Science Reporting

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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Publication Of “Comments on ‘A Unified Modeling Approach to Climate System” By R. A. Pielke Sr And “Reply” By Hurrell Et Al 2010

After a year and a half (- since September 24 2009 – see), the Bullein of the American Meterological Society has finally published my Comment on the article

James Hurrell, Gerald A. Meehl, David Bader, Thomas L. Delworth, Ben Kirtman, Bruce Wielicki
Bulletin of the American Meteorological Society, 2009: A Unified Modeling Approach to Climate System Prediction; Volume 90, Issue 12 (December 2009) pp. 1819-1832

My article is

Comments on “A Unified Modeling Approach to Climate System Prediction” by Roger A. Pielke Sr.
http://journals.ametsoc.org/doi/pdf/10.1175/2010BAMS2975.1

and the Hurrell at al reply is

Reply –  James W. Hurrell, Gerald A. Meehl, Dave Bader, Thomas L. Delworth, Ben Kirtman, Bruce Wielick.
http://journals.ametsoc.org/doi/pdf/10.1175/2010BAMS3118.1

I am commenting on the Hurrell et al Reply below. I have excerpted text from their Reply and commented below each excerpt

“Modeling evidence to date demonstrates long-term climate change is primarily a boundary value problem associated with changes in radiative forcing.”

This statement conflicts with the extensive evidence that climate is significantly affected by forcings beyond radiative forcings. For example, in

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

it is reported that

“Several types of forcings—most notably aerosols, land-use and land-cover change, and modifications to biogeochemistry—impact the climate system in nonradiative ways, in particular by modifying the hydrological cycle and vegetation dynamics. Aerosols exert a forcing on the hydrological cycle by modifying cloud condensation nuclei, ice nuclei, precipitation efficiency, and the ratio between solar direct and diffuse radiation received. Other nonradiative forcings modify the biological components of the climate system by changing the fluxes of trace gases and heat between vegetation, soils, and the atmosphere and by modifying the amount and types of vegetation. No metrics for quantifying such nonradiative forcings have been accepted. Nonradiative forcings have eventual radiative impacts, so one option would be to quantify these radiative impacts. However, this approach may not convey appropriately the impacts of nonradiative forcings on societally relevant climate variables such as precipitation or ecosystem function.”

The recently (2010) adopted official American Meteorological Society statement Inadvertent Weather Modification contains the text

“The cumulative changes in surface and atmospheric heat and moisture profiles [from aerosol radiative effects, cloud-mediated effects of aerosols, and changes in land use] modify atmospheric circulation and weather patterns on all scales, including synoptic storm tracks, in ways that are just beginning to be explored. In the aggregate, these changes can affect air quality, ecosystems, and water resources. The cumulative impacts of inadvertent weather modification may thus result in local or regional-scale climatic alterations superimposed on, and interacting with, natural and GHG-induced climate variability and change”

and

” High-priority research and new technological capabilities are required to improve understanding of the impacts of inadvertent weather modification………..research efforts on unintended weather modification should be recognized as addressing parts of the broader question of climate variability and change, which crosses geopolitical boundaries.”

Hurrell et al continue in their Reply

Pielke (2010) confuses the distinction between predicting the evolution of individual weather events beyond two weeks or so and the possibility of predicting changes in the statistics of weather events. Changes in forcing external to the climate system, as well as the amplification or diminution of the resulting changes in climate due to feedback mechanisms, can lead to predictable changes in weather statistics.

Unfortunately, the confusion is not mine.  The only difference between weather forecasts of daily weather and the forecasts of the statistics of weather (i.e., “climatology) is the averaging time. For example, a 24 hour average temperature for tomorrow, January 20 2011 is clearly considered weather (an average over 24 hours). However, so is the 2011-2020 average temperature for those ten January 20ths.

Hurrell et al also write

Consider the proven ability of climate models to simulate the annual cycle of seasonal variations (i.e., the changes in climate from winter to summer) or their ability to capture past excursions of climate resulting from changes in both natural and anthropogenic forcing, including the amount of solar energy reaching Earth, the amount of particulate matter in the atmosphere from volcanic eruptions, and atmospheric concentrations of anthropogenic gases and particles. The impressive fidelity of the twentieth-century climate simulations assessed in the latest report of the Intergovernmental Panel on Climate Change (Solomon et al. 2007) is a good example….

The models have been successful in simulating the annual cycle.   However, there has not been skill in predicting changes in the climate system despite what Hurell et al wrote. As just one (excellent) example, the paper

Anagnostopoulos, G. G., Koutsoyiannis, D., Christofides, A., Efstratiadis, A. & Mamassis, N. (2010) A comparison of local and aggregated climate model outputs with observed data. Hydrol. Sci. J. 55(7), 1094–1110.

concludes that

We compare the output of various climate models to temperature and precipitation observations at 55 points around the globe.We also spatially aggregate model output and observations over the contiguous USA using data from 70 stations, and we perform comparison at several temporal scales, including a climatic (30-year) scale. Besides confirming the findings of a previous assessment study that model projections at point scale are poor, results show that the spatially integrated projections are also poor.

Hurrell et al also write

“….there is ample evidence that climate models can capture nonlinear change thresholds and feedbacks (e.g., Holland et al. 2006; Pitman and Stouffer 2006).”

We report in our paper (with specific examples)

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

that 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, and multiple equilibria are the norm….there is a relatively poor understanding of the different types of nonlinearities, how they manifest under various conditions .and whether they reflect a climate system driven by astronomical forcings, by internal feedbacks, or by a combination of both.”

The claim by Hurrell et al that “climate models can capture nonlinear change thresholds and feedbacks”  grossly overstates their capabilities. They have failed, for example, to skillfully predict (or even simulate) the time evolution of such major climate features as El Niño, La Niña, the Pacific Decadal Ocsillation and the North Atlantic Oscillation. One of the examples that Hurrell et al present to bolster their claim that “that climate models can capture nonlinear change thresholds”   [Holland et al, 2006: Future abrupt reductions in summer arctic sea ice] is a model prediction for the coming decades! 

The excerpt from Hurrell et al is

“We do agree with Pielke (2010) that the effects of initial conditions and the presence of significant nonlinearities become more important when regional climate change over the next few decades is considered…”

This statement appears to almost completely refute what they reported earlier in their Reply where they wrote 

“Modeling evidence to date demonstrates long-term climate change is primarily a boundary value problem associated with changes in radiative forcing.”

Thus while I appreciate the opportunity to have a Comment/Reply interaction with the authors of the Hurrell et al 2009 paper. they remain unresolved issues they have not yet adequately addressed.

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Confessions In The News On The “Predictability” Of The Climate System

I was alerted to a post on Climate Progress (h/t to Dan Hughes) titled

Another terrific ABC News story — on the role global warming is playing in extreme winter weather

where it is written

“ABC news contacted 10 climate scientists to ask their take, if the extreme winter like the one we’re having is the way of the future.  The consensus:  global warming is playing a role by shifting weather patterns in unpredictable ways.  Many say the forecast for the future calls for record-breaking precipitation and extreme temperatures year-round — and that means winter with more snow”

This statement encapsulates where we are in being able to predict the climate in the coming years and decades. Climate, as affected by both natural and human forcings and feedback, is unpredictable on these time scales!

The message that weather patterns shift in unpredictable ways is one the policymakers and others should recognize. While added CO2 undoubtedly plays a role, there are other first order human climate forcings as well as the effect of poorly understood natural variations.

As we wrote in our paper

Pielke Sr., R., K. Beven, G. Brasseur, J. Calvert, M. Chahine, R. Dickerson, D. Entekhabi, E. Foufoula-Georgiou, H. Gupta, V. Gupta, W. Krajewski, E. Philip Krider, W. K.M. Lau, J. McDonnell,  W. Rossow,  J. Schaake, J. Smith, S. Sorooshian,  and E. Wood, 2009: Climate change: The need to consider human forcings besides greenhouse gases. Eos, Vol. 90, No. 45, 10 November 2009, 413. Copyright (2009) American Geophysical Union

we concluded, with respect to human climate forcings,  that

“…..the 2007 Intergovernmental Panel on Climate Change (IPCC) assessment did not sufficiently acknowledge the importance of these other human climate forcings in altering regional and global climate and their effects on predictability at the regional scale.”

The hypothesis that we reported in our paper as being supported by real world data is

“Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and involve a diverse range of first-order climate forcings, including, but not limited to, the human input of carbon dioxide (CO2). Most, if not all, of these human influences on regional and global climate will continue to be of concern during the coming decades”

differs significantly from the 2007 IPCC conclusions.

The ABC news article interview of the climate scientists is actually a confession of the failure of the scientific robustness of the 2007 IPCC WG 1 report.

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Guest Post “Global Floods – Why Were They Not Predicted?” By Will Alexander

Will Alexander has provided us with another excellent guest post which is presented below.  WJR (Will) Alexander is Professor Emeritus of the Department of Civil Engineering of the University of Pretoria, South Africa, and Honorary Fellow of the South African Institution of Civil Engineering. See also his previous posts

Climate Change: The West vs The Rest by Will Alexander

A Guest Weblog By Will Alexander “Climategate Chaos”

*************************************************************************************

Memo 01/11

Will Alexander alexwjr[at]iafrica.com

Monday 17 January 2011 while on holiday with our family in Adelaide, Australia.

Global floods – why were they not predicted?

Do you recall the following quote in my semi-final Memo 15/10 of  2 August 2010?

Scientific predictability also raises the question of the scientist’s ethical responsibilities. His conclusions must be guided by respect for truth and an honest acknowledgment of both the accuracy and the inevitable limitations of the scientific method. Certainly this means avoiding needlessly alarming predictions when these are not supported by sufficient data or exceed science’s actual ability to predict. But it also means avoiding the opposite, namely a silence, born of fear, in the face of genuine problems.
    –Pope Benedict XVI, 6 November 2006

My subsequent Memo 16/10 dated 2 August last year was titled Final Summary. It was intended to be my time to say goodbye. The last six months of 2010 were particularly stressful both personally and professionally. Our son died of cancer and I had problems with our Water Research Commission.

In June 2008 my general interest article “Likelihood of a global drought in 2009 to 2016″ was published in Civil Engineering. Droughts followed within months along the southern Cape coast and the adjacent interior as well as elsewhere in South Africa, Australia and other regions. Seawater desalination plants had to be constructed at Sedgefield and Plettenburg Bay as well as in Australia.

Those who took the trouble to study my 2008 article would have noticed the abundantly clear, sudden alternating sequences of high and low values in the hydrometeorological time series. Floods follow droughts as night follows day. This photograph of the flood in the Orange River at Aughrabies Falls in South Africa was taken on the same day as severely damaging floods entered Brisbane in Australia. It was also simultaneous with the loss of life by severe floods in Sri Lanka and Brazil. They were not the worst on record.

 

Flood in the Orange River at Aughrabies Falls in South Africa on 12 January 2011.

I now have a simple question. Were these global extremes the consequence of weather or climatic phenomena?   Nobody seems to know. In either case the answer is irrelevant. The claimed consensus views of hundreds of climate change scientists are fundamentally erroneous. Hundreds of peer reviewed papers published in the hydrological literature during the past 50 years demonstrated that climate is NOT a steady state phenomenon. Also, together with my colleagues, research assistants and students we demonstrated that variations in regional climate are the consequence of variations in the receipt and poleward redistribution of solar energy via the global oceanic and atmospheric processes. We could not find any evidence to support the views that these variations are the consequence of human activities. Unfortunately we encountered the same indifference that David Livingstone encountered during his missionary expeditions in Central Africa.

UK Met Office in deep water

The following comments are based on information from the Internet. It appears that routine studies by the UK Met Office last October indicated the possibility of severe winter conditions in the months ahead. The Met Office warned the authorities but not the public. This is a routine procedure where there is a measure of uncertainty about the forecast. The authorities then issue standby alerts to the organisations that will be involved should the events occur.

The problem arose when the Met Office also issued its own forecasts that deliberately withheld this information from the public in view of the level of uncertainty. Confusion arose when the authorities failed to issue the standby alerts and subsequent warnings to the public.

Normally this would be a domestic matter for the UK authorities to resolve. However, it is now very clear that this was a global climatic disturbance. So we must now ask a fundamentally important question. Why was it not predicted by all those international agencies with their sophisticated and costly global climate computer models?

Their self-made problem is that they have become so involved in the climate change issue that they dare not predict extreme events without blaming global warming. In this case we have the near simultaneous extreme cold weather and damaging snowfalls in the UK, Europe and parts of the USA, followed almost immediately by damaging floods in Australia, Sri Lanka, South Africa and Brazil that caused loss of life in all these countries. If these events were the worst on record, climate change scientists would have been home and dry. They could claim that they were obviously the consequence of global warming, but this was not so.

Controlled flood discharge from Vaal Dam in 1974

[ I was directly responsible for the operation of Vaal Dam during this period.]

Why did the GCMs fail to predict these extreme global events?

I continue this memo with a very serious challenge. The last time that floods of this magnitude occurred concurrently in South Africa and Australia was in 1974, approaching 40 years ago. There were three other global climatic events at that time. What were they? One had to do with global temperatures (conveniently overlooked by climate change scientists). The second was a well documented global climatic disturbance. The third had to do with the Southern Oscillation Index and possibly other climatic indices. Why have climate change scientists not investigated and reported the obvious causal linkage between these four concurrent global climatic events? This is a fundamentally important question.

I also have a more general question that climate change scientists have yet to address. What causes the El Niño/La Nina phenomena? How often have we been told that climate science is settled when they cannot even answer this obvious question?

It gets worse!

In April 2008 I was granted an urgent interview with the Council of the South African Institution of Civil Engineering. The following are short extracts from my submission titled Urgent submission to the SAICE Council on the likelihood of severe water resource droughts.

Civil engineers and climate change scientists are on a collision course.  The outcome could have very serious, nationally important consequences.  These differences should be resolved as a matter of urgency.

In this submission it is demonstrated with a very high degree of assurance that southern Africa, and possibly the rest of the world as well, is about to enter a period of severe droughts commencing within the next twelve months.  There is an estimated 20% likelihood that they will be as serious as the Great Depression Drought of the early 1930s.  These drought sequences could have disastrous consequences for South Africa if the authorities are caught unawares.

This prediction is based on the well researched multi-year periodic behaviour of the hydro-meteorological processes.  It is shown that this periodicity is in turn causally related to synchronous variations in solar activity.  This linkage is well documented, and has been studied in South Africa for more than a hundred years.

However, climate change scientists vigorously deny both the predictable, multi-year periodicity in the hydro-meteorological processes, as well as the solar linkage.

The diagram below is our river flow prediction model prepared by my co-author Alwyn vd Merwe. We are presently in period year 13 (2007-08).

Note the very clear, well above average recorded river flows for the present hydrological year (13). Even more importantly, note the succession of below average river flows in the period years that lie ahead (14 to 20). Analyses of other long hydrological data series show similar characteristics.    

Climate change scientists use complex global climate computer models to predict a whole range of undesirable consequences.  These include increases in the magnitude and frequency of damaging floods, droughts and threats to water supplies.  They go further, and specifically maintain that there is no linkage between variations in solar activity and climatic responses.  They are forced to do this, as an admission would diminish their claims of exclusive human causality of the postulated consequences of global warming.

I emphasise the word ‘postulated’, because the claims are based on unverified (and unverifiable) computer models.  This is the essence of my problem.  There is simply no evidence in the hydrological data to support these claims. For example, during the 20 years since the establishment of the IPCC in 1988, there have been no floods or droughts that have exceeded the historical maxima. Nor are there any observable trends in the rainfall and river flow data. 

My own position and responsibilities are very clear.  Since 1993 I have devoted considerable time and effort in a search for evidence that would support these claims.  Had I found this evidence, I would not have hesitated for one moment to report it and include it in my teaching, publications, articles and our Hydro course notes.

I therefore have an equal if unpleasant responsibility. It is to report that there is no observable substance to claims related to the effects of climate change on river flow and South Africa’s water resources.

I appreciate that the contents of this document are likely to be hotly contested as lucrative research funding is at stake. This debate should be encouraged, provided it is conducted in an appropriate forum where both sides are given the opportunity to present their views. In this connection I must place on record that my several attempts to have round table discussions on this subject were either refused or ignored. 

My concern was and still is the occurrence of droughts rather than floods. Fifty lives were lost in South Africa during the recent floods, but droughts of equal severity affect the lives of tens of thousands of people.

These were not the only consequences of the recent climatic disturbances that I predicted in 2008. The following information is from a report by the well-known reinsurers Swiss Re. The year 2010 was the year of natural disasters. The last time that so many lives were lost in natural disasters was in 1983 mainly caused by famine in Ethiopia (my emphases).

Conclusions

Putting all the information in this memo together, it is very clear that there have been no systematic increases in natural disasters that can be attributed to human caused global warming during the period of continuous records. Equally, it demonstrates the validity of our studies that demonstrate the causal solar linkage and the predictability of subcontinental scale alternating above and below average hydrometeorological conditions. These conclusions have long been rejected in the IPCC literature.

This whole climate change issue has become chaotic. When chaos prevails the consequences become unpredictable – and dangerous. It will be very interesting to see how this situation is handled in the months ahead as climate change scientists sink deeper and deeper into a quagmire of their own making.                  

My handbooks

April 2000. Flood risk reduction measures. 560 pp

2011. Analytical methods for water resource development and management. 500+ pp.

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