Documentation Of Bias In The 2007 IPCC WG1 Report – Part II

As I reported yesterday, there has been considerable discussion of the 2007 IPCC report and its errors and exclusion of peer reviewed scientific perspectives that differ from those of the lead author (e.g. see Judy Curry’s perceptive discussion of this topic). In 2007, I documented this clear bias in the IPCC reports in my second post on this subject  in 2007 (Part I appeared yesterday).

The 2007 post is

Documentation Of IPCC WG1 Bias by Roger A. Pielke Sr. and Dallas Staley – Part II

I have reproduced this demonstration of bias below, as it is directly relevant to the current well-justified concerns on the accuracy, balance and value of the 2007 IPCC WG1 report.

Among the findings of the 2005 National Research Council report

Radiative Forcing of Climate Change: Expanding the Concept and Addressing Uncertainties

are

I. “Determine the Importance of Regional Variation in Radiative Forcing

Regional variations in radiative forcing may have important regional and global climatic implications that are not resolved by the concept of global mean radiative forcing. Tropospheric aerosols and landscape changes have particularly heterogeneous forcings. To date, there have been only limited studies of regional radiative forcing and response. Indeed, it is not clear how best to diagnose a regional forcing and response in the observational record; regional forcings can lead to global climate responses, while global forcings can be associated with regional climate responses. Regional diabatic heating can also cause atmospheric teleconnections that influence regional climate thousands of kilometers away from the point of forcing. Improving societally relevant projections of regional climate impacts will require a better understanding of the magnitudes of regional forcings and the associated climate responses.

PRIORITY RECOMMENDATIONS:

Use climate records to investigate relationships between regional radiative forcing (e.g., land-use or aerosol changes) and climate response in the same region, other regions, and globally.

Quantify and compare climate responses from regional radiative forcings in different climate models and on different timescales (e.g., seasonal, interannual), and report results in climate change assessments.

II. Determine the Importance of Nonradiative Forcings

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. Any new metrics must also be able to characterize the regional structure in nonradiative forcing and climate response.

PRIORITY RECOMMENDATIONS:

Improve understanding and parameterizations of aerosol-cloud thermodynamic interactions and land-atmosphere interactions in climate models in order to quantify the impacts of these nonradiative forcings on both regional and global scales.

Develop improved land-use and land-cover classifications at high resolution for the past and present, as well as scenarios for the future.”

Did the IPCC WG1 Statement for Policymakers adequately discuss these issues? The answer is NO. However, these topics are discussed in Chapter 7, where, for example, it is written,

“The consequences of changes in atmospheric heating from land changes at a regional scale are similar to those from ocean temperature changes such as from El Niño, potentially producing patterns of reduced or increased cloudiness and precipitation elsewhere to maintain global energy balance. Attempts have been made to find remote adjustments (e.g., Avissar and Werth, 2005). Such adjustments may occur in multiple ways, and are part of the dynamics of climate models. The locally warmer temperatures can lead to more rapid vertical decreases of atmospheric temperature so that at some level overlying temperature is lower and radiates less. The net effect of such compensations is that averages over larger areas or longer time scales commonly will give smaller estimates of change. Thus, such regional changes are better described by local and regional metrics or at larger scales by measures of change in spatial and temporal variability rather than simply in terms of a mean global quantity.”

Why was not this conclusion headlined in the policy statement that was transmitted to the politicians?

Chapter 8 of the IPCC Report is much more poorly written on this subject

where while they write

“Evaluation of the land surface component in coupled models is severely limited by the lack of suitable observations. The terrestrial surface plays key climatic roles in influencing the partitioning of available energy between sensible and latent heat fluxes, determining whether water drains or remains available for evaporation, determining the surface albedo and whether snow melts or remains frozen, and influencing surface fluxes of carbon and momentum. Few of these can be evaluated at large spatial or long temporal scales. This section therefore evaluates those quantities for which some observational data exist”

they fail to identify the rich peer-reviewed literature on this subject but only provide a very limited presentation on this subject in the Chapter.

Indeed, while land processes are discussed in the Report, the focus is on its role in the carbon budget and in its effect on the global average radiative forcing.

To document missing papers, as with Part I (see and see) we have cross-referenced Climate Science with the IPCC WG1 Report on just one aspect of the above two topics (regional radiative forcing and nonradiative forcing), namely the role of land use change within the climate system.

This cross-referencing is given below where a bold face means that it appeared in the IPCC Report and the Chapter in which it appears is given. The IPCC Chapters referred to below have the titles

Chapter 2 Changes in Atmospheric Constituents and in Radiative Forcing

Chapter 6 Palaeoclimate

Chapter 7 Couplings Between Changes in the Climate System and Biogeochemistry

Chapter 8 Climate Models and their Evaluation

Chapter 10 Global Climate Projections

Chapter 11 Regional Climate Projections

II. ROLE OF LAND-USE CHANGE AS A MAJOR CLIMATE FORCING

Avissar, R., and Y. Liu, 1996: Three-dimensional numerical study of shallow convective clouds and precipitation induced by land surface forcing. J. Geophys. Res., 101(D3), 7499-7518, 10.1029/95JD03031.

Avissar, R., and D. Werth, 2005: Global hydroclimatological teleconnections resulting from. tropical deforestation. J. Hydrometeor., 6, 134–145. IN CHAPTER 7 & CHAPTER 11 IN CHAPTER 2 & CHAPTER 8

Brovkin, V., M. Claussen, E. Driesschaert, T. Fichefet, D. Kicklighter, M. F. Loutre, H. D. Matthews, N. Ramankutty, M. Schaeffer, and A. Sokolov, 2006: Biogeophysical effects of historical land cover changes simulated by six Earth system models of intermediate complexity. Climate Dynamics, 1-14, DOI: 10.1007/s00382-005-0092-6.

Cai, M., and E. Kalnay, 2004: Response to the comments by Vose et al. and Trenberth. Impact of land-use change on climate, Nature, 427, 214, doi:10.1038/427214a.

Chase, T.N., R.A. Pielke, T.G.F. Kittel, R.R. Nemani, and S.W. Running, 2000: Simulated impacts of historical land cover changes on global climate in northern winter. Climate Dynamics, 16, 93-105. IN CHAPTER 2 & CHAPTER 11

Chase, T.N., R.A. Pielke, Sr., T.G.F. Kittel, M. Zhao, A.J. Pitman, S.W. Running, and R.R. Nemani, 2001: The relative climatic effects of landcover change and elevated carbon dioxide combined with aerosols: A comparison of model results and observations. J. Geophys. Res., Atmospheres, 106, 31,685 -31,691.

Claussen, M., C. Kubatzki, V. Brovkin, A. Ganopolski, P. Hoelzmann, H.-J. Pachur, 1999; Simulation of an abrupt change in Saharan vegetation in the mid-Holocene. Geophys. Res. Lett., 26(14), 2037-2040, 10.1029/1999GL900494. IN CHAPTER 6, CHAPTER 10 & CHAPTER 11

Cotton, W.R. and R.A. Pielke, 2007: Human impacts on weather and climate. Cambridge University Press, 330 pp.

Cox, P. M., R. A. Betts, C. D. Jones, S. A. Spall, and I. J. Totterdell, 2000: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature, 408, 184-187. IN CHAPTER 7, CHAPTER 8, CHAPTER 10 & CHAPTER 11

Cui, X., H.-F. Graf, B. Langmann, W. Chen, and R. Huang, 2006: Climate impacts of anthropogenic land use changes on the Tibetan Plateau, Global and Planetary Change, 54, 1-2, 33-56.

Eastman, J.L., M.B. Coughenour, and R.A. Pielke, 2001: The effects of CO2 and landscape change using a coupled plant and meteorological model. Global Change Biology, 7, 797-815.

Eugster, W., W.R. Rouse, R.A. Pielke, J.P. McFadden, D.D. Baldocchi, T.G.F. Kittel, F.S. Chapin III, G.E. Liston, P.L. Vidale, E. Vaganov, and S. Chambers, 2000: Land-atmosphere energy exchange in Arctic tundra and boreal forest: available data and feedbacks to climate. Global Change Biology, 6, 84-115.

Feddema, J.J., K.W. Oleson, G.B. Bonan, L.O. Mearns, L.E. Buja, G.A. Meehl, and W.M. Washington, 2005: The importance of land-cover change in simulating future climates. Science, 310, 1674-1678. IN CHAPTER 10IN CHAPTER 7, CHAPTER 8, & CHAPTER 11

Foley, J.A., R. DeFries, G.P. Asner, C. Barford, G. Bonan, S.R. Carpenter, F.S. Chapin, M.T. Coe, G.C. Daily, H.K. Gibbs, J.H. Helkowski, T. Holloway, E.A. Howard, C.J. Kucharik, C. Monfreda, J.A. Patz, I.C. Prentice, N. Ramankutty, and P.K. Snyder, 2005: Global consequences of land use. Science, 309, 570-574. IN CHAPTER 11

Friedlingstein P., L. Bopp, P. Ciais, J.-L Dufresne, L. Fairhead, H. LeTreut, P. Monfray, and J. Orr, 2001: Positive feedback between future climate change and the carbon cycle. Geophys. Res. Lett., 28, 1543-1546.

Gero, A.F., A.J. Pitman, G.T. Narisma, C. Jacobson, and R.A. Pielke Sr., 2006: The impact of land cover change on storms in the Sydney Basin. Global and Planetary Change, 54, 57-78.

Gibbard, S., K. Caldeira, G. Bala, T. J. Phillips, and M. Wickett, 2005: Climate effects of global land cover change. Geophys. Res. Lett., 32, L23705, doi:10.1029/2005GL024550.

Hoffmann, W.A., and R.B. Jackson, 2000: Vegetation-climate feedbacks in the conversion of tropical savanna to grassland. J. Climate, 13, 1593–1602.

Holt, T.R., D. Niyogi, F. Chen, K. Manning, M.A. LeMone, and A. Qureshi, 2006: Effect of land–atmosphere interactions on the IHOP 24–25 May 2002 convection case. Mon. Wea. Rev., 134, 113–133.

Kleidon, A., 2006: The climate sensitivity to human appropriation of vegetation productivity and its thermodynamic characterization. Global and Planetary Change, 54, 109-127. doi:10.1016/j.gloplacha.2006.01.016

Lawton, R.O., U.S. Nair, R.A. Pielke Sr., and R.M. Welch, 2001: Climatic impact of tropical lowland deforestation on nearby montane cloud forests. Science, 294, 584-587.

Lee, E., R.S. Oliveira, T.E. Dawson, and I. Fung, 2005: Root functioning modifies seasonal climate. Proceedings of the National Academy of Sciences, 102, no. 49, 17576-17581.

Mahmood, R., S.A. Foster, T. Keeling, K.G. Hubbard, C. Carlson and R. Leeper, 2006: Impacts of irrigation on 20th century temperature in the northern Great Plains. Global and Planetary Change, 54, 1-18. doi:10.1016/j.gloplacha.2005.10.004.

Marland, G., R.A. Pielke, Sr., M. Apps, R. Avissar, R.A. Betts, K.J. Davis, P.C. Frumhoff, S.T. Jackson, L. Joyce, P. Kauppi, J. Katzenberger, K.G. MacDicken, R. Neilson, J.O. Niles, D. dutta S. Niyogi, R.J. Norby, N. Pena, N. Sampson, and Y. Xue, 2003: The climatic impacts of land surface change and carbon management, and the implications for climate-change mitigation policy. Climate Policy, 3, 149-157. IN CHAPTER 11

Marshall, C.H. Jr., R.A. Pielke Sr., L.T. Steyaert, and D.A. Willard, 2004: The impact of anthropogenic land-cover change on the Florida peninsula sea breezes and warm season sensible weather. Mon. Wea. Rev., 132, 28-52.

Marshall, C.H., R.A. Pielke Sr., and L.T. Steyaert, 2004: Has the conversion of natural wetlands to agricultural land increased the incidence and severity of damaging freezes in south Florida? Mon. Wea. Rev., 132, 2243-2258.

Millán, M. M., Mª. J. Estrela, M. J. Sanz, E. Mantilla, M. Martín, F. Pastor, R. Salvador, R. Vallejo, L. Alonso, G. Gangoiti, J.L. Ilardia, M. Navazo, A. Albizuri, B. Artiñano, P. Ciccioli, G. Kallos, R.A. Carvalho, D. Andrés, A. Hoff, J. Werhahn, G. Seufert, B, Versino, 2005: Climatic Feedbacks and Desertification: The Mediterranean model. J. Climate, 18 (5), 684-701.

Myhre, G., Y. Govaerts, J. M. Haywood, T. K. Berntsen, and A. Lattanzio, 2005:Radiative effect of surface albedo change from biomass burning. Geophys. Res. Lett., 32, L20812, doi:10.1029/2005GL022897.

Nair, U.S., R.O. Lawton, R.M. Welch, and R.A. Pielke Sr., 2003: Impact of land use on Costa Rican tropical montane cloud forests: 1. Sensitivity of cumulus cloud field characteristics to lowland deforestation. J. Geophys. Res. – Atmospheres, 108, 10.1029/2001JD001135.

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. Referenced as Jacob et al. in the IPCC; IN CHAPTER 2

Nemani, R.R., S.W. Running, R.A. Pielke, and T.N. Chase, 1996: Global vegetation cover changes from coarse resolution satellite data. J. Geophys. Res., 101, 7157-7162.

Niyogi, D., T. Holt, S. Zhong, P.C. Pyle, and J. Basara, 2006: Urban and land surface effects on the 30 July 2003 mesoscale convective system event observed in the southern Great Plains. J. Geophys. Res., 111, D19107, doi:10.1029/2005JD006746.

Notaro, M., Z. Liu, R. Gallimore, S.J. Vavrus, J.E. Kutzbach, I.C. Prentice, and R.L. Jacob, 2005: Simulated and observed preindustrial to modern vegetation and climate changes. J. Climate, 18, 3650–3671.

Pielke Sr., R.A., 2001: Influence of the spatial distribution of vegetation and soils on the prediction of cumulus convective rainfall. Rev. Geophys., 39, 151-177. IN CHAPTER 7

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

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. IN CHAPTER 2 & CHAPTER 11

Pitman, A.J., G.T. Narisma, R.A. Pielke Sr., and N.J. Holbrook, 2004: The impact of land cover change on the climate of southwest western Australia. J. Geophys. Res., 109, D18109, doi:10.1029/2003JD004347.

Ramunkutty, N., C. Delire and P. Snyder, 2006: Feedbacks between agriculture and climate: An illustration of the potential unintended consequences of human land use activities. Global and Planetary Change, 54, 1-2, 79-93, doi:10.1016/j.gloplacha.2005.10.005

Ray, D.K., U.S. Nair, R.O. Lawton, R.M. Welch, and R.A. Pielke Sr., 2006: Impact of land use on Costa Rican tropical montane cloud forests. Sensitivity of orographic cloud formation to deforestation in the plains. J. Geophys. Res., 111, doi:10.1029/2005JD006096.

Ray, D.K., R.M. Welch, R.O. Lawton, and U.S. Nair, 2006: Dry season clouds and rainfall in northern Central America: Implications for the Mesoamerican Biological Corridor. Global and Planetary Change, 54, 150-162.

Salmun, H., and A. Molod, 2006: Progress in modeling the impact of land cover change on the global climate. Progress in Physical Geography, 30, 737–749.

Sturm, M., T. Douglas, C. Racine, and G.E. Liston, 2005: Changing snow and shrub conditions affect albedo with global implications. J. Geophys. Res., 110, G01004, doi:10.1029/2005JG000013. IN CHAPTER 7

TerMaat, H.W., R.W.A. Hutjes, R. Ohba, H. Ueda, B. Bisselink and T. Bauer, 2006: Meteorological impact assessment of possible large scale irrigation in Southwest Saudi Arabia. Global and Planetary Change, 54, 183-201.

Timbal, B., and J.M. Arblaster, 2006: Land cover change as an additional forcing to explain the rainfall decline in the south west of Australia. Geophys. Res. Lett., 33, L07717, doi:10.1029/2005GL025361.

van der Molen, M.K., A.J. Dolman, M.J. Waterloo and L.A. Bruijnzeel, 2006: Climate is affected more by maritime than by continental land use change: A multiple scale analysis. Global and Planetary Change, 54, 128-149.

Werth, D., and R. Avissar, 2002: The local and global effects of Amazon deforestation. J. Geophys. Res., 107, 8087, doi:10.1029/2001JD000717

Here are several summary points from this assessment:

1. The 2005 NRC Report was only cited in one chapter (Chapter 2), and its recommendations are not considered in any of the following chapters.

2. None of the papers were cited in Chapter 9 which is entitled “Understanding and Attributing Climate Change“. As documented in the papers listed above, the attribution of climate change cannot be accurately accomplished without including land surface processes, including land use change.

3. The important role of land surface processes in the IPCC chapters is presented in a sporadic fashion without the needed focused evaluation of its role, as recommended in the 2005 NRC Report. The 2007 IPCC Report did not adequately honor the charge of the IPCC WG1 Report to provide “A comprehensive and rigourous picture of the global present state of knowledge of climate change”.

Finally, if one suggests that the set of papers that were referenced in the IPCC report are a representative sample that cover the range of issues with the role of land surface processes (which Climate Science concludes is not the case), than refer us to the text in the IPCC report that addresses the issue of the importance of regional radiative and non-radiative climate forcings on the climate system. The IPCC Report fails on this much needed assessment of the role of humans in the climate system.

Documentation Of Bias In The 2007 IPCC WG1 Report – Part I

There has been considerable discussion of the 2007 IPCC reports and its errors and exclusion of peer reviewed scientific perspectives that differ from those of the IPCC lead authors (e.g. see Judy Curry’s perceptive discussion of this topic). In 2007, I documented this clear bias in the IPCC reports in two posts (the second one will appear tomorrow).

I have reproduced this demonstration of bias below, as it is directly relevant to the current well-justified concerns on the accuracy, balance and value of the 2007 IPCC WG1 report.

The 2007 post is

Documentation Of IPCC WG1 Bias by Roger A. Pielke Sr. and Dallas Staley – Part I

The 2007 Intergovernmental Panel on Climate Change (IPCC) Reports have the following stated goals:

“A comprehensive and rigourous picture of the global present state of knowledge of climate change”

and

“The Intergovernmental Panel on Climate Change (IPCC) has been established by WMO and UNEP to assess scientific, technical and socio-economic information relevant for the understanding of climate change, its potential impacts and options for adaptation and mitigation.”

However, the IPCC WG 1 Chapter 3 report failed in this goal.

This weblog illustrates this defect using the example of their assessment of the multi-decadal land near-surface temperature trend data, where peer reviewed papers that conflicted with the robustness of the surface air temperature trends are ignored. Later Climate Science weblogs will document this issue with other climate issues.

Readers of Climate Science are invited to present other important peer reviewed papers that were available to the IPCC that were ignored in their assessment as further evidence to document IPCC bias.

To evaluate the IPCC’s claim to be comprehensive, we cross-compared IPCC WG1 references on near-surface air temperature trends with the peer-reviewed citations that have been given in Climate Science. We selected only papers that appeared before about May 2006 so they were readily available to the IPCC Lead authors.

The comparison follows where the bold faced citations are in the IPCC WG1 Report:

I. ISSUES WITH THE ROBUSTNESS OF THE IPCC CONFIDENCE IN THE SURFACE TEMPERATURE RECORD

Chase, T.N., R.A. Pielke Sr., J.A. Knaff, T.G.F. Kittel, and J.L. Eastman, 2000: A comparison of regional trends in 1979-1997 depth-averaged tropospheric temperatures. Int. J. Climatology, 20, 503-518.

Davey, C.A., and R.A. Pielke Sr., 2005: Microclimate exposures of surface-based weather stations – implications for the assessment of long-term temperature trends. Bull. Amer. Meteor. Soc., Vol. 86, No. 4, 497–504.

Davey, C.A., R.A. Pielke Sr., and K.P. Gallo, 2006: Differences between near-surface equivalent temperature and temperature trends for the eastern United States – Equivalent temperature as an alternative measure of heat content. Global and Planetary Change, 54, 19–32.

de Laat, A.T.J. and A.N. Maurellis, 2006: Evidence for influence of anthropogenic surface processes on lower tropospheric and surface temperature trends. International Journal of Climatology, 26, 897-913.

González, J. E., J. C. Luvall, D. Rickman, D. E. Comarazamy, A. J. Picón, E. W. Harmsen, H. Parsiani, N. Ramírez, R. Vázquez, R. Williams, R. B. Waide, and C. A. Tepley, 2005: Urban heat islands developing in coastal tropical cities. Eos Trans. AGU, 86(42), 397.

Hale, R.C., K.P. Gallo, T.W. Owen, and T.R. Loveland, 2006: Land use/land cover change effects on temperature trends at U.S. Climate Normals Stations. Geophys. Res. Lett., 33, doi:10.1029/2006GL026358.

Hanamean, J.R. Jr., R.A. Pielke Sr., C.L. Castro, D.S. Ojima, B.C. Reed, and Z. Gao, 2003: Vegetation impacts on maximum and minimum temperatures in northeast Colorado. Meteorological Applications, 10, 203-215.

Hansen, J., R. Ruedy, J. Glascoe, and Mki. Sato, 1999: GISS analysis of surface temperature change. J. Geophys. Res. 104, 30997-31022, doi:10.1029/1999JD900835.

Hansen, J.E., R. Ruedy, Mki. Sato, M. Imhoff, W. Lawrence, D. Easterling, T. Peterson, and T. Karl, 2001: A closer look at United States and global surface temperature change. J. Geophys. Res. 106, 23947-23963, doi:10.1029/2001JD000354.

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.

Hansen, J., Mki. Sato, R. Ruedy, L. Nazarenko, A. Lacis, G.A. Schmidt, G. Russell, I. Aleinov, M. Bauer, S. Bauer, N. Bell, B. Cairns, V. Canuto, M. Chandler, Y. Cheng, A. Del Genio, G. Faluvegi, E. Fleming, A. Friend, T. Hall, C. Jackman, M. Kelley, N. Kiang, D. Koch, J. Lean, J. Lerner, K. Lo, S. Menon, R. Miller, P. Minnis, T. Novakov, V. Oinas, Ja. Perlwitz, Ju. Perlwitz, D. Rind, A. Romanou, D. Shindell, P. Stone, S. Sun, N. Tausnev, D. Thresher, B. Wielicki, T. Wong, M. Yao, and S. Zhang 2005. Efficacy of climate forcings. J. Geophys. Res. 110, D18104, doi:10.1029/2005JD005776.

Hansen, J., M. Sato, R. Ruedy, K. Lo, D.W. Lea, and M. Medina-Elizade, 2006: Global temperature change. PNAS, 103, 14288 – 14293.

He, J. F., J. Y. Liu, D. F. Zhuang, W. Zhang, and M. L. Liu 2007: Assessing the effect of land use/land cover change on the change of urban heat island intensity Theor. Appl. Climatol., DOI 10.1007/s00704-006-0273-1

Holder, C., R. Boyles, A. Syed, D. Niyogi, and S. Raman, 2006: Comparison of Collocated Automated (NCECONet) and Manual (COOP) Climate Observations in North Carolina. J. Atmos. Oceanic Technol., 23, 671–682.

Huang Y., R. E. Dickinson and W. L. Chameides, 2006: Impact of aerosol indirect effect on surface temperature over East Asia. Proc. Natl. Acad. Sci., 103, 4371-4376, doi: 10.1073/pnas.0504428103.

Hubbard, K.G., and X. Lin, 2006: Reexamination of instrument change effects in the U.S. Historical Climatology Network. Geophys. Res. Lett., 33, L15710, doi:10.1029/2006GL027069.

Jones, P.D., and A. Moberg. 2003: Hemispheric and large-scale surface air temperature variations: An extensive revision and an update to 2001. J. Climate 16, 206-223.

Kalnay E., and M. Cai, 2003a: Impact of urbanization and land-use change on climate. Nature, 423, 528-531;

Kalnay, E. and M. Cai, 2003b: Impact of urbanization and land-use change on climate – Corrigenda. Nature, 425, 102.

Kalnay, E., M. Cai, H. Li, and J. Tobin, 2006: Estimation of the impact of land-surface forcings on temperature trends in eastern United States J. Geophys. Res., Vol. 111, No. D6, D06106.

Karl, T.R., S.J. Hassol, C.D. Miller, and W.L. Murray, Eds., 2006: Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences. A Report by the Climate Change Science Program and the Subcommittee on Global Change Research, Washington, DC.

Lim, Y.K., M. Cai, E. Kalnay, and L. Zhou, 2005: Observational evidence of sensitivity of surface climate changes to land types and urbanization. Geophys. Res. Lett., Vol. 32, No. 22, L2271210.1029/2005GL024267.

Mahmood, R., S.A. Foster, and D. Logan, 2006: The GeoProfile metadata, exposure of instruments, and measurement bias in climatic record revisited. Int. J. Climatology, 26(8), 1091-1124.

Parker, D.E., 2004: Large-scale warming is not urban. Nature, 432, 290, doi:10.1038/432290a;

Peterson, T.C., 2003: Assessment of urban versus rural in situ surface temperatures in the contiguous United States: No difference found. J. Climate, 16, 2941–2959.

Peterson, T.C., 2006. Examination of potential biases in air temperature caused by poor station locations. Bull. Amer. Meteor. Soc., 87, 1073-1089.

Peterson, T.C. and R.S. Vose, 1997: An overview of the Global Historical Climatology Network temperature data base. Bull. Amer. Meteor. Soc., 78, 2837-2849,

Peterson, T.C., D.R. Easterling, T.R. Karl, P. Ya. Groisman, N. Nicholls, N. Plummer, S. Torok, I. Auer, R. Boehm, D. Gullett, L. Vincent, R. Heino, H. Tuomenvirta, O. Mestre, T. Szentimre, J. Salinger, E. Førland, I. Hanssen-Bauer, H. Alexandersson, P. Jones, D. Parker, 1998: Homogeneity adjustments of in situ atmospheric climate data: A review. Int. J. Climatology, 18, 1493-1517.

Robeson, S.M., 2004: Trends in time-varying percentiles of daily minimum and maximum temperature over North America. Geophys. Res. Letts., 31, L04203, doi:10.1029/2003GL019019.

Runnalls, K.E. and T.R. Oke, 2006: A technique to detect microclimatic inhomogeneities in historical records of screen-level air temperature. J. Climate, 19, 959-978

Schmidt, G.A., R. Ruedy, J.E. Hansen, I. Aleinov, N. Bell, M. Bauer, S. Bauer, B. Cairns, V. Canuto, Y. Cheng, A. Del Genio, G. Faluvegi, A.D. Friend, T.M. Hall, Y. Hu, M. Kelley, N.Y. Kiang, D. Koch, A.A. Lacis, J. Lerner, K.K. Lo, R.L. Miller, L. Nazarenko, V. Oinas, Ja. Perlwitz, Ju. Perlwitz, D. Rind, A. Romanou, G.L. Russell, Mki. Sato, D.T. Shindell, P.H. Stone, S. Sun, N. Tausnev, D. Thresher, and M.-S. Yao, 2006: Present day atmospheric simulations using GISS ModelE: Comparison to in-situ, satellite and reanalysis data. J. Climate, 19, 153-192,

Trenberth, K.E., 2004: Rural land-use change and climate. Nature, 427, 213, doi:10.1038/427213a. doi:10.1175/JCLI3612.1.

Vose, R.S., T.R. Karl, D.R. Easterling, C.N. Williams, and M.J. Menne, 2004: Impact of land-use change on climate. Nature, 427, 213-21

Vose, R., D.R. Easterling, and B. Gleason, 2005: Maximum and minimum temperature trends for the globe: An update through 2004. Geophys. Res. Letts.,. 32, L23822, doi:10.1029/2005GL024379

Vose, R.S., D.R. Easterling, T.R. Karl, and M. Helfert, 2005: Comments on “Microclimate Exposures of Surface-Based Weather Stationsâ€?. Bull. Amer. Meteor. Soc., 86, 504–506.

Zhou, L., R.E. Dickinson , Y. Tian, J. Fang , Q. Li , R.K. Kaufmann, C.J. Tucker, and R.B. Myneni, 2004: Evidence for a significant urbanization effect on climate in China. PNAS, 101, 9540-9544.

If the papers were neglected because they were redundant, this would be no problem. However, they are ignored specifically because they conflict with the assessment that is presented in the IPCC WG1 Report, and the Lead Authors do not agree with that perspective!

That is hardly honoring the IPCC commitment to provide

“A comprehensive and rigourous picture of the global present state of knowledge of climate change”.

Moreover, the conflict of interest that was identified in the CCSP Report “”Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences” is perpetuated in the IPCC WG1 Chapter 3 Report [where the Editor of this CCSP Report, Tom Karl, is also Review Editor for the Chapter 3 of the 2007 IPCC WG1 Report].

These comments were made with respect to this CCSP Report

“The process for completing the CCSP Report excluded valid scientific perspectives under the charge of the Committee. The Editor of the Report systematically excluded a range of views on the issue of understanding and reconciling lower atmospheric temperature trends. The Executive Summary of the CCSP Report ignores critical scientific issues and makes unbalanced conclusions concerning our current understanding of temperature trendsâ€?.

“Future assessment Committees need to appoint members with a diversity of views and who do not have a significant conflict of interest with respect to their own work. Such Committees should be chaired by individuals committed to the presentation of a diversity of perspectives and unwilling to engage in strong-arm tactics to enforce a narrow perspective. Any such committee should be charged with summarizing all relevant literature, even if inconvenient, or which presents a view not held by certain members of the Committee.”

The IPCC WG1 Chapter 3 Report process made the same mistakes and failed to provide an objective assessment. Indeed the selection of papers to present in the IPCC (as well as how the work of others that was cited was dismissed) had a clear conflict of interest as the following individuals cited their research prominently yet were also a Review Editor (Tom Karl), works for the Review Editor (Tom Peterson, Russ Vose, David Easterling), were Coordinating Lead Authors (Kevin Trenberth and Phil Jones), were Lead Authors (Dave Easterling and David Parker), or a Contributing Author (Russ Vose).

In fact, as stated above, the CCSP Report “Temperature Trends in the Lower Atmosphere: Steps for Understanding and Reconciling Differences with its documented bias, was chaired by the same person as the Review Editor of the IPCC WG1 Chapter 3 Report (Tom Karl)! Regardless of his professional expertise, he is still overseeing an assessment which is evaluating his own research. There cannot be a clearer conflict of interest.

The IPCC WG1 Chapter 3 Report clearly cherrypicked information on the robustness of the land near-surface air temperature to bolster their advocacy of a particular perspective on the role of humans within the climate system. As a result, policymakers and the public have been given a false (or at best an incomplete) assessment of the multi-decadal global average near-surface air temperature trends.

Comments On Numerical Modeling As The New Climate Science Paradigm

UPDATE MAY 3 2010: I e-mailed each author of the Navarra et al 2010 paper and invited them to respond to my post; as of today’s date they have not replied to even acknowledge receipt of my e-mail.

Dick Lindzen has presented a summary of how climate science has changed over the last decade or so (see). In his article he writes [h/t to David L. for posting on Climate Audit]

“In brief, we have the new paradigm where simulation and programs have replaced theory and observation, where government largely determines the nature of scientific activity, and where the primary role of professional societies is the lobbying of the government for special advantage.”

There is an article in the March 2010 issue of the Bulletin of the American Meteorological Society which exemplifies the first of the issues that have been raised by Dick Lindzen.  The article is

A. Navarra, J. L. Kinter III, J. Tribbia, 2010: Crucial Experiments in Climate Science. Bulletin of the American Meteorological Society. Volume 91 Issue 3. 343–352.

I have provided excerpts from this article and will provide comments after each indicating points of agreement and disagreement.

There is a delicate web of interactions among the different components of the climate system. The interplay among the time scales is quite intricate, as the fast atmosphere interacts with the slow upper ocean and the even slower sea ice and deep-soil and groundwater processes. Spatial scales are tightly connected too, as small-scale cloud systems, for instance, affect the large-scale energy balance. Furthermore, everything is connected by water in its various forms. Water flows easily from place to place and exchanges energy with the environment every time it changes phase. Evaporation, condensation, freezing, and melting processes must be taken into account and evaluated as accurately as possible. The past 40 years of climate simulation have made it apparent that no shortcut is possible; every process can and ultimately does affect climate and its variability and change. It is not possible to ignore some components or some aspects without paying the price of a gross loss of realism.

This summary is a much-needed ,belated recognition of the accuracy of the 2005 NRC report [uncited in the Navarra et al 2010 BAMS article]

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.

Figure 1-1 in the NRC report [reproduced below] schematically illustrates what is written in the Navarra et al paper.

The Navarra et al 2010 article then has the text

A strict application of the scientific method requires a process of isolation of constituent subsystems and experimental verification of a hypothesis. For the climate system, this is only possible by using numerical models. Such models have become the central pillar of the quantitative scientific approach to climate science [emphasis added] because they allow us to perform “crucial” experiments under the controlled conditions that science demands. Sometimes crucial experiments are recognized as such at the design phase, like the quest for the Higgs boson currently going on at the European Organization for Nuclear Research [Conseil Européen pour la Recherche Nucléaire (CERN)]. Other times it is only in historical perspective that some experiments are recognized as truly “crucial.” This was the case of the 1887 test by Michelson and Morley that rejected the hypothesis of the existence of the “luminiferous aether” (Tipler and Llewellyn 2003), an undetected medium through which light was deemed to propagate (see Fig. 1 on title page; http://quantumrelativity.
calsci.com/Relativity/images/Michelson_Morley.jpg). Their result led to a reformulation of a physical theory of electromagnetic radiation and to special relativity and the invariance of the speed of light. “Crucial” experiments test competitive theories and the most successful one is finally selected.

This text seeks to equate climate modeling with the development of fundamental concepts in basic physics. However, these are not the same. Whereas fundamental physical constants such as the speed of light were the focus of the Michelson and Morley study, climate modeling relies on tunable parameters and functions in their parameterizations of clouds, precipitation, vegetation dynamics, etc in the construction of the models. Climate models are engineering code not basic physics. Only advection, the pressure gradient force and gravity provide the fundamental physics in climate model. The combination of a fundamental component of the model with an engineering component (in which the physics is tuned) results in engineering code, not basic physics.

I summarized the types of climate models in my post

What Are Climate Models? What Do They Do?

There are three basic classes: process studies; diagnosis; and prediction.  As I discuss in that post, the IPCC assessment models are actually process studies, although they have been marketed by the IPCC as predictions.  With respect to the  Navarra et al paper, their proposed modeling framework, in reality, is to develop a more comprehensive climate process assessment tool. The models hypotheses.

Navarra et al 2010 continue with the text

There have been no revolutionary changes in numerical models of climate since their advent over 30 years ago. The models make use of the same dynamical equations, with improved numerical methods, and have comparable resolution and similar parameterizations. Over the past 30 years, computing power has increased by a factor of 106. Of the millionfold increase in computing capability, about a factor of 1,000 was used to increase the sophistication of the model. Model resolution, the inclusion of more physical and biogeochemical processes, and more elaborate parameterizations of unresolved phenomena have all been modestly improved.

This is an accurate summary.  An interesting and important oversight, however, is any discussion on improvements in the predictive skill of the models on different time scales (i.e. seasonal; annual, multi-year; decadal). Of course, the absence of this discussion reflects the general lack of a demonstration of predictive skill beyond a few months at most by the IPCC or anyone else.

Navarra et al 2010 write

These trends indicate that the problem of weather and climate modeling can be organized in terms of four dimensions: resolution, complexity, integration length, and ensemble size.

There is an interesting oversight here. There is no mention of observational verification of the model skill.

Increasingly, century-long climate projection will become an initial-value problem requiring the current observed state of all components of the Earth system: the global atmosphere, the world oceans, cryosphere, and land surface (including physical quantities, such as temperature and soil moisture, as well as biophysical quantities, such as leaf area index, etc.) to produce the best projections of the Earth system and also giving state-of-the-art decadal and interannual predictions. The shorter time scales and weather are known to be important in their feedback on the longer-time-scale behavior. In addition, the regional manifestations of longer-time-scale changes will be felt by society mainly through the changes in the character of the shorter time scales, including extremes.

This is an accurate summary of the challenges in climate prediction. The admission that climate prediction is an initial value problem was ignored by the 2007 IPCC assessments.  See, for example, my recent post

Comments On A New Paper “A Unified Modeling Approach to Climate System Prediction” By Hurrell Et Al 2009

which refers to my paper

Pielke, R.A., 1998: Climate prediction as an initial value problem. Bull. Amer. Meteor. Soc., 79, 2743-2746. {with respect to my Comments on the Hurrell et al paper that was sent to BAMS last year, it was only sent out for review in the past month!].

Navarra et al 2010 further write

The era of industrial computing. The changes that we have described will usher in a new era of calculation on such a large scale that it will be comparable to the transition from the artisan shop to the modern factory: it will be the era of industrial computing. Issues like quality control, procedure certifications, and data integrity will no longer be the subject of discussions by researchers, but they will be matters of procedural control and monitoring. It will free climate scientists from much of the engineering work that is now necessary in the preparation of the experimental apparatus they are using in their laboratory but that is hardly necessary to the core of climate science.

It will also create some new problems. It is unclear at this point if the field is going to need more software engineers and programmers or fewer as the computing power is concentrated in larger and fewer centers. A new professional figure may emerge who will maintain the laboratory and the experiment as the routine day-by-day simulations, developing along well-planned lines, may stretch for months or years. Questions about how such professionals will be trained arise without obvious answers.

This is a remarkable proposal for a new approach in climate modeling as it removes the climate modeller  from working with the real world data.  This exemplifies what Dick Lindzen stated

“we have the new paradigm where simulation and programs have replaced theory and observation….”. 

The Navarra et al article concludes with the text

The discussions conducted for the simulations needed for the IPCC assessments have already gone in this direction, but they are still examples of a loose coordination, rather than the tight coordination that will be required by the petascale machines. The transition is similar to what happened in astronomy when that community went from coordinating observations at different telescopes to creating a consortium for the construction of one larger instrument. Industrial computing and numerical missions will rely on that capability even more to allow climate science to address problems that have never before been attempted.

The global numerical climate community soon will have to begin a proper discussion forum to develop the organization necessary for the planning of experiments in the industrial computing age.

The proposal put forth in Navarra et al 2010, if adopted, would concentrate climate modeling into a few well-funded institutions, as well as focus the use models for multi-decadal predictions of the real climate system (in which we do not, of course have observational validation data), rather than as a tool to test scientific hypotheses against real world observations. Policy decisions will be made from these unvalidated model predictions (has they have already been made based on the global-average and regional scale from the IPCC multi-decadal model forecasts).

This is a path that will likely lead to the eventual discrediting of the climate science community who participates in this activity if, as I expect, the regional multi-decadal regional (and even global average forecasts) generally fail to show skill in the coming years.

Even more importantly, they are unlikely to be useful to most of the actual needs of resource stakeholders in their plans to reduce the vulnerability to climate and other environmental and social threats; e.g. see Table E.7 in

 Pielke, R.A. Sr., and L. Bravo de Guenni, 2004: Conclusions. Chapter E.7 In: Vegetation, Water, Humans and the Climate: A New Perspective on an Interactive System. Global Change – The IGBP Series, P. Kabat et al., Eds., Springer, 537-538.

 While I support the use of climate models to examine climate processes, they must be solidly based on observational validation. It also must not be forgotten that climate models (and indeed all models) are hypotheses. Real world observations must be the standard to test the climate models.

The Navarra et al conclusion that

“Such models have become the central pillar of the quantitative scientific approach to climate science because they allow us to perform “crucial” experiments under the controlled conditions that science demands”

is not how climate science should proceed. The “central pillar” must be the real-world observations.

The American Meteorological Society, as represented by the Editor-in-Chief of the Bulletin of the AMS, Jeff Rosenfeld, agrees with the view with models as the central pillar of the quantitative scientific approach to climate science. He writes in his “Letter From The Editor” [which, unfortunately is not online at the BAMS website]

“If climate science develops the way Navarra et al suggest will this be proof that the age of numerical experimentation has matured? Perhaps so. A science shaped by Franklin and Lorenz’s critical experiments is now a critical experiment itself – a test of the viability of science when it is dependent on numerical modeling for methodology. For better or worse, the result of this grand experiment – the very state of climatology – will forever be ingrained in popular consciousness.”

Dick Lindzen’s perceptive statement that “simulation and programs have replaced theory and observation” accurately (and unfortunately) represents the current  position of the leadership of the American Meteorological Society.

April 26 2010 Reply By Kevin Trenberth

UPDATE: May 6 2010 – Roy has a response on his website  –  see Earths Missing Energy: Trenberth’s Plot Proves My Point

Below is Kevin’s response to Roy’s Guest Post

Hi Roger

I do not understand the figures Roy has presented.  I am attaching the official CERES figure from the “The State of the climate in 2008” published in BAMS and I have added in pink a characterization of the departures from normal which are rather different than those Roy presents. There are different versions of CERES and we also have a more up to date figure that includes an extra year, but it is not my figure and I can not pass it on: it does not change much though.

The biggest changes in OLR are associated with high cold clouds from convection, but such clouds are also very reflective and so the net radiation often changes very little. So one should pay most attention to the net as the large short-term perturbations, such as from the Madden Julian Oscillation or El Nino, have large canceling components in the short and long-wave.

It is noteworthy that the RSW in the figure is lower after 2005 when the data were preliminary (but these have now been confirmed) and some difficulties arose from changes in the Japanese geostationary satellite. But the biggest change seems to me to be in 2008 through 2009 in OLR.  Roy suggests that these are related to temperatures, but the second plot shows the annual mean surface temperatures for 2008.  Although January temperatures were very low, the year as whole was not and it is not an explanation.  Once the data are released by CERES, it will be interesting to plot the patterns of OLR anomaly.  We have tried that using the uncalibrated products available from the Climate Prediction Center but they are not good enough.  Similarly, cloud anomalies are not revealing, as can be seen from the figures in “The State of the climate in 2008” published as a supplement to BAMS: see Figures 2.19 and 2.20.

It would not surprise me if indeed part of the explanation for the missing energy is because of the CERES data, which are still undergoing processing before being released for the period after November 2005. However, the fact that the data are not available for full diagnostic studies highlights the needs for more priority to be given to all of these observations, which was a central point of our Science article.

Kevin Trenberth

Roy Spencer’s Response To Kevin Trenberth, April 26, 2009

Roy Spencer’s response to Kevin Trenberth, April 26, 2009 [see also a version of this post on Roy’s weblog]

Kevin Trenberth begins his blog post with, “I saw Roy Spencer’s comment for the first time and it is not correct”, but I see no specific refutation of any of my points in my blog posting.

http://www.drroyspencer.com/2010/04/some-comments-on-earth%E2%80%99s-%E2%80%9Cmissing-energy%E2%80%9D/

To support my comments, here are the global-average CERES ERBE-like ES-4 Edition 2 radiative flux anomalies for reflected solar (1^st graph) and outgoing longwave radiation (OLR, 2^nd graph)…these are daily running 91-day averages:

Clearly, the long-term “trend” during 2000 through 2008 was in the reflected solar (SW), not OLR (LW).

What is important for global warming or cooling is the sum of the global SW and LW, shown in the following graph (note I have flipped the y-axis, to correspond to the sense of the plot Kevin and John Fasullo showed in their Science Perspectives article):

What Kevin DOES discuss then is the anomalous drop in OLR around the beginning of 2008.  He should recognize that there is a very simple explanation for it: global-average temperatures were quite low at that time, as seen in the next graph:

The expected change in OLR with temperature is about 3.2 Watts per sq. meter per degree C.  This temperature plot shows a fall of about 0.4 deg. C from early 2007 to early 2008, which should cause a reduction in OLR by about (0.4 x 3.2 ), or about 1.3 Watts per sq. meter.  As seen in the LW plot above, there was indeed a fall of about 1 Watt per sq. meter.  To the extent that the drop in OLR with cooling was not quite as much as might be expected could be due to a small positive feedback in high clouds and/or water vapor. These are just rough estimates, anyway.

In our new paper accepted for publication in JGR, we show that this 2007-08 cooling event was due to a temporary increase in low cloud cover, evidence of which is clearly seen in the form of a large spike in reflected sunlight in the first plot, above.  The OLR event is completely consistent with the resulting drop in global-average temperatures.

Further Comment By Kevin Trenberth

On Sunday April 25 2010, Kevin sent me the e-mail below which continues the constructive discussion we are having on Climate Science.  It is reproduced below with his permission.

Roger

I am just back from travel: actually I was at a mtg in Atlanta with your son!

I saw Roy Spencer’s comment for the first time and it is not correct.  The CERES data are indeed processed to give the reflected solar radiation and outgoing longwave radiation, which combine to give the net radiation.  The biggest single change, which occurred abruptly, is a drop in OLR at the beginning of January 2008 and lasting throughout most of 2009 with only a brief return to “normal”.  Values are between 0.5 and 1 W m-2 below the normal which is the mean for the record from 2000 through about 2005 (I think) and thus not normal in the sense of being radiatively balanced (the zero is not a true zero).  On the other hand, the reflected solar is higher from 2000 through 2003, and runs up to about 0.5 W m-2 below the mean thereafter.

The abrupt nature of the drop in OLR made it look very suspicious to me and we looked at the daily values.  The drop seems to occur very near the start of 2008. We have raised this with the CERES team who find that it is replicated in a separate measurement from AIRS data.  It occurs during La Nina and is thus consistent with changes in high cloud (more cloud), which has some plausibility.  We explored the cloud records from three sources but all disagree and the quality of cloud information is not yet good enough for this sort of thing.  Fortunately cloud data (ISCCP) are being reprocessed.  However, definition of cloud and changes in sensitivity of the instruments are difficult challenges.  The more sensitive the instrument, the more cloud is found, even though it is very thin.

We hope that our paper is a stimulus to help improve the records of all aspects of this problem, the radiation , the ocean heat, and the way they are processed.

Kevin

I am inviting Roy to respond to Kevin’s comment.

New Paper “Twentieth Century Bipolar Seesaw Of The Arctic And Antarctic Surface Air Temperatures By Chylek et al. 2010

There is a new paper on the climate of the higher latitudes. It is

Chylek, P., C. K. Folland, G. Lesins, and M. K. Dubey (2010), Twentieth century bipolar seesaw of the Arctic and Antarctic surface air temperatures,  Geophys. Res. Lett., 37,  L08703, doi:10.1029/2010GL042793.

The abstract reads

“Understanding the phase relationship between climate changes in the Arctic and Antarctic regions is essential for our understanding of the dynamics of the Earth’s climate system. In this paper we show that the 20th century detrended Arctic and Antarctic temperatures vary in anti‐phase seesaw pattern – when the Arctic warms the Antarctica cools and visa versa. This is the first time that a bi‐polar seesaw pattern has been identified in the 20th century Arctic and Antarctic temperature records. The Arctic (Antarctic) detrended temperatures are highly correlated (anti‐correlated) with the Atlantic Multi‐decadal Oscillation (AMO) index suggesting the Atlantic Ocean as a possible link between the climate variability of the Arctic and Antarctic regions. Recent accelerated warming of the Arctic results from a positive reinforcement of the linear warming trend (due to an increasing concentration of greenhouse gases and other possible forcings) by the warming phase of the multidecadal climate variability (due to fluctuations of the Atlantic Ocean circulation).”

The summary in the paper reads in part

A bi‐polar seesaw pattern of the paleo temperature has been observed earlier in the Greenland and Antarctic ice core data. For the first time we identify a bi‐polar seesaw pattern in the 20th century Arctic and Antarctic instrumental temperature records. The detrended multidecadal scale variability of the Arctic and Antarctic temperature time series are highly anticorrelated. When the Arctic warms Antarctica cools and vice versa. This multidecadal variability combines with the general warming trend (presumably dominated by anthropogenic GHGs) to produce the observed Arctic and Antarctic temperature patterns. The intense Arctic warming since the 1970s (Figure 1a) arises from an additive combination of the general global warming trend with the warming phase of the multidecadal climate oscillation, while in Antarctica the cooling phase of the multidecadal oscillation opposes the general warming trend leading to essentially no significant Antarctic temperature change since the 1970s…”

This is another new paper that documents why we need a regionally focused assessment of atmospheric and ocean circulation changes with respect to climate variability and change rather than using a global average surface temperature as primary climate change metric. My only disagreement with the paper is that in indicates there is an overarching “general warming trend” when, as we discussed last week (e.g. see, see and see), climate system heat changes are clearly nonlinear as warming has essentially ceased since at least 2005 through mid-2009 (the last time we have seen the data).  Moreover, as discussed by Roy Spencer (e.g. see) and in our 2009 EOS article (see), it is inaccuate to just focus on the greenhouse gases with respect to how the climate system is being altered.

Article On The “Missing Heat” In The April 16 Issue of Physicsworld.com

Update April 23 2010: I sent to both Kevin Trenberth and Josh Willis an e-mail that this post was presented today on my weblog. Below is the response from Josh (with his permission), along with my response.

Josh Willis’s e-mail

Hi Roger,

Thanks for the heads up.  I think what Kevin was trying to say about the satellite sensors being able to track “the changes in net energy.” is that while the satellites do not yield a good estimate of the time-averaged radiative imbalance, they DO give a good estimate of the year to year fluctuations about that mean.  This is my understanding anyway.  So in terms of heat content, that means that the satellites are insensitive to the mean warming rate (i.e., the SLOPE of the OHC estimates).  But the year to year variations are probably much more accurate.  So if you integrate the satellite net flux over time to compare it with OHC, there is an ambiguity in the slope of the resulting curve, but it still contains useful information about the year to year accelerations in OHC.

That’s what Kevin was driving at, so I think your comment about the capabilities of the satellite data is a bit unfair:

“However, if the satellites ‘are not good enough to give accurate measurements of the net energy itself’ they be cannot expected to track ‘changes in the net energy’!”

Cheers,
Josh

My Reply

Hi Josh

 I agree that the satallite does provide a good estimate of the intra-annual (e.g. monthly) variations of the outgoing long wave and incoming (and reflected) solar fluxes. However, the year to year variations in the annual averages is a much smaller value. Unless the errors in the shorter term values were completely random, the errors in the monthly (or shorter term analyses) will accumulate so as to contaminate the year to year analyzed changes.

 The reason the OHC is so valuable is that the ocean itself does the averaging. With the satellite measurements, we are relying on the accuracy of the measured irradiances themselves.

 I will post your comments below and my reply (and unless you tell me differently). I also sent to Kevin that I posted today, but have not yet heard back from him.

Best Regards

Roger

There is an article in the publication Physicsworld.com by Hamish Johnston who is the editor titled

Where has all the heat gone? [h/t Don Bishop! for alerting us to this]

The article starts with the text

“Two leading climate scientists have urged their colleagues to find the growing amount of “missing energy” that seems to be eluding climate sensors.”

It includes the text that

“Since 2001 scientists have used satellites to compare the amount of solar energy being absorbed by the Earth to the amount of infrared energy escaping from our planet. And just as predicted by the theory of manmade climate change, the amount of energy retained by the Earth has increased along with greenhouse-gas concentrations.

At first this extra energy seems to have boosted temperatures down here on Earth. Then something unexplained happened in about 2004 – and since then terrestrial measurements suggest that the planet is losing energy.

So are the satellites wrong? While Trenberth and Fasullo say that the satellites are not good enough to give accurate measurements of the net energy itself, they claim that the instruments are “sufficiently stable” to track changes in net energy, which are the important quantity.”

However, if the satellites “are not good enough to give accurate measurements of the net energy itself” they be cannot expected to track “changes in the net energy”!

The article also writes

“Trenberth told physicsworld.com that the discrepancy probably lies in the environment’s largest heat reservoir. “I would say that the missing heat is mainly in the ocean,” he argues.

Much of our understanding of how the oceans absorb energy comes from over 3000 “Argo floats” that gather temperature data at depths of up to 2000 m. However, Trenberth says he thinks that “oceanographers are fairly new at processing this kind of data and are still learning how to do it right”. He also points out of that some of the floats deployed in the Atlantic have been problematic. “

As has been documented on my weblog, however, e.g. see the e-mail exchanges between Kevin Trenberth and Josh Willis

Comments On Two Papers By Kevin Trenberth On The Global Climate Energy Budget

Further Feedback From Kevin Trenberth And Feedback From Josh Willis On The UCAR Press Release

The Significance of the E-Mail Interchange with Kevin Trenberth and Josh Willis

the ocean data analyses are quite robust since at least 2005. There is not a significant amount of heat that is “missing” in the climate system.  See also the excellent post on this topic by Roy Spencer

Some Comments on Earth’s “Missing Energy”

To his credit, Kevin has  made a forecast that this issue will be resolved in the next year or two;  i.e.

“Trenberth believes that it is crucial to understand when this energy will return to the upper ocean, where it would have a significant effect on climate. Scientists already know the Southern Oscillation involves the absorption of solar energy by the Pacific Ocean during “La Niña” years and its release into the atmosphere during “El Niño” years – leading to significant changes in weather patterns in the Americas.

An El Niño began in 2009 and looks set to continue in 2010. Trenberth believes that it might result in much of the missing energy resurfacing – but adds that current data gathering and analysis techniques mean that it could be a year or two before we know.”

This is a scientifically testable hypothesis and we should know by the end of 2011 if Kevin is correct or not.

Finally, I do support Kevin’s recommendation with respect to the reporting of ocean heat change data

“One can argue that we should develop a system to do this in closer to real time as part of the new climate services,” he said.

Hopefully, Physicsworld.com will publish a follow-up to their article with the more up-to-date information with respect to the confidence in the robustness of the ocean heat data since 2005.

New Research Paper “Simulated impacts of land cover change on summer climate in Tibetan Plateau” By Li and Xue 2010

There is another new paper that provides additional confirmation of our conclusions in

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

where we report that the only scientific hypothesis that cannot be rejected is that

“In addition to greenhouse gas emissions, other first- order human climate forcings are important to understanding the future behavior of Earth’s climate. These forcings are spatially heterogeneous and include the effect of aerosols on clouds and associated precipitation [e.g., Rosenfeld et al., 2008], the influence of aerosol deposition (e.g., black carbon (soot) [Flanner et al. 2007] and reactive nitrogen [Galloway et al., 2004]), and the role of changes in land use/land cover [e.g., Takata et al., 2009]. Among their effects is their role in altering atmospheric and ocean circulation features away from what they would be in the natural climate system [NRC, 2005]. As with CO2, the lengths of time that they affect the climate are estimated to be on multidecadal time scales and longer.”

The new paper is

Li Q and Y. Xue, 2010: Simulated impacts of land cover change on summer climate in Tibetan Plateau. Environ. Res. Lett. 5, 015102. doi: 10.1088/1748-9326/5/1/015102

“The Tibetan Plateau (TP) is a key region of land–atmosphere interactions with severe eco-environment degradation. This study uses an atmospheric general circulation model, NCEP GCM/SSiB, to present the major TP summer climate features for six selected ENSO years and preliminarily assess the possible impact of land cover change on the summer circulation over the TP. Compared to Reanalysis II data, the GCM using satellite derived vegetation properties generally reproduces the main 6-year-mean TP summer circulation features despite some discrepancies in intensity and geographic locations of some climate features. Two existing vegetation maps with very different land cover conditions over the TP, one with bare ground and one with vegetation cover, derived from satellite derived data, are tested and produce clearer climate signals due to land cover change.’

“It shows that land cover change from vegetated land to bare ground decreases the radiation absorbed by the surface and results in weaker surface thermal effects, which lead to lower atmospheric temperature, as well as weaker vertical ascending motion, low-layer cyclonic, upper level anticyclonic, and summer monsoon circulation. These changes in circulation cause a decrease in the precipitation in the southeastern TP.”

The paper further extends what has become increasingly obvious; land use/land cover change has a major effect on regional (and global climate). Li and Xue, for example, write

The impact of land cover change (LCC) on the regional and global climate has been extensively investigated by using
the general circulation model (GCM) and regional climate model (RCM) coupled with land surface parameterization schemes (e.g., Xue and Schukla 1993, Pan et al 1999, Suh and Lee 2004). Land degradation in East Asia has significant impact on the local circulation and monsoon system (Xue 1996, Xue et al 2004, Cui et al 2006). For example, Xue et al (2004) found that land degradation could cause delayed monsoon onset.

In any new assessment of the climate system, as has been repeatedly emphasized on my weblog, land use/land cover needs to be considered with the same attention as has been given to other human climate forcings.

The Significance of the E-Mail Interchange with Kevin Trenberth and Josh Willis

On Friday of last week, and Monday and Tuesday of this week, I presented the following posts:

Further Feedback From Kevin Trenberth And Feedback From Josh Willis On The UCAR Press Release

Comments On Two Papers By Kevin Trenberth On The Global Climate Energy Budget

Is There “Missing” Heat In The Climate System? My Comments On This NCAR Press Release

My son had the post

The Missing Heat

I want to summarize today what are the main conclusions from this exchange of perspectives:

• First, when colleagues who differ can interact in a constructive manner, we all benefit by an improved understanding of the science issues and the way forward to resolve remaining uncertainties.
• In terms of climate science, a very substantive conclusion from this interchange of perspectives is that we do not need to continue to use the global average surface temperature trend (with its unresolved biases and uncertainties) to diagnose global warming. The trends in the upper ocean heat content, which has been accurately measured since at least 2005, and will for the foreseeable future, should be adopted as the primary metric to monitor global warming.

This second finding does not mean continued analyses of surface temperatures and their anomalies are not needed [they certainly are for length of growing season, heating degree days, etc], but for the specific metric of global warming (and cooling), it is an inadequate metric compared with ocean heat content changes.

We need near-real time plots of the ocean heat content changes over time, such as given in the figure in

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

Four-year rate of the global upper 700 m of ocean heat changes in Joules at monthly time intervals. One standard error value is also shown. (Figure courtesy of Josh Willis of NASA’s Jet Propulsion Laboratory).

It will be illuminating and informative to see how NCDC (Tom Karl), GISS (Jim Hansen), and CRU (Phil Jones)  respond to this recognition that it is time to move past the surface temperature trend as the “gold standard” of global warming.