A Proposal “Comparison Of GHCN Temperature Anomalies And Trends With Long Term Fluxnet Temperature Anomalies And Trends”

We [Markus Reichstein and I] have been unsucessful in obtaining funding for the proposal below, so I have posted to encourage others to pursue it. It builds on the issue of station siting quality that we discuss in our paper

Fall, S., A. Watts, J. Nielsen-Gammon, E. Jones, D. Niyogi, J. Christy, and R.A. Pielke Sr., 2011: Analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends. J. Geophys. Res.,  116, D14120, doi:10.1029/2010JD015146.Copyright (2011) American Geophysical Union.

A Proposal 

The comparison of GHCN temperature anomalies and trends with long term Fluxnet temperature anomalies and trends

The Global Historical Climate Reference Network [GHCN] is the foundation for the land portion of the annual average multi-decadal global surface temperature trends [http://www.ncdc.noaa.gov/ghcnm/; Peterson et al 1998; Karl et al, 2006]. This temperature data is assumed to be robust with respect to assessing anomalies and long term trends, as reported, for example, by Parker (2004).

However, there have been questions raised with respect to the existence of systematic biases in the data due to the local landscape around the observing sies, as well as a need to attribute what fraction of the anomalies and long term trends are due to added CO2 and other greenhouse gases, aerosols and landscape change [e.g. Mahmood et al 2010].

This need to further examine the quantitative robustness of this land surface temperature data was highlighted at the 2010 Exeter meeting –  Surface temperature datasets for the 21st Century . For example, Matt Menne, Claude Williams and Jay Lawrimore reported that

“[GHCN Monthly]Version 2 [was] released in 1997….but without station histories for stations outside the USA)”

and

“Undocumented changes [in the USHCN] can be as prevalent as documented changes even when extensive (digitized) metadata are available”.

There is also a growing divergence between multi-decadal lower tropospheric temperature trends and surface temperature trends [Klotzbach et al, 2009, 2010), a  need to simultaneously assess long term temperature and humidity trends (i.e. moist enthalpy; e.g. see Fall et al, 2010), and of the determination of specific landscape in which the temperature measurements are made and how this effects the absolute humidity and dry bulb temperature (e.g. see Fall et al 2009).

This debate is overviewed in Pielke et al (2007,2009) and Parker et al (2009). At FLUXNET sites a recent related study has shown the contrasting behavior of forest and grassland sites in terms of radiative, sensible and latent energy fluxes during heatwaves (Teuling et al. 2010). This study also showed the potential of remote sensing (e.g. land surface temperatures) in this context.

The fundamental questions include:

  • What is the role of the local landscape in the immediate vicinity of the GHCN sites on long term temperature trends? Fall et al (2010) has found that poorly sited locations in the USA (i.e. those that are not representative of the larger scale region) have biases in averaged maximum and minimum temperatures and in diurnal range.
  • What is the importance of anomalies and multi-decadal trends in absolute humidity on the anomalies and multi-decadal trends in the dry bulb temperature?  Pielke et al 2004 discussed how the same trends in heat (moist enthalpy) can be accommodated by a variety of different trends in humidity and temperature.  Land use-land cover change clearly can influence both.
  • What is the role of landscape type on temperature (and moist enthalpy) on anomalies and long term trends? Diffenbaugh et al 2009, for example, found statistically significant cooling in areas of the Great Plains where crop/mixed farming has replaced short grass, areas of the Midwest and southern Texas where crop/mixed farming has replaced interrupted forest, and areas of the western United States containing irrigated crops.

The long term measurements at the Fluxnet sites provide an opportunity to assess the quantitative the spatial representiveness of anomalies and long term trends in sites within the GHCN network that are close to Fluxnet sites. At the FLUXNET sites air temperature and humidity are measured together with energy and carbon fluxes in the boundary layer above the vegetation canopy at half-hourly time-step. In the most recent standardized collection, the La-Thuille 2007 data set, there are around 950 site-years containing observations from a total of 253 sites (documented and available subject to specific use-policies at http://www.fluxdata.org). The FLUXNET network has the highest density of sites in Europe and North America, but data from all other continents are available as well. Information on the exact instrument and configuration for temperature and humidity measurements is not generally available. External data which is available to characterize the landscape context include images from Google at a maximum of five resolutions (at some remote sites the highest resolution is not available) (Reichstein pers comm.), Visual Earth (www.fluxdata.org) and MODIS cutouts (ORNL DAAC). Some sites but not many also have webcams installed, but those are not in the current data set.

Figure 1:  Distribution of FLUXNET sites within the LaThuile database (A) in geographical space, (B) in simplified climate space. In (A) maps colors code mean annual temperature (CRU) according to legend. Grey are area which are not covered by FLUXNET sites in terms of climate space (climate space distance threshold). In (A) and (B) symbol represent land cover classes as in the legend of (B) . (from Reichstein et al. in prep.)

Our proposal is to compare the anomalies and long term trends in dry bulb temperature and absolute humidity at the Fluxnet sites with GHCN measurements of these quantities sites that are in the vicinity of the Fluxnet locations. The sensible, latent and radiative fluxes at the Fluxnet sites can be used to explain the observed anomalies and trends.

Among the research questions are:

  • Are there statistically different anomalies and trends between the Fluxnet and GHCN nearly collocated sites? Do they occur predominantly during specific synoptic situations?
  • If so, what is the reason for the differences? Can a landscape type component be used to explain some or all of the differences?

Photographs of the GHCN sites that are used for these comparisons need to be obtained, as has been completed for the USHCN (see Watts, 2009).

References

Diffenbaugh, N. S., 2009:Influence of modern land cover on the climate of the United States. Climate Dynamics. DOI 10.1007/s00382-009-0566-z

Fall, S., D. Niyogi, A. Gluhovsky, R. A. Pielke Sr., E. Kalnay, and G. Rochon, 2009: Impacts of land use land cover on temperature trends over the continental United States: Assessment using the North American Regional Reanalysis. Int. J. Climatol., DOI: 10.1002/joc.1996.

Fall, S., N. Diffenbaugh, D. Niyogi, R.A. Pielke Sr., and G. Rochon, 2010: Temperature and equivalent temperature over the United States (1979 – 2005). Int. J. Climatol., DOI: 10.1002/joc.2094.

Fall, S., A. Watts, J. Nielsen-Gammon, E. Jones, D. Niyogi, J. Christy, and R.A. Pielke Sr., 2011: Analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends. J. Geophys. Res.,  116, D14120, doi:10.1029/2010JD015146.Copyright (2011) American Geophysical Union.

Thomas R. Karl, Susan J. Hassol, Christopher D. Miller, and William L. Murray, editors, 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.

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:10.1029/2009JD01365

Mahmood, R., R.A. Pielke Sr., K.G. Hubbard, D. Niyogi, G. Bonan, P. Lawrence, B. Baker, R. McNider, C. McAlpine, A. Etter, S. Gameda, B. Qian, A. Carleton, A. Beltran-Przekurat, T. Chase, A.I. Quintanar, J.O. Adegoke, S. Vezhapparambu, G. Conner, S. Asefi, E. Sertel, D.R. Legates, Y. Wu, R. Hale, O.W. Frauenfeld, A. Watts, M. Shepherd, C. Mitra, V.G. Anantharaj, S. Fall,R. Lund, A. Nordfelt, P. Blanken, J. Du, H.-I. Chang, R. Leeper, U.S. Nair, S. Dobler, R. Deo, and J. Syktus, 2010: Impacts of land use land cover change on climate and future research priorities. Bull. Amer. Meteor. Soc., 91, 37–46, DOI: 10.1175/2009BAMS2769.1

Parker, D. E. (2004), Climate: Large-scale warming is not urban, Nature, 432, 290(18 November 2004); doi:10.1038/432290a.

Parker, D. E., P. Jones, T. C. Peterson, and J. Kennedy (2009), Comment on ‘Unresolved Issues with the Assessment of Multi-Decadal Global Land Surface Temperature Trends’ by Roger A. Pielke, Sr. et al., J. Geophys. Res., doi:10.1029/2008JD010450

Reichstein, M., Papale, D., Baldocchi, D. et al. (in prep). A new global harmonized eddy covariance data set from FLUXNET: uncertainties, limitations and robust global patterns

Teuling A.J., Seneviratne S.I., Stöckli R., Reichstein M., Moors E., Ciais P., Luyssaert S., van den Hurk B., Ammann C., Bernhofer C., Dellwik E., Gianelle D., Gielen B., Grünwald T., Klumpp K., Montagnani L., Moureaux C., Sottocornola M. & Wohlfahrt G. (2010) Contrasting response of European forest and grassland energy exchange to heatwaves. Nature Geoscience, doi:10.1038/ngeo950

Thomas C. Peterson, Russell Vose, Richard Schmoyer, Vyachevslav Razuvaëv, 1998:  Global historical climatology network (GHCN) quality control of monthly temperature data DOI: 10.1002/(SICI)1097-0088(199809)18:11<1169::AID-JOC309>3.0.CO;2-U

Pielke Sr., R.A., C. Davey, and J. Morgan, 2004: Assessing “global warming” with surface heat content. Eos, 85, No. 21, 210-211

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.

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, 2009: Reply to comment by David E. Parker, Phil Jones, Thomas C. Peterson, and John Kennedy on “Unresolved issues with the assessment of multi-decadal global land surface temperature trends. J. Geophys. Res., 114, D05105, doi:10.1029/2008JD010938.

Watts, A. 2009: Is the U.S. Surface Temperature Record Reliable? 28 pages, March 2009 The Heartland Institute.

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