Boundary-Layer Meteorology

, Volume 142, Issue 3, pp 469–493 | Cite as

Comparison of Two Closely Located Meteorological Measurement Sites and Consequences for Their Areal Representativity

  • V. Horlacher
  • S. Osborne
  • J. D. Price


We compare meteorological data collected at the Met Office Research Unit, Cardington, UK with similar data from a temporary meteorological station located approximately 8.5 km away. Data were examined for a period of 10 months to ascertain differences in mean quantities, and in heat and radiation budgets, at different heights between the two locations, one of which is located in a wide shallow valley, the other on a plateau at the valley edge. Results reveal that screen-level variables at the two sites show the greatest differences in mean quantities, for most conditions, but that at 50 m the differences are negligible, indicating that temperatures had become aggregated and homogeneous at that height. For flux measurements between 10 and 50 m, however, significant differences were observed at certain times of the year, which appear to be related to local vegetation and soil conditions, and these are discussed. The study also presents data for stable conditions that show that temperature differences at screen level are again the most significant difference between the two sites. On average these were not large, but on occasions discrepancies at low levels (up to approximately 10 m) as large as 5°C were observed. It is thought that these greater differences during stable conditions may be caused by cold air pooling at the valley site, despite the very shallow orography there. Data from the two sites have been compared with forecasts from two Met Office mesoscale models. Results show that, during daytime hours, model-predicted values lie outside the range of values observed at the two sites, indicating a possible model bias. However, the opposite was true for most nighttime hours, during which model values fell within the range observed at the two sites, indicating that at night the model predictions are representative of the region. In this case, however, comparison of the model prediction with either one of the available observations could lead to the false conclusion that the model temperatures were either too high or too low, depending on which observational site was used for the comparison.


Gradient Richardson number Local heterogeneity Model comparison Positive and negative curvature Seasonal observations Stable stratification 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Alfieri JG, Niyogi D, Zhang H, LeMone MA, Chen F (2009) Quantifying the spatial variability of surface fluxes using data from the 2002 international H2O project. Boundary-Layer Meteorol 133: 323–341CrossRefGoogle Scholar
  2. Andre JC, Mahrt L (1982) The nocturnal surface inversion and influence of clear-air radiative cooling. J Atmos Sci 39: 864–877CrossRefGoogle Scholar
  3. Avissar R, Verstraete MM (1990) The represenation of continental surface processes in atmospheric model. Rev Geophys 28: 35–52CrossRefGoogle Scholar
  4. Beyrich F, Leps JP, Mauder M, Bange J, Foken T, Huneke S, Lohse H, Lüdi A, Meijninger WML, Mironov D, Weisensee P, Zittel U (2006) Area-averaged surface fluxes over the litfas region based on eddy-covariance measurements. Boundary-Layer Meteorol 121: 33–65CrossRefGoogle Scholar
  5. Bosilovich MG, Sun WY (1995) Formulation and verification of a land-surface parameterization for atmospheric models. Boundary-Layer Meteorol 73: 321–341CrossRefGoogle Scholar
  6. Browning KA, Morcrette CJ, Nicol J, Blyth AM, Bennet LJ, Brooks BJ, Marsham J, Mobbs SD, Parker DJ, Perry F, Clark PA, Ballard SP, Dixon MA, Forbes RM, Lean HW, Li Z, Roberts NM, Clorsmeier U, Barthlott C, Deny B, Kalthoff N, Khodayar S, Kohler M, Kottmeier C, Kraut S, Kunz M, Lenfant J, Wieser A, Agnew JL, Bamber D, McGregor J, Beswick KM, Gray MD, Norton E, Ricketts HMA, Russell A, Vaughan G, Webb AR, Bitter M, Feuerle T, Hankers R, Schulz H, Bozier KE, Collier CG, Davies F, Gaffard C, Hewison TJ, Ladd DN, Slack EC, Waight J, Ramatschi M, Wareing DP, Watson RJ (2007) The convective storm initiation project. Bull Am Meteorol Soc 88: 1939–1955CrossRefGoogle Scholar
  7. Cox PM, Betts RA, Bunton CB, Essery PP, Rowntree RLH, Smith J (1999) The impact of new land surface physics on the GCM simulation of climate and climate sensitivity. Clim Dyn 15: 183–203CrossRefGoogle Scholar
  8. Edwards JM (2009a) Radiative processes in the stable boundary layer: part I. Radiative aspects. Boundary-Layer Meteorol 131: 105–126CrossRefGoogle Scholar
  9. Edwards JM (2009b) Radiative processes in the stable boundary layer: part II. The development of the nocturnal boundary layer. Boundary-Layer Meteorol 137: 127–146CrossRefGoogle Scholar
  10. Edwards JM, McGregor JM, Bush MR, Bornemann FJ (2011) Assessment of numerical weather forecasts against observations from cardington: seasonal diurnal cycles of screen-level and surface temperatures and surface fluxes. Q J Roy Meteorol Soc 137: 656–672CrossRefGoogle Scholar
  11. Garratt JR (1994) The atmospheric boundary layer. Cambridge University Press, Cambridge 316 ppGoogle Scholar
  12. Grant ALM (1994) Wind profiles in the stable boundary layer, and the effect of low relief. Q J Roy Meteorol Soc 120: 27–46CrossRefGoogle Scholar
  13. Grunwald J, Kalthoff N, Corsmeier U, Fielder F (1996) Comparison of areally averaged turbulent fluxes over non-homogeneous terrain: results from the EFEDA-field experiment. Boundary-Layer Meteorol 77: 105–134CrossRefGoogle Scholar
  14. Kaimal JC, Gaynor JE (1991) Another look at sonic thermometry. Boundary-Layer Meteorol 56: 401–410CrossRefGoogle Scholar
  15. Lapworth A, Mason PJ (1998) The new cardington balloon-borne turbulence probe system. J Atmos Ocean Technol 5: 699–714CrossRefGoogle Scholar
  16. LeMone AM, Ikeda K, Grossman R, Rotach M (2003) Horizontal variability of 2-m temperature at night during CASES-97. J Atmos Sci 11: 2431–2449CrossRefGoogle Scholar
  17. Lenschow DH, Mann J, Kristensen L (1994) How long is long enough when measuring fluxes and other turbulence statistics?. J Atmos Ocean Technol 11: 661–673CrossRefGoogle Scholar
  18. Mahrt L, Heald RC, Lenschow DH, Stankov BB, Troen I (1979) An observational study of the structure of the nocturnal boundary layer. Boundary-Layer Meteorol 17(1): 247–264CrossRefGoogle Scholar
  19. Nieuwstadt FTM (1984) The turbulent structure of the stable, nocturnal boundary layer. J Atmos Sci 41: 2202–2216CrossRefGoogle Scholar
  20. Ogunjemiyo SO, Schuepp PH (1999) Comparison of the spatial and temporal distribution of fluxes of sensible heat, latent heat, and CO2 from grid flights in BOREAS 1994 and 1996. J Geophys Res 104: 27755–27769CrossRefGoogle Scholar
  21. Oke TR (1987) Boundary layer climates. Cambridge University Press, Cambridge 435 ppGoogle Scholar
  22. Poulos SG, Blumen W, Fritts DC, Lundquist JK, Sun J, Burns SP, Nappo C, Banta R, Newsom JC, Terradellas E, Balsley B, Jensen M (2002) CASES-99: a comprehensive investigation of the stable noturnal boundary layer. Bull Am Meteorol Soc 83:555–582Google Scholar
  23. Price JD, Vosper S, Brown A, Ross A, Clark P, Davies F, Horlacher V, Claxton B, McGregor JR, Hoare JS, Jemmett-Smith B, Sheridan P (2011) COLPEX: field and numerical studies over a region of small hills. Bull Am Meteorol Soc 92: 1636–1650CrossRefGoogle Scholar
  24. Schotanus P, Nieuwstadt FTM, DeBurin HAR (1983) Temperature measurement with a sonic anemometer and its application to heat and moisture fluxes. Boudary-Layer Meteorol 26: 81–93CrossRefGoogle Scholar
  25. Stull RB (1988) An introduction to boundary layer meteorology. Kluwer, Dordrecht, 670 ppGoogle Scholar
  26. Vickers D, Mahrt L (2004) Evaluating formulations of stable boundary layer height. J Appl Meteorol 43: 1736–1749CrossRefGoogle Scholar
  27. Vickers D, Göckede M, Law BE (2010) Uncertainty estimates for 1-h averaged turbulence fluxes of carbon dioxide, latent heat and sensible heat. Tellus B 62: 87–99CrossRefGoogle Scholar
  28. Vinnichenko NK, Pinus NZ, Shmeter SM, Shur GN (1980) Turbulence in the free atmosphere. Consultants Bureau, New York, 310 ppGoogle Scholar
  29. Wulfmeyer V, Behrendt A, Bauer HS, Kottmeier C, Corsmeier U, Blyth A, Craig G, Schumann U, Hagen M, Crewell S, Girolamo PD, Flamant C, Miller M, Montani A, Mobbs SD, Richard E, Rotach MW, Arpagaus M, Russchenberg H, Schlüssel P, König M, Gärtner V, Steinacker R, Doringer M, Turner DD, Weckwerth T, Hense A, Simmer C (2008) Research campaign: the convective and orographically induced prepcipitation study. A research and development project of the world weather research program for improving quantiative precipitation forecasting in low-mountain regions. Bull Am Meteorol Soc 89: 1477–1486CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  1. 1.Met Office, Meteorological Research UnitShortstownUK

Personalised recommendations