Relating Mean Radiosounding Profiles to Surface Fluxes for the Very Stable Boundary Layer
- 365 Downloads
A dataset collected during a measurement campaign in the middle of the Po Valley, Italy, is used to investigate the boundary-layer structure in stable conditions. Empirical formulations for temperature and wind profiles derived from Monin–Obukhov similarity theory are used as regression curves to fit radiosounding profiles in the lower half of the boundary-layer. The best fitting parameters of the regression are then compared to the surface turbulent fluxes as measured by a co-located sonic anemometer. This comparison shows significant discrepancies and supports earlier results showing that surface fluxes, in the limit of high stability, are not adequate scalings for mean profiles. The most evident differences are found for cases for which the bulk Richardson number turns out to be quite large. One of the practical consequences is that boundary-layer height diagnostic formulations that mainly rely on surface fluxes are in disagreement with those obtained by inspecting the thermodynamic profiles recorded during the radiosounding ascent. Moreover the incorrect scaling of similarity profiles in stable conditions leads to the erroneous diagnosis of 2-m air temperatures used in numerical weather prediction validation.
KeywordsBoundary-layer height Similarity theory Stable boundary-layer
We are in debt to Andrea Pitacco, Simone Righi and Sandro Nanni for logistic and technical support during the experimental phase of BASE:ALFA. Giovanni Bonafé is acknowledged for providing the surface fluxes used in this study and giving advice on their use. Many thanks to Anton Beljaars, Irina Sandu and Adrian Tompkins for clarifying some of the aspects related to the practical consequences in Numerical Weather Predictions of our work. The BASE:ALFA project was in part funded by the Emilia-Romagna Region (Bologna, Italy).
- Di Giuseppe F, Riccio A, Caporaso L, Bonafé G, Paolo G, Gobbi F (2011) Automatic detection of atmospheric boundary layer height using ceilometer backscatter data assisted by a boundary layer model. Q J R Meteorol Soc 1–18Google Scholar
- Fiala J et al (2009) Spatial assessment of PM10 and ozone concentrations in Europe (2005). Tech. rep, EEA Technical reportGoogle Scholar
- Forrer J, Rotach M (1997) On the turbulence structure in the stable boundary layer over the greenland ice sheet. Boundary-Layer Meteorol 85(1):111–136Google Scholar
- Kaimal JC, Finnigan JJ (1994) Atmospheric boundary layer flows: their structure and measurement. Oxford University Press, Oxford, 304 ppGoogle Scholar
- Mahrt L (2011) The near-calm stable boundary layer. Boundary-Layer Meteorol 135(3):385–405Google Scholar
- Mahrt L, Vickers D (2002) Contrasting vertical structures of nocturnal boundary layers. Boundary-Layer Meteorol 105:351–363Google Scholar
- Monin A, Obukhov A (1954) Basic laws of turbulent mixing in the atmosphere near the ground. Tr Akad Nauk SSSR Geofiz Inst 24(151):163–187Google Scholar
- Oncley SP, Foken T, Vogt R, Kohsiek W, DeBruin H, Bernhofer C, Christen A, Gorsel E, Grantz D, Feigenwinter C, et al (2007) The energy balance experiment EBEX-2000. Part I: overview and energy balance. Boundary-Layer Meteorol 123(1):1–28Google Scholar
- Press W, Teukolsky S, Vetterling W, Flannery B (2007) Numerical recipes, 3rd edn, The Art of Scientific Computing, 2007. Cambridge University Press, 1256 ppGoogle Scholar
- Skrivankova P (2004) Vaisala radiosonde PS92 validation trial at Prague-Libus. Vaisala News 164:4–8Google Scholar
- Stull RB (1988) An introduction to boundary layer meteorology. Kluwer Academic Publishers, Dordrecht, 666 ppGoogle Scholar