Advertisement

Pure and Applied Geophysics

, Volume 169, Issue 5–6, pp 911–926 | Cite as

Deep Radiation Fog in a Wide Closed Valley: Study by Numerical Modeling and Remote Sensing

  • J. Cuxart
  • M. A. Jiménez
Article

Abstract

The Ebro river basin, in the northeastern part of the Iberian Peninsula in Europe, very often experiences radiation fog episodes in winter that can last for several days. The impact on human activities is high, especially on road and air transportation. The installation in July 2009 of a WindRASS in the area, which is able to work in the presence of fog, now allows inspecting the vertical structure of the temperature and wind profiles across the roughly 300-m-thick fog layer. We present a case study of a long-lasting (60 h) deep radiation fog that took place in December 2009 to obtain a deeper understanding of the dynamic processes governing such persistent fog. Field observations of vertical profiles of temperature, wind and turbulent kinetic energy are compared with a high-resolution mesoscale simulation, satellite imagery of fog distribution and observations taken in the area to understand why the fog is so persistent and how it dissipates only for a short period in the afternoon despite intermittent turbulence within the fog deck. The confinement of the fog inside a practically closed basin allows us to study the relevant physical processes in the establishment and subsequent evolution of the fog episode using a limited-area mesoscale model. The contribution of the WindRASS measurements allowed us to validate the numerical simulations, particularly inspecting the role of turbulence that can link the bottom and top of the fog through moderate episodic mixing. The fog layer has very weak winds inside, but is well mixed and experiences intermittent top-bottom turbulence generated in its upper part by convection due to radiative cooling and by wind shear due to the topographically generated flows that blow just above the top of the fog.

Keywords

Ebro Basin mesoscale modeling radiation fog satellite imagery turbulence WindRASS 

Notes

Acknowledgements

ECMWF and AEMET are thanked for the access to computing time. We also thank Jordi Cunillera and Antonio Gázquez (SMC) for access to data from the SMC Network and from the special devices installed in Raimat, Armand Alvarez (AEMET) for his support and knowledge of the local meteorology, Felipe Molinos for the initial treatment of the WindRASS and fog data, Daniel Martinez for insightful comments on the manuscript, and the Meso-NH team in Meteo France and Laboratoire d’Aérologie. This work was partially funded by SMC and through project CGL2009-12797-C03-01 of the Spanish Government also supplied with European FEDER funds. Data from MODIS are distributed by the Land Processes Distributed Active Archive Center (LPDAAC) located at the US Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center (http://www.lpdaac.usgs.gov).

References

  1. Bergot T., Terradellas E., Cuxart J., Mira A., Liechti O., Mueller M., and Woetmann Nielsen N. (2007), Intercomparison of single-column numerical models for the prediction of radiation fog. J. Appl. Meteorol. Clim., 46, 504-521.Google Scholar
  2. Caselles V., Valor E., Coll C., and Rubio, E. (1997), Thermal band selection for the PRISM instrument 1.Analysis of emissivity-temperature separation algorithms, J. Geophs. Res., 102, 11145-11164.Google Scholar
  3. Cermak J., Eastman R. M., Bendix J., and Warren S. G. (2009), European climatology of fog and low stratus based on geostationary satellite observations, Q. J. R. Meteorol. Soc., 135, 2125-2130.Google Scholar
  4. Coll C., Caselles V., Galve J.M., Valor E., Niclos R., Sanchez J.M., Rivas R. (2005), Ground measurements for the validation of land surface temperatures derive from AATSR and MODIS data, Remote Sens. Environ., 97, 288-300.Google Scholar
  5. Cuxart J., Cunillera J., Jiménez M.A., Martínez D., Molinos F., Palau J.L. (2011), Study of mesobeta basin flows by remote sensing, Bound.-Layer Meteorol. (in press)Google Scholar
  6. Cuxart J., Jiménez M.A. (2007), Mixing Processes in a Nocturnal Low-Level Jet: An LES Study, J. Atmos. Sci., 64, 1666-1679.Google Scholar
  7. Cuxart J., Bougeault P., Redelsperger J.-L. (2000), A turbulence scheme allowing for mesoscale and large-eddy simulations, Q. J. Roy. Meteorol. Soc., 126, 1-30.Google Scholar
  8. Duynkerke P.G. (1999), Turbulence, Radiation and fog in Dutch Stable Boundary Layers, Boundary-Layer Meteorology, 90, 447-477.Google Scholar
  9. Fitzjarrald D.R., and Lala G.G. (1989), Hudson Valley Fog Environments, J. Appl. Meterol., 28, 1303-1328.Google Scholar
  10. Gultepe I., Tardif R., Michaelides S. C., Cermak J., Bott A., Bendix J., Müller M. D., Pagowski M., Hansen B., Ellrod G., Jacobs W., Toth G., and Cober S. G. (2007), Fog Research: A Review of Past Achievements and Future Perspectives, Pure Appl. Geophys., 164, 1121-1159Google Scholar
  11. Haeffelin M., Bergot T., Elias T., Tardif R., Carrer D., Chazette P., Colomb M., Drobinski P., Dupont E., Dupont J.-C., Gomes L., Musson-Genon L., Pietras C., Plana-Fattori A., Protat A., Rangognio J., Raut J.-C., Rémy S., Richard D., Sciare J., and Zhang X. (2010), PARISFOG: Shedding New Light on Fog Physical Processes, Bull. Amer. Meterol. Soc, 91, 767-783.Google Scholar
  12. Jiménez M.A., Mira A., Cuxart J., Luque A., Alonso S., Guijarro J.A. (2008), Verification of a clear-sky mesoscale simulation using satellite-derived surface temperatures, Mon. Wea. Rev., 136, 5148-5161.Google Scholar
  13. Jiménez M. A., and Cuxart J. (2005), Large-Eddy simulations of the stable boundary layer using the standard Kolmogorov theory: Range of applicability, Bound.-Layer. Meteor., 115, 241-261.Google Scholar
  14. Lafore J.P., Stein J., Asencio N., Bougeault P., Ducrocq V., Duron J., Fisher C., Héreil P., Mascart P., Pinty J.-P., Redelsperger J.-L., Richard E., Vilá-Guerau de Arellano J. (1998), The Meso-NH atmospheric simulation system. Part I: Adiabatic formulation and control simulation, Ann. Geophys., 16 90-109.Google Scholar
  15. Martínez D., Jiménez M.A., Cuxart J., Mahrt L. (2010), Heterogeneous Nocturnal Cooling in a Large Basin Under Very Stable Conditions, Bound.-Layer Meteorol., 137, 97-113.Google Scholar
  16. Martínez D., Cuxart J., and Cunillera J. (2008), Conditioned climatology for stably stratified nights in the Lleida area. Journal of Weather and Climate of the Western Mediterranean, Tethys, 5, 13-24.Google Scholar
  17. Mlawer, E.J., Taubman S.J., Brown P.D., Iacono M.J., and Clough S.A. (1997), Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res., 102, 16663-16682.Google Scholar
  18. Nakanishi M. (2000), Large-eddy simulation of radiation fog, Bound.-Layer Meteor., 94, 461-493.Google Scholar
  19. Noilhan J., Planton S. (1989), A simple parameterization of land surface processes for meteorological models, Mon. Wea. Rev., 117, 536-549.Google Scholar
  20. Pinty J.-P., and Jabouille P. (1998), A mixed-phase cloud parameterization for use in mesoscale non-hydrostatic model: simulations of a squall line and of orographic precipitations. Proc. Conf. of Cloud Physics, Everett, WA, USA, Amer. Meteor. Soc., August 1999, 217-220.Google Scholar
  21. Salomonson V.V., Bames W.L., Maymon W.P., Montgomery H., and Ostrow H. (1989), MODIS: advanced facility instrument for studies of the Earth as a system. IEEE Trans. Geosci. Remote Sens., 27 145-153.Google Scholar
  22. van der Velde I.R., Steeneveld, G.J., Wichers Schreur, B.G.J. and Holtslag, A.A.M. (2010), Modeling and forecasting the onset and duration of severe radiation fog under frost conditions, Mon. Wea. Rev., 138, 4237-4253.Google Scholar
  23. Vicente-Serrano, S.M., Lopez-Moreno, J.I., Vega-Rodriguez, M.I., Begeria, S., Cuadrat, J.M. (2010), Comparison of regression techniques for mapping fog frequency: application to the Aragon region (northeast Spain), International Journal of Climatology, 30: 935-945.Google Scholar
  24. Wan Z., and Dozier, J. (1996), A generalised split-window algorithm for retrieving land-surface temperature from space, IEEE Trans. Geosci. Remote Sens., 34, 892-905.Google Scholar
  25. Wan Z., and Li Z.-L. (1997), A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS data, IEEE Trans. Geosci. Remote Sens., 35, 980-996.Google Scholar
  26. Wobrock W., Schell D., Maser R., Kessel M., Jaeschke W., Fuzzi S., Facchini M.C., Orsi G., Marzorati A., Winkler P., G. Arends B.G., and Bendix J. (1992), Meteorological characteristics of the Po Valley fog, Tellus B, 55, 469-488.Google Scholar
  27. Zhou B., and Ferrier B.S. (2008), Asymptotic Analysis of Equilibrium in Radiation Fog, J. Appl. Meteor. Climatol., 47, 1704-1722.Google Scholar

Copyright information

© Springer Basel AG 2011

Authors and Affiliations

  1. 1.Grup de Meteorologia, Dpt. FísicaUniv. de les Illes BalearsPalma de MallorcaSpain

Personalised recommendations