Atmospheric Chemistry and Physics Discussions
www.atmos-chem-phys-discuss.net
1680-7367
1680-7375
8
4
2008
10.5194/acpd-8-16219-2008
http://www.atmos-chem-phys-discuss.net/8/16219/2008/
http://www.atmos-chem-phys-discuss.net/8/16219/2008/acpd-8-16219-2008.html
http://www.atmos-chem-phys-discuss.net/8/16219/2008/acpd-8-16219-2008.pdf
16219
16254
2008-08-26
Spatial heterogeneity of satellite derived land surface parameters and energy flux densities for LITFASS-area
A. Tittebrand
antje.tittebrand@zmaw.de
F. H. Berger
Institute for Hydrology and Meteorology, Dresden, Germany
Deutscher Wetterdienst, Meteorologisches Observatorium Lindenberg, Germany
now at: Institute for Oceanography, Hamburg, Germany
Remote sensing data provide area integrated information of surface
properties in different spatial or temporal resolutions according to
different sensor features. Landsat ETM+, Terra MODIS and NOAA-AVHRR surface
temperature and spectral reflectance were used to infer further surface
parameters and radiant- and energy flux densities for LITFASS-area, a
20×20 km<sup>2</sup> heterogeneous area in Eastern Germany, mainly characterized by
the land use types forest, crop, grass and water. Based on the
Penman-Monteith-approach the actual latent heat flux (<i>L.E</i>), as key quantity of
the hydrological cycle, is determined for each sensor in the accordant
spatial resolution with an improved parametrization. However, using three
sensors, significant discrepancies between the inferred parameters can cause
flux distinctions resultant from differences of the sensor filter response
functions or atmospheric correction methods. The approximation of MODIS- and
AVHRR- derived surface parameters to the reference parameters of ETM (via
regression lines and histogram stretching, respectively), further the use of
accurate land use classifications (CORINE and a new Landsat-classification), and a consistent
parametrization for the three sensors were realized to obtain a uniform base
for investigations of the spatial variability. For the target area the
spatial heterogeneity is analysed investigating frequency distribution
functions (PDF) for surface parameters and energy fluxes. PDF is the most
promising way to describe subgrid heterogeneity due to the given data in
different spatial resolution. Aim of this study is to find typical
distribution pattern of parameters (albedo, NDVI) for the determination of <i>L.E</i>
determined from the highly resolved ETM data within pixel on coarser scale
(MODIS, AVHRR). The analyses for 4 scenes in 2002 and 2003 showed that clear
distribution-pattern for forest for NDVI and albedo are found. Grass and crop
distributions show higher variability and differ significantly to each other
in NDVI but only marginal in albedo. Regarding NDVI-distribution functions NDVI was
found to be the key variable for <i>L.E</i>-determination.
Allen, R. G.: A Penman for all seasons, J. Irrig. Drain Eng., 112/4, 348–368, 1986.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration – guidelines for computing crop water requirements, FAO Irrigation and Drainage paper, 56, Rome, Italy, 1998.
Arain, A. M., Miachaud, J. D., Shuttleworth, W. J., and Dolman, A. J.: Testing of vegetation parameter aggregation rules applicable to the Biosphere-Atmosphere Transfer Scheme (BATS) at the Fife site, J. Hydrol., 177, 1–22, 1996.
Avissar, R.: Conceptual aspects of a statistical-dynamical approach to represent landscape subgrid-scale heterogeneities in atmospheric models, J. Geophys. Res., 97, 2729–2742, 1992.
Bach, H., Braun, M., Lampart G., and Ranzi, R.: Estimates of surface parameters via remote sensing for the Toce watershed, in: RAPHAEL – Runoff and Atmospheric Processes for Flood Hazard Forecasting and Control, edited by: Bacchi, B. and Ranzi, R., EC, Directorate General XII, Programme Environment and Climate 1994–1998, Contract no. ENV4-CT97-0552, Final Report, 2000.
Batra, N., Islam, S., Venturini, V., Bisht G., and Jiang, L.: Estimation and comparison of evapotranspiration from MODIS and AVHRR sensors for clear sky days over the Southern Great Plains, Remote Sens. Environ., 103(1), 1–15, 2006.
Becker, F. and Li, Z.: Towards a local split window method over land surfaces, Int. J. Remote Sens., 11, 369–393, 1990.
Becker, F. and Li, Z.: Surface temperature and emissivity at various scales: Definition, measurement and related problems, Remote Sens. Rev., 12, 225–253, 1995.
Berger, F. H.: Bestimmung des Energiehaushaltes am Erdboden mit Hilfe von Satellitendaten, Tharandter Klimaprotokolle, Band 5, 206 pp., 2001.
Berger, F. H. and Schwiebus, A.: Energieflüsse heterogener Landoberflächen, abgeleitet aus Satellitendaten, Schlussbericht Projekt VERTIKO, TUD2, FK 07 AFT37-TUD2, Technische Universität Dresden, 27 pp., 2004.
Beyrich, F., Adam, W. K., Bange, J., Behrens, K., Berger, F. H., Bernhofer, C., Bösenberg, J., Dier, H., Foken, T., Gödecke, M., Görsdorf, U., Güldner, J., Hennemuth, B., Heret, C., Huneke, S., Kohsiek, W., Lammert, A., Lehmann, V., Leiterer, U., Leps, J.-P., Liebethal, C., Lohse, H., Lüdi, A., Mauder, M., Meijnger, W. M. L., Mengelkamp, H.-T., Queck, R., Richter, S. H., Spieß, T. , Stiller, B., Tittebrand, A., Weisensee, U., and Zittel, P.: Verdunstung über einer heterogenen Landoberfläche – das LITFASS-2003 Experiment: ein Bericht, Arbeitsergebnisse Nr. 79, Deutscher Wetterdienst, Offenbach, Germany, 100, 2004.
Bonan, G. B., Pollard, D., and Thompson, S. L.: Influence of Subgrid-Scale Heterogeneity in Leaf Area Index, Stomatal Resistance, and Soil Moisture on Grid-Scale Land–Atmosphere Interactions, J. Climate, 6(10), 1882–1897, 1993.
Breuer, L., Eckhardt, K., and Frede, H.-G.: Plant parameter values for models in temperate climates, Ecol. Model., 169, 237–293, 2003.
Buheaosier, K., Tsuchiya, K., Keneko, M., and Sung, S. J.: Comparison of image data aquired with AVHRR, MODIS, ETM+ and ASTER over Hokkaido, Japan, Adv. Space Res., 32, 11, 2211–2216, 2003.
Chehbouni, A., Njoku, E. G., Lhomme, J.-P., and Kerr, Y. H.: An approach for averaging surface temperature and surface fluxes over heterogeneous surfaces, J. Climate, 5, 1386–1393, 1995.
Claussen, M.: Estimation of regional heat and momentum fluxes in homogenous terrain with bluff roughness elements, J. Hydrol., 166, 353–369, 1995a.
De Rooy, W. C. and Holtslag, A. A. M.: Estimation of surface radiation and energy flux densities from single-level weather data, J. Appl. Meteorol., 38, 526–540, 1999.
EEA, European Environment Agency: The thematic accuracy of CORINE land cover 2000, assessment using LUCAS (Land Use/Cover Area frame statistical Survey), Technical report No 7, European Environment Agency, Copenhagen, 85 pp., 2006.
EOS: http://delenn.gsfc.nasa.gov/~imswww/pub/imswelcome/index.html, 5 October 2007.
Entekhabi, D. and Eagleson, P. S.: Land Surface Hydrology Parametrization for atmospheric general circulation models including subgrid scale spatial variability, J. Climate, 2, 816–831, 1989.
Gao, W., Coulter, R. L., Lesht, B. M., Qiu, J, and Wesely, M. L.: Estimating clear-sky regional surface fluxes in the Southern Great Plains Atmospheric Radiation Measurement Site with ground measurements and satellite observations, J. Appl. Meteorol., 37, 5–22, 1998.
Garrigues, S., Allard, D., Baret, F., and Weiss, M.: Quantifying spatial heterogeneity at the landscape scale using variogram models, Remote Sens. Environ., 103, 81–96, 2006.
Giorgi, P.: An approach for representation of surface heterogeneity in land surface models – Part 1: Theoretical framework, Mon. Weather Rev., 125, 1885–1899, 1996a.
Giorgi, P.: An approach for representation of surface heterogeneity in land surface models – Part 2: Validation and sensitività experiments, Mon. Weather Rev., 125, 900–1919, 1996b.
Hagemann, S.: An improved land surface parameter dataset for global and regional climate models, Report No. 336, MPI for Meteorology, Hamburg, Germany, 2002.
Keil, M., Kiefl, R., and Strunz, G.: CORINE Land Cover 2000 – Europaweit harmonisierte Aktualisierung der Landnutzungsdaten für Deutschland, Abschlussbericht zum F+E Vorhaben, UBA FKZ 201 12 209 (1 May 2001–31 December 2004), 2005.
Kelliher, F. M., Leuning, R., Raupach, M. R., and Schulze, E.-D.: Maximum conductances for evaporation from global vegetation types, Agr. Forest Meteorol., 73, 1–16, 1995.
Key, J. R.: Streamer – user's guide, Technical report 96-01, Department of Geography, Boston University, Boston, MA, USA, 1999.
Koster, R. D. and Suarez, M. J.: A comparative analysis of two land surface heterogeneity representations, J. Climate, 5, 12, 1379–1390, 1992a.
Koster, R. D. and Suarez, M. J.: Modeling the land surface boundary in climate models as a composite of independent vegetation stands. J. Geophys. Res., 97(D3), 2697–2715, 1992b.
Landsat: http://landsat.usgs.gov/project_facts/project_news/June_2003.php, 10 September 2003.
Lhomme, J.-P.: Energy balance of heterogeneous terrain: averaging the controlling parameters, Agr. Forest Meteorol., 61, 11–21, 1992.
Lhomme, J.-P., Chehbouni, A., and Monteny, B.: Effective parameters of surface energy balance in heterogeneous landscape, Bound.-Lay. Meteorol., 71, 297–309, 1994.
Li, B. and Avissar, R.: The Impact of Spatial Variability of Land-Surface-Charakteristics on Land-Surface Heat Fluxes, J. Climate, 7, 527–537, 1994.
Liang, S., Shuey, C. J., Russ, A. L., Fang, H., Chen, M., Walthall, C. L., Daughtry, C. S. T., and Hunt Jr., R.: Narrowband to Broadband conversion of land surface albedo – II: Validation, Remote Sens. Environ., 84, 25–41, 2002.
Ma, Y., Zhong, L., Su, Z., Ishikawa, H., Meneti, M., and Koike, T.: Determination of regional distributions and seasonal variations of land surface heatfluxes from Landsat-7 enhanced Themativ Mapper data over the central Tibetan Plateau area, J. Geophys. Res., 111, D10305, doi:10.1029/2005JD006742, 2006.
MAGIM: Forschergruppe 536 der Deutschen Forschungsgemeinschaft: Matter fluxes in grasslands of Inner Mongolia as influenced by stocking rate (MAGIM), Fortsetzungsantrag MAGIM-Phase II: 04/2007-03/2010, Institut für Meteorologie und Klimaforschung (IMK-IFU), Forschungszentrum Karlsruhe, Garmisch-Partenkirchen, Germany, 2006.
McClain, E. P., Pichel, W. G., and Walton, C. C.: Comparative performance of AVHRR-based multichannel sea surface temperatures, J. Geophys. Res., 90, 11 587–11 601, 1985.
Mengelkamp, H.-T., Beyrich, F., Heinemann, G., Ament, F., Bange, J., Berger, F. H., Bösenberg, J., Foken, T., Hennemuth, B., Heret, C., Huneke, S., Johnsen, K.-P., Kohsiek, W., Leps, J.-P., Liebethal, C., Lohse, H., Mauder, M., Meijninger, W., Raasch, S., Simmer, C., Spieß, T., Tittebrand, A., Uhlenbrock, J., and Zittel, P.: Evaporation over a heterogeneous land surface: the EVA_GRIPS project, B. Am. Meteorol. Soc., 775–786, 2006.
Mölders, N. and Raabe, A.: Numerical investigations on the influence of subgrid-scale surface heterogeneity on evapotranspiration and cloud processes, J. Appl. Meteor., 35, 782–795, 1996.
NASA Goddard Space Flight Center: LANDSAT 7 Science Data User Handbook, Landsat Project Science Office, NASA Goddard Space Flight Center, MD, USA, 2004.
Njoku, E. G., Hook, S. J., and Chehbouni, A.: Effects of surface heterogeneity on thermal remote sensing of land parameters, in: Scaling up in Hydrology using Remote Sensing, edited by: Stewart, J. B, Engmann, E. T., Feddes, R. A., and Kerr, Y., John Wiley and Sons, hichester, 1996.
Noilhan, J., Lacarrere, P., Dolman, A. J., and Blyth, E. M.: Defining area-average parameters in meteorological models for land surfaces with mesoscale heterogeneity, J. Hydrol., 190, 302–316, 1997.
Pinker, R. T.: Satellites and our understanding of the surface energy balance, Palaeogeogr. Palaeocl., 82, 321–342, 1990.
Sellers, P. J., Heiser, M. D., Hall, F. G., Verma, S. B., Desjardins, R. L., Schuepp P. M., and MacPherson, J. I.: The impact of using area-averaged land surface properties – topography, vegetation condition, soil wetness – in calculations of intermediate scale (approximately 10 km$^2)$ surface-atmosphere heat and moisture fluxes, J. Hydrol., 190, 269–301, 1997.
Shuttleworth, W. J., Yang, Z.-L., and Arain, M. A.: Aggregation rules for surface parameters in global models, Hydrol. Earth Syst. Sci., 1, 217–226, 1997.
Sobrino J. A., Jimenez-Munoz, J. C., and Paolini, L.: Land surface temperature retrieval from LANDSAT TM 5, Remote Sens. Environ., 90, 434–440, 2004.
Sonntag, D. and Heinze, D.: Sättigungsdampfdruck- und Sättigungsdampfdichtetafeln für Wasser und Eis, 1. Ed., VEB Deutscher Verlag für Grundstoffindustrie, Leipzig, 1982.
Teillet, P. M., Staenz, K., and Williams, D. J.: Effects of spectral, spatial, and radiometric characteristics on remote sensing vegetation indices of forested regions, Remote Sens. Environ., 61, 139–149, 1997.
Tittebrand, A., Schwiebus, A., and Berger, F. H.: The influence of land surface parameters on energy flux densities derived from remote sensing data, Meteorol. Z., 14(2), 227–236, 2005.
Van Leeuwen, W. J. D., Huete, A. R., and Laing, T. W.: MODIS Vegetation Index Compositing Approach: a prototype with AVHRR data, Remote Sens. Environ., 69, 264–280, 1999.
Van Leeuwen, W. J. D., Orr, B. J., Marsh, S. E, and Herrmann, S. M.: Multi-sensor NDVI data continuity: uncertainties and implications for vegetation monitoring applications, Remote Sens. Environ., 100, 67–81, 2006.
Vermote, E., Tandre, D., Deutze, J. L., Herman, M., Morcrette, J. J.: Second Simulation of the Satellite Signal in the Solar Spectrum (6S), 6S User Guide, NASA Goddard Space Flight Center, Greenbelt, 54 pp., 1997.
Wan, Z. and Dozier, J.: Land surface temperature measurement from space: Physical principles and inverse modelling, IEEE T. Geosci. Remote, 27, 268–278, 1989.