Editorial Type:
Article
Article Type:
Research Article

Variational Estimation of Land–Atmosphere Heat Fluxes and Land Surface Parameters Using MODIS Remote Sensing Data

Chunlei Meng Institute of Urban Meteorology, China Meteorological Administration, Beijing, China

Search for other papers by Chunlei Meng in
Current site
Google Scholar
PubMed Close
,
Chaolin Zhang Department of Earth Sciences, National Natural Science Foundation of China, Beijing, China

Search for other papers by Chaolin Zhang in
Current site
Google Scholar
PubMed Close
, and
Ronglin Tang Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing, China

Search for other papers by Ronglin Tang in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Apr 2013
DOI:
https://doi.org/10.1175/JHM-D-12-028.1
Page(s):
608–621
Restricted access

Abstract

A variational data assimilation algorithm for assimilating the land surface temperature (LST) into the Common Land Model (CLM) was implemented using the land surface energy balance equation as the adjoint physical constraint. In this data assimilation algorithm, the evaporative fractions of the soil and canopy were adjusted according to the remotely sensed surface temperature observations. This paper developed a very simple analytical algorithm to characterize the errors’ weighting matrices in the cost function. The leaf area index (LAI) retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) was also assimilated into CLM using the direct insertion method. The analysis results from the CLM with the LST assimilation algorithm compare well with MODIS and field observations for the Yucheng site, especially in daytime. On the basis of the histogram of the error of the LST, it can be concluded that after assimilation, the LST was greatly improved in comparison with the MODIS observations, especially in daytime. These results indicate that this surface temperature assimilation method is efficient and effective, even when only one time observational LST data point is available for each day, especially in daytime. The regional spatial patterns of evapotranspiration and soil surface moisture were also compared before assimilation on the basis of LAI data calculated using the empirical formula, before assimilation on the basis of MODIS LAI data, and after assimilation on the basis of MODIS LAI data.

Corresponding author address: Chunlei Meng, Institute of Urban Meteorology, CMA, No. 55 Beiwaxili, Haidian District, Beijing 100089, China. E-mail: clmeng@ium.cn

Abstract

A variational data assimilation algorithm for assimilating the land surface temperature (LST) into the Common Land Model (CLM) was implemented using the land surface energy balance equation as the adjoint physical constraint. In this data assimilation algorithm, the evaporative fractions of the soil and canopy were adjusted according to the remotely sensed surface temperature observations. This paper developed a very simple analytical algorithm to characterize the errors’ weighting matrices in the cost function. The leaf area index (LAI) retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) was also assimilated into CLM using the direct insertion method. The analysis results from the CLM with the LST assimilation algorithm compare well with MODIS and field observations for the Yucheng site, especially in daytime. On the basis of the histogram of the error of the LST, it can be concluded that after assimilation, the LST was greatly improved in comparison with the MODIS observations, especially in daytime. These results indicate that this surface temperature assimilation method is efficient and effective, even when only one time observational LST data point is available for each day, especially in daytime. The regional spatial patterns of evapotranspiration and soil surface moisture were also compared before assimilation on the basis of LAI data calculated using the empirical formula, before assimilation on the basis of MODIS LAI data, and after assimilation on the basis of MODIS LAI data.

Corresponding author address: Chunlei Meng, Institute of Urban Meteorology, CMA, No. 55 Beiwaxili, Haidian District, Beijing 100089, China. E-mail: clmeng@ium.cn
Save
Cover Journal of Hydrometeorology
Journal of Hydrometeorology

  • Balsamo, G., Mahfouf J.-F. , and Belair S. , 2007: A land data assimilation system for soil moisture and temperature: An information content study. J. Hydrometeor., 8, 1225–1242.

    • Search Google Scholar
    • Export Citation

  • Boussetta, S., Koike T. , Yang K. , Graf T. , and Pathmathevan M. , 2008: Development of a coupled land–atmosphere satellite data assimilation system for improved local atmospheric simulations. Remote Sens. Environ., 112, 720–734.

    • Search Google Scholar
    • Export Citation

  • Caparrini, F., Castelli F. , and Entekhabi D. , 2003: Mapping of land–atmosphere heat fluxes and surface parameters with remote sensing data. Bound.-Layer Meteor., 107, 605–633.

    • Search Google Scholar
    • Export Citation

  • Caparrini, F., Castelli F. , and Entekhabi D. , 2004a: Estimation of surface turbulent fluxes through assimilation of radiometric surface temperature sequences. J. Hydrometeor., 5, 145–159.

    • Search Google Scholar
    • Export Citation

  • Caparrini, F., Castelli F. , and Entekhabi D. , 2004b: Variational estimation of soil and vegetation turbulent transfer and heat flux parameters from sequences of multisensor imagery. Water Resour. Res., 40, W12515, doi:10.1029/2004WR003358.

    • Search Google Scholar
    • Export Citation

  • Castelli, F., Entekhabi D. , and Caporali E. , 1999: Estimation of surface heat flux and an index of soil moisture using adjoint-state surface energy balance. Water Resour. Res., 35, 3115–3125.

    • Search Google Scholar
    • Export Citation

  • Crago, R., and Brutsaert W. , 1996: Daytime evaporation and the self-preservation of the evaporative fraction and the Bowen ratio. J. Hydrol., 178, 241–255.

    • Search Google Scholar
    • Export Citation

  • Dai, Y., and Coauthors, 2003: The Common Land Model. Bull. Amer. Meteor. Soc., 84, 1013–1023.

  • Gitelson, A. A., Wardlow B. D. , Keydan G. P. , and Leavitt B. , 2007: An evaluation of MODIS 250-m data for green LAI estimation in crops. Geophys. Res. Lett., 34, L20403, doi:10.1029/2007GL031620.

    • Search Google Scholar
    • Export Citation

  • Kundu, P. K., and Bell T. L. , 2003: A stochastic model of space-time variability of mesoscale rainfall: Statistics of spatial averages. Water Resour. Res., 39, 1328, doi:10.1029/2002WR001802.

    • Search Google Scholar
    • Export Citation

  • Margulis, S. A., and Entekhabi D. , 2003: Variational assimilation of radiometric surface temperature and reference-level micrometeorology into a model of the atmospheric boundary layer and land surface. Mon. Wea. Rev., 131, 1272–1288.

    • Search Google Scholar
    • Export Citation

  • Margulis, S. A., Kim J. , and Hogue T. , 2005: A comparison of the triangle retrieval and variational data assimilation methods for surface turbulent flux estimation. J. Hydrometeor., 6, 1063–1072.

    • Search Google Scholar
    • Export Citation

  • McLaughlin, D., 2002: An integrated approach to hydrologic data assimilation: Interpolation, smoothing, and filtering. Adv. Water Resour., 25, 1275–1286.

    • Search Google Scholar
    • Export Citation

  • Meng, C., Li Z. , Zhan X. , Shi J. , and Liu C. , 2009: Land surface temperature data assimilation and its impact on evapotranspiration estimates from the Common Land Model. Water Resour. Res., 45, W02421, doi:10.1029/2008WR006971.

    • Search Google Scholar
    • Export Citation

  • Myneni, R. B., and Coauthors, 2002: Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ., 83, 214–231.

    • Search Google Scholar
    • Export Citation

  • Pisek, J., and Chen J. M. , 2007: Comparison and validation of MODIS and VEGETATION global LAI products over four BigFoot sites in North America. Remote Sens. Environ., 109, 81–94.

    • Search Google Scholar
    • Export Citation

  • Privette, J. L., and Coauthors, 2002: Early spatial and temporal validation of MODIS LAI product in Southern Africa Kalahari. Remote Sens. Environ., 83, 232–243.

    • Search Google Scholar
    • Export Citation

  • Reichle, R. H., Entekhabi D. , and McLaughlin D. B. , 2001a: Downscaling of radio brightness measurements for soil moisture estimation: A four-dimensional variational data assimilation approach. Water Resour. Res., 37, 2353–2364.

    • Search Google Scholar
    • Export Citation

  • Reichle, R. H., McLaughlin D. B. , and Entekhabi D. , 2001b: Variational data assimilation of microwave radiobrightness observations for land surface hydrology applications. IEEE Trans. Geosci. Remote Sens., 39, 1708–1718.

    • Search Google Scholar
    • Export Citation

  • Rodell, M., and Coauthors, 2004: The Global Land Data Assimilation System. Bull. Amer. Meteor. Soc., 85, 381–394.

  • Ronda, R. J., and Bosveld F. C. , 2009: Deriving the surface soil heat flux from observed soil temperature and soil heat flux profile using a variational data assimilation approach. J. Appl. Meteor. Climatol., 48, 644–656.

    • Search Google Scholar
    • Export Citation

  • Sabater, J.-M., Jarlan L. , Calvet J.-C. , Bouyssel F. , and De Rosnay P. , 2007: From near-surface to root-zone soil moisture using different assimilation techniques. J. Hydrometeor., 8, 194–206.

    • Search Google Scholar
    • Export Citation

  • Sabater, J.-M., Rudiger C. , Calvet J.-C. , Fritz N. , Jarlan L. , and Kerr Y. , 2008: Joint assimilation of surface soil moisture and LAI observations into a land surface model. Agric. For. Meteor., 148, 1362–1373.

    • Search Google Scholar
    • Export Citation

  • Tian, X., Xie Z. , and Dai A. , 2008: An ensemble-based explicit four-dimensional variational assimilation method. J. Geophys. Res., 113, D21124, doi:10.1029/2008JD010358.

    • Search Google Scholar
    • Export Citation

  • Tian, Y., and Coauthors, 2002a: Multiscale analysis and validation of the MODIS LAI product: I. Uncertainty assessment. Remote Sens. Environ., 83, 414–430.

    • Search Google Scholar
    • Export Citation

  • Tian, Y., and Coauthors, 2002b: Multiscale analysis and validation of the MODIS LAI product: II. Sampling strategy. Remote Sens. Environ., 83, 431–441.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 163 75 7
PDF Downloads 80 35 3