Advertisement

Estimation of net surface shortwave radiation from land surface temperature in regional scale

  • Pei Leng
  • Xiaoning Song
  • Zhaoliang Li
Article
  • 117 Downloads

Abstract

The method to estimate NSSR (net surface shortwave radiation) from LST (land surface temperature) in regional scale is discussed. First, an elliptical model between the time series of normalized LST and NSSR was developed using the daily evolution of LST and NSSR. Second, time series of LST and NSSR were simulated by common land model (CoLM) and were proved to be of high accuracy. On the basis of these, a non-linear least square ellipse fitting using the genetic algorithm method was used to fit the normalized LST and NSSR. Finally, LST was inverted using MODIS (moderate resolution imaging spectroradiometer) data with the split-window algorithm, and the regional NSSR was then estimated with LST and an elliptical model. The validation result shows that the derived average NSSR of 50×50 pixels of MODIS data was quite close to the observed data, and the distribution was reasonable, which indicates that the proposed method was capable of estimating NSSR on a regional scale.

Key words

net surface shortwave radiation land surface temperature elliptical model common land model (CoLM) moderate resolution imaging spectroradiometer (MODIS) 

CLC number

TP 79 

References

  1. [1]
    Pinker R T, Corio L. Surface radiation budget from satellites [J]. Monthly Weather Review, 1984, 112: 209–215.CrossRefGoogle Scholar
  2. [2]
    Pinker R T, Ewing J A. Modeling surface solar radiation: Model formulation and validation [J]. Journal of Climate and Applied Meteorology, 1985, 24: 389–401.CrossRefGoogle Scholar
  3. [3]
    Pinker R T, Tarpley J D. The relationship between the planetary and surface net radiation: An update [J]. Journal of Applied Meteorology, 1988, 27: 957–964.CrossRefGoogle Scholar
  4. [4]
    Cess R D, Vulis I L. Inferring surface-solar absorption from broadband satellite measurements [J]. Journal of Climate, 1989, 2: 974–985.CrossRefGoogle Scholar
  5. [5]
    Cess R D, Dutton E G, DeLuisi J J, et al. Determining surface solar absorption from broadband satellite measurements for clear skies: Comparisons with surface measurements [J]. Journal of Climate, 1991, 4: 236–247.CrossRefGoogle Scholar
  6. [6]
    Li Z, Leighton H G, Masuda K, et al. Estimation of shortwave flux absorbed at the surface from TOA reflected flux [J]. Journal of Climate, 1993, 6: 317–330.CrossRefGoogle Scholar
  7. [7]
    Tang B H, Li Z L, Zhang R H. A direct method for estimating net surface shortwave radiation from MODIS data [J]. Remote Sensing of Environment, 2006, 103: 115–126.CrossRefGoogle Scholar
  8. [8]
    Kim H Y, Liang S L. Development of a hybrid method for estimating land surface shortwave net radiation from MODIS data [J]. Remote Sensing of Environment, 2010, 114: 2393–2402.CrossRefGoogle Scholar
  9. [9]
    Göttsche F M, Olesen F S. Modelling the effect of optical thickness on diurnal cycles of land surface temperature [J]. Remote Sensing of Environment, 2009, 113: 2306–2316.CrossRefGoogle Scholar
  10. [10]
    Wang Shusen, Chen Wenjun, Josef C. New calculation methods of diurnal distribution of solar radiation and its interception by canopy over complex terrain [J]. Ecological Modelling, 2002, 00: 1–14.Google Scholar
  11. [11]
    Li Fuqin, Thomas J J, William P K, et al. Deriving land surface temperature from Landsat 5 and 7 during SEMEX02/SMACEX [J]. Remote Sensing of Environment, 2004, 92: 521–534.CrossRefGoogle Scholar
  12. [12]
    Wan Z, Dozier J. A generalized split-window algorithm for retrieving land surface temperature from space [J]. IEEE Trans Geosci Remote Sensing, 1996, 34: 892–905.CrossRefGoogle Scholar
  13. [13]
    Qin Zhihao, Zhang Minghua, Arnon K. Split window algorithms for retrieving land surface temperature from NOAA-AVHRR data [J]. Remote Sensing for Land & Resources, 2001, 48: 33–42(Ch).Google Scholar
  14. [14]
    Dai Yongjiu, Ji Duoying. The Common Land Model (CoLM) User’s Guide [EB/OL]. [2010-10-20]. http://globalchange.bnu.edu.cn/research/models.
  15. [15]
    Anandaroop R, Deepak C S. Non-linear least squares ellipse fitting using the genetic algorithm with applications to strain analysis [J]. Journal of Structural Geology, 2008, 30: 1593–1602.CrossRefGoogle Scholar
  16. [16]
    Mao K B, Qin Z H, Shi J C, et al. A practical split-window algorithm for retrieving land-surface temperature from MODIS data [J]. International Journal of Remote Sensing, 2005, 26: 3181–3204.CrossRefGoogle Scholar

Copyright information

© Wuhan University and Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.College of Resources and EnvironmentGraduate School of Chinese Academy of SciencesBeijingChina
  2. 2.Institute of Geographic Sciences and Natural Resources ResearchBeijingChina

Personalised recommendations