Climate and Dynamics
Improving land surface temperature modeling for dry land of China
Article first published online: 19 OCT 2011
Copyright 2011 by the American Geophysical Union.
Journal of Geophysical Research: Atmospheres (1984–2012)
Volume 116, Issue D20, 27 October 2011
How to Cite
2011), Improving land surface temperature modeling for dry land of China, J. Geophys. Res., 116, D20104, doi:10.1029/2011JD015921., , , , , , and (
- Issue published online: 19 OCT 2011
- Article first published online: 19 OCT 2011
- Manuscript Accepted: 3 AUG 2011
- Manuscript Revised: 29 JUL 2011
- Manuscript Received: 7 MAR 2011
- dry land of China;
- land surface temperature modeling
 The parameterization of thermal roughness length z0h plays a key role in land surface modeling. Previous studies have found that the daytime land surface temperature (LST) on dry land (arid and semiarid regions) is commonly underestimated by land surface models (LSMs). This paper presents two improvements of Noah land surface modeling for China's dry-land areas. The first improvement is the replacement of the model's z0h scheme with a new one. A previous study has validated the revised Noah model at several dry-land stations, and this study tests the revised model's performance on a regional scale. Both the original Noah and the revised one are driven by the Global Land Data Assimilation System (GLDAS) forcing data. The comparison between the simulations and the daytime Moderate Resolution Imaging Spectroradiometer- (MODIS-) Aqua LST products indicates that the original LSM produces a mean bias in the early afternoon (around 1330, local solar time) of about −6 K, and this revision reduces the mean bias by 3 K. Second, the mean bias in early afternoon is further reduced by more than 2 K when a newly developed forcing data set for China (Institute of Tibetan Plateau Research, Chinese Academy of Sciences (ITPCAS) forcing data) is used to drive the revised model. A similar reduction is also found when the original Noah model is driven by the new data set. Finally, the original Noah model, when driven by the new forcing data, performs satisfactorily in reproducing the LST for forest, shrubland and cropland. It may be sensible to select the z0h scheme according to the vegetation type present on the land surface for practical applications of the Noah LSM.