The dominant parameters in the Noah land surface model （LSM） are identified, and the effects of parameter optimization on the surface heat exchange are investigated at a temperate desert steppe site during growing s...The dominant parameters in the Noah land surface model （LSM） are identified, and the effects of parameter optimization on the surface heat exchange are investigated at a temperate desert steppe site during growing season in Inner Mongolia, China. The relative impacts of parameters on surface heat flux are examined by the distributed evaluation of local sensitivity analysis （DELSA）, and the Noah LSM is calibrated by the global shuffled complex evolution （SCE） against the corresponding observations during May-September of 2008 and 2009. The differences in flux sim- ulations are assessed between the Noah LSM calibrated by the SCE with 27 parameters and 12 dominant parameters. The systematic error, unsystematic error, root mean squared error, and mean squared error decompositions are used to evaluate the model performance. Compared to the control experiment, parameter optimization by the SCE using net radiation, sensible heat flux, latent heat flux, and ground heat flux as the objective criterion, respectively, can ob- viously reduce the errors of the Noah LSM. The calibrated Noah LSM is further validated against flux observations of growing season in 2010, and it is found that the calibrated Noah LSM can be applied in the longer term at this site. The Noah LSM with 12 dominant parameters calibrated performs similar to that with 27 parameters calibrated.展开更多
基金Supported by the National Natural Science Foundation of China(41505010)Chinese Academy of Meteorological Sciences(CAMS)Basic Research Special Project(2017Y014 and 2015Z002)+1 种基金China Meteorological Administration Special Public Welfare Research Fund(GYHY201506001)National Basic Research and Development(973)Program of China(2010CB951303)
文摘The dominant parameters in the Noah land surface model （LSM） are identified, and the effects of parameter optimization on the surface heat exchange are investigated at a temperate desert steppe site during growing season in Inner Mongolia, China. The relative impacts of parameters on surface heat flux are examined by the distributed evaluation of local sensitivity analysis （DELSA）, and the Noah LSM is calibrated by the global shuffled complex evolution （SCE） against the corresponding observations during May-September of 2008 and 2009. The differences in flux sim- ulations are assessed between the Noah LSM calibrated by the SCE with 27 parameters and 12 dominant parameters. The systematic error, unsystematic error, root mean squared error, and mean squared error decompositions are used to evaluate the model performance. Compared to the control experiment, parameter optimization by the SCE using net radiation, sensible heat flux, latent heat flux, and ground heat flux as the objective criterion, respectively, can ob- viously reduce the errors of the Noah LSM. The calibrated Noah LSM is further validated against flux observations of growing season in 2010, and it is found that the calibrated Noah LSM can be applied in the longer term at this site. The Noah LSM with 12 dominant parameters calibrated performs similar to that with 27 parameters calibrated.
