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Analysis of parameter sensitivity on surface heat exchange in the Noah land surface model at a temperate desert steppe site in China

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Abstract

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 simulations 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 obviously 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.

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References

  • Abramowitz, G., R. Leuning, M. Clark, et al., 2008: Evaluating the performance of land surface models. J. Climate, 21, 5468–5481, doi: 10.1175/2008JCLI2378.1.

    Article  Google Scholar 

  • Alfieri, J. G., D. Niyogi, P. D. Blanken, et al., 2008: Estimation of the minimum canopy resistance for croplands and grasslands using data from the 2002 International H2O Project. Mon. Wea. Rev., 136, 4452–4469, doi: 10.1175/2008MWR2524.1.

    Article  Google Scholar 

  • Cai, X. T., Z. L. Yang, Y. L. Xia, et al., 2014: Assessment of simulated water balance from Noah, Noah‐MP, CLM, and VIC over CONUS using the NLDAS test bed. J. Geophys. Res., 119, 13751–13770, doi: 10.1002/2014JD022113.

    Google Scholar 

  • Chen, F., and Y. Zhang, 2009: On the coupling strength between the land surface and the atmosphere: From viewpoint of sur-face exchange coefficients. Geophys. Res. Lett., 36, L10404, doi: 10.1029/2009GL037980.

    Article  Google Scholar 

  • Chen, F., K. Mitchell, J. Schaake, et al., 1996: Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J. Geophys. Res., 101, 7251–7268, doi: 10.1029/95JD02165.

    Article  Google Scholar 

  • Chen, F., Z. Janjic, and K. Mitchell, 1997: Impact of atmospheric surface-layer parameterizations in the new land-surface scheme of the NCEP mesoscale Eta model. Bound.-Layer Meteor., 85, 391–421, doi: 10.1023/A:1000531001463.

    Article  Google Scholar 

  • Chen, Y. Y., K. Yang, D. G. Zhou, et al., 2010: Improving the Noah land surface model in arid regions with an appropriate parameterization of the thermal roughness length. J. Hydrometeor., 11, 995–1006, doi: 10.1175/2010JHM1185.1.

    Article  Google Scholar 

  • Duan, Q. Y., V. K. Gupta, and S. Sorooshian, 1993: Shuffled complex evolution approach for effective and efficient global minimization. J. Optim. Theory Appl., 76, 501–521, doi: 10.1007/BF00939380.

    Article  Google Scholar 

  • Ek, M. B., K. E. Mitchell, Y. Lin, et al., 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational Mesoscale Eta Model. J. Geophys. Res., 108, 8851, doi: 10.1029/2002JD003296.

    Article  Google Scholar 

  • Guan, X. D., J. P. Huang, and R. X. Guo, 2017: Changes in aridity in response to the global warming hiatus. J. Meteor. Res., 31, 117–125, doi: 10.1007/s13351-017-6038-1.

    Article  Google Scholar 

  • Gupta, H. V., H. Kling, K. K. Yilmaz, et al., 2009: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling. J. Hydrol., 377, 80–91, doi: 10.1016/j.jhydrol.2009.08.003.

    Article  Google Scholar 

  • Herman, J. D., P. M. Reed, and T. Wagener, 2013: Time-varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior. Water Resour. Res., 49, 1400–1414, doi: 10.1002/wrcr.20124.

    Article  Google Scholar 

  • Hornberger, M. G., and C. R. Spear, 1981: Approach to the preliminary analysis of environmental systems. J. Environ. Manage., 12, 7–18.

    Google Scholar 

  • Hu, Y. Q., Y. J. Qi, and X. L. Yang, 1990: Preliminary analyses about characteristics of microclimate and heat energy budget in HEXI Gobi (Huayin). Plateau Meteor., 9, 113–119. (in Chinese)

    Google Scholar 

  • Li, J., Q. Y. Duan, W. Gong, et al., 2013: Assessing parameter importance of the Common Land Model based on qualitative and quantitative sensitivity analysis. Hydrol. Earth Syst. Sci., 17, 3279–3293, doi: 10.5194/hess-17-3279-2013.

    Article  Google Scholar 

  • Li, J. D., Y. P. Wang, Q. Y. Duan, et al., 2016: Quantification and attribution of errors in the simulated annual gross primary production and latent heat fluxes by two global land surface models. J. Adv. Model. Earth Syst., 8, 1270–1288, doi: 10.1002/2015MS000583.

    Article  Google Scholar 

  • Ma, Y. M., O. Tsukamoto, J. M. Wang, et al., 2002: Analysis of aerodynamic and thermodynamic parameters on the grassy marshland surface of Tibetan Plateau. Prog. Nat. Sci., 12, 36–40.

    Google Scholar 

  • Marcé, R., C. E. Ruiz, and J. Armengol, 2008: Using spatially distributed parameters and multi-response objective functions to solve parameterization of complex applications of semi-distributed hydrological models. Water Resour. Res., 44, W02436, doi: 10.1029/2006WR005785.

    Article  Google Scholar 

  • Morris, M. D., 1991: Factorial sampling plans for preliminary computational experiments. Technometrics, 33, 161–174, doi: 10.2307/1269043.

    Article  Google Scholar 

  • Oliphant, A. J., C. S. B. Grimmond, H. N. Zutter, et al., 2004: Heat storage and energy balance fluxes for a temperate deciduous forest. Agric. For. Meteor., 126, 185–201, doi: 10.1016/j.agrformet.2004.07.003.

    Article  Google Scholar 

  • Rakovec, O., M. C. Hill, M. P. Clark, et al., 2014: Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models. Water Resour. Res., 50, 409–426, doi: 10.1002/2013WR014063.

    Article  Google Scholar 

  • Rode, M., U. Suhr, and G. Wriedt, 2007: Multi-objective calibration of a river water quality model-information content of calibration data. Ecological Modelling, 204, 129–142, doi: 10.1016/j.ecolmodel.2006.12.037.

    Article  Google Scholar 

  • Rosero, E., Z. L. Yang, T. Wagener, et al., 2010: Quantifying parameter sensitivity, interaction, and transferability in hydrologically enhanced versions of the Noah land surface model over transition zones during the warm season. J. Geophys. Res., 115, D03106, doi: 10.1029/2009JD012035.

    Article  Google Scholar 

  • Rosero, E., L. E. Gulden, Z. L. Yang, et al., 2011: Ensemble evaluation of hydrologically enhanced Noah-LSM: Partitioning of the water balance in high-resolution simulations over the Little Washita River experimental watershed. J. Hydrometeor., 12, 45–64, doi: 10.1175/2010JHM1228.1.

    Article  Google Scholar 

  • Rosolem, R., H. V. Gupta, W. J. Shuttleworth, et al., 2012: Towards a comprehensive approach to parameter estimation in land surface parameterization schemes. Hydrol. Processes, 27, 2075–2097, doi: 10.1002/hyp.9362.

    Article  Google Scholar 

  • Saltelli, A., 2002: Making best use of model evaluations to compute sensitivity indices. Comput. Phys. Commun., 145, 280–297, doi: 10.1016/S0010-4655(02)00280-1.

    Article  Google Scholar 

  • Sen, O. L., L. A. Bastidas, W. J. Shuttleworth, et al., 2001: Impact of field-calibrated vegetation parameters on GCM climate simulations. Quart. J. Roy. Meteor. Soc., 127, 1199–1223, doi: 10.1002/qj.49712757404.

    Article  Google Scholar 

  • Shangguan, W., Y. J. Dai, B. Y. Liu, et al., 2013: A China data set of soil properties for land surface modeling. J. Adv. Model. Earth Syst., 5, 212–224, doi: 10.1002/jame.20026.

    Article  Google Scholar 

  • Sobol, I. M., 1993: Sensitivity analysis for nonlinear mathematical models. Math. Mod. Comput. Exp., 1, 407–414.

    Google Scholar 

  • Tang, Y., P. Reed, T. Wagener, et al., 2007: Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation. Hydrol. Earth Syst. Sci., 3, 793–817, doi: 10.5194/hess-11-793-2007.

    Article  Google Scholar 

  • Trier, S. B., M. A. LeMone, F. Chen, et al., 2011: Effects of surface heat and moisture exchange on ARW-WRF warm-season precipitation forecasts over the central United States. Wea. Forecasting, 26, 3–25, doi: 10.1175/2010WAF2222426.1.

    Article  Google Scholar 

  • Twine, T. E., W. P. Kustas, J. M. Norman, et al., 2000: Correcting eddy-covariance flux underestimates over a grassland. Agric. For. Meteor., 103, 279–300, doi: 10.1016/S0168-1923(00)00123-4.

    Article  Google Scholar 

  • van Werkhoven, K., T. Wagener, P. Reed, et al., 2008: Characterization of watershed model behavior across a hydroclimatic gradient. Water Resour. Res., 44, W01429, doi: 10.1029/2007WR006271.

    Google Scholar 

  • Verhoef, A., B. J. J. M. van den Hurk, A. F. G. Jacobs, et al., 1996: Thermal soil properties for vineyard (EFEDA-I) and savanna (HAPEX-Sahel) sites. Agric. For. Meteor., 78, 1–18, doi: 10.1016/0168-1923(95)02254-6.

    Article  Google Scholar 

  • Wang, G. S., J. Xia, and J. Chen, 2009: Quantification of effects of climate variations and human activities on runoff by a monthly water balance model: A case study of the Chaobai River basin in northern China. Water Resour. Res., 45, W00A11, doi: 10.1029/2007WR006768.

    Google Scholar 

  • Webb, E. K., G. I. Pearman, and R. Leuning, 1980: Correction of flux measurements for density effects due to heat and water vapour transfer. Quart. J. Roy. Meteor. Soc., 106, 85–100, doi: 10.1002/qj.49710644707.

    Article  Google Scholar 

  • Wilczak, J. M., S. P. Oncley, and S. A. Stage, 2001: Sonic anemometer tilt correction algorithms. Bound.-Layer Meteor., 99, 127–150, doi: 10.1023/A:1018966204465.

    Article  Google Scholar 

  • Willmott, C. J., 1981: On the validation of models. Phys. Geogr., 2, 184–194.

    Google Scholar 

  • Wilson, K., A. Goldstein, E. Falge, et al., 2002: Energy balance closure at FLUXNET sites. Agric. For. Meteor., 113, 223–243, doi: 10.1016/S0168-1923(02)00109-0.

    Article  Google Scholar 

  • Yang, F. L., and G. S. Zhou, 2011: Characteristics and modeling of evapotranspiration over a temperate desert steppe in Inner Mongolia, China. J. Hydrol., 396, 139–147, doi: 10.1016/j.jhydrol.2010.11.001.

    Article  Google Scholar 

  • Yang, K., T. Koike, H. Ishikawa, et al., 2008: Turbulent flux transfer over bare-soil surfaces: Characteristics and parameterization. J. Appl. Meteor. Climatol., 47, 276–290, doi: 10.1175/2007JAMC1547.1.

    Article  Google Scholar 

  • Yin, J. F., X. W. Zhan, Y. F. Zheng, et al., 2016: Improving Noah land surface model performance using near real time surface albedo and green vegetation fraction. Agric. For. Meteor., 218–219, 171–183, doi: 10.1016/j.agrformet.2015.12.001.

  • Zeng, X. B., Z. Wang, and A. H. Wang, 2012: Surface skin temperature and the interplay between sensible and ground heat fluxes over arid regions. J. Hydrometeor., 13, 1359–1370, doi: 10.1175/JHM-D-11-0117.1.

    Article  Google Scholar 

  • Zhang, G., G. S. Zhou, F. Chen, et al., 2014a: A trial to improve surface heat exchange simulation through sensitivity experiments over a desert steppe site. J. Hydrometeor., 15, 664–684, doi: 10.1175/JHM-D-13-0113.1.

    Article  Google Scholar 

  • Zhang, G., G. S. Zhou, F. Chen, et al., 2014b: Analysis of the variability of canopy resistance over a desert steppe site in Inner Mongolia, China. Adv. Atmos. Sci., 31, 681–692, doi: 10.1007/s00376-013-3071-6.

    Article  Google Scholar 

  • Zhang, Q., X. Y. Cao, G. A. Wei, et al., 2002: Observation and study of land surface parameters over Gobi in typical arid region. Adv. Atmos. Sci., 19, 121–135, doi: 10.1007/s00376-002-0039-3.

    Article  Google Scholar 

  • Zilitinkevich, S. S., 1995: Non-local turbulent transport: Pollution dispersion aspects of coherent structure of convective flows. Air Pollution III, Vol. I, Air Pollution Theory and Simulation, Power H., N. Moussiopoulos, and C. A. Brebbia, Eds., Computational Mechanics Publications, Boston, Mass, 53–60.

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Authors and Affiliations

  1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, 100081, China

    Guo Zhang, Guangsheng Zhou & Fei Chen

  2. National Center for Atmospheric Research, Boulder, CO, 80302, USA

    Fei Chen

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  1. Guo Zhang
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  2. Guangsheng Zhou
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Correspondence to Guangsheng Zhou.

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Supported by the National Natural Science Foundation of China (41505010), Chinese Academy of Meteorological Sciences (CAMS) Basic Research Special Project (2017Y014 and 2015Z002), China Meteorological Administration Special Public Welfare Research Fund (GYHY201506001), and National Basic Research and Development (973) Program of China (2010CB951303).

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Zhang, G., Zhou, G. & Chen, F. Analysis of parameter sensitivity on surface heat exchange in the Noah land surface model at a temperate desert steppe site in China. J Meteorol Res 31, 1167–1182 (2017). https://doi.org/10.1007/s13351-017-7050-1

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