SpringerLink
Log in

Numerical simulation and data assimilation of the water-energy cycle over semiarid northeastern China

  • Research Paper
  • Published:
Science China Earth Sciences Aims and scope Submit manuscript

Abstract

The default fractional vegetation cover and terrain height were replaced by the estimated fractional vegetation cover, which was calculated by the Normalized Difference Vegetation Index (NDVI) of Earth Observing System Moderate-Resolution Imaging Spectroradiometer (EOS-MODIS) and the Digital Elevation Model of the Shuttle Radar Topography Mission (SRTM) system. The near-surface meteorological elements over northeastern China were assimilated into the three-dimensional variational data assimilation system (3DVar) module in the Weather Research and Forecasting (WRF) model. The structure and daily variations of air temperature, humidity, wind and energy fields over northeastern China were simulated using the WRF model. Four groups of numerical experiments were performed, and the simulation results were analyzed of latent heat flux, sensible heat flux, and their relationships with changes in the surface energy flux due to soil moisture and precipitation over different surfaces. The simulations were compared with observations of the stations Tongyu, Naiman, **zhou, and Miyun from June to August, 2009. The results showed that the WRF model achieves high-quality simulations of the diurnal characteristics of the surface layer temperature, wind direction, net radiation, sensible heat flux, and latent heat flux over semiarid northeastern China in the summer. The simulated near-surface temperature, relative humidity, and wind speed were improved in the data assimilation case (Case 2) compared with control case (Case 1). The simulated sensible heat fluxes and surface heat fluxes were improved by the land surface parameterization case (Case 3) and the combined case (Case 4). The simulated temporal variations in soil moisture over the northeastern arid areas agree well with observations in Case 4, but the simulated precipitation should be improved in the WRF model. This study could improve the land surface parameters by utilizing remote sensing data and could further improve atmospheric elements with a data assimilation system. This work provides an effective attempt at combining multi-source data with different spatial and temporal scales into numerical simulations. The assimilation datasets generated by this work can be applied to research on climate change and environmental monitoring of arid lands, as well as research on the formation and stability of climate over semiarid areas.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Barker D M, Huang W, Guo Y R, et al. 2004. A three-dimensional variational data assimilation system for mm5: Implementation and initial results. Mon Weather Rev, 132: 897–914

    Article  Google Scholar 

  • Barrett D J, Renzullo L J. 2009. On the efficacy of combining thermal and microwave satellite data as observational constraints for root-zone soil moisture estimation. J Hydrometeorol, 10: 1109–1127

    Article  Google Scholar 

  • Case J L, Crosson W L, Kumar S V, et al. 2008. Impacts of high-resolution land surface initialization on regional sensible weather forecasts from the wrf model. J Hydrometeorol, 9: 1249–1266

    Article  Google Scholar 

  • Chen F, Dudhia J. 2001a. Coupling an advanced land surface-hydrology model with the penn state-ncar mm5 modeling system. Part I: Model implementation and sensitivity. Mon Weather Rev, 129: 569–585

    Article  Google Scholar 

  • Chen F, Dudhia J. 2001b. Coupling an advanced land surface-hydrology model with the penn state-ncar mm5 modeling system. Part II: Preliminary model validation. Mon Weather Rev, 129: 587–604

    Google Scholar 

  • Chen F, Manning K W, LeMone M A, et al. 2007. Description and evaluation of the characteristics of the ncar high-resolution land data assimilation system. J Appl Meteorol Clim, 46: 694–713

    Article  Google Scholar 

  • Cheng T T, Han Z W, Zhang R J, et al. 2010. Black carbon in a continental semiarid area of northeast China and its possible sources of fire emission. J Geophys Res-Atmos, 115: D23

    Article  Google Scholar 

  • Chu P C, Lu S H, Chen Y C. 2005. A numerical modeling study on desert oasis self-supporting mechanisms. J Hydrol, 312: 256–276

    Article  Google Scholar 

  • Courtier P. 1997. Variational methods. J Meteorol Soc Jpn, 75: 211–218

    Google Scholar 

  • Dong J L, Han Z W, Zhang R J, et al. 2011. Evaluation and analysis of wrf-simulated meteorological variables in the urban and semiarid areas of China (in Chinese). Sci Meteorol Sin, 31: 484–492

    Google Scholar 

  • Dudhia J. 1989. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J Atmos Sci, 46: 3077–3107

    Article  Google Scholar 

  • Fu C B, Wen G. 2002. Several issues on aridification in the northern China (in Chinese). Clim Environ Res, 7: 22–29

    Google Scholar 

  • Fu C B, Ma Z G. 2008. Global change and regional aridification (in Chinese). Chin J Atmos Sci, 32: 752–760

    Google Scholar 

  • Grell G A, Dudhia J, Stauffer D R. 1994, A description of the fifth-generation penn state/ncar mesoscale model (mm5). NCAR Technical Note. NCAR/TN-398+STR, doi: 10.5065/D60Z716B

    Google Scholar 

  • Gu J F, **ao Q N, Kuo Y H, et al. 2005. Assimilation and simulation of typhoon rusa (2002) using the wrf system. Adv Atmos Sci, 22: 415–427

    Article  Google Scholar 

  • Gutman G, Ignatov A. 1998. The derivation of the green vegetation fraction from noaa/avhrr data for use in numerical weather prediction models. Int J Remote Sens, 19: 1533–1543

    Article  Google Scholar 

  • Hanna S R, Yang R X. 2001. Evaluations of mesoscale models’ simulations of near-surface winds, temperature gradients, and mixing depths. J Appl Meteorol, 40: 1095–1104

    Article  Google Scholar 

  • Huang J P, Zhang W, Zuo J Q, et al. 2008. An overview of the semiarid climate and environment research observatory over the Loess Plateau. Adv Atmos Sci, 25: 906–921

    Article  Google Scholar 

  • Irmak A, Kamble B. 2009. Evapotranspiration data assimilation with genetic algorithms and swap model for on-demand irrigation. Irrigation Sci, 28: 101–112

    Article  Google Scholar 

  • Janjic Z I. 1990. The step-mountain coordinate-physical package. Mon Weather Rev, 118: 1429–1443

    Article  Google Scholar 

  • Janjic Z I. 1996. The surface layer in the ncep eta model. Eleventh Conference on Numerical Weather Prediction. 354-355

  • Janjic Z I. 2002, Nonsingular implementation of the mellor-yamada level 2.5 scheme in the ncep meso model. NCEP Office Note. 61

    Google Scholar 

  • Janjic Z I, Black T L, DiMego G. 1998. Contributions toward development of a future community mesoscale model (wrf). 16th Conference on Weather Analysis and Forecasting/Symposium on the Research Foci of the US Weather Research Program. 258–261

    Google Scholar 

  • Kain J S, Fritsch J M. 1993. Convective parameterization for mesoscale models: The Kain-Fritsch scheme. The representation of cumulus convection in numerical models. Meteor Monogr, 46: 165–170

    Google Scholar 

  • Kumar S, Sekhar M, Bandyopadhyay S. 2009. Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling. Curr Sci India, 97: 1196–1202

    Google Scholar 

  • Li F Q, Crow W T, Kustas W P. 2010. Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals. Adv Water Resour, 33: 201–214

    Article  Google Scholar 

  • Li X, Huang C L, Che T, et al. 2007. Development of a Chinese land data assimilation system: Its progress and prospects (in Chinese). Prog Nat Sci, 17: 163–173

    Article  Google Scholar 

  • Lin Y L, Farley R D, Orville H D. 1983. Bulk parameterization of the snow field in a cloud model. J Clim Appl Meteorol, 22: 1065–1092

    Article  Google Scholar 

  • Liu H Z, Dong W J, Fu C B, et al. 2004. The long-term field experiment on aridification and the ordered human activity in semiarid area at Tongyu, northeast China (in Chinese). Clim Environ Res, 9: 378–389

    Google Scholar 

  • Liu H Z, Tu G, Dong W J, et al. 2006. Seasonal and diurnal variations of the exchange of water vapor and CO2 between the land surface and atmosphere in the semiarid area (in Chinese). Chin J Atmos Sci, 30: 108–118

    Google Scholar 

  • Liu S, Gong P. 2012. Change of surface cover greenness in china between 2000 and 2010. Chin Sci Bull, 57: 2835–2845

    Article  Google Scholar 

  • Liu W, Gao Y H, Ran Y H, et al. 2007. Contrast analyses of simulation results in Heihe basin utilizing the different resolution dem data (in Chinese). Plateau Meteorol, 26: 525–531

    Google Scholar 

  • Lorenc A C. 1986. Analysis-methods for numerical weather prediction. Q J Roy Meteor Soc, 112: 1177–1194

    Article  Google Scholar 

  • Ma Y M, Wang J M, Menenti M, et al. 1997. The study of regional surface heat fluxes over the heterogenous landscape of Heife (in Chinese). Clim Environ Res, 2: 293–301

    Google Scholar 

  • Meng X H, Lu S H, Zhang T T, et al. 2009. Numerical simulations of the atmospheric and land conditions over the **ta oasis in northwestern China with satellite-derived land surface parameters. J Geophys Res-Atmos, 114: 100–120

    Article  Google Scholar 

  • Mlawer E J, Taubman S J, Brown P D, et al. 1997. Radiative transfer for inhomogeneous atmospheres: Rrtm, a validated correlated-K model for the longwave. J Geophys Res, 102: 16663–16682

    Article  Google Scholar 

  • Pan X D, Li X, Ran Y H, et al. 2012a. Impact of underlying surface information on wrf modeling in Heihe River basin (in Chinese). Plateau Meteorol, 31: 657–667

    Google Scholar 

  • Pan X D, Tian X J, Li X, et al. 2012b. Assimilating doppler radar radial velocity and reflectivity observations in the weather research and forecasting model by a proper orthogonal-decomposition-based ensemble, three-dimensional variational assimilation method. J Geophys Res-Atmos, 117: D17

    Google Scholar 

  • Tanaka K, Ishikawa H, Hayashi T, et al. 2001. Surface energy budget at amdo on the Tibetan Plateau using game/Tibet IOP98 data. J Meteorol Soc Jpn, 79: 505–517

    Article  Google Scholar 

  • Tu G, Liu H Z, Dong W J, et al. 2006. The near surface layer energy budge on degraded-grassland in semiarid area at tongyu in Jilin Province (in Chinese). Clim Environ Res, 11: 723–732

    Google Scholar 

  • Wen X H. 2011. The numerical simulation of water-energy budget and micro-climate effect on inhomogeneous underlying surface over **ta oasis-gobi. Doctoral Dissertation. Lanzhou: Chinese Academy of Science. 131

    Google Scholar 

  • Wen X H, Lu S H, ** J M. 2012. Integrating remote sensing data with wrf for improved simulations of oasis effects on local weather processes over an arid region in northwestern China. J Hydrometeorol, 13: 573–587

    Article  Google Scholar 

  • Xue M, Droegemeier K K, Wong V. 2000. The advanced regional prediction system (arps)-A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification. Meteorol Atmos Phys, 75: 161–193

    Article  Google Scholar 

  • Yan Y P, Wang J M, Menenti M, et al. 2001. Numerical simulation of surface energy fluxes over heterogeneous land surfaces in heife area (in Chinese). Plateau Meteorol, 20: 132–139

    Google Scholar 

  • Yang K, Wang J M. 2008. A temperature prediction-correction method for estimating surface soil heat flux from soil temperature and moisture data. Sci China Ser D-Earth Sci, 51: 721–729

    Article  Google Scholar 

  • Yang K, Koike T, Kaihotsu I, et al. 2009. Validation of a dual-pass microwave land data assimilation system for estimating surface soil moisture in semiarid regions. J Hydrometeorol, 10: 780–793

    Article  Google Scholar 

  • Zeng J, Zhang Q. 2012a. Mean characteristics of land surface key parameters in semiarid and arid regions of China in summer of 2008 (in Chinese). Plateau Meteorol, 31: 1539–1550

    Google Scholar 

  • Zeng J, Zhang Q. 2012b. A comparative study of the characteristics of the clear-sky land surface processes over the different underlying surfaces in the northern part of china during July-September 2008 (in Chinese). Acta Meteorol Sin, 70: 821–836

    Google Scholar 

  • Zhang Q, Zhao M. 1998. A numerical simulation of characteristics of land surface process under interaction of oasis and desert in arid region (in Chinese). Plateau Meteorol, 17: 336–346

    Google Scholar 

  • Zhang Q, Zeng J, Zhang L Y. 2012. Characteristics of land surface thermal-hydrologic processes for different regions over North China during prevailing summer monsoon period. Sci China Earth Sci, 55: 1872–1880

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Bei**g Normal University, Bei**g, 100875, China

    **aoHang Wen, Wen** Yuan, **aoDong Yan, ZhiGang Wei & WenJie Dong

  2. National Remote Sensing Center of China, Bei**g, 100036, China

    **aoHan Liao

  3. Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Chinese Academy of Sciences, Bei**g, 100029, China

    HuiZhi Liu & **Ming Feng

  4. Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000, China

    ShiHua Lu

Authors
  1. **aoHang Wen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. **aoHan Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wen** Yuan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. **aoDong Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. ZhiGang Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. HuiZhi Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. **Ming Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. ShiHua Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. WenJie Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to **aoHang Wen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wen, X., Liao, X., Yuan, W. et al. Numerical simulation and data assimilation of the water-energy cycle over semiarid northeastern China. Sci. China Earth Sci. 57, 2340–2356 (2014). https://doi.org/10.1007/s11430-014-4914-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11430-014-4914-4

Keywords

Search

Navigation