• Avissar, R., , and Pielke R. A. , 1989: A parameterization of heterogeneous land surface for atmospheric numerical models and its impact on regional meteorology. Mon. Wea. Rev., 117 , 21132136.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bastidas, L. A., , Gupta H. V. , , and Sorooshian S. , 2003: : Parameter, structure and performance evaluation for land surface models. Advances in the Calibration of Watershed Models, Geophys. Monogr., No. 6, Amer. Geophys. Union, 229–238.

    • Crossref
    • Export Citation
  • Calder, I. R., , Hall R. A. , , Bastable H. G. , , Gunston H. M. , , Shela O. , , Chirwa A. , , and Kafundu R. , 1995: The impact of land use changes on water resources in sub-Saharan Africa: A modelling study of Lake Malawi. J. Hydrol., 170 , 123136.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Calhoun, F. G., , Smeck N. E. , , Slater B. L. , , Bigham J. M. , , and Hall G. F. , 2001: Predicting bulk density of Ohio soils from morphology, genetic principles, and laboratory characterization data. Soil Sci. Soc. Amer. J., 65 , 811819.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Callies, U., , Rhodin A. , , and Eppel D. P. , 1998: A case study on variational soil moisture analysis from atmospheric observations. J. Hydrol., 212–213 , 95108.

    • Search Google Scholar
    • Export Citation
  • Carey, S. K., , and Woo M. , 1999: Hydrology of two slopes in subarctic Yukon, Canada. Hydrol. Processes, 13 , 25492562.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, F., , and Dudhia J. , 2001: Coupling an advanced land surface hydrology model with the Penn State/NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129 , 569585.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Clapp, R. B., , and Hornberger G. M. , 1978: Empirical equations for some soil hydraulic properties. Water Resour. Res., 14 , 601604.

  • Cosby, B. J., , Hornberger G. M. , , Clapp R. B. , , and Ginn T. R. , 1984: A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils. Water Resour. Res., 20 , 682690.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cuenca, R. H., , Ek M. , , and Mahrt L. , 1996: Impact of soil water property parameterization on atmospheric boundary layer simulation. J. Geophys. Res., 101D , 72697277.

    • Search Google Scholar
    • Export Citation
  • de Groot, S. R., 1951: Thermodynamics of Irreversible Processes. Interscience, 242 pp.

  • de Vries, D. A., 1958: Simultaneous transfer of heat and moisture in porous media. Eos, Trans. Amer. Geophys. Union, 39 , 909916.

  • Douville, H., , and Chauvin F. , 2000: Relevance of soil moisture for seasonal climate predictions: A preliminary study. Climate Dyn., 16 , 719736.

  • Dudhia, J., 1993: A nonhydrostatic version of the Penn State–NCAR Mesoscale Model: Validation tests and simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev., 121 , 14931513.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Farouki, O., 1981: Thermal Properties of Soils. CRREL Monogr., No. 81-1, U.S. Army Cold Regions Research and Engineering Laboratories, 136 pp.

  • Flerchinger, G. N., , and Saxton K. E. , 1989: Simultaneous heat and water model of a freezing snow–residue–soil system. I. Theory and development. Trans. ASAE, 32 , 565571.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gao, X., , Sorooshian S. , , and Gupta H. V. , 1996: Sensitivity analysis of the Biosphere–Atmosphere Transfer Scheme. J. Geophys. Res., 101D , 72797289.

    • Search Google Scholar
    • Export Citation
  • Grell, G., , Kuo Y-H. , , and Pasch R. J. , 1991: Semi-prognostic tests of cumulus parameterization schemes in the middle latitudes. Mon. Wea. Rev., 119 , 531.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grell, G., , Dudhia J. , , and Stauffer D. , 1994: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR/TN-398+STR, 122 pp.

  • Grunwald, S., , Rooney D. J. , , McSweeney K. , , and Lowery B. , 2001: Development of pedotransfer functions for a profile cone penetrometer. Geoderma, 100 , 2547.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gutman, G., , and Ignatov A. , 1998: The derivation of green vegetation from NOAA/AVHHRR data for use in numerical weather prediction models. Int. J. Remote Sens., 19 , 15331543.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Henderson-Sellers, 1993: A factorial assessment of the sensitivity of the BATS land-surface parameterization. J. Climate, 6 , 227247.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hong, S-Y., , and Pan H-L. , 1996: Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon. Wea. Rev., 124 , 23222339.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kramm, G., 1995: Zum Austausch von Ozon und reaktiven Stickstoffverbindungen zwischen Atmosphäre und Biosphäre. Maraun-Verlag, 268 pp.

    • Search Google Scholar
    • Export Citation
  • Kramm, G., , Dlugi R. , , Foken T. , , Mölders N. , , Müller H. , , and Paw U K. T. , 1994: On the determination of the sublayer Stanton numbers of heat and matter for different types of surfaces. The Proceedings of the EUROTRAC Symposium ’94, P. Borrell, P. M. Borrell, and W. Seiler, Eds., SPB Academic, 644–648.

    • Search Google Scholar
    • Export Citation
  • Kramm, G., , Beier N. , , Foken T. , , Müller H. , , Schröder P. , , and Seiler W. , 1996: A SVAT scheme for NO, NO2, and O3—Model description. Meteor. Atmos. Phys., 61 , 89106.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Laurén, A., , and Heiskannen J. , 1997: Physical properties of the moor layer in a Scots pine stand. I. Hydraulic conductivity. Can. J. Soil Sci., 77 , 627634.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lohmann, D., and Coauthors, 1998: The Project for Intercomparison of Land Surface Parameterization Schemes Phase (PILPS) phase 2(c) Red–Arkansas river basin experiement: 3. Spatial and temporal analysis of water fluxes. Global Planet. Change, 19 , 161179.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Luo, L., and Coauthors, 2003: Effects of frozen soil on soil temperature, spring infiltration, and runoff: Results from the PILPS2(d) experiment at Valdai, Russia. J. Hydrometeor., 4 , 334351.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McCumber, M. C., , and Pielke R. A. , 1981: Simulation of the effects of surface fluxes of heat and moisture in a mesoscale model. I. Soil-layer. J. Geophys. Res., 86 , 99299938.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Miller, D. A., , and White R. A. , 1998: A conterminous United States multilayer soil characteristics dataset for regional climate and hydrological modeling. Earth Interactions, 2 .[Available online at http://EarthInteractions.org.].

    • Search Google Scholar
    • Export Citation
  • Mölders, N., 2001: On the uncertainty in mesoscale modeling caused by surface parameters. Meteor. Atmos. Phys., 76 , 119141.

  • Mölders, N., , and Walsh J. E. , 2004: Atmospheric response to soil-frost and snow in Alaska in March. Theor. Appl. Climatol., 77 , 77105.

  • Mölders, N., , Raabe A. , , and Tetzlaff G. , 1996: A comparison of two strategies on land surface heterogeneity used in a mesoscale β meteorological model. Tellus, 48A , 733749.

    • Search Google Scholar
    • Export Citation
  • Mölders, N., , Strasser U. , , Schneider K. , , Mauser W. , , and Raabe A. , 1997: A sensitivity study on the initialization of surface characteristics in meso-β/γ-modeling using digitized vs. satellite derived landuse data. Contrib. Atmos. Phys., 70 , 173187.

    • Search Google Scholar
    • Export Citation
  • Mölders, N., , Haferkorn U. , , Döring J. , , and Kramm G. , 2003a: Long-term numerical investigations on the water budget quantities predicted by the hydro-thermodynamic soil vegetation scheme (HTSVS)—Part I: Description of the model and impact of long-wave radiation, roots, snow, and soil frost. Meteor. Atmos. Phys., 84 , 115135.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mölders, N., , Haferkorn U. , , Döring J. , , and Kramm G. , 2003b: Long-term numerical investigations on the water budget quantities predicted by the hydro-thermodynamic soil vegetation scheme (HTSVS)—Part II: Evaluation, sensitivity, and uncertainty. Meteor. Atmos. Phys., 84 , 137156.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Montaldo, N., , and Albertson J. D. , 2001: On the use of the force–restore SVAT model formulation for stratified soils. J. Hydrometeor., 2 , 571578.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Niu, G-Y., , and Yang Z-L. , 2004: The effects of canopy processes on snow surface energy and mass balances. J. Geophys. Res., 109 .D23111, doi:10.1029/2004JD004884.

    • Search Google Scholar
    • Export Citation
  • Peters-Lidard, C. D., , Blackburn E. , , Liang X. , , and Wood E. F. , 1998: The effect of soil thermal conductivity parameterization on surface energy fluxes and temperatures. J. Atmos. Sci., 55 , 12091224.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Philip, J. R., , and de Vries D. A. , 1957: Moisture in porous materials under temperature gradients. Eos, Trans. Amer. Geophys. Union, 18 , 222232.

    • Search Google Scholar
    • Export Citation
  • Raymond, D., , and Emanuel K. , 1993: : The Kuo cumulus parameterization. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 145–151.

    • Crossref
    • Export Citation
  • Reichle, R. H., , McLaughlin D. B. , , and Entekhabi D. , 2001: Variational data assimilation of microwave radiobrightness observations for land surface hydrology applications. IEEE Trans. Geosci. Remote Sens., 39 , 17081718.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reisner, J., , Rasmussen R. M. , , and Bruintjes R. T. , 1998: Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Quart. J. Roy. Meteor. Soc., 124B , 10711107.

    • Search Google Scholar
    • Export Citation
  • Robock, A., , Vinnikov K. Y. , , Schlosser C. A. , , Speranskaya N. A. , , and Xue Y. , 1995: Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models. J. Climate, 8 , 1535.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schlotzhauer, S. M., , and Price J. S. , 1999: Soil water flow dynamics in a managed cutover peat field, Quebec: Field and laboratory investigations. Water Resour. Res., 35 , 36753683.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shao, Y., , and Henderson-Sellers A. , 1996: Modeling soil moisture: A project for intercomparison of land surface parameterization schemes phase 2 (b). J. Geophys. Res., 101D , 72277250.

    • Search Google Scholar
    • Export Citation
  • Shao, Y., , and Irannejad P. , 1999: On the choice of soil hydraulic models in land-surface schemes. Bound.-Layer Meteor., 90 , 83115.

  • Sievers, U., , Forkel R. , , Wilson M. F. , , Henderson-Sellers A. , , Dickinson R. E. , , and Kennedy P. J. , 1987: Sensitivity of the Biosphere–Atmosphere Transfer Scheme (BATS) to the inclusion of variable soil characteristics. J. Climate Appl. Meteor., 26 , 341362.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Slater, A. G., , Pitman A. J. , , and Desborough C. E. , 1998: Simulation of freeze-thaw cycles in general circulation land surface scheme. J. Geophys. Res., 103D , 1130311312.

    • Search Google Scholar
    • Export Citation
  • van den Hurk, J. J. M., , Bastiaanssen W. G. M. , , Pelgrum H. , , and van Meijgaard E. , 1997: A new methodology for assimilation of initial soil moisture fields in weather prediction models using Meteosat and NOAA data. J. Appl. Meteor., 36 , 12711283.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Verseghy, D. L., 1991: CLASS—A Canadian land surface scheme for GCMs. 1. Soil model. Int. J. Climatol, 11 , 111133.

  • Viterbo, P., , and Beljaars A. , 1995: An improved land surface parameterization scheme in the ECMWF model and its validation. J. Climate, 8 , 27162748.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Viterbo, P., , Beljaars A. , , Mahouf J-F. , , and Teixeira J. , 1999: The representation of soil moisture freezing and its impact on the stable boundary layer. Quart. J. Roy. Meteor. Soc., 125 , 24012447.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, W., , and Kumar A. , 1998: A GCM assessement of atmospheric seasonal predictability associated with soil moisture anomalies over North America. J. Geophys. Res., 103 , 2863728646.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Warrach, K., , Mengelkamp H-T. , , and Raschke E. , 2001: Treatment of frozen soil and snow cover in the land surface model SEWAB. Theor. Appl. Climatol., 69 , 2337.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wetzel, P. J., , and Boone A. , 1995: A parameterization for land–cloud–atmosphere exchange (PLACE): Documentation and testing of a detailed process model of the partly cloudy boundary layer over heterogeneous land. J. Climate, 8 , 18101837.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, K., , Koike T. , , Ye B. , , and Bastidas L. , 2005: Inverse analysis of the role of soil vertical heterogeneity in controlling surface soil state and energy partition. J. Geophys. Res., 110 .D08101, doi:10.1029/2004JD005500.

    • Search Google Scholar
    • Export Citation
  • Yang, Z-L., , Dickinson R. E. , , Henderson-Sellers A. , , and Pitman A. J. , 1995: Preliminary study of spin-up processes in land surface models with the first stage data of Project for Intercomparison of Land Surface Parameterization Schemes Phase 1(a). J. Geophys. Res., 100D , 1655316578.

    • Search Google Scholar
    • Export Citation
  • Yang, Z-L., , Dickinson R. E. , , Robock A. , , and Vinnikov K. Y. , 1997: Validation of the snow submodel of the biosphere–atmosphere transfer scheme with Russian snow cover and meteorological observation data. J. Climate, 10 , 353373.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 171 171 22
PDF Downloads 83 83 13

Application of Gaussian Error Propagation Principles for Theoretical Assessment of Model Uncertainty in Simulated Soil Processes Caused by Thermal and Hydraulic Parameters

View More View Less
  • 1 Geophysical Institute, University of Alaska Fairbanks, Fairbanks, Alaska
© Get Permissions Rent on DeepDyve
Restricted access

Abstract

Statistical uncertainty in soil temperature and volumetric water content and related moisture and heat fluxes predicted by a state-of-the-art soil module [embedded in a numerical weather prediction (NWP) model] is analyzed by Gaussian error-propagation (GEP) principles. This kind of uncertainty results from the indispensable use of empirical soil parameters. Since for the same thermodynamic and hydrological surface forcing and mean empirical parameters a soil module always provides the same mean value and standard deviation, uncertainty is first theoretically analyzed using artificial data for a wide range of soil conditions. Second, NWP results obtained for Alaska during a July episode are elucidated in relation to the authors’ theoretical findings.

It is shown that uncertainty in predicted soil temperature and volumetric water content is of minor importance except during phase transition. Then the freeze–thaw term dominates and leads to soil temperature and moisture uncertainties of more than 15.8 K and 0.212 m3 m−3 in mineral soils. Heat-flux uncertainty is of the same order of magnitude as typical errors in soil-heat-flux measurements.

Uncertainty in the pore-size distribution index dominates uncertainty for all state variables and soil fluxes under most conditions. Uncertainties in hydraulic parameters (saturated hydraulic conductivity, pore-size distribution index, porosity, saturated water potential) affect soil-temperature uncertainty more than those in thermal parameters (density and specific heat capacity of dry soil material). Based on a thermal conductivity approach alternatively used, it is demonstrated that GEP principles are indispensable for evaluating parameterized soil-transfer processes.

Generally, statistical uncertainty decreases with depth. Close beneath the surface, the uncertainty in predicted soil temperature, volumetric water content, and soil-moisture and heat fluxes undergoes a diurnal cycle.

Corresponding author address: Nicole Mölders, Geophysical Institute, University of Alaska Fairbanks, 903 Koyukuk Drive, P.O. Box 757320, Fairbanks, AK 99775-7320. Email: molders@gi.alaska.edu

Abstract

Statistical uncertainty in soil temperature and volumetric water content and related moisture and heat fluxes predicted by a state-of-the-art soil module [embedded in a numerical weather prediction (NWP) model] is analyzed by Gaussian error-propagation (GEP) principles. This kind of uncertainty results from the indispensable use of empirical soil parameters. Since for the same thermodynamic and hydrological surface forcing and mean empirical parameters a soil module always provides the same mean value and standard deviation, uncertainty is first theoretically analyzed using artificial data for a wide range of soil conditions. Second, NWP results obtained for Alaska during a July episode are elucidated in relation to the authors’ theoretical findings.

It is shown that uncertainty in predicted soil temperature and volumetric water content is of minor importance except during phase transition. Then the freeze–thaw term dominates and leads to soil temperature and moisture uncertainties of more than 15.8 K and 0.212 m3 m−3 in mineral soils. Heat-flux uncertainty is of the same order of magnitude as typical errors in soil-heat-flux measurements.

Uncertainty in the pore-size distribution index dominates uncertainty for all state variables and soil fluxes under most conditions. Uncertainties in hydraulic parameters (saturated hydraulic conductivity, pore-size distribution index, porosity, saturated water potential) affect soil-temperature uncertainty more than those in thermal parameters (density and specific heat capacity of dry soil material). Based on a thermal conductivity approach alternatively used, it is demonstrated that GEP principles are indispensable for evaluating parameterized soil-transfer processes.

Generally, statistical uncertainty decreases with depth. Close beneath the surface, the uncertainty in predicted soil temperature, volumetric water content, and soil-moisture and heat fluxes undergoes a diurnal cycle.

Corresponding author address: Nicole Mölders, Geophysical Institute, University of Alaska Fairbanks, 903 Koyukuk Drive, P.O. Box 757320, Fairbanks, AK 99775-7320. Email: molders@gi.alaska.edu

Save