Editorial Type:
Article
Article Type:
Research Article

Sensitivity of Near-Surface Temperature Forecasts to Soil Properties over a Sparsely Vegetated Dryland Region

Jeffrey D. Massey Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah

Search for other papers by Jeffrey D. Massey in
Current site
Google Scholar
PubMed Close
,
W. James Steenburgh Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah

Search for other papers by W. James Steenburgh in
Current site
Google Scholar
PubMed Close
,
Sebastian W. Hoch Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah

Search for other papers by Sebastian W. Hoch in
Current site
Google Scholar
PubMed Close
, and
Jason C. Knievel National Center for Atmospheric Research,* Boulder, Colorado

Search for other papers by Jason C. Knievel in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Aug 2014
Collections:
Mountain Terrain Atmospheric Modeling and Observations (MATERHORN)
DOI:
https://doi.org/10.1175/JAMC-D-13-0362.1
Page(s):
1976–1995
Restricted access

Abstract

Weather Research and Forecasting Model forecasts over the Great Salt Lake Desert erroneously underpredict nocturnal cooling over the sparsely vegetated silt loam soil area of Dugway Proving Ground in northern Utah, with a mean positive bias error in temperature at 2 m AGL of 3.4°C in the early morning [1200 UTC (0500 LST)]. Positive early-morning bias errors also exist in nearby sandy loam soil areas. These biases are related to the improper initialization of soil moisture and parameterization of soil thermal conductivity in silt loam and sandy loam soils. Forecasts of 2-m temperature can be improved by initializing with observed soil moisture and by replacing Johansen's 1975 parameterization of soil thermal conductivity in the Noah land surface model with that proposed by McCumber and Pielke in 1981 for silt loam and sandy loam soils. Case studies illustrate that this change can dramatically reduce nighttime warm biases in 2-m temperature over silt loam and sandy loam soils, with the greatest improvement during periods of low soil moisture. Predicted ground heat flux, soil thermal conductivity, near-surface radiative fluxes, and low-level thermal profiles also more closely match observations. Similar results are anticipated in other dryland regions with analogous soil types, sparse vegetation, and low soil moisture.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Jeffrey D. Massey, Dept. of Atmospheric Sciences, University of Utah, 135 S 1460 E Rm. 819, Salt Lake City, UT 84112. E-mail: jeff.massey@utah.edu

This article is included in the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) special collection.

Abstract

Weather Research and Forecasting Model forecasts over the Great Salt Lake Desert erroneously underpredict nocturnal cooling over the sparsely vegetated silt loam soil area of Dugway Proving Ground in northern Utah, with a mean positive bias error in temperature at 2 m AGL of 3.4°C in the early morning [1200 UTC (0500 LST)]. Positive early-morning bias errors also exist in nearby sandy loam soil areas. These biases are related to the improper initialization of soil moisture and parameterization of soil thermal conductivity in silt loam and sandy loam soils. Forecasts of 2-m temperature can be improved by initializing with observed soil moisture and by replacing Johansen's 1975 parameterization of soil thermal conductivity in the Noah land surface model with that proposed by McCumber and Pielke in 1981 for silt loam and sandy loam soils. Case studies illustrate that this change can dramatically reduce nighttime warm biases in 2-m temperature over silt loam and sandy loam soils, with the greatest improvement during periods of low soil moisture. Predicted ground heat flux, soil thermal conductivity, near-surface radiative fluxes, and low-level thermal profiles also more closely match observations. Similar results are anticipated in other dryland regions with analogous soil types, sparse vegetation, and low soil moisture.

The National Center for Atmospheric Research is sponsored by the National Science Foundation.

Corresponding author address: Jeffrey D. Massey, Dept. of Atmospheric Sciences, University of Utah, 135 S 1460 E Rm. 819, Salt Lake City, UT 84112. E-mail: jeff.massey@utah.edu

This article is included in the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) special collection.

Save
Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Al Nakshabandi, G., and H. Kohnke, 1965: Thermal conductivity and diffusivity of soils as related to moisture tension and other physical properties. Agric. Meteor., 2, 271–279, doi:10.1016/0002-1571(65)90013-0.

    • Search Google Scholar
    • Export Citation

  • Avissar, R., and R. A. Pielke, 1989: A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology. Mon. Wea. Rev., 117, 2113–2136, doi:10.1175/1520-0493(1989)117<2113:APOHLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Balland, V., and P. A. Arp, 2005: Modeling soil thermal conductivities over a wide range of conditions. J. Eng. Environ. Sci., 4, 549–558, doi:10.1139/s05-007.

    • Search Google Scholar
    • Export Citation

  • Banta, R. M., and P. T. Gannon, 1995: Influence of soil moisture on simulations of katabatic flow. Theor. Appl. Climatol., 52, 85–94, doi:10.1007/BF00865509.

    • Search Google Scholar
    • Export Citation

  • Bowen, I. S., 1926: The ratio of heat losses by conduction and by evaporation from any water surface. Phys. Rev., 27, 779–787, doi:10.1103/PhysRev.27.779.

    • Search Google Scholar
    • Export Citation

  • Campbell, G. S., 1985: Soil Physics with BASIC: Transport Models for Soil–Plant Systems. Developments in Soil Science, Vol. 14, Elsevier, 150 pp.

  • Case, J. L., S. V. Kumar, J. Srikishen, and G. J. Jedlovec, 2011: Improving numerical weather predictions of summertime precipitation over the southeastern United States through a high-resolution initialization of the surface state. Wea. Forecasting, 26, 785–807, doi:10.1175/2011WAF2222455.1.

    • Search Google Scholar
    • Export Citation

  • Chen, F., and J. Dudhia, 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, 569–585, doi:10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Cheng, W. Y. Y., and W. J. Steenburgh, 2005: Evaluation of surface sensible weather forecasts by the WRF and the Eta Models over the western United States. Wea. Forecasting, 20, 812–821, doi:10.1175/WAF885.1.

    • Search Google Scholar
    • Export Citation

  • Clapp, R. B., and G. M. Hornberger, 1978: Empirical equations for some soil hydraulic properties. Water Resour. Res., 14, 601–604, doi:10.1029/WR014i004p00601.

    • Search Google Scholar
    • Export Citation

  • Cosby, B. J., G. M. Hornberger, R. B. Clapp, and T. R. Ginn, 1984: A statistical exploration of the relationship of moisture characteristics to the physical properties of soils. Water Resour. Res., 20, 682–690, doi:10.1029/WR020i006p00682.

    • Search Google Scholar
    • Export Citation

  • Cosenza, P., R. Guerin, and A. Tabbagh, 2003: Relationship between thermal conductivity and water content of soils using numerical modeling. Eur. J. Soil Sci., 54, 581–587, doi:10.1046/j.1365-2389.2003.00539.x.

    • Search Google Scholar
    • Export Citation

  • Côté, J., and J. M. Konrad, 2005: A generalized thermal conductivity model for soils and construction materials. Can. Geotech. J., 42, 443–458, doi:10.1139/t04-106.

    • Search Google Scholar
    • Export Citation

  • Davis, C., T. Warner, E. Astling, and J. Bowers, 1999: Development and application of an operational, relocatable, mesogamma-scale weather analysis and forecasting system. Tellus, 51A, 710–727, doi:10.1034/j.1600-0870.1999.00013.x.

    • Search Google Scholar
    • Export Citation

  • de Vries, D. A., 1963: Thermal properties of soils. Physics of Plant Environment, W. R. van Wijk, Ed., North-Holland, 210–235.

  • Dirmeyer, P. A., F. J. Zeng, A. Ducharne, J. C. Morrill, and R. D. Koster, 2000: The sensitivity of surface fluxes to soil water content in three land surface schemes. J. Hydrometeor., 1, 121–134, doi:10.1175/1525-7541(2000)001<0121:TSOSFT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Dirmeyer, P. A., X. Gao, and T. Oki, 2002: GSWP-2: The Second Global Soil Wetness Project science and implementation plan. International GEWEX Project Office Publication Series 37, 65 pp. [Available online at http://www.iges.org/gswp/GSWP2_SIplan.pdf.]

  • Doran, J. C., and S. Zhong, 1995: Variations in mixed-layer depths arising from inhomogeneous surface conditions. J. Climate, 8, 1965–1973, doi:10.1175/1520-0442(1995)008<1965:VIMLDA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • 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, doi:10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Edwards, J. M., J. R. McGregor, M. R. Bush, and F. J. Bornemann, 2011: Assessment of numerical weather forecasts against observations from Cardington: Seasonal diurnal cycles of screen-level and surface temperatures and surface fluxes. Quart. J. Roy. Meteor. Soc., 137, 656–672, doi:10.1002/qj.742.

    • Search Google Scholar
    • Export Citation

  • Ek, M., and L. Mahrt, 1991: OSU 1-D PBL model user’s guide. Version 1.04, 120 pp. [Available from Department of Atmospheric Sciences, Oregon State University, Corvallis, OR 97331-2209.]

  • Ek, M., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarplay, 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.

    • Search Google Scholar
    • Export Citation

  • Farouki, O. T., 1986: Thermal Properties of Soils. Series on Rock and Soil Mechanics, Vol. 11, Trans Tech, 136 pp.

  • Fry, J., and Coauthors, 2011: Completion of the 2006 National Land Cover Database for the conterminous United States. Photogramm. Eng. Remote Sens., 77, 858–864. [Available online at http://digital.ipcprintservices.com/publication/?i=78634.]

    • Search Google Scholar
    • Export Citation

  • Godfrey, C. M., and D. J. Stensrud, 2008: Soil temperature and moisture errors in operational Eta Model analyses. J. Hydrometeor., 9, 367–387, doi:10.1175/2007JHM942.1.

    • Search Google Scholar
    • Export Citation

  • Hanna, S. R., and R. Yang, 2001: Evaluations of mesoscale models’ simulations of near-surface winds, temperature gradients, and mixing depths. J. Appl. Meteor., 40, 1095–1104, doi:10.1175/1520-0450(2001)040<1095:EOMMSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Hart, K. A., W. J. Steenburgh, and D. J. Onton, 2005: Model forecast improvements with decreased horizontal grid spacing over finescale intermountain orography during the 2002 Olympic Winter Games. Wea. Forecasting, 20, 558–576, doi:10.1175/WAF865.1.

    • Search Google Scholar
    • Export Citation

  • Holt, T. R., D. Niyogi, F. Chen, K. Manning, M. A. LeMone, and A. Qureshi, 2006: Effect of land–atmosphere interactions on the IHOP 24–25 May 2002 convection case. Mon. Wea. Rev., 134, 113–133, doi:10.1175/MWR3057.1.

    • Search Google Scholar
    • Export Citation

  • Holtslag, A. A. M., and Coauthors, 2013: Stable atmospheric boundary layers and diurnal cycles: Challenges for weather and climate models. Bull. Amer. Meteor. Soc., 94, 1691–1706, doi:10.1175/BAMS-D-11-00187.1.

    • Search Google Scholar
    • Export Citation

  • Hong, S. Y., Y. Noh, and J. Dudhia, 2006: A new vertical diffusion package with an explicit treatment of entrainment processes. Mon. Wea. Rev., 134, 2318–2341, doi:10.1175/MWR3199.1.

    • Search Google Scholar
    • Export Citation

  • Horel, J., and Coauthors, 2002: MesoWest: Cooperative mesonets in the western United States. Bull. Amer. Meteor. Soc., 83, 211–225, doi:10.1175/1520-0477(2002)083<0211:MCMITW>2.3.CO;2.

    • Search Google Scholar
    • Export Citation

  • Huang, J., H. M. van den Dool, and K. P. Georgarakos, 1996: Analysis of model-calculated soil moisture over the United States (1931–1993) and applications to long-range temperature forecasts. J. Climate, 9, 1350–1362, doi:10.1175/1520-0442(1996)009<1350:AOMCSM>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Idso, S., R. Jackson, B. Kimball, and F. Nakayama, 1975: The dependence of bare soil albedo on soil water content. J. Appl. Meteor., 14, 109–113, doi:10.1175/1520-0450(1975)014<0109:TDOBSA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Jackson, T. J., and Coauthors, 2010: Validation of advanced microwave scanning radiometer soil moisture products. IEEE Trans. Geosci. Remote Sens., 48, 4256–4272, doi:10.1109/TGRS.2010.2051035.

    • Search Google Scholar
    • Export Citation

  • Johansen, O., 1975: Thermal conductivity of soils. Ph.D. thesis, University of Trondheim, 236 pp. [Available from Universitetsbiblioteket i Trondheim, Høgskoleringen 1, 7034 Trondheim, Norway.]

  • Kain, J. S., 2004: The Kain–Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170–181, doi:10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kersten, M. S., 1949: Thermal properties of soils. University of Minnesota Engineering Experiment Station Bulletin 28, 227 pp. [Available from University of Minnesota Agricultural Experiment Station, St. Paul, MN 55108.]

  • Kilpelainen, T., T. Vihma, M. Manninen, A. Sjoblom, E. Jakobson, T. Palo, and M. Maturilli, 2012: Modelling the vertical structure of the atmospheric boundary layer over Arctic fjords in Svalbard. Quart. J. Roy. Meteor. Soc., 138, 1867–1883, doi:10.1002/qj.1914.

    • Search Google Scholar
    • Export Citation

  • Knievel, J. C., G. H. Bryan, and J. P. Hacker, 2007: Explicit diffusion in the WRF Model. Mon. Wea. Rev., 135, 3808–3824, doi:10.1175/2007MWR2100.1.

    • Search Google Scholar
    • Export Citation

  • Li, B., D. Toll, X. Zhan, and B. Cosgrove, 2012: Improving estimated soil moisture fields through assimilation of AMSR-E soil moisture retrievals with an ensemble Kalman filter and a mass conservation constraint. Hydrol. Earth Syst. Sci., 16, 105–119, doi:10.5194/hess-16-105-2012.

    • Search Google Scholar
    • Export Citation

  • Lin, Y.-L., R. D. Farley, and H. D. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 1065–1092, doi:10.1175/1520-0450(1983)022<1065:BPOTSF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Liu, Q., and Coauthors, 2011: The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates in a land data assimilation system. J. Hydrometeor., 12, 750–765, doi:10.1175/JHM-D-10-05000.1.

    • Search Google Scholar
    • Export Citation

  • Liu, Y., and Coauthors, 2008: The operational mesogamma-scale analysis and forecast system of the U.S. Army Test and Evaluation Command. Part I: Overview of the modeling system, the forecast products, and how the products are! used. J. Appl. Meteor. Climatol., 47, 1077–1092, doi:10.1175/2007JAMC1653.1.

    • Search Google Scholar
    • Export Citation

  • Lu, S., T. S. Ren, Y. S. Gong, and R. Horton, 2007: An improved model for predicting soil thermal conductivity from water content at room temperature. Soil Sci. Soc. Amer. J., 71, 8–14, doi:10.2136/sssaj2006.0041.

    • Search Google Scholar
    • Export Citation

  • Mahfouf, J. F., A. O. Manzi, J. Noilhan, H. Giordani, and M. Deque, 1995: The land surface scheme ISBA within the Météo-France climate model ARPEGE. Part I: Implementation and preliminary results. J. Climate, 8, 2039–2057, doi:10.1175/1520-0442(1995)008<2039:TLSSIW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Marshall, C. H., K. C. Crawford, K. E. Mitchell, and D. J. Stensrud, 2003: The impact of the land surface physics in the operational NCEP Eta Model on simulating the diurnal cycle: Evaluation and testing using Oklahoma Mesonet data. Wea. Forecasting, 18, 748–768, doi:10.1175/1520-0434(2003)018<0748:TIOTLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Mass, C. F., D. Ovens, K. Westrick, and B. A. Colle, 2002: Does increasing horizontal resolution produce more skillful forecasts? The results of two years of real-time numerical weather prediction over the Pacific Northwest. Bull. Amer. Meteor. Soc., 83, 407–430, doi:10.1175/1520-0477(2002)083<0407:DIHRPM>2.3.CO;2.

    • Search Google Scholar
    • Export Citation

  • McCumber, M. C., and R. A. Pielke, 1981: Simulation of the effects of surface fluxes of heat and moisture in a mesoscale numerical model. J. Geophys. Res., 86, 9929–9938, doi:10.1029/JC086iC10p09929.

    • Search Google Scholar
    • Export Citation

  • McInnes, K. J., 1981: Thermal conductivities of soils from dryland wheat regions of eastern Washington. M.S. thesis, Dept. of Agronomy and Soils, Washington State University, Pullman, WA, 51 pp. [Available from Owen Science Library, Washington State University, Pullman, WA 99163-3200.]

  • Mlawer, E. J., S. J. Taubman, P. D. Brown, M. J. Iacono, and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102, 16 663–16 682, doi:10.1029/97JD00237.

    • Search Google Scholar
    • Export Citation

  • Mostovoy, G. V., and V. G. Anantharaj, 2008: Observed and simulated soil moisture variability over the lower Mississippi Delta region. J. Hydrometeor., 9, 1125–1150, doi:10.1175/2008JHM999.1.

    • Search Google Scholar
    • Export Citation

  • Ngan, F., H. Kim, P. Lee, B. Dornblaser, and K. Al-Wali, 2013: A study of nocturnal surface wind speed overprediction by the WRF-ARW model in southeastern Texas. J. Appl. Meteor. Climatol., 52, 2638–2653, doi:10.1175/JAMC-D-13-060.1.

    • Search Google Scholar
    • Export Citation

  • Noilhan, J., and S. Planton, 1989: A simple parameterization of land surface processes for meteorological models. Mon. Wea. Rev., 117, 536–549, doi:10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Ookouchi, Y., M. Segal, R. C. Kessler, and R. A. Pielke, 1984: Evaluation of soil moisture effects on the generation and modification of mesoscale circulations. Mon. Wea. Rev., 112, 2281–2292, doi:10.1175/1520-0493(1984)112<2281:EOSMEO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Overduin, P. P., D. L. Kane, and W. K. P. van Loon, 2006: Measuring thermal conductivity in freezing and thawing soil using the soil temperature response to heating. Cold Reg. Sci. Technol., 45, 8–22, doi:10.1016/j.coldregions.2005.12.003.

    • Search Google Scholar
    • Export Citation

  • Peters-Lidard, C. D., E. Blackburn, X. Liang, and E. F. Wood, 1998: The effect of soil thermal conductivity parameterization on surface energy fluxes and temperatures. J. Atmos. Sci., 55, 1209–1224, doi:10.1175/1520-0469(1998)055<1209:TEOSTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Reeves, H. D., K. L. Elmore, G. S. Manikin, and D. J. Stensrud, 2011: Assessment of forecasts during persistent valley cold pools in the Bonneville basin by the North American Mesoscale Model. Wea. Forecasting, 26, 447–467, doi:10.1175/WAF-D-10-05014.1.

    • Search Google Scholar
    • Export Citation

  • Rife, D. L., T. T. Warner, F. Chen, and E. G. Astling, 2002: Mechanisms for diurnal boundary layer circulations in the Great Basin Desert. Mon. Wea. Rev., 130, 921–938, doi:10.1175/1520-0493(2002)130<0921:MFDBLC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Rife, D. L., C. A. Davis, Y. Liu, and T. T. Warner, 2004: Predictability of low-level winds by mesoscale meteorological models. Mon. Wea. Rev., 132, 2553–2569, doi:10.1175/MWR2801.1.

    • Search Google Scholar
    • Export Citation

  • Robock, A., and Coauthors, 2003: Validation of North American Land Data Assimilation Systems retrospective forcing over the southern Great Plains. J. Geophys. Res., 108, 8846, doi:10.1029/2002JD003245.

    • Search Google Scholar
    • Export Citation

  • Schaefer, G. L., M. H. Cosh, and T. J. Jackson, 2007: The USDA Natural Resources Conservation Service Soil Climate Analysis Network (SCAN). J. Atmos. Oceanic Technol., 24, 2073–2077, doi:10.1175/2007JTECHA930.1.

    • Search Google Scholar
    • Export Citation

  • Segal, M., J. R. Garratt, G. Kallos, and R. A. Pielke, 1989: The impact of wet soil and canopy temperatures on daytime boundary-layer growth. J. Atmos. Sci., 46, 3673–3684, doi:10.1175/1520-0469(1989)046<3673:TIOWSA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Seyfried, M. S., L. E. Grant, E. Du, and K. Humes, 2005: Dielectric loss and calibration of the Hydra Probe soil water sensor. Vadose Zone J., 4, 1070–1079, doi:10.2136/vzj2004.0148.

    • Search Google Scholar
    • Export Citation

  • Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN-475+STR, 113 pp. [Available online at http://www.mmm.ucar.edu/wrf/users/docs/arw_v3_bw.pdf.]

  • Steeneveld, G. J., T. Mauritsen, E. I. F. de Bruijn, J. Vilà-Guerau de Arellano, G. Svensson, and A. A. M. Holtslag, 2008: Evaluation of limited area models for the representation of the diurnal cycle and contrasting nights in CASES99. J. Appl. Meteor. Climatol., 47, 869–887, doi:10.1175/2007JAMC1702.1.

    • Search Google Scholar
    • Export Citation

  • Tapper, N. J., 1988: Some evidence for a mesoscale thermal circulation at The Salt Lake, New South Wales. Aust. Meteor. Mag., 36, 101–102.

    • Search Google Scholar
    • Export Citation

  • Tarnawski, V. R., and W. H. Leong, 2000: Thermal conductivity of soils at very low moisture content and moderate temperatures. Transp. Porous Media, 41, 137–147, doi:10.1023/A:1006738727206.

    • Search Google Scholar
    • Export Citation

  • Tarnawski, V. R., T. Momose, and W. H. Leong, 2009: Assessing the impact of quartz content on the prediction of soil thermal conductivity. Geotechnique, 59, 331–338, doi:10.1680/geot.2009.59.4.331.

    • Search Google Scholar
    • Export Citation

  • Viterbo, P., and A. C. M. Beljaars, 1995: An improved land surface parameterization scheme in the ECMWF model and its validation. J. Climate, 8, 2716–2748, doi:10.1175/1520-0442(1995)008<2716:AILSPS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Wen, X., S. Lu, and J. Jin, 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. Hydrometeor., 13, 573–587, doi:10.1175/JHM-D-10-05001.1.

    • Search Google Scholar
    • Export Citation

  • Zhang, H., Z. Pu, and X. Zhang, 2013: Examination of errors in near-surface temperature and wind from WRF numerical simulations in regions of complex terrain. Wea. Forecasting, 28, 893–914, doi:10.1175/WAF-D-12-00109.1.

    • Search Google Scholar
    • Export Citation

  • Zhou, X., and B. Geerts, 2013: The Influence of soil moisture on the planetary boundary layer and on cumulus convection over an isolated mountain. Part I: Observations. Mon. Wea. Rev., 141, 1061–1078, doi:10.1175/MWR-D-12-00150.1.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 852 379 16
PDF Downloads 244 48 7