• Benjamin, S. G., , and T. N. Carlson, 1986: Some effects of surface heating and topography on the regional severe storm environment. Part I: Three-dimensional simulations. Mon. Wea. Rev., 114 , 307329.

    • Search Google Scholar
    • Export Citation
  • Betts, A. K., 1986: A new convective adjustment scheme. Part 1: Observational and theoretical basis. Quart. J. Roy. Meteor. Soc., 112 , 677691.

    • Search Google Scholar
    • Export Citation
  • Betts, A. K., , and M. J. Miller, 1986: A new convective adjustment scheme. Part II: Single column test using GATE wave, BOMEX, ATEX and Arctic airmass data sets. Quart. J. Roy. Meteor. Soc., 112 , 693709.

    • Search Google Scholar
    • Export Citation
  • Betts, A. K., , J. H. Ball, , A. C. Beljaars, , M. J. Miller, , and P. A. Viterbo, 1996: The land surface–atmosphere interaction: A review based on observational and global modeling perspectives. J. Geophys. Res., 101D , 72097225.

    • Search Google Scholar
    • Export Citation
  • Bright, D. R., , and S. L. Mullen, 2002: Short-range ensemble forecasts of precipitation during the southwest monsoon. Wea. Forecasting, 17 , 10801100.

    • Search Google Scholar
    • Export Citation
  • Buizza, R., , J. Barkmeijer, , T. N. Palmer, , and D. S. Richardson, 2000: Current status and future developments of the ECMWF ensemble prediction system. Meteor. Appl., 7 , 163175.

    • Search Google Scholar
    • Export Citation
  • Buizza, R., , D. S. Richardson, , and T. N. Palmer, 2003: Benefits of increased resolution in the ECMWF ensemble prediction system and comparison with poor man’s ensembles. Quart. J. Roy. Meteor. Soc., 129 , 12691288.

    • Search Google Scholar
    • Export Citation
  • Chang, J-T., , and P. J. Wetzel, 1991: Effects of spatial variations of soil moisture and vegetation on the evolution of a pre-storm environment: A numerical case study. Mon. Wea. Rev., 119 , 13681390.

    • 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 , 569585.

    • Search Google Scholar
    • Export Citation
  • Chen, F., and Coauthors, 1996: Modeling of land-surface evaporation by four schemes and comparison with FIFE observations. J. Geophys. Res., 101D , 72517268.

    • Search Google Scholar
    • Export Citation
  • Chen, F., , T. T. Warner, , and K. Manning, 2001: Sensitivity of orographic moist convection to landscape variability: A study of the Buffalo Creek, Colorado, flash flood case of 1996. J. Atmos. Sci., 58 , 32043223.

    • Search Google Scholar
    • Export Citation
  • Crook, N. A., 1996: Sensitivity of moist convection forced by boundary layer processes to low-level thermodynamic fields. Mon. Wea. Rev., 124 , 17671785.

    • Search Google Scholar
    • Export Citation
  • Davis, C. A., , K. W. Manning, , R. E. Carbone, , S. B. Trier, , and J. D. Tuttle, 2003: Coherence of warm-season continental rainfall in numerical weather prediction models. Mon. Wea. Rev., 131 , 26672679.

    • Search Google Scholar
    • Export Citation
  • Diak, G., , S. Heikkinen, , and J. Rates, 1986: The influence of variations in surface treatment on 24-hour forecasts with a limited area model, including a comparison of modeled and satellite-measured surface temperatures. Mon. Wea. Rev., 114 , 215232.

    • 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 , 30773107.

    • Search Google Scholar
    • Export Citation
  • Ehrendorfer, M., , and J. J. Tribbia, 1997: Optimal prediction of forecast error covariances through singular vectors. J. Atmos. Sci., 54 , 286313.

    • Search Google Scholar
    • Export Citation
  • Ek, M., , and R. H. Cuenca, 1994: Modeling surface fluxes and boundary layer development. Bound.-Layer Meteor., 70 , 369383.

  • Fast, J. D., , and M. D. McCorcle, 1991: The effect of heterogeneous soil moisture on a summer baroclinic circulation in the central United States. Mon. Wea. Rev., 119 , 21402167.

    • Search Google Scholar
    • Export Citation
  • Gallus, W. A., 1999: Eta simulations of three extreme precipitation events: Sensitivity to resolution and convective parameterization. Wea. Forecasting, 14 , 405426.

    • Search Google Scholar
    • Export Citation
  • Gallus, W. A., , and M. Segal, 2000: Sensitivity of forecast rainfall in a Texas convective system to soil moisture and convective parameterization. Wea. Forecasting, 15 , 509525.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., 1997: Short-range ensemble forecasting using the Eta/RSM forecast models. Ph.D. dissertation, Cornell University, 216 pp. [Available from UMI Dissertation Services, 300 N. Zeeb Rd., P.O. Box 1346, Ann Arbor, MI 48106-1346.].

  • Hamill, T. M., , and S. J. Colucci, 1997: Verification of Eta-RSM short-range ensemble forecasts. Mon. Wea. Rev., 125 , 13121327.

  • Hamill, T. M., , and S. J. Colucci, 1998: Perturbations to the land surface condition in short-range ensemble forecasts. Preprints, 12th Conf. on Numerical Weather Prediction, Phoenix, AZ, Amer. Meteor. Soc., 273–276.

  • Hamill, T. M., , C. Snyder, , and R. E. Morss, 2000: A comparison of probabilistic forecasts from bred, singular vector, and perturbed observation ensembles. Mon. Wea. Rev., 128 , 18351851.

    • Search Google Scholar
    • Export Citation
  • Hamill, T. M., , C. Snyder, , and J. S. Whitaker, 2003: Ensemble forecasts and the properties of flow-dependent analysis-error covariance singular vectors. Mon. Wea. Rev., 131 , 17411758.

    • Search Google Scholar
    • Export Citation
  • Janjic, Z. I., 1994: The step-mountain Eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122 , 927945.

    • Search Google Scholar
    • Export Citation
  • Janjic, Z. I., 1996: The surface layer in the NCEP Eta Model. Preprints, 11th Conf. on Numerical Weather Prediction, Norfolk, VA, Amer. Meteor. Soc., 354–355.

  • Janjic, Z. I., 2002: Nonsingular implementation of the Mellor-Yamada level 2.5 scheme in the NCEP Meso model. NCEP Office Note 437, 61 pp. [Available online at http://www.emc.ncep.noaa.gov/officenotes/FullTOC.html.].

  • Kain, J. S., , and J. M. Fritsch, 1990: A one-dimensional entraining/ detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47 , 27842802.

    • Search Google Scholar
    • Export Citation
  • Kain, J. S., , and J. M. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain–Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor Monogr., No. 46, Amer. Meteor. Soc., 165–170.

    • Search Google Scholar
    • Export Citation
  • Koster, R. D., , and M. J. Suarez, 1996: Energy and water balance calculations in the Mosaic LSM. NASA Tech. Memo. 104606, Vol. 9, 59 pp.

  • Koster, R. D., , and P. C. D. Milly, 1997: The interplay between transpiration and runoff formulations in land surface schemes used with atmospheric models. J. Climate, 10 , 15781591.

    • Search Google Scholar
    • Export Citation
  • Lakhtakia, M. N., , and T. T. Warner, 1987: A real-data numerical study of the development of precipitation along the edge of an elevated mixed layer. Mon. Wea. Rev., 115 , 156168.

    • Search Google Scholar
    • Export Citation
  • Lanicci, J. M., , T. N. Carlson, , and T. T. Warner, 1987: Sensitivity of the Great Plains severe storm environment to soil moisture distribution. Mon. Wea. Rev., 115 , 26602673.

    • 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 , 10651092.

    • Search Google Scholar
    • Export Citation
  • Lorenz, E. N., 1969: The predictability of a flow which possesses many scales of motion. Tellus, 21 , 289307.

  • Mahanama, S. P. P., , and R. D. Koster, 2003: Intercomparison of soil moisture memory in two land surface models. J. Hydrometeor., 4 , 11341146.

    • Search Google Scholar
    • Export Citation
  • Mesinger, F., and Coauthors, 2006: North American Regional Reanalysis. Bull. Amer. Meteor. Soc., 87 , 343360.

  • Michalakes, J., , S. Chen, , J. Dudhia, , L. Hart, , J. Klemp, , J. Middlecoff, , and W. Skamarock, 2001: Development of a next generation regional weather research and forecast model. Developments in Teracomputing: Proceedings of the Ninth ECMWF Workshop on the Use of High Performance Computing in Meteorology, W. Zwieflhofer and N. Kreitz, Eds., World Scientific, 269–276.

    • Search Google Scholar
    • Export Citation
  • Mitchell, K. E., and Coauthors, 2004: The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res., 109 .D07S90, doi:10.1029/2003JD003823.

    • Search Google Scholar
    • Export Citation
  • Mlawer, E. J., , S. J. Taubman, , P. D. Brown, , M. J. Iacono, , and S. A. Clough, 1997: Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the long-wave. J. Geophys. Res., 102D , 1666316682.

    • Search Google Scholar
    • Export Citation
  • Mullen, S. L., , and R. Buizza, 2001: Quantitative precipitation forecasts over the United States by the ECMWF ensemble prediction system. Mon. Wea. Rev., 129 , 638663.

    • Search Google Scholar
    • Export Citation
  • Mullen, S. L., , and R. Buizza, 2002: The impact of horizontal resolution and ensemble size on probabilistic forecasts of precipitation by the ECMWF ensemble prediction system. Wea. Forecasting, 17 , 173191.

    • 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 , 22812292.

    • Search Google Scholar
    • Export Citation
  • Philip, J., 1957: Evaporation, and moisture and heat fields in the soil. J. Meteor., 14 , 354366.

  • Pielke Sr., R. A., 2001: Influence of the spatial distribution of vegetation and soils on the preduction of cumulus convective rainfall. Rev. Geophys., 39 , 151177.

    • Search Google Scholar
    • Export Citation
  • Reichle, R. H., , D. B. McLaughlin, , and D. Entekhabi, 2002a: Hydrologic data assimilation with an ensemble Kalman filter. Mon. Wea. Rev., 130 , 103114.

    • Search Google Scholar
    • Export Citation
  • Reichle, R. H., , J. P. Walker, , R. D. Koster, , and P. R. Houser, 2002b: Extended versus ensemble Kalman filtering for land data assimilation. J. Hydrometeor., 3 , 728740.

    • Search Google Scholar
    • Export Citation
  • Rogers, E., , D. Deaven, , and G. J. DiMego, 1995: The regional analysis system for the operational “early” Eta model: Original 80-km configuration and recent changes. Wea. Forecasting, 10 , 810825.

    • Search Google Scholar
    • Export Citation
  • Rogers, E., , T. L. Black, , D. G. Deaven, , G. J. DiMego, , Q. Zhao, , M. Baldwin, , N. W. Junker, , and Y. Lin, 1996: Changes to the operational “early” Eta analysis/forecast system at the National Centers for Environmental Prediction. Wea. Forecasting, 11 , 391413.

    • Search Google Scholar
    • Export Citation
  • Sasamori, T., 1970: A numerical study of atmospheric and soil boundary layers. J. Atmos. Sci., 27 , 11221137.

  • Segal, M., , and R. W. Arritt, 1992: Nonclassical mesoscale circulations caused by surface sensible heat flux gradients. Bull. Amer. Meteor. Soc., 73 , 15931604.

    • Search Google Scholar
    • Export Citation
  • Sellers, P. J., , Y. Mintz, , Y. C. Sud, , and A. Dalcher, 1986: A simple biosphere model (SIB) for use with general circulation models. J. Atmos. Sci., 43 , 505531.

    • Search Google Scholar
    • Export Citation
  • Skamarock, W. C., , J. B. Klemp, , and J. Dudhia, 2001: Prototypes for the WRF (weather research and forecasting) model. Preprints, Ninth Conf. on Mesoscale Processes, Fort Lauderdale, FL, Amer. Meteor. Soc., J11–J15.

  • Skamarock, W. C., , J. B. Klemp, , J. Dudhia, , D. O. Gill, , D. M. Barker, , W. Wang, , and J. G. Powers, 2005: A description of the Advanced Research WRF Version 2. NCAR Tech. Note NCAR/TN-468+STR, 94 pp.

  • Stensrud, D. J., , and S. J. Weiss, 2002: Mesoscale model ensemble forecasts of the 3 May 1999 tornado outbreak. Wea. Forecasting, 17 , 526543.

    • Search Google Scholar
    • Export Citation
  • Stensrud, D. J., , J-W. Bao, , and T. T. Warner, 2000: Using initial conditions and model physics perturbations in short-range ensemble simulations of mesoscale convective systems. Mon. Wea. Rev., 128 , 20772107.

    • Search Google Scholar
    • Export Citation
  • Szunyogh, I., , and Z. Toth, 2002: The effect of increased horizontal resolution on the NCEP global ensemble mean forecasts. Mon. Wea. Rev., 130 , 11251143.

    • Search Google Scholar
    • Export Citation
  • Tribbia, J. J., , and D. P. Baumhefner, 2004: Scale interactions and atmospheric predictability: An updated perspective. Mon. Wea. Rev., 132 , 703713.

    • Search Google Scholar
    • Export Citation
  • Trier, S. B., , F. Chen, , and K. W. Manning, 2004: A study of convection initiation in a mesoscale model using high-resolution land surface initial conditions. Mon. Wea. Rev., 132 , 29542976.

    • Search Google Scholar
    • Export Citation
  • Wang, W., , and N. L. Seaman, 1997: A comparison study of convective parameterization schemes in a mesoscale model. Mon. Wea. Rev., 125 , 252278.

    • Search Google Scholar
    • Export Citation
  • Wang, X., , and C. H. Bishop, 2003: A comparison of breeding and ensemble transform Kalman filter ensemble forecast schemes. J. Atmos. Sci., 60 , 11401158.

    • Search Google Scholar
    • Export Citation
  • Wicker, L. J., , and W. C. Skamarock, 2002: Time splitting methods for elastic models using forward time schemes. Mon. Wea. Rev., 130 , 20882097.

    • Search Google Scholar
    • Export Citation
  • Xue, Y., , P. J. Sellers, , J. L. Kinter III, , and J. Shukla, 1991: A simplified biosphere model for global climate studies. J. Climate, 4 , 345364.

    • Search Google Scholar
    • Export Citation
  • Yan, H., , and R. A. Anthes, 1988: The effect of variations in surface moisture on mesoscale circulations. Mon. Wea. Rev., 116 , 192208.

    • Search Google Scholar
    • Export Citation
  • Zhang, D., , and R. A. Anthes, 1982: A high-resolution model of the planetary boundary layer—Sensitivity tests and comparison with SESAME-79 data. J. Appl. Meteor., 21 , 15941609.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 31 31 5
PDF Downloads 20 20 4

Will Perturbing Soil Moisture Improve Warm-Season Ensemble Forecasts? A Proof of Concept

View More View Less
  • 1 Program in Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado
  • | 2 Physical Sciences Division, NOAA/Earth System Research Laboratory, Boulder, Colorado
  • | 3 Program in Atmospheric and Oceanic Sciences, University of Colorado, and National Center for Atmospheric Research, Boulder, Colorado
© Get Permissions
Restricted access

Abstract

Current generation short-range ensemble forecast members tend to be unduly similar to each other, especially for components such as surface temperature and precipitation. One possible cause of this is a lack of perturbations to the land surface state. In this experiment, a two-member ensemble of the Advanced Research Weather Research and Forecasting (WRF) model (ARW) was run from two different soil moisture analyses. One-day forecasts were conducted for six warm-season cases over the central United States with moderate soil moistures, both with explicit convection at 5-km grid spacing and with parameterized convection at 20-km grid spacing. Since changing the convective parameterization has previously been demonstrated to cause significant differences between ensemble forecast members, 20-km simulations were also conducted that were initialized with the same soil moisture but that used two different convective parameterizations as a reference. At 5 km, the forecast differences due to changing the soil moisture were comparable to the differences in 20-km simulations with the same soil moisture but with a different convective parameterization. The differences of 20-km simulations from different soil moistures were occasionally large but typically smaller than the differences from changing the convective parameterization. Thus, perturbing the state of the land surface for this version of WRF/ARW was judged to be likely to increase the spread of warm-season operational short-range ensemble forecasts of precipitation and surface temperature when soil moistures are moderate in value, especially if the ensemble is comprised of high-resolution members with explicit convection.

* Current affiliation: Shell Oil, Houston, Texas

Corresponding author address: Dr. Thomas M. Hamill, NOAA/ESRL/PSD, R/PSD1, 325 Broadway, Boulder, CO 80305. Email: tom.hamill@noaa.gov

Abstract

Current generation short-range ensemble forecast members tend to be unduly similar to each other, especially for components such as surface temperature and precipitation. One possible cause of this is a lack of perturbations to the land surface state. In this experiment, a two-member ensemble of the Advanced Research Weather Research and Forecasting (WRF) model (ARW) was run from two different soil moisture analyses. One-day forecasts were conducted for six warm-season cases over the central United States with moderate soil moistures, both with explicit convection at 5-km grid spacing and with parameterized convection at 20-km grid spacing. Since changing the convective parameterization has previously been demonstrated to cause significant differences between ensemble forecast members, 20-km simulations were also conducted that were initialized with the same soil moisture but that used two different convective parameterizations as a reference. At 5 km, the forecast differences due to changing the soil moisture were comparable to the differences in 20-km simulations with the same soil moisture but with a different convective parameterization. The differences of 20-km simulations from different soil moistures were occasionally large but typically smaller than the differences from changing the convective parameterization. Thus, perturbing the state of the land surface for this version of WRF/ARW was judged to be likely to increase the spread of warm-season operational short-range ensemble forecasts of precipitation and surface temperature when soil moistures are moderate in value, especially if the ensemble is comprised of high-resolution members with explicit convection.

* Current affiliation: Shell Oil, Houston, Texas

Corresponding author address: Dr. Thomas M. Hamill, NOAA/ESRL/PSD, R/PSD1, 325 Broadway, Boulder, CO 80305. Email: tom.hamill@noaa.gov

Save