• Baines, P. G., 1995: Topographic Effects in Stratified Flows. Cambridge University Press, 482 pp.

  • Barcilon, A., , J. C. Jusem, , and P. G. Drazin, 1979: On the two-dimensional hydrostatic flow of a stream of moist air over a mountain ridge. Geophys. Astrophys. Fluid Dyn., 13, 125140, doi:10.1080/03091927908243765.

    • Search Google Scholar
    • Export Citation
  • Bougeault, P., and et al. , 2001: The MAP Special Observing Period. Bull. Amer. Meteor. Soc., 82, 433462, doi:10.1175/1520-0477(2001)082<0433:TMSOP>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., , and J. M. Fritsch, 2002: A benchmark simulation for moist nonhydrostatic numerical models. Mon. Wea. Rev., 130, 29172928, doi:10.1175/1520-0493(2002)130<2917:ABSFMN>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Bryan, G. H., , J. C. Wynguard, , and J. M. Fritsch, 2003: Resolution requirements for the simulation of deep moist convection. Mon. Wea. Rev., 131, 23942416, doi:10.1175/1520-0493(2003)131<2394:RRFTSO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Buzzi, A., , and L. Foschini, 2000: Mesoscale meteorological features associated with heavy precipitation in the Southern Alpine Region. Meteor. Atmos. Phys., 72, 131146, doi:10.1007/s007030050011.

    • Search Google Scholar
    • Export Citation
  • Cannon, D. J., , D. J. Kirshbaum, , and S. L. Gray, 2012: Under what conditions does embedded convection enhance orographic precipitation? Quart. J. Roy. Meteor. Soc., 138, 391406, doi:10.1002/qj.926.

    • Search Google Scholar
    • Export Citation
  • Colle, B. A., 2004: Sensitivity of orographic precipitation to changing ambient conditions and terrain geometries: An idealized modeling perspective. J. Atmos. Sci., 61, 588606, doi:10.1175/1520-0469(2004)061<0588:SOOPTC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Deardorff, J. W., 1980: Stratocumulus-capped mixed layer derived from a three-dimensional model. Bound.-Layer Meteor., 18, 495527, doi:10.1007/BF00119502.

    • Search Google Scholar
    • Export Citation
  • Delle Monache, L., and et al. , 2008: Bayesian inference and Markov chain Monte Carlo to reconstruct a contaminant source at continental scale. J. Appl. Meteor. Climatol., 47, 26002613, doi:10.1175/2008JAMC1766.1.

    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., III, , C. Ramis, , R. Romero, , and S. Alonso, 1998: A diagnostic study of three heavy precipitation episodes in the western Mediterranean. Wea. Forecasting, 13, 102124, doi:10.1175/1520-0434(1998)013<0102:ADSOTH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Douglas, C. K. M., , and J. Glasspoole, 1947: Meteorological conditions in orographic rainfall in the British Isles. Quart. J. Roy. Meteor. Soc., 73, 1138, doi:10.1002/qj.49707331503.

    • Search Google Scholar
    • Export Citation
  • Durran, D. R., , and J. B. Klemp, 1982: The effects of moisture on trapped lee waves. J. Atmos. Sci., 39, 24902506, doi:10.1175/1520-0469(1982)039<2490:TEOMOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Durran, D. R., , and J. B. Klemp, 1983: A compressible model for the simulation of moist mountain waves. Mon. Wea. Rev., 111, 23412361, doi:10.1175/1520-0493(1983)111<2341:ACMFTS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Gelman, A., , J. B. Carlin, , H. S. Stern, , and D. B. Rubin, 2004: Bayesian Data Analysis. 2nd ed. Chapman and Hall/CRC, 696 pp.

  • Haario, H., , E. Saksman, , and J. Tamminen, 1999: Adaptive proposal distribution for random walk Metropolis algorithm. Comput. Stat., 14, 375395, doi:10.1007/s001800050022.

    • Search Google Scholar
    • Export Citation
  • Jiang, Q., 2003: Moist dynamics and orographic precipitation. Tellus, 55A, 301316, doi:10.1034/j.1600-0870.2003.00025.x.

  • Kessler, E., 1969: On the Distribution and Continuity of Water Substance in Atmospheric Circulations. Meteor. Monogr., No. 32, Amer. Meteor. Soc., 84 pp.

  • Kingsmill, D., and et al. , 2006: Overview of the Sierra Hydrometeorology Atmospheric River Experiment (SHARE). 12th Conf. on Mountain Meteorology, Santa Fe, NM, Amer. Meteor. Soc., P1.1. [Available online at https://ams.confex.com/ams/SantaFe2006/techprogram/paper_114479.htm.]

  • Kirshbaum, D. J., , and R. B. Smith, 2008: Temperature and moist-stability effects on midlatitude orographic precipitation. Quart. J. Roy. Meteor. Soc., 134, 11831199, doi:10.1002/qj.274.

    • Search Google Scholar
    • Export Citation
  • Miglietta, M. M., , and A. Buzzi, 2001: A numerical study of moist stratified flows over isolated topography. Tellus, 53A, 481499, doi:10.1111/j.1600-0870.2001.00481.x.

    • Search Google Scholar
    • Export Citation
  • Miglietta, M. M., , and R. Rotunno, 2005: Simulations of moist nearly neutral flow over a ridge. J. Atmos. Sci., 62, 14101427, doi:10.1175/JAS3410.1.

    • Search Google Scholar
    • Export Citation
  • Miglietta, M. M., , and R. Rotunno, 2006: Further results on moist nearly neutral flow over a ridge. J. Atmos. Sci., 63, 28812897, doi:10.1175/JAS3793.1.

    • Search Google Scholar
    • Export Citation
  • Miglietta, M. M., , and R. Rotunno, 2009: Numerical simulations of conditionally unstable flows over a mountain ridge. J. Atmos. Sci., 66, 18651885, doi:10.1175/2009JAS2902.1.

    • Search Google Scholar
    • Export Citation
  • Miglietta, M. M., , and R. Rotunno, 2010: Numerical simulations of low-CAPE flows over a mountain ridge. J. Atmos. Sci., 67, 23912401, doi:10.1175/2010JAS3378.1.

    • Search Google Scholar
    • Export Citation
  • Miglietta, M. M., , and R. Rotunno, 2012: Application of theory to observed cases of orographically forced convective rainfall. Mon. Wea. Rev., 140, 30393053, doi:10.1175/MWR-D-11-00253.1.

    • Search Google Scholar
    • Export Citation
  • Miglietta, M. M., , and R. Rotunno, 2014: Numerical simulations of sheared conditionally unstable flows over a mountain ridge. J. Atmos. Sci., 71, 1747–1762, doi:10.1175/JAS-D-13-0297.1.

    • Search Google Scholar
    • Export Citation
  • Muraki, D. J., , and R. Rotunno, 2013: Internal gravity waves in a saturated moist neutral atmosphere. J. Amos. Sci., 70, 36933709, doi:10.1175/JAS-D-13-051.1.

    • Search Google Scholar
    • Export Citation
  • Neiman, P. J., , F. M. Ralph, , A. B. White, , D. E. Kingsmill, , and P. O. G. Persson, 2002: The statistical relationship between upslope flow and rainfall in California’s coastal mountains: Observations during CALJET. Mon. Wea. Rev., 130, 14681492, doi:10.1175/1520-0493(2002)130<1468:TSRBUF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Neiman, P. J., , L. J. Schick, , F. M. Ralph, , M. Hughes, , and G. A. Wick, 2011: Flooding in western Washington: The connection to atmospheric rivers. J. Hydrometeor., 12, 13371358, doi:10.1175/2011JHM1358.1.

    • Search Google Scholar
    • Export Citation
  • Posselt, D. J., 2013: Markov chain Monte Carlo methods: Theory and applications. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications, S. K. Park and L. Xu, Eds., Vol. II, Springer, 59–87.

  • Posselt, D. J., , and T. Vukicevic, 2010: Robust characterization of model physics uncertainty for simulations of deep moist convection. Mon. Wea. Rev., 138, 15131535, doi:10.1175/2009MWR3094.1.

    • Search Google Scholar
    • Export Citation
  • Posselt, D. J., , and C. H. Bishop, 2012: Nonlinear parameter estimation: Comparison of an ensemble Kalman smoother with a Markov chain Monte Carlo algorithm. Mon. Wea. Rev., 140, 19571974, doi:10.1175/MWR-D-11-00242.1.

    • Search Google Scholar
    • Export Citation
  • Posselt, D. J., , T. S. L’Ecuyer, , and G. L. Stephens, 2008: Exploring the error characteristics of thin ice cloud property retrievals using a Markov chain Monte Carlo algorithm. J. Geophys. Res., 113, D24206, doi:10.1029/2008JD010832.

    • Search Google Scholar
    • Export Citation
  • Posselt, D. J., , D. Hodyss, , and C. H. Bishop, 2014: Errors in ensemble Kalman smoother estimates of cloud microphysical parameters. Mon. Wea. Rev., 142, 16311654, doi:10.1175/MWR-D-13-00290.1.

    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., , and M. D. Dettinger, 2011: Storms, floods, and the science of atmospheric rivers. Eos, Trans. Amer. Geophys. Union, 92, 265266, doi:10.1029/2011EO320001.

    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., , P. J. Neiman, , and G. A. Wick, 2004: Satellite and CALJET aircraft observations of atmospheric rivers over the eastern North Pacific Ocean during the winter of 1997/98. Mon. Wea. Rev., 132, 17211745, doi:10.1175/1520-0493(2004)132<1721:SACAOO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ralph, F. M., , P. J. Nieman, , and R. Rotunno, 2005: Dropsonde observations in low-level jets over the northeastern Pacific Ocean from CALJET-1998 and PACJET-2001: Mean vertical-profile and atmospheric-river characteristics. Mon. Wea. Rev., 133, 889910, doi:10.1175/MWR2896.1.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., , and R. Ferretti, 2003: Orographic effects on rainfall in MAP cases IOP 2b and IOP 8. Quart. J. Roy. Meteor. Soc., 129, 373390, doi:10.1256/qj.02.20.

    • Search Google Scholar
    • Export Citation
  • Rotunno, R., , and R. A. Houze, 2007: Lessons on orographic precipitation from the Mesoscale Alpine Programme. Quart. J. Roy. Meteor. Soc., 133, 811830, doi:10.1002/qj.67.

    • Search Google Scholar
    • Export Citation
  • Rutz, J. J., , W. J. Steenburgh, , and F. M. Ralph, 2014: Climatological characteristics of atmospheric rivers and their inland penetration over the western United States. Mon. Wea. Rev., 142, 905921, doi:10.1175/MWR-D-13-00168.1.

    • Search Google Scholar
    • Export Citation
  • Sarker, R. P., 1967: Some modifications in a dynamical model of orographic rainfall. Mon. Wea. Rev., 95, 673684, doi:10.1175/1520-0493(1967)095<0673:SMIADM>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Sawyer, J. S., 1956: The physical and dynamical problems of orographic rain. Weather, 11, 375381, doi:10.1002/j.1477-8696.1956.tb00264.x.

    • Search Google Scholar
    • Export Citation
  • Schultz, D. M., and et al. , 2002: Understanding Utah winter storms: The Intermountain Precipitation Experiment. Bull. Amer. Meteor. Soc., 83, 189210, doi:10.1175/1520-0477(2002)083<0189:UUWSTI>2.3.CO;2.

    • Search Google Scholar
    • Export Citation
  • Seibert, P., 1990: South foehn studies since the ALPEX experiment. Meteor. Atmos. Phys., 43, 91103, doi:10.1007/BF01028112.

  • Smith, R. B., 1979: The influence of mountains on the atmosphere. Advances in Geophysics, Vol. 21, Academic Press, 87–230.

  • Smith, R. B., 2006: Progress on the theory of orographic precipitation. GSA Spec. Pap., 398, 116.

  • Stoelinga, M. T., and et al. , 2003: Improvement of microphysical parameterization through observational verification experiment. Bull. Amer. Meteor. Soc., 84, 18071826, doi:10.1175/BAMS-84-12-1807.

    • Search Google Scholar
    • Export Citation
  • Tamminen, J., , and E. Kyrölä, 2001: Bayesian solution for nonlinear and non-Gaussian inverse problems by Markov chain Monte Carlo method. J. Geophys. Res., 106, 14 37714 390, doi:10.1029/2001JD900007.

    • Search Google Scholar
    • Export Citation
  • Vukicevic, T., , and D. J. Posselt, 2008: Analysis of the impact of model nonlinearities in inverse problem solving. J. Atmos. Sci., 65, 28032823, doi:10.1175/2008JAS2534.1.

    • Search Google Scholar
    • Export Citation
  • Zängl, G., , and M. Hornsteiner, 2007: The exceptional Alpine south foehn event of 14–16 November 2002: A case study. Meteor. Atmos. Phys., 98, 217238, doi:10.1007/s00703-006-0257-9.

    • 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 2

Bayesian Exploration of Multivariate Orographic Precipitation Sensitivity for Moist Stable and Neutral Flows

View More View Less
  • 1 Space Science and Engineering Center, University of Wisconsin–Madison, Madison, Wisconsin
  • | 2 University of Michigan, Ann Arbor, Michigan
  • | 3 Institute of Atmospheric Sciences and Climate (ISAC), Italian National Research Council (CNR), Lecce, Italy
  • | 4 National Center for Atmospheric Research, Boulder, Colorado
© Get Permissions
Restricted access

Abstract

Recent idealized studies examined the sensitivity of topographically forced rain and snowfall to changes in mountain geometry and upwind sounding in moist stable and neutral environments. These studies were restricted by necessity to small ensembles of carefully chosen simulations. Research presented here extends earlier studies by utilizing a Bayesian Markov chain Monte Carlo (MCMC) algorithm to create a large ensemble of simulations, all of which produce precipitation concentrated on the upwind slope of an idealized Gaussian bell-shaped mountain. MCMC-based probabilistic analysis yields information about the combinations of sounding and mountain geometry favorable for upslope rain, as well as the sensitivity of orographic precipitation to changes in mountain geometry and upwind sounding. Exploration of the multivariate sensitivity of rainfall to changes in parameters also reveals a nonunique solution: multiple combinations of flow, topography, and environment produce similar surface rainfall amount and distribution. Finally, the results also divulge that the nonunique solutions have different sensitivity profiles, and that changes in observation uncertainty also alter model sensitivity to input parameters.

Corresponding author address: Samantha A. Tushaus, Space Science and Engineering Center, University of Wisconsin–Madison, 1225 W. Dayton St., Madison, WI 53706-1612. E-mail: sam.tushaus@ssec.wisc.edu

Abstract

Recent idealized studies examined the sensitivity of topographically forced rain and snowfall to changes in mountain geometry and upwind sounding in moist stable and neutral environments. These studies were restricted by necessity to small ensembles of carefully chosen simulations. Research presented here extends earlier studies by utilizing a Bayesian Markov chain Monte Carlo (MCMC) algorithm to create a large ensemble of simulations, all of which produce precipitation concentrated on the upwind slope of an idealized Gaussian bell-shaped mountain. MCMC-based probabilistic analysis yields information about the combinations of sounding and mountain geometry favorable for upslope rain, as well as the sensitivity of orographic precipitation to changes in mountain geometry and upwind sounding. Exploration of the multivariate sensitivity of rainfall to changes in parameters also reveals a nonunique solution: multiple combinations of flow, topography, and environment produce similar surface rainfall amount and distribution. Finally, the results also divulge that the nonunique solutions have different sensitivity profiles, and that changes in observation uncertainty also alter model sensitivity to input parameters.

Corresponding author address: Samantha A. Tushaus, Space Science and Engineering Center, University of Wisconsin–Madison, 1225 W. Dayton St., Madison, WI 53706-1612. E-mail: sam.tushaus@ssec.wisc.edu
Save