Articles | Volume 4, issue 3
https://doi.org/10.5194/wcd-4-725-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-4-725-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
31 Aug 2023
Research article |
| 31 Aug 2023
| 31 Aug 2023
Adverse impact of terrain steepness on thermally driven initiation of orographic convection
Matthias Göbel
CORRESPONDING AUTHOR
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
Regional Office Salzburg and Upper Austria, GeoSphere Austria, Salzburg, Austria
Stefano Serafin
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
Mathias W. Rotach
Department of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, Austria
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Cited articles
Baek, S.: A Revised Radiation Package of G-packed McICA and Two-Stream
Approximation: Performance Evaluation in a Global Weather Forecasting
Model, J. Adv. Model Earth Syst., 9, 1628–1640, https://doi.org/10.1002/2017MS000994, 2017. a
Banacos, P. C. and Ekster, M. L.: The Association of the Elevated Mixed
Layer with Significant Severe Weather Events in the Northeastern
United States, Weather Forecast., 25, 1082–1102,
https://doi.org/10.1175/2010WAF2222363.1, 2010. a
Banta, R. M.: The Role of Mountain Flows in Making Clouds, in: Atmospheric
Processes over Complex Terrain, Springer, 229–283, https://doi.org/10.1007/978-1-935704-25-6_9, 1990. a, b
Bechis, H., Galligani, V., Alvarez Imaz, M., Cancelada, M., Simone, I.,
Piscitelli, F., Maldonado, P., Salio, P., and Nesbitt, S. W.: A Case Study of
a Severe Hailstorm in Mendoza, Argentina, during the
RELAMPAGO-CACTI Field Campaign, Atmos. Res., 271, 106127,
https://doi.org/10.1016/j.atmosres.2022.106127, 2022. a
Chen, F. and Dudhia, J.: 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, https://doi.org/10.1175/1520-0493(2001)129<0569:CAALSH>2.0.CO;2, 2001. a
Colle, B. A.: Theory, Observations, and Predictions of Orographic
Precipitation, in: Theory, Observations, and Predictions of
Orographic Precipitation, vol. Mountain Weather Research and Forecasting,
Springer, 291–344, https://doi.org/10.1007/978-94-007-4098-3_6, 2013. a
Crook, N. A. and Tucker, D. F.: Flow over Heated Terrain. Part I:
Linear Theory and Idealized Numerical Simulations, Mon. Weather Rev.,
133, 2552–2564, https://doi.org/10.1175/MWR2964.1, 2005. a
Damiani, R., Zehnder, J., Geerts, B., Demko, J., Haimov, S., Petti, J., Poulos, G. S., Razdan, A., Hu, J., Leuthold, M., and French, J.: The Cumulus, Photogrammetric, In Situ, and Doppler Observations Experiment of 2006, B. Am. Meteorol. Soc., 89, 57–74, https://doi.org/10.1175/BAMS-89-1-57, 2008. a
Deardorff, J. W.: Stratocumulus-Capped Mixed Layers Derived from a
Three-Dimensional Model, Bound.-Lay. Meteorol., 18, 495–527, https://doi.org/10.1007/BF00119502, 1980. a
Demko, J. C. and Geerts, B.: A Numerical Study of the Evolving Convective Boundary Layer and Orographic Circulation around the Santa Catalina Mountains in Arizona. Part II: Interaction with Deep
Convection, Mon. Weather Rev., 138, 3603–3622, https://doi.org/10.1175/2010MWR3318.1, 2010. a, b, c, d, e, f, g, h
Demko, J. C., Geerts, B., Miao, Q., and Zehnder, J. A.: Boundary Layer Energy Transport and Cumulus Development over a Heated Mountain: An Observational Study, Mon. Weather Rev., 137, 447–468,
https://doi.org/10.1175/2008MWR2467.1, 2009. a
Done, J. M., Craig, G. C., Gray, S. L., Clark, P. A., and Gray, M. E. B.:
Mesoscale Simulations of Organized Convection: Importance of Convective
Equilibrium, Q. J. Roy. Meteorol. Soc., 132, 737–756, https://doi.org/10.1256/qj.04.84, 2006. a, b
Done, J. M., Craig, G. C., Gray, S. L., and Clark, P. A.: Case-to-Case
Variability of Predictability of Deep Convection in a Mesoscale Model, Q. J.
Roy. Meteorol. Soc., 138, 638–648, https://doi.org/10.1002/qj.943, 2012. a
Doswell, C. A., Brooks, H. E., and Maddox, R. A.: Flash Flood Forecasting: An Ingredients-Based Methodology, Weather Forecast., 11, 560–581, https://doi.org/10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2, 1996. a
Göbel, M.: Data and Code for “Adverse Impact of Terrain Steepness on
Thermally-Driven Initiation of Orographic Convection”, Zenodo [code and data set], https://doi.org/10.5281/zenodo.8046464, 2023a. a, b, c
Göbel, M., Serafin, S., and Rotach, M. W.: Numerically Consistent Budgets
of Potential Temperature, Momentum, and Moisture in Cartesian Coordinates: Application to the WRF Model, Geosci. Model Dev., 15, 669–681, https://doi.org/10.5194/gmd-15-669-2022, 2022. a, b, c
Griewank, P. J., Heus, T., and Neggers, R. A. J.: Size-Dependent
Characteristics of Surface-Rooted Three-Dimensional Convective Objects
in Continental Shallow Cumulus Simulations, J. Adv. Model Earth Syst., 14, e2021MS002612, https://doi.org/10.1029/2021MS002612, 2022. a
Hagen, M., van Baelen, J., and Richard, E.: Influence of the Wind Profile on
the Initiation of Convection in Mountainous Terrain, Q. J. Roy. Meteorol. Soc., 137, 224–235, https://doi.org/10.1002/qj.784, 2011. a
Houze, R. A.: Orographic Effects on Precipitating Clouds, Rev. Geophys.,
50, RG1001, https://doi.org/10.1029/2011RG000365, 2012. a
Jiménez, P. A., Dudhia, J., González-Rouco, J. F., Navarro, J.,
Montávez, J. P., and García-Bustamante, E.: A Revised Scheme
for the WRF Surface Layer Formulation, Mon. Weather Rev., 140, 898–918,
https://doi.org/10.1175/MWR-D-11-00056.1, 2012. a
Kalthoff, N., Adler, B., Barthlott, C., Corsmeier, U., Mobbs, S., Crewell, S., Träumner, K., Kottmeier, C., Wieser, A., Smith, V., and Di Girolamo, P.: The Impact of Convergence Zones on the Initiation of Deep Convection: A Case Study from COPS, Atmos. Res., 93, 680–694,
https://doi.org/10.1016/j.atmosres.2009.02.010, 2009. a
Kealy, J. C., Efstathiou, G. A., and Beare, R. J.: The Onset of Resolved Boundary-Layer Turbulence at Grey-Zone Resolutions, Bound.-Lay. Meteorol., 171, 31–52, https://doi.org/10.1007/s10546-018-0420-0, 2019. a, b
Keil, C., Heinlein, F., and Craig, G. C.: The Convective Adjustment Time-Scale as Indicator of Predictability of Convective Precipitation, Q. J. Roy. Meteorol. Soc., 140, 480–490, https://doi.org/10.1002/qj.2143, 2014. a
Kirshbaum, D. J., Adler, B., Kalthoff, N., Barthlott, C., and Serafin, S.:
Moist Orographic Convection: Physical Mechanisms and Links to
Surface-Exchange Processes, Atmosphere, 9, 1–26, https://doi.org/10.3390/atmos9030080, 2018. a, b
Klemp, J. B.: A Terrain-Following Coordinate with Smoothed Coordinate
Surfaces, Mon. Weather Rev., 139, 2163–2169, https://doi.org/10.1175/MWR-D-10-05046.1, 2011. a
Klemp, J. B., Dudhia, J., and Hassiotis, A. D.: An Upper Gravity-Wave
Absorbing Layer for NWP Applications, Mon. Weather Rev., 136, 3987–4004, https://doi.org/10.1175/2008MWR2596.1, 2008. a
Kumjian, M. R., Gutierrez, R., Soderholm, J. S., Nesbitt, S. W., Maldonado, P., Luna, L. M., Marquis, J., Bowley, K. A., Imaz, M. A., and Salio, P.:
Gargantuan Hail in Argentina, B. Am. Meteorol. Soc., 101, E1241–E1258, https://doi.org/10.1175/BAMS-D-19-0012.1, 2020. a
Leukauf, D., Gohm, A., and Rotach, M. W.: Quantifying Horizontal and Vertical
Tracer Mass Fluxes in an Idealized Valley during Daytime, Atmos. Chem. Phys.,
16, 13049–13066, https://doi.org/10.5194/acp-16-13049-2016, 2016. a
Liu, X.-D., Osher, S., and Chan, T.: Weighted Essentially Non-oscillatory
Schemes, J. Comput. Phys., 115, 200–212, https://doi.org/10.1006/jcph.1994.1187, 1994. a
Manzato, A.: A Climatology of Instability Indices Derived from Friuli Venezia Giulia Soundings, Using Three Different Methods, Atmos. Res., 67–68, 417–454, https://doi.org/10.1016/S0169-8095(03)00058-9, 2003. a
Manzato, A., Serafin, S., Miglietta, M. M., Kirshbaum, D., and Schulz, W.: A
Pan-Alpine Climatology of Lightning and Convective Initiation,
Mon. Weather Rev., 150, 2213–2230, https://doi.org/10.1175/MWR-D-21-0149.1, 2022. a
Marquis, J. N., Varble, A. C., Robinson, P., Nelson, T. C., and Friedrich, K.: Low-Level Mesoscale and Cloud-Scale Interactions Promoting Deep
Convection Initiation, Mon. Weather Rev., 149, 2473–2495,
https://doi.org/10.1175/MWR-D-20-0391.1, 2021. a, b
Morrison, H. and Milbrandt, J. A.: Parameterization of Cloud Microphysics
Based on the Prediction of Bulk Ice Particle Properties. Part I: Scheme Description and Idealized Tests, J. Atmos. Sci., 72, 287–311, https://doi.org/10.1175/JAS-D-14-0065.1, 2015. a
Morrison, H., Peters, J. M., Chandrakar, K. K., and Sherwood, S. C.: Influences of Environmental Relative Humidity and Horizontal Scale of Subcloud Ascent on Deep Convective Initiation, J. Atmos. Sci., 79, 337–359, https://doi.org/10.1175/JAS-D-21-0056.1, 2022. a
Mulholland, J. P., Nesbitt, S. W., Trapp, R. J., Rasmussen, K. L., and Salio,
P. V.: Convective Storm Life Cycle and Environments near the
Sierras de Córdoba, Argentina, Mon. Weather Rev., 146, 2541–2557, https://doi.org/10.1175/MWR-D-18-0081.1, 2018. a
Mulholland, J. P., Nesbitt, S. W., Trapp, R. J., and Peters, J. M.: The
Influence of Terrain on the Convective Environment and Associated Convective Morphology from an Idealized Modeling
Perspective, J. Atmos. Sci., 77, 3929–3949, https://doi.org/10.1175/JAS-D-19-0190.1, 2020. a
Nelson, T. C., Marquis, J., Peters, J. M., and Friedrich, K.: Environmental
Controls on Simulated Deep Moist Convection Initiation Occurring
during RELAMPAGO-CACTI, J. Atmos. Sci., 79, 1941–1964,
https://doi.org/10.1175/JAS-D-21-0226.1, 2022. a, b, c
Nesbitt, S. W., Salio, P. V., Ávila, E., Bitzer, P., Carey, L.,
Chandrasekar, V., Deierling, W., Dominguez, F., Dillon, M. E., Garcia, C. M.,
Gochis, D., Goodman, S., Hence, D. A., Kosiba, K. A., Kumjian, M. R., Lang,
T., Luna, L. M., Marquis, J., Marshall, R., McMurdie, L. A., Nascimento, E.
D. L., Rasmussen, K. L., Roberts, R., Rowe, A. K., Ruiz, J. J., Sabbas, E. F.
M. T. S., Saulo, A. C., Schumacher, R. S., Skabar, Y. G., Machado, L. A. T.,
Trapp, R. J., Varble, A. C., Wilson, J., Wurman, J., Zipser, E. J., Arias,
I., Bechis, H., and Grover, M. A.: A Storm Safari in Subtropical South
America: Proyecto RELAMPAGO, B. Am. Meteorol. Soc., 102, E1621–E1644, https://doi.org/10.1175/BAMS-D-20-0029.1, 2021. a
Panosetti, D., Böing, S., Schlemmer, L., and Schmidli, J.: Idealized
Large-Eddy and Convection-Resolving Simulations of Moist
Convection over Mountainous Terrain, J. Atmos. Sci., 73, 4021–4041,
https://doi.org/10.1175/JAS-D-15-0341.1, 2016. a
Panosetti, D., Schlemmer, L., and Schär, C.: Convergence Behavior of
Idealized Convection-Resolving Simulations of Summertime Deep Moist
Convection over Land, Clim. Dynam., 55, 215–234, https://doi.org/10.1007/s00382-018-4229-9, 2018. a
Peters, J. M., Nowotarski, C. J., and Mullendore, G. L.: Are Supercells
Resistant to Entrainment Because of Their Rotation?, J. Atmos.
Sci., 77, 1475–1495, https://doi.org/10.1175/JAS-D-19-0316.1, 2020. a
Scheffknecht, P., Serafin, S., and Grubišić, V.: A Long-Lived
Supercell over Mountainous Terrain, Q. J. Roy. Meteorol. Soc., 143, 2973–2986, https://doi.org/10.1002/qj.3127, 2017. a
Schlemmer, L., Hohenegger, C., Schmidli, J., Bretherton, C. S., Schär, C.: An Idealized Cloud-Resolving Framework for the Study of Midlatitude Diurnal Convection over Land, J. Atmos. Sci., 68,
1041–1057, https://doi.org/10.1175/2010JAS3640.1, 2011. a
Schmidli, J.: Daytime Heat Transfer Processes over Mountainous Terrain, J. Atmos. Sci., 70, 4041–4066, https://doi.org/10.1175/JAS-D-13-083.1, 2013. a
Skamarock, W. C. and Klemp, J. B.: A Time-Split Nonhydrostatic Atmospheric
Model for Weather Research and Forecasting Applications, J. Comput. Phys.,
227, 3465–3485, https://doi.org/10.1016/j.jcp.2007.01.037, 2008. a
Soderholm, B., Ronalds, B., and Kirshbaum, D. J.: The Evolution of
Convective Storms Initiated by an Isolated Mountain Ridge, Mon. Weather Rev., 142, 1430–1451, https://doi.org/10.1175/MWR-D-13-00280.1, 2013. a
Tucker, D. F. and Crook, N. A.: Flow over Heated Terrain. Part II:
Generation of Convective Precipitation, Mon. Weather Rev., 133,
2565–2582, https://doi.org/10.1175/MWR2965.1, 2005. a
Varble, A. C., Nesbitt, S. W., Salio, P., Hardin, J. C., Bharadwaj, N., Borque, P., DeMott, P. J., Feng, Z., Hill, T. C. J., Marquis, J. N., Matthews, A., Mei, F., Öktem, R., Castro, V., Goldberger, L., Hunzinger, A., Barry, K. R., Kreidenweis, S. M., McFarquhar, G. M., McMurdie, L. A., Pekour, M., Powers, H., Romps, D. M., Saulo, C., Schmid, B., Tomlinson, J. M., van den Heever, S. C., Zelenyuk, A., Zhang, Z., and Zipser, E. J.: Utilizing a Storm-Generating Hotspot to Study Convective Cloud Transitions: The CACTI Experiment, Bu. Am. Meteorol. Soc., 102, E1597–E1620, https://doi.org/10.1175/BAMS-D-20-0030.1, 2021. a
Wagner, J. S., Gohm, A., and Rotach, M. W.: The Impact of Valley Geometry on
Daytime Thermally Driven Flows and Vertical Transport Processes, Q. J. Roy.
Meteorol. Soc., 141, 1780–1794, https://doi.org/10.1002/qj.2481, 2015. a
Weckwerth, T. M., Wilson, J. W., Hagen, M., Emerson, T. J., Pinto, J. O., Rife, D. L., and Grebe, L.: Radar Climatology of the COPS Region, Q. J. Roy. Meteorol. Soc., 137, 31–41, https://doi.org/10.1002/qj.747, 2011. a
Weinkaemmerer, J., Göbel, M., Serafin, S., Ďurán, I. B., and Schmidli, J.: Boundary-layer plumes over mountainous terrain in idealized large-eddy simulations, Q. J. R. Meteorol. Soc., https://doi.org/10.1002/qj.4551, 2023. a
Wicker, L. J. and Skamarock, W. C.: Time-Splitting Methods for Elastic
Models Using Forward Time Schemes, Mon. Weather Rev., 130, 2088–2097,
https://doi.org/10.1175/1520-0493(2002)130<2088:TSMFEM>2.0.CO;2, 2002. a
Wulfmeyer, V., Behrendt, A., Kottmeier, C., Corsmeier, U., Barthlott, C.,
Craig, G. C., Hagen, M., Althausen, D., Aoshima, F., Arpagaus, M., Bauer,
H.-S., Bennett, L., Blyth, A., Brandau, C., Champollion, C., Crewell, S.,
Dick, G., Girolamo, P. D., Dorninger, M., Dufournet, Y., Eigenmann, R.,
Engelmann, R., Flamant, C., Foken, T., Gorgas, T., Grzeschik, M., Handwerker,
J., Hauck, C., Höller, H., Junkermann, W., Kalthoff, N., Kiemle, C.,
Klink, S., König, M., Krauss, L., Long, C. N., Madonna, F., Mobbs, S.,
Neininger, B., Pal, S., Peters, G., Pigeon, G., Richard, E., Rotach, M. W.,
Russchenberg, H., Schwitalla, T., Smith, V., Steinacker, R., Trentmann, J.,
Turner, D. D., van Baelen, J., Vogt, S., Volkert, H., Weckwerth, T., Wernli,
H., Wieser, A., and Wirth, M.: The Convective and Orographically-induced Precipitation Study (COPS): The Scientific
Strategy, the Field Phase, and Research Highlights, Q. J. Roy. Meteorol. Soc., 137, 3–30, https://doi.org/10.1002/qj.752, 2011.
a
Xue, M., Droegemeier, K. K., and Wong, V.: 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, https://doi.org/10.1007/s007030070003, 2000. a
Zardi, D. and Whiteman, C. D.: Diurnal Mountain Wind Systems, in: Mountain Weather Research and Forecasting, Springer,
https://doi.org/10.1007/978-94-007-4098-3_2, 2013. a
Zimmer, M., Craig, G. C., Keil, C., and Wernli, H.: Classification of
Precipitation Events with a Convective Response Timescale and Their
Forecasting Characteristics, Geophys. Res. Lett., 38, L05802, https://doi.org/10.1029/2010GL046199, 2011. a
Short summary
On summer days over mountains, upslope winds transport moist air towards mountain tops and beyond, making local rain showers more likely. We use idealized simulations to investigate how mountain steepness affects this mechanism. We find that steeper mountains lead to a delayed onset and lower intensity of the storms, because less moisture accumulates over the ridges and the thermal updraft zone at the top is narrower and thus more prone to the intrusion of dry air from the environment.
On summer days over mountains, upslope winds transport moist air towards mountain tops and...
