On the Predictability of Mesoscale Convective Systems: Three-Dimensional Simulations

Wandishin, Matthew S.; Stensrud, David J.; Mullen, Steven L.; Wicker, Louis J.
March 2010
Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p863
Academic Journal
Mesoscale convective systems (MCSs) are a dominant climatological feature of the central United States and are responsible for a substantial fraction of warm-season rainfall. Yet very little is known about the predictability of MCSs. To help address this situation, a previous paper by the authors examined a series of ensemble MCS simulations using a two-dimensional version of a storm-scale (Δ x = 1 km) model. Ensemble member perturbations in the preconvective environment, namely, wind speed, relative humidity, and convective instability, are based on current 24-h forecast errors from the North American Model (NAM). That work is now extended using a full three-dimensional model. Results from the three-dimensional simulations of the present study resemble those found in two dimensions. The model successfully produces an MCS within 100 km of the location of the control run in around 70% of the ensemble runs using perturbations to the preconvective environment consistent with 24-h forecast errors, while reducing the preconvective environment uncertainty to the level of current analysis errors improves the success rate to nearly 85%. This magnitude of improvement in forecasts of environmental conditions would represent a radical advance in numerical weather prediction. The maximum updraft and surface wind forecast uncertainties are of similar magnitude to their two-dimensional counterparts. However, unlike the two-dimensional simulations, in three dimensions, the improvement in the forecast uncertainty of storm features requires the reduction of preconvective environmental uncertainty for all perturbed variables. The MCSs in many of the runs resemble bow echoes, but surface winds associated with these solutions, and the perturbation profiles that produce them, are nearly indistinguishable from the nonbowing solutions, making any conclusions about the bowlike systems difficult.


Related Articles

  • Evaluation of Planetary Boundary Layer Scheme Sensitivities for the Purpose of Parameter Estimation. Nielsen-Gammon, John W.; Hu, Xiao-Ming; Zhang, Fuqing; Pleim, Jonathan E. // Monthly Weather Review;Sep2010, Vol. 138 Issue 9, p3400 

    Meteorological model errors caused by imperfect parameterizations generally cannot be overcome simply by optimizing initial and boundary conditions. However, advanced data assimilation methods are capable of extracting significant information about parameterization behavior from the...

  • Simulating the IHOP_2002 Fair-Weather CBL with the WRF-ARW–Noah Modeling System. Part II: Structures from a Few Kilometers to 100 km across. LeMone, Margaret A.; Fei Chen; Tewari, Mukul; Dudhia, Jimy; Geerts, Bart; Qun Miao; Coulter, Richard L.; Grossman, Robert L. // Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p745 

    Fair-weather data along the May–June 2002 International H2O Project (IHOP_2002) eastern track and the nearby Argonne Boundary Layer Experiments (ABLE) facility in southeast Kansas are compared to numerical simulations to gain insight into how the surface influences convective boundary...

  • Using ARM Observations to Evaluate Cloud and Clear-Sky Radiation Processes as Simulated by the Canadian Regional Climate Model GEM. Paquin-Ricard, Danahé; Jones, Colin; Vaillancourt, Paul A. // Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p818 

    The total downwelling shortwave (SWD) and longwave (LWD) radiation and its components are assessed for the limited-area version of the Global Environmental Multiscale Model (GEM-LAM) against Atmospheric Radiation Measurements (ARM) at two sites: the southern Great Plains (SGP) and the North...

  • An Immersed Boundary Method for the Weather Research and Forecasting Model. Lundquist, Katherine A.; Chow, Fotini Katopodes; Lundquist, Julie K. // Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p796 

    This paper describes an immersed boundary method that facilitates the explicit resolution of complex terrain within the Weather Research and Forecasting (WRF) model. Mesoscale models, such as WRF, are increasingly used for high-resolution simulations, particularly in complex terrain, but errors...

  • Validation of Cloud-Resolving Model Background Data for Cloud Data Assimilation. Polkinghorne, Rosanne; Vukicevic, Tomislava; Evans, K. Franklin // Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p781 

    Results from a cloud-resolving model are systematically compared with a variety of observations, both ground based and satellite, in order to better understand the mean background errors and their correlations. This is a step in the direction of developing a background error covariance matrix...

  • The Life Cycle of an Undular Bore and Its Interaction with a Shallow, Intense Cold Front. Hartung, Daniel C.; Otkin, Jason A.; Martin, Jonathan E.; Turner, David D. // Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p886 

    The evolution of an undular bore and its associated wind shift, spawned by the passage of a shallow surface cold front over the Southern Great Plains of the United States, is examined using surface and remote sensing observations along with output from a high-resolution numerical model...

  • Sensitivity of Simulated Tropical Cyclone Structure and Intensity to Horizontal Resolution. Gentry, Megan S.; Lackmann, Gary M. // Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p688 

    The Weather Research and Forecasting (WRF) model is used to test the sensitivity of simulations of Hurricane Ivan (2004) to changes in horizontal grid spacing for grid lengths from 8 to 1 km. As resolution is increased, minimum central pressure decreases significantly (by 30 hPa from 8- to 1-km...

  • Predictability of the Performance of an Ensemble Forecast System: Predictability of the Space of Uncertainties. Satterfield, Elizabeth; Szunyogh, Istvan // Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p962 

    The performance of an ensemble prediction system is inherently flow dependent. This paper investigates the flow dependence of the ensemble performance with the help of linear diagnostics applied to the ensemble perturbations in a small local neighborhood of each model gridpoint location...

  • A Quasi-Variational Algorithm for Nonlinear Normal-Mode Initialization. Bourchtein, Andrei // Monthly Weather Review;Mar2010, Vol. 138 Issue 3, p951 

    Balance equations of normal-mode initialization are nonlinear time-independent partial differential equations solved by iterative methods. For the given geopotential, there are regions where these equations are not elliptic, which is reflected in the divergence of iterative algorithms....


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics