Wavelet Analysis of Properties of Marine Boundary Layer Mesoscale Cells Observed From AMSR‐E
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A mesoscale atmospheric simulation system is described that is being developed in order to improve the simulation of subsynoptic and mesoscale adjustments associated with cyclogenesis, severe storm development, and significant atmospheric transport processes. Present emphasis in model development is in the parameterization of physical processes, time-dependent boundary conditions, sophisticated initialization and analysis procedures, nested grid solutions, and applications software development. Basic characteristics of the system as of March 1982 are listed. In a case study, the Grand Island tornado outbreak of 3 June 1980 is considered in substantial detail. Results of simulations with a mesoscale atmospheric simulation system indicate that over the high plains subtle interactions between existing jet streaks and deep well mixed boundary layers can lead to well organized patterns of mesoscale divergence and pressure falls. The amplitude and positioning of these mesoscale features is a function of the subtle nonlinear interaction between the pre-existing jet-streak and deep well mixed boundary layers. Model results for the case study indicate that the model has the potential for forecasting the precursor mesoscale convective environment.
The session on validation of coupled models is reviewed. The current use of a mesoscale model with a grid size of 20-km during STORM-FEST in 1992 has proven to be extremely valuable. The availability of forecast products at a much higher temporal and spatial resolution was very helpful for mesoscale forecasting, mission planning, and the guidance of research aircraft. Recent numerical simulation of ocean cyclones and mesoscsle convective systems using nonhydrostatic cloud/mesoscale models with a grid size as small as 2-km have demonstrated the potential of these models for predicting mesoscale convective systems, squall lines, hurricane rainbands, mesoscale gravity waves, and mesoscale frontal structures embedded within an extratropical cyclone. Although mesoscale/cloud scale models have demonstrated strong potential for use in operational forecasting, very limited quantitative evaluation (and verification) of these models were performed. As a result, the accuracy, the systematic biases, and the useful forecasts limits were not properly defined for these models. Also, no serious attempts were made to use these models for operational prediction of mesoscale convective systems.
A set of relatively high resolution three-dimensional (3D) simulations were produced to investigate the triggering of moist convection by landscape generated mesoscale circulations. The local accumulated rainfall varied monotonically (linearly) with the size of individual landscape patches, demonstrating the need to develop a trigger function that is sensitive to the size of individual patches. A new triggering function that includes the effect of landscapes generated mesoscale circulations over patches of different sizes consists of a parcel's perturbation in vertical velocity (nu(sub 0)), temperature (theta(sub 0)), and moisture (q(sub 0)). Each variable in the triggering function was also sensitive to soil moisture gradients, atmospheric initial conditions, and moist processes. The parcel's vertical velocity, temperature, and moisture perturbation were partitioned into mesoscale and turbulent components. Budget equations were derived for theta(sub 0) and q(sub 0). Of the many terms in this set of budget equations, the turbulent, vertical flux of the mesoscale temperature and moisture contributed most to the triggering of moist convection through the impact of these fluxes on the parcel's temperature and moisture profile. These fluxes needed to be parameterized to obtain theta(sub 0) and q(sub 0). The mesoscale vertical velocity also affected the profile of nu(sub 0). We used similarity theory to parameterize these fluxes as well as the parcel's mesoscale vertical velocity.
An overview is presented of the Mars-Global Reference Atmospheric Model (Mars-GRAM 2005) and its new features. One important new feature is the "auxiliary profile" option, whereby a simple input file is used to replace mean atmospheric values from Mars-GRAM's conventional (General Circulation Model) climatology. An auxiliary profile can be generated from any source of data or alternate model output. Results are presented using auxiliary profiles produced from mesoscale model output (Southwest Research Institute's Mars Regional Atmospheric Modeling System (MRAMS) model and Oregon State University's Mars mesoscale model (MMM5) model) for three candidate Mars Science Laboratory (MSL) landing sites (Terby Crater, Melas Chasma, and Gale Crater). A global Thermal Emission Spectrometer (TES) database has also been generated for purposes of making 'Mars-GRAM auxiliary profiles. This data base contains averages and standard deviations of temperature, density, and thermal wind components, averaged over 5-by-5 degree latitude bins and 15 degree L(sub S) bins, for each of three Mars years of TES nadir data. Comparisons show reasonably good consistency between Mars-GRAM with low dust optical depth and both TES observed and mesoscale model simulated density at the three study sites. Mean winds differ by a more significant degree. Comparisons of mesoscale and TES standard deviations' with conventional Mars-GRAM values, show that Mars-GRAM density perturbations are somewhat conservative (larger than observed variability), while mesoscale-modeled wind variations are larger than Mars-GRAM model estimates. Input parameters rpscale (for density perturbations) and rwscale (for wind perturbations) can be used to "recalibrate" Mars-GRAM perturbation magnitudes to better replicate observed or mesoscale model variability.
Mesoscale and microscale features of the turbulent winds over the ocean are related to the synoptic scale winds in terms of published spectral forms for the microscale, a mesoscale valley and published values of U*, VAR u', VAR v' and z/L, as defined in the text and as obtained for moderate to gale force winds. The frequencies involved correspond to periods longer than 1 hour and extend to the microscale, which starts at a period near 2 minutes, or so, and continues to the Kolmogorov inertial range. Nondimensional spectra that span both the mesoscale and the microscale are derived as a function of u, f(= n z/u) and z/L, where z is 10 meters, L is the Monin Obukov stability length and u is evaluated at 10 meters. For the same u, different values of z/L produce a range of values of u which in turn result in variations of the eddy structure of the mesoscale and microscale spectra. Both conventional anemometer averages and remotely sensed winds contain a random component of the mesoscale wind in their values. These components are differnces and not errors when winds are compared, and quantitative values for these differences are given. Ways to improve the measurement of the synoptic scale wind by transient ships, data buoys and scatterometers on future spacecraft are described. These ways are loner averaging times for ships and data buoys, depending on the synoptic conditions, and pooling spacecraft to form super observations. Design considerations for future remote sensing systems are given.