Slayt 1 - RTC, Regional Training Centre - Turkey

Accounting for the Effects of PhysicalProcessesEach important physical process that cannot be directly predicted requires aparameterization scheme based on reasonable physical (for example, radiation) orstatistical (for example, inferring cloudiness from relative humidity) representations. Thescheme must derive information about the processes from the variables in the forecastequations using a set of assumptions. Closure refers to the link between the assumptionsin the parameterization and the forecast variables. (It closes the loop between theparameterization and forecast equations.)Several types of assumptions are used to "create" information.Empirical/statistical: This assumes that a given relationship holds in every case (forexample, surface layer wind speed variations with height for PBL processes and surfacewind forecasts). Note that for a normal statistical distribution, one of every 20 cases isexpected to be an outlier.Dynamical/thermodynamical constraining assumption: A complex process is summarizedthrough a simplified relationship, for example, equilibrium of instability for Arakawa-Schubert convective parameterization.Model within a model: Although the use of nested models (for example, one-dimensionalcloud models and soil models) pushes the assumption back to a finer detail, assumptionsmust still be made. Running a model within a model requires far more development bymodelers and takes longer to run.The key problem of numerical parameterization is trying to predict with incompleteinformation, for example, the effects of sub grid-scale processes with information at thegrid scale. Imagine using the wind forecast in a grid box to predict boundary-layerturbulence without knowing topography details, vegetation characteristics, or the detailsof structures at the surface.