Diagnostic modeling of the ARM experimental configuration. Final report

A major accomplishment of this work was to demonstrate the viability of using in-situ data in both mid-continent North America (SGP CART site) and Tropical Western Pacific (TOGA-COARE) locations to provide the horizontal advective flux convergences which force and constrain the Single-Column Model (SCM) which was the main theoretical tool of this work. The author has used TOGA-COARE as a prototype for the ARM TWP site. Results show that SCMs can produce realistic budgets over the ARM sites without relying on parameterization-dependent operational numerical weather prediction objective analyses. The single-column model is diagnostic rather than prognostic. It is numerically integrated in time as an initial value problem which is forced and constrained by observational data. The input is an observed initial state, plus observationally derived estimates of the time-dependent advection terms in the conservation equations, provided at all model layers. Its output is a complete heat and water budget, including temperature and moisture profiles, clouds and their radiative properties, diabatic heating terms, surface energy balance components, and hydrologic cycle elements, all specified as functions of time. These SCM results should be interpreted in light of the original motivation and purpose of ARM and its goal to improve the treatment of cloud-radiation interactions in climate models

Single-Column Modeling, GCM Parameterizations and Atmospheric Radiation Measurement Data

Our overall goal is identical to that of the Atmospheric Radiation Measurement (ARM) Program: the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global and regional models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have first compared single-column model (SCM) output with ARM observations at the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Topical Western Pacific (TWP) sites. We focus on the predicted cloud amounts and on a suite of radiative quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments of cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art 3D atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable. We are currently testing the performance of our ARM-based parameterizations in state-of-the--art global and regional models. One fruitful strategy for evaluating advances in parameterizations has turned out to be using short-range numerical weather prediction as a test-bed within which to implement and improve parameterizations for modeling and predicting climate variability. The global models we have used to date are the CAM atmospheric component of the National Center for Atmospheric Research (NCAR) CCSM climate model as well as the National Centers for Environmental Prediction (NCEP) numerical weather prediction model, thus allowing testing in both climate simulation and numerical weather prediction modes. We present detailed results of these tests, demonstrating the sensitivity of model performance to changes in parameterizations

Penetrative convection in a fluid layer with throughflow

Linear and nonlinear stability analyses of vertical throughflow in a fluid layer, where the density is quadratic in temperature, are studied. To avoid the loss of key terms a weighted functional is used in the energy analysis. Both conditional and unconditional thresholds are derived. When the throughflow is ascending the linear and nonlinear boundaries show substantial agreement. The linear boundary remains close to the conditional nonlinear boundary for descending throughflow, whilst the unconditional threshold begins to diverge. © 2008 Università degli Studi di Napoli "Federico II"