THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

Emergence: From Chaos to Order by John H. Holland .

A Hydraulic MultiModel Ensemble Framework for Visualizing Flood Inundation Uncertainty

System of systems (SoS) architecting is the process of bringing together and connecting a set of systems so that the collection of the systems, i.e., the SoS is equipped with a set of required capabilities. A system is defined as inflexible in case it contributes to the SoS with all of the capabilities it can provide. On the other hand, a flexible system can collaborate with the SoS architect in the capabilities it will provide. In this study, we formulate and analyze a SoS architecting problem representing a military mission planning problem with inflexible and flexible systems as a multi-objective mixed-integer-linear optimization model. We discuss applications of an exact and an evolutionary method for generating and approximating the Pareto front of this model, respectively. Furthermore, we propose a decomposition approach, which decomposes the problem into smaller sub-problems by adding equality constraints, to improve both the exact and the evolutionary methods. Results from a set of numerical studies suggest that the proposed decomposition approach reduces the computational time for generating the exact Pareto front as well as it reduces the computational time for approximating the Pareto front while not resulting in a worse approximated Pareto front. The proposed decomposition approach can be easily used for different problems with different exact and heuristic methods and thus is a promising tool to improve the computational time of solving multi-objective combinatorial problems. Furthermore, a sample scenario is presented to illustrate the effects of system flexibility.

A multi-objective military system of systems architecting problem with inflexible and flexible systems: formulation and solution methods

: The Weather Research and Forecasting Model (WRF) is a numerical weather prediction model maintained by the National Center for Atmospheric Research (NCAR). The US Army Research Laboratory (ARL) has developed the Weather Running Estimate Nowcast (WRE N) model based on the Weather Research and Forecasting Model Advanced Research WRF (WRF ARW) to predict small-scale phenomena of interest to Warfighters, such as mountain/valley breezes and land/sea breezes. NCAR has developed the Model Evaluation Tools (MET) to evaluate the accuracy of WRF forecasts using observations of meteorological variables. The traditional use of MET calculates model performance over the entire model domain. High-resolution modeling requires more focused verification at subdomain levels. A Geographical Information System (GIS) enables consideration of terrain variables in model assessments using a location-based approach. We discuss our GIS approach to verify WRF-ARW with a 1-kilometer horizontal resolution inner domain centered near San Diego, California. We selected 5 case study days from February and March of 2012. The literature indicated that elevation is strongly correlated with meteorological parameters, which became our focus. We found that elevation accounts for a significant portion of the variance in the model error. The study demonstrated that a GIS can analyze spatially distributed point forecast errors over subdomains, to reveal the dependence of forecast errors on elevation.

Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

: Over the course of the last several years there has been much discussion of a concept called the "system of systems" (SoS), and many proposed definitions that capture features of various SoS. These numerous definitions offer the means to identify SoS; yet, from an analytical point of view, we feel they do not offer the clarity required to construct a well grounded framework to analyze these SoS. Over the course of our research to develop such a framework, we realized that there is another perspective from which to view the notion of a SoS. This perspective, rooted in the analysis of a military SoS, explicitly recognizes three existential concepts present in any military SoS that are also likely present in non-military SoS. The purpose of this report is to highlight these concepts, and relate them to the base of established literature regarding SoS.

/pdf/an-army-centric-system-of-systems-analysis-sosa-definition-3umqa9o8ml.pdf

An Army-Centric System of Systems Analysis (SoSA) Definition

Numerical weather prediction (NWP) models are limited with respect to initial and boundary condition data and possess an incomplete description of underlying physical processes. To account for this, modelers have adopted the method of ensemble prediction to quantify the uncertainty within a model framework; however, the generation of ensemble members requires considerably more computational time and/or resources than a single deterministic simulation, especially at convection-allowing horizontal grid spacings. One approach to solving this issue is the development of both a large and small horizontal grid spacing model framework over the same domain for ensemble and deterministic simulations, respectively. This approach assumes that model grid spacing has no influence on model uncertainty; therefore, the objective of this paper is to quantify the influence of horizontal grid spacing on the statistical spread of NWP model ensembles over a regional domain. A series of 24-h simulations using the Weath...

Defining the Influence of Horizontal Grid Spacing on Ensemble Uncertainty within a Regional Modeling Framework

Intercomparison of 7 Planetary Boundary- Layer/Surface-Layer Physics Schemes over Complex Terrain for Battlefield Situational Awareness

: The Weather Research and Forecasting Model (WRF) is a numerical weather-prediction model that has been used for many applications including My Weather Impacts Decision Aid. WRF is maintained by the National Center for Atmospheric Research, which has developed a suite of Model Evaluation Tools (MET) to evaluate the accuracy of WRF forecasts. In this technical report, we discuss our use of the MET to assess the domain-level errors of the Weather Running Estimate Nowcast (WREN) model. In addition, the domain-level errors were calculated for the Global Forecast System (GFS) model, which is used to initialize the WREN. The output used for this study was generated using 3 different configurations of the WREN, with and without observation assimilation, that were run over 2 different triple-nested domains centered near San Diego, California. We selected 5 case-study days in February March 2012 with varied weather conditions. The results of the study suggest the observation assimilation improves the forecast under certain conditions. The results show the WREN generally performs better than the GFS model with some limitations. More comprehensive verification studies are needed to conclusively determine the value added by varying configurations of the WREN.

/pdf/domain-level-assessment-of-the-weather-running-estimate-khfnfy2jsq.pdf

Jeffrey A. Smith

Papers

Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

An Army-Centric System of Systems Analysis (SoSA) Definition

Defining the Influence of Horizontal Grid Spacing on Ensemble Uncertainty within a Regional Modeling Framework

Intercomparison of 7 Planetary Boundary- Layer/Surface-Layer Physics Schemes over Complex Terrain for Battlefield Situational Awareness

Domain-Level Assessment of the Weather Running Estimate-Nowcast (WREN) Model