Studies in the Atmospheric Sciences

1 Introduction. - 1 Statistics in the Climate and Weather Sciences. - 2 A Guide to this Volume. - 2.1 Chapter Outline. - 2.2 What Is Missing? - 3 Software, Datasets, and the Web Companion. - 2 A Statistical Perspective on Data Assimilation in Numerical Models. - 1 Introduction. - 2 Assimilation and Penalized Least Squares. - 3 Time-Dependent Assimilation Methods. - 3.1 The Kalman Filter. - 4 Ensemble Forecasting. - 4.1 Methodology. - 4.2 Statistical Perspective. - 5 Numerical Studies. - 5.1 Precipitation Model. - 6 Conclusions. - 3 Multivariate Spatial Models. - 1 Introduction. - 1.1 Motivating Example: Ozone and Meteorology. - 1.2 Optimal Spatial Prediction-Kriging. - 1.3 Universal Kriging. - 1.4 Multivariate Approaches. - 2 Cokriging. - 3 Kriging with External Drift. - 3.1 Prediction Variance Misspecification in the KED Model. - 4 A Hierarchical Model. - 5 Miscellaneous Topics. - 5.1 K-Variate Extensions. - 5.2 Latent Process Models. - 5.3 Modeling Orthogonal Contrasts. - 5.4 Multivariate Space-Time Models. - 6 Applications. - 6.1 Modeling Wind Fields. - 6.2 Modeling Temperature Fields. - 7 Conclusions. - 4 Hierarchical Space-Time Dynamic Models. - 1 Introduction. - 1.1 A Brief Review of Space-Time Modeling. - 1.2 Space-Time Dynamic Models. - 2 Hierarchical Space-Time Dynamic Modeling. - 2.1 A General Space-Time Dynamic Model. - 2.2 Reformulated Space-Time Dynamic Model. - 2.3 A Bayesian Model. - 3 Tropical Wind Process. - 3.1 Deterministic View. - 3.2 Stochastic View. - 3.3 Combined Stochastic/Dynamic View. - 3.4 Physically Informative Priors. - 4 Ocean Wind Implementation. - 4.1 Results. - 5 Discussion. - 5 Experimental Design for Spatial and Adaptive Observations. - 1 Introduction. - 1.1 Scientific Background. - 1.2 Overview of Statistical Design. - 2 Experimental Design: Spatial Fields. - 2.1 Optimal Design. - 2.2 Special Solutions. - 2.3 Greedy Algorithms. - 3 Experimental Design in Space-Time. - 4 Discussion. - 6 Seasonal Variation in Stratospheric Ozone Levels, a Functional Data Analysis Study. - 1 Introduction. - 2 Stratospheric Ozone Data. - 3 Principal Component Analysis. - 3.1 Principal Component Analysis of the Interpolated Profiles. - 4 Continuous Basis Functions to Represent Ozone. - 4.1 Basis Function Coefficients. - 5 Varying Coefficient Models. - 6 Discussion. - 7 Neural Networks: Cloud Parameterizations. - 1 Introduction. - 1.1 The Essence of Parameterization. - 1.2 Neural Networks and Fitting Nonlinear Models. - 2 Cloud Parameterizations. - 2.1 A Preliminary Model. - 2.2 Toward a GCM Cloud Parameterization. - 3 Simulation of Cloud Cover. - 4 Conclusions and Future Work. - 8 Exploratory Statistical Analysis of Tropical Oceanic Convection Using Discrete Wavelet Transforms. - 1 Introduction. - 1.1 Atmospheric Motivation. - 1.2 Statistical Motivation. - 1.3 Objectives. - 2 Description of the Dataset. - 2.1 Cloud System Regimes. - 3 Discrete Wavelets. - 3.1 Wavelets in One Dimension. - 3.2 Discrete Wavelet Transform in Two Dimensions. - 4 Statistical Study of Cloud Systems. - 4.1 Detecting Squall-Lines. - 4.2 The Orientation Problem. - 4.3 Examples. - 4.4 Identifying the Scattered Cloud Regime. - 5 Conclusions and Future Work. - 9 Predicting Clear-Air Turbulence. - 1 Introduction. - 2 Indices Derived from the RUC-60 Model. - 3 Data Structure. - 4 The Single Index Approach. - 5 Modeling Strategy. - 5.1 MARS. - 5.2 FDA. - 5.3 FDA + MARS Algorithm. - 6 Implementing FDA + MARS for CAT Forecast. - 6.1 Training the Procedure: In-Sample Performances. - 6.2 Testing the Procedure: Prediction Ability. - 7 MARS as Variable Subset Selection. - 8 Conclusions. - 10 Spatial Structure of the SeaWiFS Ocean Color Data for the North Atlantic Ocean. - 1 Introduction. - 2 SeaWiFS Ocean Color Data. - 3 Semivariograms and Other Tools in Spatial Statistics. - 3.1 Stationarity and Isotropy. - 3.2 Estimating the Empirical Semivariogram. - 3.3 Semivariogram Parameters: Nugget, Sill, and Range. - 3.4 Some Isotropic Semivariogram Models. - 4 Ocean Color Semivariograms. - 4.1 Spatial Analysis for the Ocean Chlorophyll. - 4.2 Semivariograms in the Original Scale. - 4.3 Effect of Sampling Resolution. - 5 Spatial Patterns for the North Atlantic Ocean. - 6 Conclusions and Final Remarks. - References.