This study aims to present an encouraging example of prediction of super cyclone Gonu over the northern Indian Ocean in 2007. A series of experiments are conducted using the advanced Weather Research and Forecasting model with three-dimensional variational method to assimilate GPS RO...

The center for Analysis and Prediction of Storms (CAPS) has developed a radar data assimilation system. The system consists of several principal components: (1) a program that quality-controls and remaps (or super-ob) radar data to the analysis grid, (2) a Bratseth analysis method (ADAS), or a...

While qualitative information from meteorological satellites has long been recognized as critical for monitoring weather events such as tropical cyclone activity, quantitative data are required to improve the numerical prediction of these events. In this paper, the sea surface winds from...

Analyzing the risks of anthropogenic climate change requires sound probabilistic projections of CO2 emissions. Previous projections have broken important new ground, but many rely on out-of-range projections, are limited to the 21st century, or provide only implicit probabilistic information....

The performance of the ensemble Kalman filter (EnKF) in forced, dissipativeflow under imperfect model conditions is investigated through simultaneous state andparameter estimation where the source of model error is the uncertainty in the modelparameters. Two numerical models with increasing...

The main goal of my research is to improve the performance of the EnKF in assimilating real observations in order to accelerate the development of EnKF systems towards operational applications. A Local Ensemble Transform Kalman Filter (LETKF, Hunt et al. 2007) is used as an efficient...

Analyzing the risks of anthropogenic climate change requires sound probabilistic projections of CO2 emissions. Previous projections have broken important new ground, but many rely on out-of-range projections, are limited to the 21st century, or provide only implicit probabilistic information....

The atmospheric motion vectors (AMVs) retrieved from geostationary satellites are recognized as one of the important inputs for numerical weather prediction models to improve the tropical cyclone (TC) forecast. In this study, the weather research and forecasting (WRF) model, WRF...

We discuss a new class of spatially varying, simultaneous autoregressive (SVSAR) models motivated by interests in flexible, non-stationary spatial modelling scalable to higher dimensions. SVSAR models are hierarchical Markov random fields extending traditional SAR models. We develop Bayesian...

In this paper a method is presented which allows for estimation of the location and rate of an unknown point stationary source of passive atmospheric pollutant in a complex urban geometry. The variational formulation is used in which the cost function characterizing difference of the calculated...