Journals

An Efficient, General-Purpose Technique for Identifying Storm Cells in Geospatial Images (J. Oceanic and Atmos. Tech.)

In (1), an efficient sequential morphological technique called the watershed transform is adapted and extended so that it can be used for identifying storms. The parameters available in the technique and the effect of these parameters are also explained.

The method is demonstrated on different types of geospatial radar and satellite images. Pointers are provided on the effective choice of parameters to target the resolutions, data quality constraints and dynamic range found in observational datasets.

[ read (pdf) online ].

Support Vector Machines for Spatiotemporal Tornado Prediction (Int'l J. of General Systems)

In (2), we extend our earlier study (published in IJCNN) to use a set of 33 storm days and demonstrate that it is possible to create a principled estimate of the probability of a tornado at a particular location within a circumscribed time window. The use of support vector machines for predicting the location and time of tornadoes is presented. We utilize a least-squares methodology to estimate shear, quality control of radar reflectivity, morphological image processing to estimate gradients, fuzzy logic to generate compact measures of tornado possibility and support vector machine classification to generate the final spatiotemporal probability field. On the independent test set, this method achieves a Heidke Skill Score (HSS) of 0.60 and a Critical Success Index (CSI) of 0.45.

[ read (pdf) online ].

The Warning Decision Support System - Integrated Information (Weather and Forecasting)

In (3), we lay out the case for multi-radar, multi-sensor weather applications, describe the WDSS-II framework and briefly touch upon many of the WDSS-II applications including the display. This is the paper to cite if you wish to cite WDSS-II from your research papers. [ read (pdf) online ].

An Automated Technique to Quality Control Radar Reflectivity Data (J. Applied Meteorology)

In (4), we describe an automated technique to perform quality control on WSR-88D reflectivity data.In this paper, we use a neural network to combine the individual features, some of which have already been proposed in the literature and some of which we introduce in this paper, into a single discriminator that can distinguish between ``good'' and ``bad'' echoes. The gate-by-gate discrimination provided by the neural network is followed by more holistic post-processing based on spatial contiguity constraints and object identification to yield quality-controlled radar reflectivity scans that have most of the bad echo removed, while leaving most of the good echo untouched.

The quality control algorithm described in this paper is compared against the quality control algorithm currently used in operations on the NEXRAD Radar Products Generator. A possible multi-sensor extension to this technique is demonstrated.

Cite this paper to cite w2qcnn

[ read (pdf) online ].

Fuzzy Rule-Based Approach for Detection of Bounded Weak-Echo Regions in Radar Images (J. Appl. Meteo. Clim. 2006)

In (5), A method for the detection of a bounded weak-echo region (BWER) within a storm structure that can help in the prediction of severe weather phenomena is presented. A fuzzy rule-based approach that takes care of the various uncertainties associated with a radar image containing a BWER has been adopted. The proposed technique automatically finds some interpretable (fuzzy) rules for classification of radar data related to BWER. The radar images are preprocessed to find subregions (or segments) that are suspected candidates for BWERs. Each such segment is classified into one of three possible cases: strong BWER, marginal BWER, or no BWER. In this regard, spatial properties of the data are being explored. The method has been tested on a large volume of data that are different from the training set, and the performance is found to be very satisfactory. It is also demonstrated that an interpretation of the linguistic rules extracted by the system described herein can provide important characteristics about the underlying process.

[ read (pdf) online at AMS website].

A Real-Time, Three Dimensional, Rapidly Updating, Heterogeneous Radar Merger Technique for Reflectivity, Velocity and Derived Products (Weather and Forecasting)

In (6), we describe a technique for taking the base radar data, and derived products, from multiple radars and combining them in real-time into a rapidly updating 3D merged grid such that an estimate of that radar product combined from all the different radars can extracted from these agents at any time. We describe the model for the intelligent agents so as to account for the varying radar beam geometry with range, vertical gaps between radar scans, lack of time synchronization between radars, varying beam resolutions between different types of radars, beam blockage due to terrain, differing radar calibration and inaccurate time stamps on radar data.

Further, we describe techniques for merging scalar products like reflectivity as well as innovative, real-time techniques for combining velocity and velocity-derived products. We also describe precomputation techniques that can be utilized such that users can select a domain and start seeing three-dimensional, combined radar data over that domain in a matter of minutes. Finally, we also give pointers on derived products that can be computed from these three-dimensional merger grids.

Cite this paper to cite w2merger

[ read (pdf) online ].

A Separable Filter for Directional Smoothing (IEEE Trans. on Geosciences Letters)

We develop a directional filter that is separable (7). A directional filter allows you to smooth an image without degrading edges. A separable filter is computationally efficient, but allows you to do logical operations on the pixels (such as checking for missing data). The separable filter is demonstrated on radar imagery. [ read (pdf) online ].

Cite this paper to cite w2smooth

Multiscale Storm Identification and Forecast (J. Atmos. Research)

We describe a method (8) of multiscale storm identification, computing motion estimates and making short range forecasts from radar and satellite images. [ read (pdf) online ].

Cite this paper to cite w2segmotionll/w2segmotioncg

Speeding up a Large Scale Filter (J. Tech.)

In (9), I show how to speed up an elliptically-shaped filter so that the filtering process can be carried out in real-time. The trade-offs that this involves, including avoiding operations that are non-linear in the initial stages are described. [ read (html) online ]. This method can not deal with missing data. The fast method in (7) can.

Using a Genetic Algorithm to tune a Bounded Weak Echo Region Algorithm (J. Appl. Meteo. )

In (10), I describe how to set up a weather detection algorithm so that it is possible to tune that algorithm as more and more cases get verified. I also discuss the possibility of being able to tune an algorithm to the local climatology. I demonstrate this method on the BWER detection algorithm and describe the genetic algorithm that can make all this possible. [ read (html) online ].

On the Uniqueness of Gandin and Murphy's Equitable Performance Measures (M. Weather Rev.)

Gandin and Murphy showed that a measure they called the True Skill Score is unique in a property they call equitability. In (11), we show that it is impossible to come up with any measure that is ``equitable'' (infact, any measure that involves constraints of the form posed by equitability) without making some rather daring assumptions.

A Fuzzy Logic Approach to Detecting Severe Updrafts (AI Appl.)

The May issue of AI Applications carried this (12) comprehensive paper on the fuzzy logic scheme to detect Bounded Weak Echo Regions (BWERs) in radar images. [ read (html) online ].