Journals

A Gaussian Mixture Model Approach to Forecast Verification (Weather and Forecasting)

In (1), we introduce a new approach in which the observed and forecast fields are broken down into a mixture of Gaussians and the parameters of the Gaussian Mixture Model fit are examined to identify translation, rotation and scaling errors. We discuss the advantages of this method in terms of the traditional filtering or object-based methods and interpret resulting scores on a standard verification dataset.

[ read (pdf) online ].

An Objective Method of Evaluating and Devising Storm Tracking Algorithms (Weather and Forecasting)

In (2), we introduce a set of easily computable bulk statistics that can be used to directly evaluate the performance of tracking algorithms on specific characteristics. We apply the evaluation method to a diverse set of radar reflectivity data cases and note the characteristic behavior of five different storm tracking algorithms proposed in the literature and now employed in widely used nowcasting systems. Based on this objective evaluation, we devise a storm tracking algorithm that performs consistently and better than any of the previously suggested techniques.

[ read (pdf) online ].

Reaching Scientific Consensus Through A Competition (Bull. of Amer. Meteo. Soc.)

In (3), we describe the AI competition that we (members of the STAC commitee for AI in the American Meteo. Society) have been conducting for the past two years and what we learned in each year.

[ read (pdf) online ].

Real-time, rapidly updating severe weather products for virtual globes (Computers and Geoscience)

In (4), we demonstrate that the availability of standards for the specification and transport of virtual globe data products has made it possible to generate spatially precise, geo-referenced images and to distribute these centrally-created products via a web server to a wide audience.

In this paper, we describe the data and methods for enabling severe weather threat analysis information inside a KML framework. The method of creating severe weather diagnosis products that are generated and translating them to KML and image files is described. We illustrate some of the practical applications of these data when they are integrated into a virtual globe display. The availability of standards for interoperable virtual globe clients has not completely alleviated the need for custom solutions. We conclude by pointing out several of the limitations of the general-purpose virtual globe clients currently available.

[ read (pdf) online ].

Doppler Radar based Nowcasting of Cyclone Ogni (J. Earth System Science)

In (5), we describe offline analysis of Indian Doppler radar data from Cyclone Ogni using a suite of radar algorithms as implemented on NEXRAD and advanced algorithms developed jointly by the National Severe Storms Laboratory (NSSL) and the University of Oklahoma. We demonstrate the applicability of the various algorithms to Indian radar data, the improvement in the quality of the data and evaluate the benefit of nowcasting capabilities in Indian conditions using this data. New information about the tropical cyclone structure, as derived from application of the algorithms is also discussed in this study. Finally, we suggest improvements that could be made to the Indian data collection strategies, networking and realtime analysis. Since this is a first study of its kind to utilize doppler radar data in a tropical climate, the recommendations on realtime analysis and data collection strategies that we make, would in many cases, be beneficial to other countries embarking on Doppler radar network modernization programs.

[ read (pdf) online ].

A Technique to Censor Biological Echoes in Radar Reflectivity Data (J. Appl. Meteo.)

In (6), we describe a technique that identifies candidate bloom based on the range-variance of reflectivity in areas of bloom, and uses the global, rather than local, characteristic of the echo to discriminate between bloom and wide-spread rain. Every range gate is assigned a probability that it corresponds to bloom using morphological operations and a neural network is trained using this probability as one of the input features. We demonstrate that this technique is capable of identifying and removing echoes due to biological targets and other types of artifacts while retaining echoes that correspond to precipitation.

[ read (pdf) online ].

Data Mining Storm Attributes from Spatial Grids (J. Oceanic and Atmos. Tech.)

In (7), a technique to identify storms and capture scalar features within the geographic and temporal extent of the identified storms is described. The identification technique relies on clustering grid points in an observation field to find self-similar and spatially coherent clusters that meet the traditional understanding of what storms are. From these storms, geometric, spatial and temporal features can be extracted. These scalar features can then be data mined to answer many types of research questions in an objective, data-driven manner. This is illustrated by using the technique to answer questions of forecaster skill and lightning predictability.

[ read (pdf) online ].

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

In (8), 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 (9), 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 (10), 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 (11), 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 (12), 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 (13), 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 (14). 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 (15) 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 (16), 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 (14) can.

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

In (17), 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 (18), 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 (19) comprehensive paper on the fuzzy logic scheme to detect Bounded Weak Echo Regions (BWERs) in radar images. [ read (html) online ].