<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The paper is focused on the processing of 3D weather radar data to minimize the impact of a number of errors from different sources, both meteorological and non-meteorological. The data is also quantitatively characterized in terms of its quality. A set of dedicated algorithms based on analysis of the reflectivity field pattern is described. All the developed algorithms were tested on data from the Polish radar network POLRAD. Quality control plays a key role in avoiding the introduction of incorrect information into applications using radar data. One of the quality control methods is radar data assimilation in numerical weather prediction models to estimate initial conditions of the atmosphere. The study shows an experiment with quality controlled radar data assimilation in the COAMPS model using the ensemble Kalman filter technique. The analysis proved the potential of radar data for such applications; however, further investigations will be indispensable.</p></abstract>

The paper is focused on the processing of 3D weather radar data to minimize the impact of a number of errors from different sources, both meteorological and non-meteorological. The data is also quantitatively characterized in terms of its quality. A set of dedicated algorithms based on analysis of the reflectivity field pattern is described. All the developed algorithms were tested on data from the Polish radar network POLRAD. Quality control plays a key role in avoiding the introduction of incorrect information into applications using radar data. One of the quality control methods is radar data assimilation in numerical weather prediction models to estimate initial conditions of the atmosphere. The study shows an experiment with quality controlled radar data assimilation in the COAMPS model using the ensemble Kalman filter technique. The analysis proved the potential of radar data for such applications; however, further investigations will be indispensable.

Processing of 3D Weather Radar Data with Application for Assimilation in the NWP Model

Department of Ground Based Remote Sensing Institute of Meteorology and Water Management National Research Institute

Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw

Miscellanea Geographica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The paper is focused on the processing of 3D weather radar data to minimize the impact of a number of errors from different sources, both meteorological and...

Processing of 3D Weather Radar Data with Application for Assimilation in the NWP Model

Publié en ligne: 30 sept. 2014

Pages: 31 - 39

Reçu: 10 févr. 2014

Accepté: 30 avr. 2014

DOI: https://doi.org/10.2478/mgrsd-2014-0023

Mots clés
Weather radar, radar refectivity, data quality, data assimilation

© 2014 Katarzyna Ośródka et. al.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Processing of 3D Weather Radar Data with Application for Assimilation in the NWP Model

Publié en ligne: 30 sept. 2014

Pages: 31 - 39

Reçu: 10 févr. 2014

Accepté: 30 avr. 2014

DOI: https://doi.org/10.2478/mgrsd-2014-0023

Mots clésWeather radar, radar refectivity, data quality, data assimilation

© 2014 Katarzyna Ośródka et. al.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Weather radar, radar refectivity, data quality, data assimilation