Radar data

"Visual" phenomena such as agile motion, distractions, and occlusions (Rasmussen and Hager 2001) interfere with identification and tracking of radar structures. It is therefore necessary to extract these artifacts from the total set of storm initiation locations before to characterize storm initiation in this area. The study area is a rectangle defined by the geographical coordinates: 41.3ºN and 41.9ºN ; 1.3ºE and 0.3ºW, and located in western Catalonia plains and its westward prolongation. The dimensions of the rectangle are 130 km long, 70 km wide and 9100 km 2. 3. DATA AND METHODOLOGY Main characteristics of the Doppler radar used in this study are given in section 3.1. The other tools used and their role in the identification and characterization of convective structures are given in section 3.2.

Attenuation due to rainfall is one of the most fundamental constraints on the performance of satellite links above 10 GHz. This work presents the results of rain attenuation measurement using radar data collected from MMD and DIDM Malaysia. The results were compared with newly improved ITU-R P530-16 and four other selected tropical rain attenuation prediction models. The statistical analysis showed that ITU-R P 530-16 has significantly addressed the problem of rain attenuation underestimation prediction as presented by older version of the recommendation.

Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts...

This paper describes the methods for extraction and analysis of surface track data for Runway 11 Occupancy Time (ROT). Runway occupancy time (ROT) data is essential to effectively 12 monitor current airport operating efficiencies and to plan for the introduction ...

Attenuation due to rainfall is one of the most fundamental constraints on the performance of satellite links above 10 GHz. This work presents the results of rain attenuation measurement using radar data collected from MMD and DIDM Malaysia. The results were compared with newly improved ITU-R P530-16 and four other selected tropical rain attenuation prediction models. The statistical analysis showed that ITU-R P 530-16 has significantly addressed the problem of rain attenuation underestimation prediction as presented by older version of the recommendation

Short- or mid-term rainfall forecasting is a major task with several environmental applications such as agricultural management or flood risk monitoring. Existing data-driven approaches, especially deep learning models, have shown significant skill at this task, using only rainfall radar images as inputs. In order to determine whether using other meteorological parameters such as wind would improve forecasts, we trained a deep learning model on a fusion of rainfall radar images and wind velocity produced by a weather forecast model. The network was compared to a similar architecture trained only on radar data, to a basic persistence model and to an approach based on optical flow. Our network outperforms by 8% the F1-score calculated for the optical flow on moderate and higher rain events for forecasts at a horizon time of 30 min. Furthermore, it outperforms by 7% the same architecture trained using only rainfall radar images. Merging rain and wind data has also proven to stabilize t...

This paper describes the methods for extraction and analysis of surface track data for Runway 11 Occupancy Time (ROT). Runway occupancy time (ROT) data is essential to effectively 12 monitor current airport operating efficiencies and to plan for the introduction ...

Ponencia presentada en: III Congreso de la Asociación Española de Climatología “El agua y el clima”, celebrado en Palma de Mallorca del 16 al 19 de junio de 2002.[ES]El objetivo de este caso-estudio estriba en la comparación, a los efectos de la estimación del campo de precipitaciones, de un método tradicional basado en la regresión sobre la altitud e interpolación kriging de las anomalías y de un método nuevo en que se efectúa la regresión sobre el dato radar. Se ha seleccionado para la comparación un área alrededor de Madrid, estimándose el campo de precipitaciones totales mensuales de diciembre de 1996. De los errores cuadráticos medios obtenidos por ambos métodos se deduce que la estimación con datos radar mejora ligeramente el método tradicional, y ambos son claramente superiores al krigeado simple de las observaciones.[EN]The objective of this case-study consists in the comparison, for precipitation field estimation purposes, between a traditional method based on a regression ...

The southern North Sea is part of an important flyway for nocturnal bird migration, but is also risky as it stretches over a large surface of water. Selecting nights with suitable weather conditions for migration can be critical for a bird's survival. The aim of this study is to unravel the weather-related bird migration decisions, by providing a descriptive analysis of the synoptic weather conditions over the North Sea on nights with very high and low migration intensities and compare these conditions to the prevailing climatology. For this study, bird radar data were utilized from an offshore wind farm off the Dutch coast, in the North Sea. The study suggests that atmospheric conditions clear of rain and frontal systems, dominated by high pressure systems and tailwinds in spring and sidewinds in autumn are most suitable for nights of intense migration. Differences in temperature, relative humidity and cloud cover appear less significant between intense and low migration nights, suggesting that these variables exert only a secondary role on migration. We discuss how future developments in radar aeroecology and the integration of meteorology can help improve our ability to forecast bird migration.

Performance indexes obtained in idealized
simulated scenarios are the primary source of data for
evaluating different target tracking algorithms in most
researches presented in the literature. Despite the
convenience of simulation, ultimate evaluation of a tracking
algorithm must be made in real scenarios. Unfortunately,
real radar measurements as well as accurate aircraft
position, necessary for calculating tracking errors, are not
easily available. In this paper, we present an evaluation of the
well-known Interacting Multiple-Model with Probabilistic Data
Association Filtering algorithm using data obtained from a flight
inspection of a Brazilian Air Force ground-based long-range
surveillance radar. The presented results show that, in this
scenario the Interacting Multiple-Model with Probabilistic Data
Association Filtering algorithm performance using real data is
worse compared to simulation. Statistical properties of the
real radar measurements are also investigated, and some
evidence is found that embedded noise is not well modeled
as perfectly white.