CARPE DIEM
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Picture 1: Distribution of data points of a thunderstorm in the Entropy-Alpha plane derived from a time series measured with POLDIRAD on 2nd November 2005 |
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Picture 2: Range-height plot of the thunderstorm in the previous image with high reflectivity values. The colours represent volume scattering in dBZ as shown in the colour scale |
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Picture 3: Classification of hydrometeors for the thunderstorm shown in the previous figures. Dark green denotes light rain, lighter greens transition to heavy rain, cyan and blue is assumed to be very heavy rain, whereas purple, pink and red denote highly anisotropic scattering from very heavy rain mixed with sleet and/or hail |
In the framework of the European project CARPE DIEM (
anagement) several work packages with regard to polarimetric techniques have been investigated. The project contributed to the Energy, Environment and Sustainable Development Programme for Research, Technology Development and Demonstration under the fifth Framework Programme with the goal of improving flood forecasting capabilities. The Institute’s tasks comprised the exploitation of advanced radar capabilities to allow the enhanced assimilation of weather radar data from operational networks in hydrological and numerical weather prediction models. As the data source, the coherent and fully polarimetric C-band weather radar POLDIRAD was used.
The first task dealt with the use of polarimetric measurements to estimate effects of variation in drop-size distributions on the uncertainty inherent in rainfall estimates collected at different spatial and temporal scales. The parameters particularly taken into account are the differential reflectivity and phase, which occur due to the oblate nature of rain drops. The outcome was that the differential phase could potentially still provide a more accurate estimate of the average rainfall across an area (or equivalently from a series of rapid scans averaged over a period of time).
The second task was dedicated to the problem that there is a significant lack of "ground truth" for weather radar observations, i.e. the scattering particles are usually pretty much unknown or have to be guessed by using empirical methods (mostly based on fuzzy logic classification).
Polarimetry has the great advantage that the scattering can be related to the physics without
a priori or empirical knowledge. Hence, Entropy-Alpha decomposition and classification (originally used for land classification in SAR imaging) has been used in order to identify different types of hydrometeors. The most important premise for a precise decomposition is the correction of differential propagation errors, which can only be performed on time series (raw) data. This type of data is usually not available, but POLDIRAD is now able to deliver also the required time series. Picture 1 shows a typical distribution of Entropy-Alpha values in the case of a thunderstorm, which provides a broad variation of scatterers (light rain, heavy rain, hail, sleet, snow). Using this distribution and an additional weighting with reflectivity values, a classification scheme could be compiled.
In Picture 2 and 3 , the reflectivity can be compared with the classification result. The first impression is that this purely physically derived result is very promising, although a comparison with common techniques has still to be performed and will be part of future activities. The method could not only improve the ability to extract weather information from terrestrial radars, but also from radars on airborne and spaceborne platforms.
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