In this cumulative dissertation, different features and methods are presented to assess and process multi-sensor derived radar data for climatological analysis. The overall objectives were to appraise the limitations of an hourly radar-based quantitative precipitation estimate (QPE) product and to develop and apply reasonable approaches to process these data. Hence the spatial and temporal limitations of radar-derived precipitation rates are discussed in the context of climatological applications, and two types of climatologies are obtained, first a climatology of daily precipitation fields and second a long term precipitation climatology. These relate to questions concerning the methodologies rather than climatological significance or assessment of precipitation and its role in the water balance. Current radar data availability limits such a hydro-climatic analysis. The thesis consists of three peer-reviewed publications. All investigations in this thesis are based on the RADOLAN rw-product of the German Weather Service (DWD) for an extended study region including the Free State of Saxony, Germany, for the period from April 2004 to November 2011. The first publication is dedicated to the classification of daily precipitation fields by unsupervised neural networks. In the presented work, the quality of the radar-derived precipitation rates is analysed by a temporal comparison between recording and non-recording gauges and the corresponding pixels of the RADOLAN rw-product on hourly and daily bases. The analysis shows that a temporal aggregation of the original product should be limited to a temporal scale up to 24 h because of the processing algorithms and the reappearance of previously suppressed errors. Nevertheless, an unsupervised neural network was successfully used for the classification of daily patterns. The derived daily precipitation classes and corresponding precipitation patterns could be assigned to properties of the associated weather patterns and seasonal dependencies. Hence, it could be shown that the classified patterns not only occurred by chance but by statistically proven properties of the atmosphere and of the season. The second publication is primarily concerned with two tasks: first, the pixel-wise fitting of mixture distributions on the bases of the obtained patterns from the first publication, and second, the analysis of spatial consistency of the radar-derived precipitation data set. The fitted parametric distribution functions were analysed in terms of Akaike\'s information criterion and the Kolmogorov-Smirnov test. These benchmarks showed, that the performances are best for mixture distributions derived by an initial classification by an unsupervised neural network and cluster analysis, and by gamma distributions. These results underline the significance of the derived precipitation classes obtained in the first publication. Furthermore, the Kolmogorov-Smirnov test indicates that independent of the distribution function, the radar-derived daily precipitation rates under the assumption of the deployed parametric distribution function has the best or most natural order of precipitation rates at spatial scales from 2 to 4 km for daily precipitation fields. Thus, it is recommended to use the original radar product at these scales rather than at 1 km resolution for daily precipitation sums. In the last publication, the focus shifts from daily to long-term precipitation climatology. The work introduces a rapid and simple approach for processing radar-derived precipitation rates for long-term climatologies. The method could successfully be applied to the radar-derived precipitation rates by excluding or correcting the errors that reappear due to temporal aggregation. Despite the fact that the approach is empirical, the introduced parameters could almost be objectively derived by means of simulation and optimisation. This could be achieved by utilising the reasonable relationship between elevation and precipitation rates for longer periods. Finally, the obtained results are compared to two independently derived precipitation data sets. The comparison shows good agreement of the precipitation fields and illustrates a reasonable application of the introduced procedure. The presented results support the application of the approach for precipitation aggregates of, at least, annual or longer periods. However the derivation of climatologies led to satisfactory results at the respective temporal scales, though the influence of radar-specific errors can only be minimized to a certain degree. Further studies have to prove if an application independent processing of radar-derived precipitation rates leads to higher qualities and validities of the derived data in time and space.

Made available in DSpace on 2014-06-11T19:31:37Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-06-29Bitstream added on 2014-06-13T19:02:02Z : No. of bitstreams: 1 held_amg_dr_botfca.pdf: 4163192 bytes, checksum: db80ee83ff94cbb037cbf6cd62d8a9f0 (MD5) / Foi realizada uma análise para se obter a caracterização das tempestades sob o aspecto climatológico para a área central do Estado de São Paulo cujos parâmetros foram obtidos com o software TITAN, desenvolvido no NCAR e implementado nos computadores do IPMet. Os parâmetros que caracterizam as propriedades das tempestades tais como volume médio, área média, altura dos topos dos ecos, refletividade máxima e média bem como velocidade e deslocamento dos sistemas precipitantes foram determinados considerando o limiar de refletividade>30 dBZ, e volume>30 km3. A distribuição espacial de parâmetros tais como volume médio, área média, refletividade média e máxima mostrou, pela primeira vez para a área central do Estado de São Paulo, como os mesmos se distribuíram pela área monitorada pelo radar de Bauru e também a existência de regiões preferenciais onde se concentra a maior atividade convectiva, durante os verões analisados. Todas as varreduras observadas pelo radar de Bauru foram também processadas para se determinar as áreas de tempestades definidas pelo limiar de refletividade maior que 25 dBZ, para a partir daí obter a integração dessas áreas para o tempo de duração de cada tempestade e calcular a IAT, que é a integral área-tempo. O método da Integral-Área-Tempo (IAT), para se medir precipitação volumétrica baseada na informação de cobertura da precipitação em área foi aplicado aos dados de radar meteorológico de Bauru, para dois períodos de verão, o de 1998-1999 e 1999-2000. A premissa de que a porção crescente do conglomerado convectivo seria suficiente para calcular uma IAT que ainda seria altamente correlacionada com o volume total de chuva resultando, portanto numa técnica para o nowcasting é testada e verificada para os dois períodos analisados. Os resultados das análises mostraram que as células de tempestade... / A climatological characterization of storm properties during two summer seasons, viz. 1998-1999 and 1999-2000, based on observations from the Bauru S-band Doppler radar, was obtained with the TITAN Software of NCAR, implemented at IPMet. Parameters, such as mean volume, mean area, mean and maximum echo tops, mean and maximum reflectivity, as well as speed and direction of precipitating systems were determined using the reflectivity> 30 dBZ and a volume> 30 km3 as a threshold for storm identification. The spatial distribution for parameters such as mean volume, mean area, mean and maximum reflectivity, mean and maximum echo top, etc, were determined for the first time in the central State of São Paulo, based on radar data information. It has shown some preferential areas where most of the convective activity was concentrated during the study period. The Area Time-Integration (ATI) method was then applied to these observations using the 25 dBZ thresholds, to determine the rainfall volume in the central area of the State of São Paulo, taking into account the entire lifetime of all observed storms that exceeded the threshold considered. Furthermore, it was also investigated, if it would be possible to estimate the ATIs only for the growth period of a convective storm and still obtain a good correlation. This method could then be applied to obtain the total rain volume of a convective system at the stage of its maximum development, which could be considered as a nowcasting tool to be explored in subsequent studies. The time span for the storms reaching their maximum area was found to be about 2 hours on average and this was reached within...(Complete abstract, click electronic access below)

In this cumulative dissertation, different features and methods are presented to assess and process multi-sensor derived radar data for climatological analysis. The overall objectives were to appraise the limitations of an hourly radar-based quantitative precipitation estimate (QPE) product and to develop and apply reasonable approaches to process these data. Hence the spatial and temporal limitations of radar-derived precipitation rates are discussed in the context of climatological applications, and two types of climatologies are obtained, first a climatology of daily precipitation fields and second a long term precipitation climatology. These relate to questions concerning the methodologies rather than climatological significance or assessment of precipitation and its role in the water balance. Current radar data availability limits such a hydro-climatic analysis. The thesis consists of three peer-reviewed publications. All investigations in this thesis are based on the RADOLAN rw-product of the German Weather Service (DWD) for an extended study region including the Free State of Saxony, Germany, for the period from April 2004 to November 2011. The first publication is dedicated to the classification of daily precipitation fields by unsupervised neural networks. In the presented work, the quality of the radar-derived precipitation rates is analysed by a temporal comparison between recording and non-recording gauges and the corresponding pixels of the RADOLAN rw-product on hourly and daily bases. The analysis shows that a temporal aggregation of the original product should be limited to a temporal scale up to 24 h because of the processing algorithms and the reappearance of previously suppressed errors. Nevertheless, an unsupervised neural network was successfully used for the classification of daily patterns. The derived daily precipitation classes and corresponding precipitation patterns could be assigned to properties of the associated weather patterns and seasonal dependencies. Hence, it could be shown that the classified patterns not only occurred by chance but by statistically proven properties of the atmosphere and of the season. The second publication is primarily concerned with two tasks: first, the pixel-wise fitting of mixture distributions on the bases of the obtained patterns from the first publication, and second, the analysis of spatial consistency of the radar-derived precipitation data set. The fitted parametric distribution functions were analysed in terms of Akaike\'s information criterion and the Kolmogorov-Smirnov test. These benchmarks showed, that the performances are best for mixture distributions derived by an initial classification by an unsupervised neural network and cluster analysis, and by gamma distributions. These results underline the significance of the derived precipitation classes obtained in the first publication. Furthermore, the Kolmogorov-Smirnov test indicates that independent of the distribution function, the radar-derived daily precipitation rates under the assumption of the deployed parametric distribution function has the best or most natural order of precipitation rates at spatial scales from 2 to 4 km for daily precipitation fields. Thus, it is recommended to use the original radar product at these scales rather than at 1 km resolution for daily precipitation sums. In the last publication, the focus shifts from daily to long-term precipitation climatology. The work introduces a rapid and simple approach for processing radar-derived precipitation rates for long-term climatologies. The method could successfully be applied to the radar-derived precipitation rates by excluding or correcting the errors that reappear due to temporal aggregation. Despite the fact that the approach is empirical, the introduced parameters could almost be objectively derived by means of simulation and optimisation. This could be achieved by utilising the reasonable relationship between elevation and precipitation rates for longer periods. Finally, the obtained results are compared to two independently derived precipitation data sets. The comparison shows good agreement of the precipitation fields and illustrates a reasonable application of the introduced procedure. The presented results support the application of the approach for precipitation aggregates of, at least, annual or longer periods. However the derivation of climatologies led to satisfactory results at the respective temporal scales, though the influence of radar-specific errors can only be minimized to a certain degree. Further studies have to prove if an application independent processing of radar-derived precipitation rates leads to higher qualities and validities of the derived data in time and space.

Orientador: João Francisco Escobedo / Banca: Roberto Vicente Calheiros / Banca: Jonas Teixeira Nery / Banca: Luci Hidalgo Nunes / Banca: Oswaldo Massambani / Resumo: Foi realizada uma análise para se obter a caracterização das tempestades sob o aspecto climatológico para a área central do Estado de São Paulo cujos parâmetros foram obtidos com o software TITAN, desenvolvido no NCAR e implementado nos computadores do IPMet. Os parâmetros que caracterizam as propriedades das tempestades tais como volume médio, área média, altura dos topos dos ecos, refletividade máxima e média bem como velocidade e deslocamento dos sistemas precipitantes foram determinados considerando o limiar de refletividade>30 dBZ, e volume>30 km3. A distribuição espacial de parâmetros tais como volume médio, área média, refletividade média e máxima mostrou, pela primeira vez para a área central do Estado de São Paulo, como os mesmos se distribuíram pela área monitorada pelo radar de Bauru e também a existência de regiões preferenciais onde se concentra a maior atividade convectiva, durante os verões analisados. Todas as varreduras observadas pelo radar de Bauru foram também processadas para se determinar as áreas de tempestades definidas pelo limiar de refletividade maior que 25 dBZ, para a partir daí obter a integração dessas áreas para o tempo de duração de cada tempestade e calcular a IAT, que é a integral área-tempo. O método da Integral-Área-Tempo (IAT), para se medir precipitação volumétrica baseada na informação de cobertura da precipitação em área foi aplicado aos dados de radar meteorológico de Bauru, para dois períodos de verão, o de 1998-1999 e 1999-2000. A premissa de que a porção crescente do conglomerado convectivo seria suficiente para calcular uma IAT que ainda seria altamente correlacionada com o volume total de chuva resultando, portanto numa técnica para o nowcasting é testada e verificada para os dois períodos analisados. Os resultados das análises mostraram que as células de tempestade...(Resumo completo, clicar acesso eletrônico abaixo) / Abstract: A climatological characterization of storm properties during two summer seasons, viz. 1998-1999 and 1999-2000, based on observations from the Bauru S-band Doppler radar, was obtained with the TITAN Software of NCAR, implemented at IPMet. Parameters, such as mean volume, mean area, mean and maximum echo tops, mean and maximum reflectivity, as well as speed and direction of precipitating systems were determined using the reflectivity> 30 dBZ and a volume> 30 km3 as a threshold for storm identification. The spatial distribution for parameters such as mean volume, mean area, mean and maximum reflectivity, mean and maximum echo top, etc, were determined for the first time in the central State of São Paulo, based on radar data information. It has shown some preferential areas where most of the convective activity was concentrated during the study period. The Area Time-Integration (ATI) method was then applied to these observations using the 25 dBZ thresholds, to determine the rainfall volume in the central area of the State of São Paulo, taking into account the entire lifetime of all observed storms that exceeded the threshold considered. Furthermore, it was also investigated, if it would be possible to estimate the ATIs only for the growth period of a convective storm and still obtain a good correlation. This method could then be applied to obtain the total rain volume of a convective system at the stage of its maximum development, which could be considered as a nowcasting tool to be explored in subsequent studies. The time span for the storms reaching their maximum area was found to be about 2 hours on average and this was reached within...(Complete abstract, click electronic access below) / Doutor