This work is dealing with regional climate models. Firstly, their principle and use of them is described, including advantages and disadvantages of this approach. Further, the application of WRF numerical weather prediction model in climate mode is described and differences in use of CLWRF modification and its advantages for getting results are discussed. Possibilities of this implementation and testing runs for finding appropriate settings are presented. Finally, the results of one ten-year and four five-year simulations of model with different settings are compared with observed values. Some chapters are dedicated to possibilities of processing and graphics outputs of model results and discussion.

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-08-15T19:02:39Z No. of bitstreams: 1 RAFAEL CASTELO GUEDES MARTINS – TESE (PPGMet) 2014.pdf: 3362803 bytes, checksum: 5a99c28e73f6a95fef76f82f96d2edc4 (MD5) / Made available in DSpace on 2018-08-15T19:02:39Z (GMT). No. of bitstreams: 1 RAFAEL CASTELO GUEDES MARTINS – TESE (PPGMet) 2014.pdf: 3362803 bytes, checksum: 5a99c28e73f6a95fef76f82f96d2edc4 (MD5) Previous issue date: 2014-12-12 / Um dos principais desafios atuais da modelagem numérica da atmosfera trata da previsão quantitativa da precipitação e do posicionamento das nuvens de chuva. Este trabalho tem com o principal objetivo avaliar o desempenho das arametrizações de microfísicas na modelagem regional com ênfase no papel da informação de grande escala e sua influência sobre as simulações, e no uso de dados observados de radiossondagens como forma de acrescentar informação à modelagem . Inicialmente, duas reanálises (NCEP2 e ERAI) foram estatisticamente comparadas com dados de PCDs do Estado do Ceará. Verificou - se qu e a ERAI apresentou maior semelhança com as observações, principalmente para as variáveis diretamente ligadas à convecção. Em seguida, a ERAI foi utilizada como forçamento de grande escala em simulações com o modelo WRF. Observou- se que o uso de microfísica detalhada não melhora necessariamente a previsão do modelo, caso não sejam utilizados dados observados no local de estudo. Por último, duas simulações de alta resolução foram realizadas. Uma forçada pela reanálise sem modificação e outra forçada pela reanálise modificada utilizando o método de análise objetiva do WRF, para incluir as séries temporais de radiossondagens coletadas durante campanha experimental do Projeto CHUVA, em Fortaleza- CE. As duas simulações foram comparadas com dados observados pelo radiômetro para o mesmo local e período das radiossondagens . Observou - se que a inclusão das observações de sondagens na modelagem possibilita melhor modelagem de um sistema convectivo ocorrido em abril de 2011, principalmente para as variáveis ligadas à convecção. Este trabalho aponta, utilizando análises comparativas e estatísticas, que a utilização de uma maior densidade de dados observacionais válidos no modelo pode melhorar de forma muito mais eficiente o resultado da modelagem, do que mesmo a utilização do downscaling dinâmico do dado de grande escala ou a utilização de esquemas de microfísica detalhada, que, em algumas situações, pode inclusive inserir mais erros nos sistema s modelados. / The quantitative prediction of precipitation and the positioning of the rain clouds is one of the main challenges of numerical modeling of the atmosphere in present days. This work aims to evaluate the performance of the microphysical parameterizations in regional modeling, with emphasis on the role of large- scale information and its influence on the simulations, and the use of observational data from radiosondes as a way to add information to modeling. Initially, two reanalysis (NCEP2 and ERAI) were statistically compared with data from PCDs from the Ceará State. It was found that the ERAI showed similarity to the observations, especially for variables directly linked to convection. Then, the ERAI is used as large scale forcing in simulations with the WRF model. It was observed that the use of detailed microphysics does not necessarily improve the model performance, if in situ data were not used. Finally, two high resolution simulations were performed. The first f orced by reanalysis without modification and other forced by reanalysis using the modified method of objective analysis of the WRF, to include the time series of radiosonde observations collected during the experimental campaign of the CHUVA Project in Fortaleza- CE. The two simulations were compared with data observed by the radiometer to the same place and period of the radiosonde. It was observed that the inclusion of radiosonde observations in to the model leads to a better simulation of a convective system that occurred in April 2011, mostly for the variables related to convection. Using comparative statistical analysis, t his work points that the use of a higher density of valid observational data in the model can improve much more efficiently the model results than the use of a dynamic downscal ing of large- scale data or the use of schemes with detailed microphysics, which in some circumstances may even introduce more errors into the modeled system s.

With the insertion of the numerical models, it became possible to carry out a more reliable and short-term forecast of the time in search of more efficient results besides being necessary to improve the model and to acquire knowledge of its performance. In this work we apply simple statistical methods to compare the performance of the model by comparing the meteorological variables with observed data from an automated weather station (AWS) and data simulated by the WRF model. The analyzed data of these variables were from July 10 to 19, 2017, using statistical and computational tools: atmospheric mesoscale model (WRF), spreadsheets, as well as specific programming languages and scripts for data execution. The (AWS) from which the observed data was extracted is located in Maceió. The WRF simulations were validated through data series and statistical analyzes and it was verified that in the variables there was efficiency of the WRF in the predictions. The results expected with correlation coefficient between average and strong for 24h in most simulated and a mean correlation for 48h and 72h in most of the simulated, it was possible to conclude that the model is adjusted to predict average values and that in some moments that the minimum and maximum results could not be simulated, it is therefore possible to indicate the model as a tool to be used to carry out short-term forecasting provided there is updating of topography and land use for the city of Maceió. In this research it was possible to obtain expected results, but the equipment of measurement and data processing can be improved to obtain even more satisfactory results. / Neste trabalho aplicam-se métodos simples de estatística para comparar o desempenho do modelo realizando o comparativo das variáveis meteorológicas com dados observados de uma estação automática e dados simulados pelo modelo WRF. Com a inserção dos modelos numéricos, se tornou possível realizar previsão do tempo com melhor confiabilidade e um curto prazo em busca de resultados mais eficientes. Os dados analisados dessas variáveis foram do período de 10 a 19 de julho de 2017, utiliza-se estatística e ferramentas computacionais: modelo atmosférico de mesoescala (WRF), planilhas eletrônicas, além de linguagens de programação específicas e scripts para execução dos dados. A estação automática da qual foram extraídos os dados observados está localizada em Maceió. As simulações do WRF foram validadas através de séries de dados e análises estatísticas e ficou comprovado que nas variáveis houve eficiência do WRF nas previsões. Os resultados mostraram-se eficiente com coeficiente de correlação entre média e forte para 24h na maioria dos simulados e uma correlação média para 48h e 72h na maioria dos simulados, foi possível concluir que o modelo está ajustado para prever valores médios e que em alguns momentos que os resultados mínimos e máximos não conseguiram ser simulados, logo é possível indicar o modelo como uma ferramenta a ser utilizada para realizar previsão de curto prazo desde que haja atualização de topografia e uso do solo para o município de Maceió. Nessa pesquisa foi possível obter resultados satisfatórios, porém pode-se aperfeiçoar os equipamentos de medição e processamento de dados para se obter resultados ainda mais satisfatórios.

In the current study, we have presented a systematic analysis of the diurnal cycle of rainfall over the Indian region using satellite observations, and evaluated the ability of the Weather Research and Forecasting Model (WRF) to simulate some of the salient features of the observed diurnal characteristics of rainfall. Using high resolution simulations, we also investigate the underlying mechanisms of some of the observed diurnal signatures of rainfall. Using the Tropical Rain-fall Measuring Mission (TRMM) 3-hourly, 0.25 ×0.25 degree 3B42 rainfall product for nine years (1999-2007), we extract the finer spatial structure of the diurnal scale signature of Indian summer monsoon rainfall. Using harmonic analysis, we construct a signal corresponding to diurnal and sub-diurnal variability. Subsequently, the 3-hourly time-period or the octet of rain-fall peak for this filtered signal, referred to as the “peak octet,” is estimated with care taken to eliminate spurious peaks arising out of Gibbs oscillations. Our analysis suggests that over the Bay of Bengal, there are three distinct modes of the peak octet of diurnal rainfall corresponding to 1130, 1430 and 1730 IST, from north central to south Bay. This finding could be seen to be consistent with southward propagation of the diurnal rainfall pattern reported by earlier studies. Over the Arabian sea, there is a spatially coherent pattern in the mode of the peak octet (1430 IST), in a region where it rains for more than 30% of the time. In the equatorial Indian Ocean, while most of the western part shows a late night/early morning peak, the eastern part does not show a spatially coherent pattern in the mode of the peak octet, owing to the occurrence of a dual maxima (early morning and early/late afternoon). The Himalayan foothills were found to have a mode of peak octet corresponding to 0230 IST, whereas over the Burmese mountains and the Western Ghats (west coast of India) the rainfall peaks during late afternoon/early evening (1430-1730 IST). This implies that the phase of the diurnal cycle over inland orography (e.g., Himalayas) is significantly different from coastal orography (e.g., Western Ghats). We also find that over the Gangetic plains, the peak octet is around 1430 IST, a few hours earlier compared to the typical early evening maxima over land. The second part of our study involves evaluating the ability of the Weather Research and Fore-casting Model (WRF) to simulate the observed diurnal rainfall characteristics. It also includes conducting high resolution simulations to explore the underlying physical mechanisms of the observed diurnal signatures of rainfall. The model (at 54km resolution) is integrated for the month of July 2006 since this period was particularly favourable for the study of diurnal cycle. We first evaluate the sensitivity of the model to the prescribed sea surface temperature (SST) by using two different SST datasets, namely Final Analyses (FNL) and Real-time Global (RTG). The overall performance of RTG SST was found to be better than FNL, and hence it was used for further model simulations. Next, we investigated the impact of different parameterisations (convective, microphysical, boundary layer, radiation and land surface) on the simulation of diurnal cycle of rainfall. Following this sensitivity study, we identified the suite of physical parameterisations in the model that “best” reproduces the observed diurnal characteristics of Indian monsoon rainfall. The “best” model configuration was used to conduct two nested simulations with one-way, three-level nesting (54-18-6km) over central India and Bay of Bengal. While the 54km and 18km simulations were conducted for July 2006, the 6km simulation was carried out for the period 18-24 July 2006. This period was chosen for our study since it is composed of an active period (19-21 July 2006), followed by a break period (22-24 July 2006). At 6km grid-spacing the model is able to realistically simulate the active and break phases in rainfall. During the chosen active phase, we find that the observed rainfall over central India tends to reach a maximum in the late night/early morning hours. This is in contrast to the observed climatological diurnal maxima of late evening hours. Interestingly, the 6km simulation for the active phase is able to reproduce this late night/early morning maxima. Upon further analysis, we find that this is because of the strong moisture convergence at the mid-troposphere during 2030-2330 IST, leading to the rainfall peak seen during 2330-0230 IST. Based on our analysis, we conclude that during both active and break phases of summer monsoon, mid-level moisture convergence seems to be one of the primary factors governing the phase of the diurnal cycle of rainfall. Over the Bay of Bengal, the 6km model simulation is in very good agreement with observations, particularly during the active phase. The southward propagation observed during 19-20 July 2006, which was not captured by the coarse resolution simulation (54km), is exceedingly well captured by the 6km simulation. The positive anomalies in specific humidity attain a maxima during 2030-0230 IST in the north and during 0830-1430 IST in the south. This confirms the role of moisture convergence in the southward propagation of rainfall. Equally importantly we find that while low level moisture convergence is dominant in the north Bay, it is the mid-level moisture convergence that is predominant in the south Bay.