The aim of this diploma thesis analyze the processing of meteorological messages in XML format. There are described various meteorological reports and the developing data format WXXM. The result of the practical part is application enable to load meteorological messages in XML format and displays basic information obtained in map environment of Bing Maps.

Diploma thesis deals with the aeronautical data format AIXM and exploring possibilities for processing meteorological messages in the format WXXM. This diploma thesis describes the development of application which handles both formats. Final application can evaluate appropriate runway on the basis of meteorological information.

Submitted by Emanuel Varela Cardoso (emanuel.varela@ufcg.edu.br) on 2018-05-15T19:33:49Z No. of bitstreams: 1 LEONARDO FAGNER PONCIANO BARBIERI – DISSERTAÇÃO (PPGMET) 2016.pdf: 2556569 bytes, checksum: 2d377d114fdccde32b6d4af9ee448c47 (MD5) / Made available in DSpace on 2018-05-15T19:33:49Z (GMT). No. of bitstreams: 1 LEONARDO FAGNER PONCIANO BARBIERI – DISSERTAÇÃO (PPGMET) 2016.pdf: 2556569 bytes, checksum: 2d377d114fdccde32b6d4af9ee448c47 (MD5) Previous issue date: 2016-02-26 / CNPq / O desenvolvimento deste trabalho teve como objetivo caracterizar o regime de vento em superfície na área do Aeroporto Internacional de Petrolina (Senador Nilo Coelho) e identificar condições meteorológicas adversas cruciais às operações de pouso e decolagem. Enfoque especial foi dado aos episódios de vento cruzado, também denominado vento de través (vento perpendicular à pista de pouso). Os principais dados utilizados são as mensagens METAR do período 2003 - 2014. Um aumento significativo na frequência de vento de través, que chega a 100% no mês de julho, é informação importante a ser considerada pelos pilotos que atuam na Região. A Análise Fatorial por Componentes Principais (ACP) foi utilizada para identificar mecanismos físicos associados com mudanças significativas no vento local. Foram retidos três fatores que explicaram 94,9% da variabilidade dos dados no mês de abril. Os episódios mais significativos de vento de través do quadrante Nordeste (TRV_NE) ocorreram no ano de 2012 em condições atmosféricas influenciadas pela atuação de VCAN (Vórtice Ciclônico de Altos Níveis). Movimentos descendentes no centro do VCAN, redução na umidade atmosférica e um número maior de nuvens mais altas estão entre as principais características desses eventos. As análises mostram ainda uma relação positiva entre o número de registros de VCAN e a frequência de TRV_NE, e que a circulação da brisa lacustre induzida pela implantação do Lago de Sobradinho ao sul do aeroporto de Petrolina contribuiu para o aumento na frequência de vento de través do quadrante Sudoeste (TRV_SW). / The development of this work aimed to characterize the surface wind regime in the Petrolina International Airport area (Senator Nilo Coelho) and to identify adverse weather conditions crucial to landing and takeoff operations. Special focus was given to cross-wind (wind perpendicular to the runway) episodes. The main data used are the METAR messages for the period 2003 – 2014. A significant increase in cross-wind frequency, that reaches 100% in the month of July, is important information to be considered by the pilots that operate in the region. The Factor Analysis by Principal Components (PCA) was used to identify physical mechanisms associated with significant changes in the local wind. Three factors explaining 94.9% of the variance in the month of April were retained. The most significant episodes of cross-wind on the Northeast quadrant (TRV_NE) occurred in 2012 under atmospheric conditions influenced by UTCV (Upper Tropospheric Cyclonic Vortex). Descending motion in the UTCV center, reduction in atmospheric humidity and a larger number of higher base clouds are among the main characteristics of these events. The analyses show also a positive relationship between the number of UTCV reports and the frequency of TRV_NE, and that the lake breeze circulation induced by the implantation of the Sobradinho Lake to the south of the Petrolina airport contributed for the increase in the frequency of cross-wind on the Southwest quadrant (TRV_SW).

<p>Emergency services (ES) pilots operate in a dynamic, high-risk team environment, as a subset of general aviation (GA) operations. The time constraints associated with ES operations means that ES pilots must make flight decisions quickly and often with limited or incomplete information (Worm, 1999). Due to the nature of ES operations, the consequences of an incorrect flight decision can be severe, including loss of life. ES operations are often initiated by extreme weather events, and ES pilots are frequently required to fly on the boundary between marginal visual flight rules (MVFR) weather conditions and instrument meteorological conditions (IMC). Unfortunately, an unintended transition into IMC is the leading cause of fatal accidents in GA operations (Ayiei et al., 2020). Mission objectives dictate that most ES pilots fly below 1,500’ above ground level (AGL) for extended periods of time, and low-altitude flight in hazardous weather can reduce a pilot’s outside visual reference, thus leading to spatial disorientation, loss of control, or controlled flight into terrain. To mitigate this problem, ES pilots must be able to accurately assess weather conditions before and during flight. However, the current method of presenting meteorological aerodrome reports (METARs) on weather displays can be misleading to pilots. Weather conditions in the areas between weather observation stations can be different than what is reported by the METAR observations at those stations. This can cause current or forecasted weather conditions <em>between</em> weather stations to be incompletely represented. However, pilots are given no obvious indication of how incompletely represented weather conditions can affect weather-related risk. This research demonstrates that a <em>Kth</em> Nearest Neighbor (KNN) analysis can be used to identify areas where the variability of conditions between weather stations (and thus weather-related risk) is incompletely represented by METAR observations. In addition, it is shown that areas where there is an increased risk of an unintended transition from MVFR to IMC can be identified among areas with incompletely represented conditions and depicted to pilots on aviation weather displays. Machine learning tactics are proposed as a way to consider additional inputs in future KNN analyses, and several emerging technologies are proposed as mediums to collect additional weather observations. The ability for an ES pilot to more accurately assess weather-related risk in MVFR conditions using the proposed technologies is evaluated, the benefits to ES pilots and the GA community are discussed, and the requirements and limitations of the study are examined.</p>