Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies-Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

Deriving meteorological variables across Africa for the study and control of vector-borne disease:a comparison of remote sensing and spatial interpolation of climate

This paper presents the results of an investigation into the utility of remote sensing (RS) using meteorological satellites sensors and spatial interpolation (SI) of data from meteorological stations, for the prediction of spatial variation in monthly climate across continental Africa in 1990. Information from the Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration's (NOAA) polar-orbiting meteorological satellites was used to estimate land surface temperature (LST) and atmospheric moisture. Cold cloud duration (CCD) data derived from the High Resolution Radiometer (HRR) onboard the European Meteorological Satellite programme's (EUMETSAT) Meteosat satellite series were also used as a RS proxy measurement of rainfall. Temperature, atmospheric moisture and rainfall surfaces were independently derived from SI of measurements from the World Meteorological Organization (WMO) member stations of Africa. These meteorological station data were then used to test the accuracy of each methodology, so that the appropriateness of the two techniques for epidemiological research could be compared. SI was a more accurate predictor of temperature, whereas RS provided a better surrogate for rainfall; both were equally accurate at predicting atmospheric moisture. The implications of these results for mapping short and long-term climate change and hence their potential for the study anti control of disease vectors are considered. Taking into account logistic and analytical problems, there were no clear conclusions regarding the optimality of either technique, but there was considerable potential for synergy.

Federal plan for meteorological rocket observations : fiscal years 1973-1977 /

"FCM 73-2"

Index numbers for North and Central America, the Caribbean, and U.S. stations in the Pacific /

Mode of access: Internet.

Aircraft hazard assessment from a clear-air radar and meteorological tower study of gravity wave events /

"June 1983."

Operator's and organizational maintenance manual : meteorological station, manual AN/TMQ-4 (NSN 6660-00-537-9195).

"May 1967."

Setting up a network of agrometeorological stations in East Timor

A developed and sustainable agriculture requires a permanent and reliable monitoring of climatic/ meteorological elements in (agro) meteorological stations which should be located close to agricultural, silvicultural or pastoral activities. An adequate network of meteorological stations is then a necessary condition to support innovation and development in any country. Developing countries, mainly those with a history of frequent conflicts, presents deficient number of weather stations, often poorly composed and improperly distributed within their territories, and without a regular operation that allows continuity of records for a sufficiently long period of time. The objective of this work was to build a network of meteorological and agro-meteorological stations in East Timor. To achieve this goal, the number and location of pre-existing stations, their structure and composition (number and type of sensors, communication system,… ), the administrative division of the country and the available agro-ecological zoning, the agricultural and forestry practices in the country, the existing centres for the agricultural research and the history of the weathers records were taken into account. Several troubles were found (some of the automatic stations were assembled incorrectly, others stations duplicated information regarding the same agricultural area, vast areas with relevant agro-ecological representativeness were not monitored …). It was proposed the elimination of 11 existing stations, the relocation of 7 new stations in places not covered until then, the automation of 3 manual meteorological stations. Two networks were then purposed, a major with 15 agro-meteorological stations (all automatized) and one other secondary composed by 32 weather stations (only two were manual). The set of the 47 stations corresponded to a density of 329 km2/station. The flexibility in the composition of each of the networks was safeguarded and intends to respond effectively to any substantive change in the conditions in a country in constant change. It was also discussed the national coverage by these networks under a “management concept for weather stations”.

Prospects for wind energy utilisation in Karnataka State

An examination of the data available at 22 meteorological stations in Karnataka State shows that wind velocities in the State as a whole are neither spectacularly high nor negligibly low. The highest winds (annual mean of around 13 km/hr) are experienced in parts of the northern maidan region of the State (Gulbarga, Raichur and Bidar districts) and in Bangalore. The winds are strongly seasonal: typically, the five monsoon months May-September account for about 80% of the annual wind energy flux. Although the data available are inadequate to make precise estimates, they indicate that the total wind energy potential of the State is about an order of magnitude higher than the current electrical energy consumption. The possible exploitation of wind energy for applications in rural areas therefore requires serious consideration, but it is argued that to be successful it is essential to formulate an integrated and carefully planned programme. The output of current windpumps needs to be increased; a doubling should be feasible by the design of suitable load-matching devices. The first cost has to be reduced by careful design, by the use of local materials and skills and by employing a labour-intensive technology. A consideration of the agricultural factors in the northern maidan region of the State shows that there is likely to be a strong need for mechanical assistance in supplemental and life-saving irrigation for the dry crops characteristic of the area. A technological target for a windmill that could find applications in this area would be one with a rotor diameter of about 10 m that can lift about 10,000 litres of water per hour in winds of 10 km/hr (2.8 m/s) hourly average speed and costs less than about Rs 10,000. Although no such windmills exist as of today, the authors believe that achievement of this target is feasible. An examination of various possible scenarios for the use of windmills in this area suggests that with a windpump costing about Rs 12,000, a three hectare farm growing two dry crops a year can expect an annual return of about 150% from an initial investment of about Rs 15,000. It is concluded that it should be highly worthwhile to undertake a coordinated programme for wind energy development that will include more detailed wind surveys in the northern maidan area (as well as some others, such as the Western Ghats), the development of suitable windmill designs and a study of their applications to agriculture as well as to other fields.

Mineração de dados para previsão de eventos extremos de precipitação

No presente trabalho foram desenvolvidos modelos de classificação aplicados à mineração de dados climáticos para a previsão de eventos extremos de precipitação com uma hora de antecedência. Mais especificamente, foram utilizados dados observacionais registrados pela estação meteorológica de superfície localizada no Instituto Politécnico da Universidade do Estado do Rio de Janeiro em Nova Friburgo RJ, durante o período de 2008 a 2012. A partir desses dados foi aplicado o processo de Descoberta de Conhecimento em Banco de Dados (KDD Knowledge Discovery in Databases), composto das etapas de preparação, mineração e pós processamento dos dados. Com base no uso de algoritmos de Redes Neurais Artificiais e Árvores de Decisão para a extração de padrões que indicassem um acúmulo de precipitação maior que 10 mm na hora posterior à medição das variáveis climáticas, pôde-se notar que a utilização da observação meteorológica de micro escala para previsões de curto prazo é suscetível a altas taxas de alarmes falsos (falsos positivos). Para contornar este problema, foram utilizados dados históricos de previsões realizadas pelo Modelo Eta com resolução de 15 km, disponibilizados pelo Centro de Previsão de Tempo e Estudos Climáticos do Instituto Nacional de Pesquisas Espaciais CPTEC/INPE. De posse desses dados, foi possível calcular os índices de instabilidade relacionados à formação de situação convectiva severa na região de Nova Friburgo e então armazená-los de maneira estruturada em um banco de dados, realizando a união entre os registros de micro e meso escala. Os resultados demonstraram que a união entre as bases de dados foi de extrema importância para a redução dos índices de falsos positivos, sendo essa uma importante contribuição aos estudos meteorológicos realizados em estações meteorológicas de superfície. Por fim, o modelo com maior precisão foi utilizado para o desenvolvimento de um sistema de alertas em tempo real, que verifica, para a região estudada, a possibilidade de chuva maior que 10 mm na próxima hora.

中国特有针叶树种对气候变化的敏感性研究

About 214 trees in 9 sampling sites, representing 5 endemic conifer species, were collected from the western Sichuan Province and eastern Qinghai Province, China. In this study, structure we try to investigate tree-ring sensitivity to climate in order to obtain primary information of reconstructing past climate from the trees in this region. All the 5 species present distinct ring boundaries ^ few ABS(absent rings) and available for cross-dating,which are all past the test by program COFECHA. Statistics for all the 8 tree-ring width residual chronologies present significant inter-correlation between series and high values of mean sensitivity. As well as the maximum latewood density of Picea crassifolia Kom and Pinus densata Mast. These results indicate usefulness of these chronologies for dendrochronological studies. Pearson correlation analyses were applied to provide a basic estimate of the causal relationships between tree-ring width and climate factors. We found some significant relationships between tree-ring width> maximum density and temperature as well as precipitation. Especially, there is high correlation between the maximum density of the Picea crassifolia Kom and the index of moisture, the ratio of precipitation and temperature, which can indicate well the climate; however the higher correlation can be see between the maximum density of Pinus densata Mast and the total temperature from June to September. Regardless of tree species, chronologies in our study region presented accordant variations of which may reveal strong common climate signal. Thus these chronologies are shown to be dependable for building tree-ring network in the nearly future. However, there are limitations in this study, only monthly mean of temperature and precipitation were available. Also, for this typical subtropical mountain system, meteorological stations are usually located in valley and biased to represent moisture conditions on the slopes. Thus the estimation of precipitation both in temporal and spatial domain was rather restricted. Further study, such as wood anatomy, physiology and densitometry, are needed for better understanding the environmental and climatic history in this area.

Farmer perception of suitable conditions for slurry application compared with decision support system recommendations

The application of slurry nutrients to land can be associated with unintended losses to the environment depending on soil and weather conditions. Correct timing of slurry application, however, can increase plant nutrient uptake and reduce losses. A decision support system (DSS), which predicts optimum conditions for slurry spreading based on the Hybrid Soil Moisture Deficit (HSMD) model, was investigated for use as a policy tool. The DSS recommendations were compared to farmer perception of suitable conditions for slurry spreading for three soil drainage classes (well, moderate and poorly drained) to better understand on farm slurry management practices and to identify potential conflict with farmer opinion. Six farmers participated in a survey over two and a half years, during which they completed a daily diary, and their responses were compared to Soil Moisture Deficit (SMD) calculations and weather data recorded by on farm meteorological stations. The perception of land drainage quality differed between farmers and was related to their local knowledge and experience. It was found that the allocation of grass fields to HSMD drainage classes using a visual assessment method aligned farmer perception of drainage at the national scale. Farmer opinion corresponded to the theoretical understanding that slurry should not be applied when the soil is wetter than field capacity, i.e. when drainage can occur. While weather and soil conditions (especially trafficability) were the principal reasons given by farmers not to spread slurry, farm management practices (grazing and silage) and current Nitrates Directive policies (closed winter period for spreading) combined with limited storage capacities were obstacles to utilisation of slurry nutrients. Despite the slightly more restrictive advice of the DSS regarding the number of suitable spreading opportunities, the system has potential to address an information deficit that would help farmers to reduce nutrient losses and optimise plant nutrient uptake by improved slurry management. The DSS advice was in general agreement with the farmers and, therefore, they should not be resistant to adopting the tool for day to day management.

Offshore wind resource estimation using wave buoy data

In the coming decade installed offshore wind capacity is expected to expand rapidly. This will be both technically and economically challenging. Precise wind resource assessment is one of the more imminent challenges. It is more difficult to assess wind power offshore than onshore due to the paucity of representative wind speed data. Offshore site-specific data is less accessible and is far more costly to collect. However, offshore wind speed data collected from sources such as wave buoys, remote sensing from satellites, national weather ships, and coastal meteorological stations and met masts on barges and platforms may be extrapolated to assess offshore wind power. This study attempts to determine the usefulness of pre-existing offshore wind speed measurements in resource assessment, and presents the results of wind resource estimation in the Atlantic Ocean and in the Irish Sea using data from two offshore meteorological buoys. © 2012 IEEE.