Agroclimatic classification: numerical- taxonomic procedures - a review.

The paper catalogues the procedures and steps involved in agroclimatic classification. These vary from conventional descriptive methods to modern computer-based numerical techniques. There are three mutually independent numerical classification techniques, namely Ordination, Cluster analysis, and Minimum spanning tree; and under each technique there are several forms of grouping techniques existing. The vhoice of numerical classification procedure differs with the type of data set. In the case of numerical continuous data sets with booth positive and negative values, the simple and least controversial procedures are unweighted pair group method (UPGMA) and weighted pair group method (WPGMA) under clustering techniques with similarity measure obtained either from Gower metric or standardized Euclidean metric. Where the number of attributes are large, these could be reduced to fewer new attributes defined by the principal components or coordinates by ordination technique. The first few components or coodinates explain the maximum variance in the data matrix. These revided attributes are less affected by noise in the data set. It is possible to check misclassifications using minimum spanning tree.

Instalação de um pomar de kiwi em Pontevedra, Galiza

Mestrado em Engenharia Agronómica - Instituto Superior de Agronomia - UL

Probabilistic methods for seasonal forecasting in a changing climate: Cox-type regression models.

For climate risk management, cumulative distribution functions (CDFs) are an important source of information. They are ideally suited to compare probabilistic forecasts of primary (e.g. rainfall) or secondary data (e.g. crop yields). Summarised as CDFs, such forecasts allow an easy quantitative assessment of possible, alternative actions. Although the degree of uncertainty associated with CDF estimation could influence decisions, such information is rarely provided. Hence, we propose Cox-type regression models (CRMs) as a statistical framework for making inferences on CDFs in climate science. CRMs were designed for modelling probability distributions rather than just mean or median values. This makes the approach appealing for risk assessments where probabilities of extremes are often more informative than central tendency measures. CRMs are semi-parametric approaches originally designed for modelling risks arising from time-to-event data. Here we extend this original concept beyond time-dependent measures to other variables of interest. We also provide tools for estimating CDFs and surrounding uncertainty envelopes from empirical data. These statistical techniques intrinsically account for non-stationarities in time series that might be the result of climate change. This feature makes CRMs attractive candidates to investigate the feasibility of developing rigorous global circulation model (GCM)-CRM interfaces for provision of user-relevant forecasts. To demonstrate the applicability of CRMs, we present two examples for El Ni ? no/Southern Oscillation (ENSO)-based forecasts: the onset date of the wet season (Cairns, Australia) and total wet season rainfall (Quixeramobim, Brazil). This study emphasises the methodological aspects of CRMs rather than discussing merits or limitations of the ENSO-based predictors.

Impactos das mudanças climáticas sobre o controle biológico de doenças de plantas.

2009

Novo sistema de medidas de evaporacao para o tangue classe A.

O estudo aborda o projeto de construcao e analise de desempenho de um novo sistema de medida evaporometrica que e acoplado a um tanque classe "A" padrao convencional, dando-se ao sistema o nome "Tanque Classe A Modificado". A viabilidade do sistema foi testada contra medidas simultaneas com o sistema classico (tanque classe "A" padrao e micrometro), revelando, atraves de testes estatisticos, que o Tanque Classe "A" Modificado pode substituir com vantagens o sistema classico, minimizando os erros de leitura que sao cometidos mesmo quando se dispoe de pessoal qualificado para esta operacao e permitindo tambem a realizacao de medidas evaporometricas com boa aproximacao em dias de chuva.

Atlas climático da Região Sul do Brasil: Estados do Paraná, Santa Catarina e Rio Grande do Sul.

Este atlas é dividido em quatro principais seções, sendo a primeira a descrição conceitual e metodológica das variáveis meteorológicas. A segunda seção compreende uma análise, por meio de gráficos, das principais características climáticas dos mais diversos ambientes regionais. Em seguida, estão disponíveis, na forma de tabelas, os dados mensais, estacionais e anuais que podem ser usados para outros fins, conforme a necessidade do leitor. Por último, ele apresenta mais de duas centenas de mapas que revelam, de forma ilustrada e de fácil visualização, um conjunto de variáveis de temperatura, precipitação pluvial, classificações climáticas, entre outras informações.

Março termina com muito sol e pouca chuva.

2016

Total de chuvas em maio supera a média mensal.

2016

Análise de DFA e de agrupamento do perfil de densidade de poços de petróleo

In recent years, the DFA introduced by Peng, was established as an important tool capable of detecting long-range autocorrelation in time series with non-stationary. This technique has been successfully applied to various areas such as: Econophysics, Biophysics, Medicine, Physics and Climatology. In this study, we used the DFA technique to obtain the Hurst exponent (H) of the profile of electric density profile (RHOB) of 53 wells resulting from the Field School of Namorados. In this work we want to know if we can or not use H to spatially characterize the spatial data field. Two cases arise: In the first a set of H reflects the local geology, with wells that are geographically closer showing similar H, and then one can use H in geostatistical procedures. In the second case each well has its proper H and the information of the well are uncorrelated, the profiles show only random fluctuations in H that do not show any spatial structure. Cluster analysis is a method widely used in carrying out statistical analysis. In this work we use the non-hierarchy method of k-means. In order to verify whether a set of data generated by the k-means method shows spatial patterns, we create the parameter Ω (index of neighborhood). High Ω shows more aggregated data, low Ω indicates dispersed or data without spatial correlation. With help of this index and the method of Monte Carlo. Using Ω index we verify that random cluster data shows a distribution of Ω that is lower than actual cluster Ω. Thus we conclude that the data of H obtained in 53 wells are grouped and can be used to characterize space patterns. The analysis of curves level confirmed the results of the k-means

Análisis del estado hídrico del Humedal Tibanica y alternativas de compensación hidrológica

39 p.

Comparação da análise de diferentes perfis de poços pelo método DFA

The study of complex systems has become a prestigious area of science, although relatively young . Its importance was demonstrated by the diversity of applications that several studies have already provided to various fields such as biology , economics and Climatology . In physics , the approach of complex systems is creating paradigms that influence markedly the new methods , bringing to Statistical Physics problems macroscopic level no longer restricted to classical studies such as those of thermodynamics . The present work aims to make a comparison and verification of statistical data on clusters of profiles Sonic ( DT ) , Gamma Ray ( GR ) , induction ( ILD ) , neutron ( NPHI ) and density ( RHOB ) to be physical measured quantities during exploratory drilling of fundamental importance to locate , identify and characterize oil reservoirs . Software were used : Statistica , Matlab R2006a , Origin 6.1 and Fortran for comparison and verification of the data profiles of oil wells ceded the field Namorado School by ANP ( National Petroleum Agency ) . It was possible to demonstrate the importance of the DFA method and that it proved quite satisfactory in that work, coming to the conclusion that the data H ( Hurst exponent ) produce spatial data with greater congestion . Therefore , we find that it is possible to find spatial pattern using the Hurst coefficient . The profiles of 56 wells have confirmed the existence of spatial patterns of Hurst exponents , ie parameter B. The profile does not directly assessed catalogs verification of geological lithology , but reveals a non-random spatial distribution

Normal Climatológica 1986-2015. Posto Meteorológico da Escola Superior Agrária de Castelo Branco

A recolha e o registo dos dados foi efetuada pelo colaborador da ESA/IPCB João Nunes.

Methodology for climate risk assessment of maize intercropped with Brachiaria in the Cerrado of Brazil.

2015

Les macroclimats viticoles mondiaux et l'influence du mesoclimat sur la typicite de la Syrah et du Muscat de Hamboug dans le sud de la France: methodologie de caracterisation.

1999