The paper presents some interim results from an ongoing research on the application of data/text mining methodologies being investigated to modelling the seasonal climate variability and its effects on the world famous Marlborough vintage wines. The research in an extension to the investigations thus far conducted on modelling the effects of seasonal climate variability on Kumeu wines and all the sub-projects contribute to an overarching project which is aimed at developing a suitable set of schemes/ procedures for the identification and characterisation of wines produced from New Zealand's major wine regions. The distinctive New Zealand wine styles along with the regions from where the wines come from are initially elaborated. The major issues regarding the topic are; firstly, there is no single method that could be considered as the best way to establish the links between precise independent (climate/ weather) and the rather imprecise dependent (subjective wine quality) data sets. Secondly, the data on New Zealand wine quality is not sufficient enough to perform any conventional rigorous analytical approaches as data on wine quality spans only a decade, hence we look at data/ text mining methods and a combination of explorative and statistical data analysis methodologies to resolve the issues. Following a brief outline on the methods investigated and results achieved in the Kumeu wine case study, the paper presents the new methods and approaches explored with Marlborough wines produced from 1996 to 2007. Finally, wine descriptors that are found to be linked with wine quality and therefore considered as correlated to the regional climatic conditions experienced in different wine regions of New Zealand, are discussed.