A functional evaluation of virtual climate station rainfall data

Model simulations are increasingly being, used to assess farm performance and its impact on the environment. A crucial input in most of these models is daily rainfall data, which are difficult to obtain for remote areas or if the period required is long. Recently, a new long-term daily climate dataset for all New Zealand. known as Virtual Climate Station (VCS) data, has become available from NIWA (National Institute of Water & Atmospheric Research Ltd). A reasonable agreement between the VCS and observed data has been reported; nonetheless the effect of the Uncertainty in the estimated rainfall oil model simulations remains all issue to be examined. Ill this study we investigated the differences in simulated evapotranspiration, drainage and pasture growth by two models of varying complexity when Using VCS or observed rainfall data from several locations around New Zealand. The results showed a general agreement between model outputs whether Using observed or VCS rain fall datasets. Model outputs that are closely related to rainfall events, such as drainage, were more sensitive to deviations in the rainfall datasets than the indirect outputs, such as evapotranspiration. Data aggregation and correction of bias improved agreement between observed and VCS data and this was reflected in the model outputs. Although short-term simulations should be analysed with care, overall results were promising. The NIWA VCS rainfall data have the potential to be extensively used in conjunction with simulation models for the assessment of land use and management practices.