The pathfinder AVHRR NDVI data are widely used for analyzing the response of vegetation condition to climate change. However

the Pathfinder NDVI data sets contain a lot of random errors due to various factors such as cloud

aerosols

instrumental interruption and changes and so on. To what extent these errors can influence the results of NDVI/climate connections? In the present work

the authors analyzed the impacts of NDVI errors on NDVI/temperature coupling in spring

by using singular value composition analysis technique. Four kinds of errors are tested

including the continuous

discontinuous and volcanic errors

and the error trends as well. Results show that when the errors are less than half the original NDVI standard deviation the SVD spatial modes and temporal changes are stable and independent of the error. However

if the error gets larger

the results would be distorted apparently. Comparison experiments conducted in the present study suggest that the upper limit of potential errors for reasonable results is about 0 5 standard deviations of the original NDVI series. Actual errors are likely to be within this limit

thus the results from the original data are acceptable. In addition

the methods applied in the study can be applied to the similar research to test the significance and robustness of the results in case of unknowing how large the error is.