One of reasons for non-translation of weather based prediction systems for groundnut late leafspot is inability of the models to account for the variability due to prime contributing weather parameters and inadequate data on microclimate of the pathogen in the canopy. The instruments for measuring microclimate are not only expensive but also need timely calibration. Hence, an effort was made to find out relationships between observatory meteorological data and microclimate at canopy level. Field trials were laid out during kharif seasons of 2004 and 2006 and wireless sensors were placed in the field near to crop canopy to record weather. During 2004 Tmax, Tmin and RHe were significantly positively correlated (‘r’=0.729, 0.943 and 0.680, respectively) whereas RHm was not significant (‘r’=0.201). On the other hand, during 2006, both Tmax and RHe were strongly positively correlated (‘r’=0.791 and 0.652, respectively) whereas ‘r’ values of RHm and Tmin were not significant (-0.380 and 0.151, respectively). The relationship between the Tmax of observatory and canopy level showed logistic relationship with a mean deviation of 8.1±1.4 and a range of 5.7 to10.6. Similarly, Tmin of observatory and canopy level showed logistic relationship with a mean deviation of 1.0±1.6 and a range of –2.0 to 4.3. During kharif 2004, RHm and RHe showed an exponential relationship between observatory and canopy level data. However, during kharif 2006, the relationships were sinusoidal. These functional relationships for temperatures could be used for developing weather based forewarning systems. Though the apparent infection rate in 2004 (0.0664) was similar to ‘r’ in 2004 (0.0759), the area under disease progress curve (AUDPC) was relatively less in 2006 as compared to 2004, which signifies the role of weather and other crop husbandry practices including date of sowing. The results are discussed in this paper.