The coconut yield is harvested in six picks per year at two-monthly intervals. The yield variation between and within years is very complex and this variability has not yet been explained. The analysis of long-term nut yield and monthly climate data: rainfall (RF), pan evaporation (EV), sunshine duration (SS), wind velocity (WV), minimum and maximum air temperatures (TMIN and TMAX), and relative humidity in forenoons and afternoons (RHAM and RHPM), using multivariate methods enabled the use of the variables TMAX, RHPM and EV as significantly important determinants (parsimonious set of variables) to represent the effects of climate on coconut irrespective of picks. Parsimonious models developed using these three variables explain how the development of bunches during the active growth period responded to climate variables without physiological parameters. The models are desirable where interpretation is concerned. The yields of picks one to six were determined by the climate variability during February, June, July, September, December and February respectively. Based on the models the proper timing of the use of some agronomic practices to enhance the productivity was recommended. A common model was also fitted (R2 = 0.81; p < 0.002) to estimate the annual yield 18 months in advance using EV, RHPM and TMAX. The three variables influence the microclimate around the crown of the palm for utilizing solar radiation in dry matter partitioning and thereby nut production. The method used to screen climatic variables so as to develop parsimonious crop–weather models using multivariate and univariate techniques can be used for other tree crops.