We study the relationship between climate variability and crop yields using a county level panel for Lithuania (2000-2024) covering 13 major crops. Climate conditions are summarized by 18 pre-defined temperature and precipitation indices constructed from daily meteorological observations and standardized to allow comparison across indicators. For each crop, we estimate county fixed-effects models with year effects and include contemporaneous and lagged elimate indices. Yield responses are heterogeneous across crops and counties. Warmer conditions are beneficial in some settings, but higher climatic instability, especially within-season precipitation variability and exposure to spring frost, is generally associated with lower yields. Overall, the results underscore the importance of modeling climate variability, not only mean conditions, and motivate crop- and region specific adaptation strategies. The discussed measures can also be integrated in productivity analysis.
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