The distribution of colors in natural images can vary widely across different environments or within the same environment over time. We have examined how color distributions at a single location can vary with changes in seasons. A large set of digital images were collected from a rural valley in Maharashtra India during monsoon (wet) and winter (dry) months. Each image included a reference palette of known reflectance (MacBeth color checker measured with a spectroradiometer), which allowed the rgb values to be calibrated to derive the cone excitations at each pixel. The seasonal changes in rainfall and consequent changes in vegetation result in large changes in both the mean chromaticity of the images and the dominant chromatic axis along which color signals vary. Mean color shifts were largely along the L-M chromatic axis (shifting toward +L for drier environments). This average seasonal shift is notably similar to the +L shift that allows ripening fruit to be distinguished from the background foliage (Regan et al., Phil. Trans. R. Soc., 2001). The principal axes of the distributions rotated from near the S-LM axis to a bluish-yellowish axis intermediate to the L-M and S-LM axes. These shifts are consistent with previous measurements sampled from different environments (Webster and Mollon, Vision Research, 1997). Both the mean changes and the axis changes are many times larger than the differences resulting from variations in the illumination, and have important implications for understanding how visual coding might be matched to particular environments.