Monitoring the amount of Chlorophyll-a (Chla). a pigment present in photosynthetic algae, is essential for monitoring the health of lakes, rivers, and coastal waters. High levels of Chla can indicate threats like harmful algal blooms, low oxygen levels, or other water quality problems that affect things like fishing, public health and tourism. Scientists can estimate the Chla present in a water body from satellite data, enabling widespread and timely monitoring of different water bodies. An essential step in any satellite-based analysis is to remove the effects of the atmosphere from the measured data— or Atmospheric correction (AC). There are many methods designed for aquatic AC processing each with their own individual methodologies. Different AC methods can give very different results, which makes the final Chla estimates less reliable. In this study, we show that domain adaptation (DA), a technique designed to make satellite and field data more compatible, also helps make the results from the different AC methods more consistent. Aligning all satellite data to a common reference, reduces differences in model accuracies across AC methods by a large amount.