Abstract: The retrieval algorithm based on an eigenvector regression method was summarized. The vertical distributions of the atmospheric temperature and moisture were retrieved using EOS/MODIS infrared data and were verified along the latitude and pressure altitude with isobaric surface reanalysis field data from NCEP (national centers for environmental prediction). The results indicate that the atmospheric temperature and moisture parameters retrieved by MODIS data can reveal its vertical distributions. The average of root mean square (RMS) errors at each isobaric surface is 3.39 K in middle latitude region and 1.40 K in low latitude region, respectively. The errors are significant near the ground and tropopause region as well as in complicated underlying surface region. In general, temperature retrieval results are better in low latitude regions than in middle latitude regions, so are vapor retrieval results. With the increasing of the height, the error decreases gradually in middle and high latitudes regions and is close to each other.

Key words: MODIS infrared data, Retrieval, Eigenvector regression algorithm, Atmospheric temperature and moisture profile