An atmospheric correction algorithm using a radiative transfer code combined with NOAA/NCEP global data assimilation system (GDAS) products is one of standard algorithms for five thermal infrared channels of Terra/ASTER. In the present article, this GDAS-based algorithm is validated by three approaches using AVHRR channels 4 and 5 data around Japan.<BR>In the first approach, the GDAS-based algorithm is validated using in-situ measurements of lake surface temperature on Lake Kasumigaura. The results show that 1) the error of the GDAS-based algorithm for channel 4 is almost within ±0.5 K in winter though it is almost within ±1 K in summer, 2) the error of the GDAS-based algorithm for channel 5 is much larger than that for channel 4, and 3) the GDAS-based algorithm is much more sensitive to cloud-contamination than the split window (SW) algorithm. In the second approach, the GDAS-based algorithm is compared with the SW algorithm along the nadir track of a satellite. As the results, the GDAS-based algorithm encounters a trouble for a localized dry region whose size is almost equal to one scene of ASTER. This is an essential problem for the GDAS-based algorithm because this trouble is most likely caused by the low spatial/temporal resolution of GDAS products. In the third approach, the GDAS-based algorithm is validated using the precipitable water vapor (PWV) derived from GPS wet delay data. First, the PWV derived from the GDAS profile is compared with that derived from the GPS wet delay data. For 850 permanent GPS stations of Japan, the differential RMS of them is 5.54 mm in early September. And then, the GDAS-based algorithm is compared with the SW algorithm for cloud-free sea surfaces adjacent to cloud-free GPS stations. The GDAS-based algorithm demonstrates a possibility that its accuracy is improved by the scaling of the water vapor profile with the GPS PWV from the nearest GPS station.<BR>In the final part of this article, future problems are discussed. Especially, the necessity of validation experiments in the Southern Hemisphere with less permanent meteorological stations is emphasized.