5:15 PM - 7:15 PM
[U04-P01] Estimation of water vapor distribution over land and sea by near-infrared imaging from small satellites
★Invited Papers
Keywords:Water Vapor, multispectral imaging, small sattelites
In recent years, developing cumulonimbus clouds have caused torrential rains that have caused significant damage. In order to reduce these damages, it is necessary to predict the development of cumulonimbus clouds that bring torrential rains earlier and more accurately.
Although numerical prediction has been widely used in the past, it is difficult to predict mesoscale phenomena such as torrential rains, and as Bryan et al, However, the time and spatial resolutions of observation equipment are insufficient for the lidar observations and satellite microwave observations that have been conducted so far. Therefore, it would be effective to improve the prediction if observations could be made with high spatial resolution of about 100 m.
In this study, we used the DIWATA-2 satellite equipped with a liquid crystal variable filter to obtain pixel-by-pixel spectra from images taken in the water vapor absorption band at 722 [nm] and the peripheral bands of 671 [nm], 710 [nm], 749 [nm], and 780 [nm] where there is no absorption. Then, by performing inter-fall interpolation on the data in the bands with no absorption, we estimated the reflection spectrum in the absence of any water vapor and calculated the intensity of water vapor absorption by comparing it with the observed reflection spectrum. Observations were targeted off the Philippine Sea in July 2024 in conjunction with the MR24-04 voyage of the observation vessel Mirai, in North America and Chihuahua Hill on October 22, 2024, and in the Pacific Ocean in February 2025 in conjunction with the MR25-01 voyage of Mirai. Data from satellites were compared with column water vapor content observations obtained by radiosondes from vessels and from the ground station, and the relationship between water vapor content and water vapor absorption was calculated.
In this presentation, we will present the results of the analysis to date and future tasks.
Although numerical prediction has been widely used in the past, it is difficult to predict mesoscale phenomena such as torrential rains, and as Bryan et al, However, the time and spatial resolutions of observation equipment are insufficient for the lidar observations and satellite microwave observations that have been conducted so far. Therefore, it would be effective to improve the prediction if observations could be made with high spatial resolution of about 100 m.
In this study, we used the DIWATA-2 satellite equipped with a liquid crystal variable filter to obtain pixel-by-pixel spectra from images taken in the water vapor absorption band at 722 [nm] and the peripheral bands of 671 [nm], 710 [nm], 749 [nm], and 780 [nm] where there is no absorption. Then, by performing inter-fall interpolation on the data in the bands with no absorption, we estimated the reflection spectrum in the absence of any water vapor and calculated the intensity of water vapor absorption by comparing it with the observed reflection spectrum. Observations were targeted off the Philippine Sea in July 2024 in conjunction with the MR24-04 voyage of the observation vessel Mirai, in North America and Chihuahua Hill on October 22, 2024, and in the Pacific Ocean in February 2025 in conjunction with the MR25-01 voyage of Mirai. Data from satellites were compared with column water vapor content observations obtained by radiosondes from vessels and from the ground station, and the relationship between water vapor content and water vapor absorption was calculated.
In this presentation, we will present the results of the analysis to date and future tasks.