Evaluation of the estimation method for nonuniformity of rainfall within a footprint of TRMM/PR using the data during 180-degree yaw maneuver

摘要

The Tropical Rainfall Measuring Mission (TRMM) satellite performs 180-degree yaw maneuver (yaw-around). when the solar beta angle which is the angle between the satellite orbit plane and the direction to the sun crosses the 0-degree The yaw-maneuver is completed about 16 minutes (about 7000 km in flight length on the Earth) in the TRMM case. During the yaw-around, the Precipitation Radar (PR) onboard TRMM continues nominal observation (but data processing is limited to level-1 algorithms). Therefore very dense observation is realized during the yaw-around. Since nearly fixed target (rain echo and surface echo) is observed by different incident angles in a short time, new information can be obtained that cannot be obtained nominal observation. On the incident angle dependency of the sea surface echo, we can avoid the uncertainties comes from the changes in the target. Range profiles of the sea surface echo of different incident angles can be compared with the long-term global average data. The same approach can be used to quantitative estimation of bright band structure such as blurring effect of the off-nadir incident angles. For convective echoes, the nonuniform beam filling (NUBF) effect can be estimated by the different incident angle data and the data which location is slightly offset from the center. More reliable path integrated attenuation (PIA) can be obtained from different incident angle data and the NUBF can be estimated both by the range profiles of surface echo of off-nadir angle bin data with an approach by Takahashi et al. (2006) and their change with the location within a footprint. Two NUBF cases are demonstrated in this paper showing the horizontal sub-footprint size distribution of PIA. The results are confirmed by the consistency of different angle data with slight offset location. In addition, this method is evaluated by the PIA pattern data obtained from densely distributed (because of 180-degree yaw maneuver) data using the method similar to the standard algorithm for TRMM/PR.