5:15 PM - 6:45 PM
[ACG36-P19] Improvement for GSMaP precipitation tracking algorithm using a high-resolution cloud moving vector and ForTraCC
Keywords:GPM, Precipitaiton tracking algorithm, higher resolution
The Global Satellite Mapping of Precipitation (GSMaP) utilizes observations from geostationary meteorological satellites (GEO) to fill gaps in the precipitation observation network created by microwave radiometers (PMW) on multiple polar-orbiting satellites. In this interpolation method, continuous observations from GEO are employed to track cloud movement, and the destination of precipitation clouds observed by PMW is calculated. While the cloud moving vectors were initially computed every hour on a 2.5° grid, recent advancements in GEO's temporal and spatial resolution allow for calculations every 10 minutes on a 1.0° grid.
In this study, we conducted experiments to improve the precipitation tracking algorithm of GSMaP using high-resolution cloud moving vectors. In experiments conducted in mid-latitudes, an enhancement in the accuracy of east-west precipitation tracking was observed. However, under strong vertical shear, the tracking accuracy for mid-to-low-level precipitation did not show sufficient improvement. This is attributed to the strong influence of upper-level clouds with high coverage on the direction of cloud moving vectors.
Although the vertical shear-induced tracking accuracy of precipitation improved to some extent with high resolution, errors in predicting the destination of mid-to-low-level precipitation still occurred, especially in regions with persistent strong vertical shear such as the tropics. To address this, we introduced a different precipitation tracking method, ForTraCC (Vila et al. 2008). ForTraCC detects precipitation clusters using intensity thresholds and tracks each cluster individually. Experiments conducted under strong vertical shear in tropical regions confirmed that ForTraCC could accurately track precipitation clusters in cases where cloud moving vectors misidentified the direction of mid-to-low-level precipitation.
By combining high-resolution cloud moving vectors with ForTraCC, further improvement in the precipitation tracking accuracy of GSMaP can be expected. This study is supported by the Japan Aerospace Exploration Agency (JAXA) and conducted as part of the collaborative research project "Development of High-Resolution GSMaP Algorithms."
In this study, we conducted experiments to improve the precipitation tracking algorithm of GSMaP using high-resolution cloud moving vectors. In experiments conducted in mid-latitudes, an enhancement in the accuracy of east-west precipitation tracking was observed. However, under strong vertical shear, the tracking accuracy for mid-to-low-level precipitation did not show sufficient improvement. This is attributed to the strong influence of upper-level clouds with high coverage on the direction of cloud moving vectors.
Although the vertical shear-induced tracking accuracy of precipitation improved to some extent with high resolution, errors in predicting the destination of mid-to-low-level precipitation still occurred, especially in regions with persistent strong vertical shear such as the tropics. To address this, we introduced a different precipitation tracking method, ForTraCC (Vila et al. 2008). ForTraCC detects precipitation clusters using intensity thresholds and tracks each cluster individually. Experiments conducted under strong vertical shear in tropical regions confirmed that ForTraCC could accurately track precipitation clusters in cases where cloud moving vectors misidentified the direction of mid-to-low-level precipitation.
By combining high-resolution cloud moving vectors with ForTraCC, further improvement in the precipitation tracking accuracy of GSMaP can be expected. This study is supported by the Japan Aerospace Exploration Agency (JAXA) and conducted as part of the collaborative research project "Development of High-Resolution GSMaP Algorithms."