The Impact of Spatio-temporal Resolution of GEO-KOMPSAT-2A Rapid Scan Imagery on the Retrieval of Mesoscale Atmospheric Motion Vector

This paper illustrates the impact of the temporal gap between satellite images and target size in mesoscale atmospheric motion vector (AMV) algorithm. A test has been performed using GEO-KOMPSAT-2A (GK2A) rapid-scan data sets with a temporal gap varying between 2 and 10 minutes and a target size between 8 x 8 and 40 x 40. Results show the variation of the number of AMVs produced, mean AMV speed, and validation scores as a function of temporal gap and target size. As a results, it was confirmed that the change in the number of vectors and the normalized root-mean squared vector difference (NRMSVD) became more pronounced when smaller targets are used. In addition, it was advantageous to use shorter temporal gap and smaller target size for the AMV calculation in the lower layer, where the average speed is low and the spatio-temporal scale of atmospheric phenomena is small. The temporal gap and the target size are closely related to the spatial and temporal scale of the atmospheric circulation to be observed with AMVs. Thus, selecting the target size and temporal gap for an optimum calculation of AMVs requires considering them. This paper recommends that the optimized configuration to be used operationally for the near-real time analysis of mesoscale meteorological phenomena is 4-min temporal gap and 16 x 16 pixel target size, respectively.

Automated summary

This paper examines the impact of the temporal gap between satellite images and target size on the mesoscale atmospheric motion vector (AMV) algorithm. The study suggests that shorter temporal gaps and smaller target sizes are advantageous for AMV calculations in the lower layer of the atmosphere.