With the tremendous development of remote sensing technologies, large-scale data sets are collected from environmental and meteorological sensors. Edge computing for large-scale data sets is hard to be conducted in real time on the sensors, thus data transfer to cloud system and data processing play an important role. One of the barriers in such system is high-speed data transfer on long-distance networks. Even low packet loss condition leads to decrease in throughput by conventional transmission control protocol (TCP)-based tools. In this paper, we overcome this issue by proposing a high-performance data transfer tool to improve real-time data processing of phased array weather radar on long-distance networks. The proposed tool, called high-performance copy (hcp), is designed based on an open source tool for file copy operations and implemented using our socket library specialized for long-distance networks. We evaluate our tool with simulations and real data transfer scenarios. The results show that the hcp enables concurrent data transfer from radar sites to cloud system (data processing site) in real time. The throughput of data transfer from a radar site to a data processing site increases from 40 Mbps using the conventional TCP-based tool to 489.2 Mbps using the hcp.