## 1 Introduction
The objective is to allow the NWP centers to use near-real-time data of the LEO satellite measurements to maximize the positive impact of the LEO satellites on the weather forecasting. The satellite data are acquired in real time through a worldwide network of local DBNet receiving stations, processed locally on agreed standards, and disseminated in near real time. The DBNet system carries out three sequential tasks. First, the LEO satellite sounder measurements are acquired by the local DBNet ground stations following the scheduling priorities determined by the DBNet coordination group. Second, the received satellite raw data are processed to calibrated radiances using agreed data processing packages such as the Advanced TIROS Operational Vertical Sounder (ATOVS) and Advanced Very High-Resolution Radiometer (AVHRR) Pre-processing Package (AAPP) and the Community Satellite Processing Package (CSPP). Third, the processed satellite data are re-transmitted to the global user community via the Global Telecommunication System (GTS) or the File Transfer Protocol (FTP) in near real time. With the global DBNet system, the length of data latency of the LEO satellite sounder measurements is significantly reduced. However, the average data latency of the LEO satellites is still longer than 20 min recommended by the WSP in terms of the global model system. For example, for the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS), data are delivered with an averaged data latency of 80 min, leading to about 74% of observation usage [12]. There are two main reasons for longer data latency. Firstly, there is still an insufficient number of DBNet ground stations to deliver the LEO satellite data in a timely fashion. As of now, DBNet stations are located over land. In the Southern Hemisphere, where most of the surface is covered by ocean, the number of the stations is relatively small. Moreover, there are still few DBNet stations over the vast regions (i.e., the continent of Africaand Australia). Secondly, it is still technically difficult for the DBNet station to process all operating LEO satellites. The number of LEO satellites each DBNet station can handle is limited by the processing power of the station (e.g., availability of processors and its spatial coverage) and the usefulness of the satellite (e.g., forecast impact and data quality). Thus, the number of the assigned DBNet stations to each LEO satellite sounder is significantly different, leading to different data latency depending on the satellite types. Considering the aforementioned limitations, the current data latency of the LEO satellite sounders can be further reduced by expanding the number of DBNet stations over regions where coverage is limited and upgrading the data processing system of the DBNet station. In two recent studies, it was demonstrated that the reduced data latency for the satellite observations has a positive forecast impact for the global and regional forecast models [13; 14]. However, these studies mainly focused on assessing the forecast impact in the range of the data latency from 3 h to 0 with a one-hour interval, not considering that the current data latency is already less than 2 h in the operational model system. In order to shed light on how to enhance the global forecasts from the currently operating NWP system, it is more significant to diagnose the forecast benefit on the global forecast from reducing the current data latency through enhancing the operational DBNet system. Moreover, while the WSP recommends a 20-min data latency, it is still unknown if the forecast will benefit with an even shorter data latency. Thus, in this study, we assessed the data latency impact on the global forecasts under the assumption that the current data latency of all LEO satellite sounders is no longer than 20 min as recommended by the WSP, and if a short data latency of less than 20 min is beneficial using the NCEP GFS. This paper is organized as follows.