## 4 Results
### Assessment of Global Forecast Impact  
The impact of different data latency length of LEO IR and MW sounders on the GFS forecast was evaluated by comparing forecast against self-analyses using the NCEP Verification Statistics DataBase (VSDB) package. For the forecast verification, the anomaly correlation (AC) metric, which is one of the most widely used indexes to diagnose the impact of advanced data assimilation skill on weather forecasting, was used. The AC values indicate the spatial correlation between the forecast anomaly and the analysis anomaly for the designated atmospheric parameter. In particular, the forecast errors of 500 hPa geopotential height are widely used to be the key indicators to measure the overall forecast performance because large-scale weather patterns in the middle-level atmosphere near 500 hPa pressure level are well linked with lower-level atmospheric patterns. In addition to the AC, the root-mean-square errors (RMSEs) of the forecast field were also used to diagnose the forecast performance for the trial runs. Figures 7 and 8 show mean difference in the ACs and RMSEs of geopotential height at three pressure levels (i.e., 250, 500, and 700 hPa) between the latency_20m run and the control run. In addition to the mean difference, the normalized difference of ACs with respect to the control run was also plotted. A positive difference in the AC indicates that the forecast errors for the experiment run are smaller than the control run, meaning that the reduced data latency has a positive forecast impact. On the contrary, a negative difference in the RMSEs indicates a positive forecast impact. Figure 7: The (**a**) mean and (**b**) normalized difference of AC of 250 hPa, 500 hPa, and 700 hPa geopotential height forecast up to 120–h forecast hours between the latency_20m and control runs. Grey, green, red, and magenta boxes indicate the results over the Global, Northern Hemisphere, Tropic, and Southern Hemispheres, respectively. Vertical bars representing 95% confidence level of the uncertainty are overlaid. For all three geopotential heights, the ACs tend to decrease with increasing forecast hour (not shown), indicating that the forecast accuracy decreases with the length of forecast hour. As shown in Figure 7a, a positive difference is exhibited in the forecast range from T+48 to T+120, becoming larger with the forecast hour. In particular, the global mean ACs of 500 hPa geopotential height increase up to about 0.3% at 120-h forecast. Moreover, a strong positive impact is found in the Southern Hemisphere for all three geopotential heights (i.e., 250, 500, and 700 hPa), especially at T+96 forecast hour. In the Northern Hemisphere, the difference in the ACs is close to zero and its percentage change is small. However, in the Tropic, a negative impact is shown at 250 hPa at T+120 forecast hour. Similar to the results of ACs, the negative difference of RMSEs of three geopotential heights increases in the forecast range of T+24 to T+96, indicating that the forecast errors are reduced for the latency_20m run as compared to the control run (Figure 8). The forecast errors are significantly reduced in the Southern Hemisphere, with a maximum reduction of about -1.3 m at 250 hPa for the T+96 forecast hour. In terms of the percentage analysis, a steady error reduction of about 2.0% is exhibited for the whole forecast range except for the T+120 forecast hour. As shown in Figure 9, strong error reduction is mainly shown in the latitudinal range from 30\({}^{\circ}\) S to 70\({}^{\circ}\) S at T+72 and T+96 forecast hours, in particular at 250 hPa and 500 hPa pressure levels. In the Tropic and the Northern Hemisphere, the forecast impact is overall neutral. Even though the largest negative value (-4.2%) is present at 500 hPa for the T+120 forecast hour in the Tropics (Figure 8b), this value is statistically insignificant considering the error confidence level.