# Applications of GNSS-RO to Numerical Weather Prediction and Tropical Cyclone Forecast
## 2 Research and Applications of RO in NWP
### Progress in the Application of RO to NWP
Figure 4: Impact of RO data in 100, 200, 500, and 1000 hPa on the ECMWF operational forecast in the southern hemisphere, where the positive values indicate improved NWP. The y-axis represents the fractional improvement in the RMS geopotential height errors as a function of the forecast range, which is plotted along the x-axis, in the southern hemisphere (latitude \(>20^{\circ}\)) [40]. The error bars represent the 95% confidence interval. Figure 3: Impact of RO data for heights of 100, 200, 500, and 1000 hPa on the ECMWF operational forecast in the northern hemisphere, where the positive values indicate improved NWP. The y-axis represents the fractional improvement in the root mean square (RMS) geopotential height errors as a function of the forecast range, which is plotted along the x-axis, in the northern hemisphere (latitude \(>20^{\circ}\)) [40]. The error bars represent the 95% confidence interval. In addition to the height and region, the amount of RO data is considered in a further sensitivity analysis. The authors of [45] studied the impact of the amount of RO data available at that time at different heights using the NWP assimilation system. As shown in Figure 5, the forecast error reduces more in the stratosphere above 200 hPa than in the troposphere below 500 hPa when assimilating RO data. As shown in Figure 5a-d, at heights of 50, 100, 150, and 200 hPa, increasing the amount of assimilated RO data decreases the relative forecast error. This is also consistent with the results, shown in Figures 3 and 4, in that the improvement for the southern hemisphere is more significant than for the northern hemisphere and the tropics. RO measurements reduced the forecast error by approximately 10% with assimilating RO data of only 5%. However, at 1000 hPa and 500 hPa, as shown in Figure 5e,f, RO measurements have a modest impact on the forecast, due to the relatively low SNR in the troposphere. Nevertheless, in actual operation, every observation's weight metric varies with the height. Therefore, the impact of RO measurements on the NWP is positive. The authors of [44] analyzed the height at which the RO measurements have the most significant impact and found that the quality of the RO data in the lower troposphere is not ideal, particularly below a height of 2 km. In contrast, RO has a pronounced positive impact in the UTLS region, which is approximately in the height range of 10-20 km. Thus, in an operational NWP assimilation system, the range between 10 and 20 km is the main region where RO data yield optimal results. To assess the impact of RO measurement on NWP, the authors of [44] evaluated the forecast error reduction of various observations assimilated by the ECMWF. Figure 6 shows that, while accounting for only approximately 7% of all observations, RO data rank 4 th in terms of the contribution, reducing the error by approximately 10%. Notably, the assimilated RO data in the 2014 ECMWF assimilation system are estimated to be less than 3000 soundings per day. With such a modest amount and yet a tremendous impact on the NWP, the RO data are deemed promising. Figure 5: Sensitivity of height to the amount of RO data in NWP [45]. Dependence of 24-h temperature forecast. error relative to 0%-GPS-RO experiment (%) at (**a**) 50, (**b**) 100, (**c**) 150, (**d**) 200, (**e**) 500, and (**f**) 1000 hPa. The 24 h temperature relative forecast error, plotted along the y-axis, decreases with an increase in the GPS-RO data density. Above 500 hPa, more RO data induces less error, and the phenomenon in the stratosphere is more obvious than in the troposphere. The solid, dotted, and dashed lines indicate the results for the northern hemisphere, southern hemisphere, and tropics, respectively.