# Joint Use of Spaceborne Microwave Sensor Data and CYGNSS Data to Observe Tropical Cyclones
## 3 Data Processing
Note that the time interval during which the CYGNSS data were intercepted for data fusion is determined by the movement speed of hurricane. In other words, a faster hurricane speed corresponds to a shorter time interval used for the CYGNSS data interception. For example, only a fraction of Hurricane Florence was captured by the SMAP radiometer at 20:23 UTC on 11 September 2018. Since the central location of the hurricane can be roughly estimated according to the high wind speed region shown in most SMAP radiometer and CYGNSS data, such as Figure 4-m, the difference in the spatial location of the hurricane between the adjacent SMAP radiometer and CYGNSS data can be obtained. At the same time, the time interval between these two data can also be easily calculated. As a result, the speed of the hurricane can be obtained in terms of the difference in its spatial location and the  
Figure 5: Flow chart of the data processing. corresponding time interval. After a rough estimate of Hurricane Florence's speed, the CYGNSS data acquired from 20:30 to 23:30 UTC were chosen for data fusion, as shown in Figure 8.
* Case 3. In addition to the observation data already used in the above cases, the remaining CYGNSS data are also fused in terms of the movement speed of the hurricane to provide a better visualization of the TC for fixing its center due to the sparse tracks of CYGNSS satellite. An example is shown in Figure 7. After a rough estimate of Hurricane Florence's speed on 9 September 2018, we selected the CYGNSS data acquired from 13:30 to 15:30 UTC for data fusion. The method used here to roughly estimate the speed of hurricane is the same as that described in Case 2. The second step is data fusion, i.e., fusing the SMAP radiometer and CYGNSS data or only the CYGNSS data, as mentioned in the first step. A pixel-level data fusion method, which is similar to the region-based fusion method described in [34], was used in this study. The essential problem of pixel-level fusion can be defined as  
\[P_{f}(x,y)= m(P_{1}(x,y),P_{2}(x,y),\cdots,P_{N}(x,y)) \tag{1}\]  
where \(P_{1}(x,y)\), \(P_{2}(x,y)\),... \(P_{N}(x,y)\) represents \(N\) images capturing the same region, \(m(\cdot)\) is the fusion operator, which are typically represented by mean and maximum operators. Figure 6: Two observation results for Hurricane Florence acquired by the SMAP radiometer at 09:43 UTC and 21:12 UTC on 12 September 2018, respectively. (**a**) The observation result contains the complete structure of Hurricane Florence; (**b**) Hurricane Florence was not observed as it was not covered by the swaths of the SMAP radiometer. Since the observation results obtained by the SMAP radiometer provide a better visualization to analyze the tropical cyclone (TC) position than those acquired by the CYGNSS constellation, these two results were reserved with no further processing. Figure 2:0 Three observation results for Hurricane Florence acquired by the CYGNSS constellation at (**a**) 13:30 UTC, (**b**) 14:30 UTC and (**c**) 15:30 UTC on 9 September 2018. Since it is difficult to fix the center of Hurricane Florence using any of the three results, they were fused to obtain the complete structure of Hurricane Florence. The result of the final fusion is shown in subplot (**d**). Data preprocessing is the first step in data fusion. Here, both SMAP radiometer data and CYGNSS data were averaged in space on a 0.2\({}^{\circ}\) latitude and longitude grid, and then the image registration was performed due to the differences in the acquisition time and configuration of each result. In addition, a unified scale was adopted for the surface wind speeds retrieved from the SMAP radiometer and CYGNSS data. After data preprocessing, a single result was divided into two parts using a threshold segmentation, i.e., the region-of-interest (ROI) and non-ROI. Here, ROI was defined as a region with a high pixel value because it may be a TC. The rest of the pixels were defined as a non-ROI because they cannot provide any useful information related to a TC.