## 3 Methodology
### EASE Grid 2.0  
Spatial mismatch is the most common problem when the CYGNSS product is compared with SMAP satellite data. When compared to 2D images with the 36 km \(\times\) 36 km spatial resolution from the SMAP product, CYGNSS data are provided with a list of tables containing post-processed results that are a sequence of observation results and metadata regarding orbit and satellite information. We applied the averaging method that was used in [12] to overcome the spatial resolution mismatch in comparing CYGNSS and SMAP reflectivity and dielectric constant. For this reason, CYGNSS reflectivity data on each EASE are located in the same grid of SMAP data. The EASE grid is defined as a global scale of gridding with the use of an equal area projection. Because the resolution of the EASE grid is varies depending on usage, the SMAP data provide soil moisture and other variables with varying spatial resolution, such as 3 km, 9 km, or 36 km. V2.0 denotes the updated method for reducing the spatial distortion when the projection is applied.  
Figure 3 illustrates the orbit of CYGNSS satellites when one of eight satellites passes above the site TxSON in the United States. The white straight lines depict the EASE grid border and red dots represent the specular points that are measured by a CYGNSS satellite. The selected locations for analysis can be converted from geographic coordinates into the EASE grid using the conversion function shown in [49]. Subsequently, 2D images can be drawn by removing the average from the reflectivities belonging to same EASE grid of SMAP. When the average is applied, the time interval for the average is one day, and the data from eight satellites are used simultaneously without distinction. It is assumed that every satellite has identical measurement properties when they are measured by the reflected signals over the land. The assumption is caused by the fact that a specialized calibration process was not created for the measurement data from individual satellites. The calibration method for land-reflected GNSS signals will be specified by future work, and the soil moisture and dielectric constant values that are derived from GNSS-R observations will become more accurate.  
The averaged 2D global image of reflectivity using CYGNSS data can be obtained every day; then, by iterating the same process with another date of observation, a global number reflectivity is acquired. Figure 4 shows the global reflectivity map that was calculated with CYGNSS data using Equations (2) through (6) on the EASE grid v2.0 and accumulated observation data of satellite 1 from 18 March 2017 to 28 February 2018. Despite the low spatial resolution that is given by the 36 km \(\times\) 36 km EASE grid, this method simplifies the comparison between CYGNSS and SMAP data. Additionally, it is a straightforward approach for applying the same process to other locations by changing the target pixel of analysis. As noted earlier, the data with incident angle greater than 20\({}^{\circ}\) have been removed in CYGNSS data. Iterated results at diverse locales are given in the following sections. The data correlation time series and seasonal variations will be examined in order to determine the time related properties.  
Figure 4: Global image of reflectivity drawn on EASE grid 2.0 using CYGNSS data that were measured by satellite 1 from 18 March 2017 to 28 February 2018.  
Figure 3: Specular points (red dots) occurred on EASE grid when eight CYGNSS satellite were passing above the TxSON region during Mar 2017. The straight white lines denote an EASE grid, which is the grid system having equal distance in both the latitude and longitude directions.