## 4 Discussion
This would make our study less valuable. Therefore, the extensive range of spatial resolution (1000 km to 20 km) and temporal resolution (240 min to 1 min) of this study is useful with consideration of the state of the art and future improvement of the technology, though the maximum of the spatial resolution and temporal resolution cannot be reached under the state of the art. The MERO instrument has a focal plane array (FPA) with a multi-detector unit, and each unit views a part of the Earth TOA (represented by a pixel), respectively (Figure 3); therefore, the generated data is the multi-pixel image of TOA OSR and OLR fluxes. In the actual MERO operation stage, the received irradiance of one detector will be converted to the Earth TOA flux of the corresponding pixel using an anisotropic factor; the anisotropic factor of one pixel is the ratio of the received radiance by the corresponding detector to the Earth TOA flux (Equation (2)). Therefore, the pixel-scale anisotropic factor is vital for the data-producing of the MERO system. To calculated the pixel-scale anisotropic factor, we used the numerical discretizing method: the pixel is discretized into sub grid points, and one grid point represents one TOA area of 0.1\({}^{\circ}\) latitude \(\times\) 0.1\({}^{\circ}\) longitude (discretization of pixel 8\({}^{\prime}\) in Figure 3), then the anisotropic factors of these sub grids are area-weighting summed to derive the anisotropic factor of the whole pixel (Equation (3)). The OSR and OLR anisotropic factors of one sub grid are derived by the CERES angular distribution models (ADMs) [19; 20]. The ADMs generate the TOA OSR/OLR anisotropic factor based on the scene type by considering their dependence on the viewing geometry, the beneath surface type and the related cloud and meteorological parameters. In the ADMs, every OSR/OLR scene type corresponds to one TOA OSR/OLR anisotropic factor, respectively; when the scene type is confirmed, the anisotropic factor can be derived. ADMs describe the scene type by a discrete bin method: related parameters (surface type, related cloud and meteorological parameters, viewing geometry angles, see Tables 1 and 2) are discretized into several bins, a possible combination of bins of every of these parameters is set as one scene type. In the actual operation of a MERO mission, the meteorological parameter and surface-type data mentioned above should be firstly derived to generate the real-time OSR/OLR anisotropic factors for every pixel. The surface type can be determined by the IGBP or NOAA JPSS-VIIRS-AST global surface data or other global surface-type products. The meteorological parameters could be derived through mounting a meteorological observation payload (like MODIS (moderate-resolution imaging spectroradiometer)) on the MERO or by utilizing the global meteorological database. The real-time instantaneous regionally half-globe Earth TOA OSR and OLR images are the basic category of the MERO dataset, which are generated as follows. At one time point, the focal plane detector array (FPA) (ensemble of amounts of individual detector units) of the MERO system would \"photograph\" the full Earth disk instantaneously; every detector unit just simultaneously \"photographs\" the OSR/OLR radiation of part of the Earth TOA (represented by an image pixel) respectively (see Figure 3) [24]. The left bottom hollow green rectangle in Figure 1 shows the example of one image pixel; the upper right solid green rectangle is the corresponding detector unit. In the FPA, one detector unit is an individual system; it converts the received radiation of the pixel to the electrical signal and process it to a digital number, then this digital number is converted to the incident flux by radiometric calibration function, and such an incident flux would afterward be converted to the incident radiance using the MERO observing geometry. This incident radiance would be then converted to the flux of the corresponding image pixel using the anisotropic factor (Equation (2)).