## 2 Data and Method
### Sources of Uncertainty and Datasets  
#### 2.2.1 Constellation Changes-Induced Uncertainties  
The time evolution of the microwave constellation induces inhomogeneity in the time series of constellation-based precipitation estimates, as in [18]. This can be thought of as uncertainty arising from the changes in the platform number and configuration that forms the constellation. Such uncertainty can readily be estimated using data-denial experiments whereby the change of the configuration can be easily simulated with the Global Interpolated RAinFall Estimation (GIRAFE, [22]) framework. GIRAFE is an algorithm that provides \(1^{\circ}\)/daily rain accumulation estimates based on the combination of multi-source satellite observations/estimates (i.e., from geostationary and low earth orbit satellites), globally and has been available since 2000 for up to \(55^{\circ}\)N/S. GIRAFE evolved from the Tropical Amount of Precipitation with an Estimate of ERrors (TAPEER) approach [19; 23], which is based on the Universally Adjusted GOES Precipitation Index (UAGPI) technique [24; 25]. In the present GIRAFE version, the instantaneous rain rate retrievals (i.e., the L2 input database) were extracted from the Goddard Profiling Algorithm (GPROF2017, [26]) and the Precipitation Retrieval and Profiling Scheme (PRPS2019, [27]) PMW algorithms were obtained from the GPM V05 and V06 database, respectively. [PERSON] et al. [28] provided a systematic analysis of this source of uncertainty over the last decades and here we illustrated the resulting uncertainty distributions by exploring only 2 configurations that are representative of the actual changes in the constellation setup. The GPM \"golden era\" constellation period was selected as a reference for comparison with the other two different configurations, namely (i) an idealized case for a single SSMI/S and (ii) a configuration used to exploit the impact in the absence of MT1.SAPHIR and GPM.GMI. Table 1 shows the PMW radiometers considered for each experimental configuration. Data-denial experiments were performed for June-July-August of 2014 (JJA2014) and December-January-February of 2014/5 (DJF2014/5). The study domain corresponds to a quasi-global zone between \(55^{\circ}\)N/S. The GIRAFE framework training volume of \(5^{\circ}\times 5^{\circ}\times 5\) days was adopted for both the intensity and detection parameters, which were assumed as 1.5 and 0.5 mm h\({}^{-1}\), respectively. It is worth mentioning that the rain estimation framework used in this work (i.e., GIRAFE), for describing the uncertainty according to the constellation changes, was re-designed to accordingly geo-collocate the distinct platforms (imagers and sounders) and their different footprint sizes and shapes (retrieval resolution) that fall into an \(1^{\circ}\times 1^{\circ}\) grid. However, the uncertainty due to platform characteristics' effect is still expected and remains due to the physical approaches at the sensor-level rain retrieval scheme. For instance, in the GPROF retrieval algorithm, which is commonly used as an input data source for L3 precipitation estimates (e.g., the IMERG V06 product), despite being able to considers multiple channels for providing the surface rain rate, its retrieval resolution is based on the \(\sim\)19 GHz channel resolutions for most of the radiometers considered (i.e., imagers). Further, sounders (e.g., MHS, ATMS and SAPHIR), as cross-track sensors, have varying footprint sizes with the scan position and the adopted retrieval resolutions are taken at nadir by GPROF algorithm. Therefore, both the assumptions can lead to uncertainties at L2 rain retrievals, which can also be propagated to the L3 precipitation estimates. In this study, the footprint size artifact leading to uncertainty can be explained as part of the constellation configuration differences, however, its quantification was not explicitly explored. Nevertheless, further studies exploring the sensor footprint features as a component of uncertainty in daily precipitation estimates are recommended.