## 5 Weather Forecasting Models  
We have discussed a variety of instruments and their data products, such as sounders and radars. However, effectively utilizing these instruments has posed a significant challenge due to one primary limiting factor that has yet to be adequately addressed. Referring back to our initial distinction between climate and weather, it becomes evident that the continuous acquisition of observational data is critical for developing short-term forecasting models for weather applications. In this context, the term satellite revisit rate describes the temporal frequency at which a satellite observes the same location on Earth. In other words, it represents the time interval between consecutive satellite observations of a specific geographic point. A higher revisit rate translates to an increased data refresh rate, thereby improving the accuracy, resolution, and practicality of near-real-time weather forecasting models and enabling new operational capabilities. As illustrated in Table 1, to date, satellite revisit rates have been relatively low, limiting the effectiveness of such forecasting models. Internalizing the critical role of revisit rates in the scalability and accuracy of forecasting models, and building upon decades of advancements in remote sensing, new satellite missions have been launched to deepen understanding of Earth's global water cycle and to investigate atmospheric convective systems, cyclic storms, and precipitation processes using radar and radiometer technologies. One example is the launch of the Tropical Rainfall Measuring Mission (TRMM) to Low Earth Orbit (LEO) on 27 November 1997, a joint venture between NASA (Washington, DC, \begin{table}
\begin{tabular}{c c c} \hline
**Satellite System** & **Revisit Rate** & **Date of Operation** \\ \hline TRMM & 3 days & 1997–2015 \\ \hline CloudSat & 16 days & 2006–2024 (decommissioned) \\ \hline GPM & 3 days & 2014–2028 \\ \hline RainCube & Limited & 2018–2021 \\ \hline EarthCare & 16 days & 2023 \\ \hline INCUS & Limited & Start—2027 \\ \hline \end{tabular}
\end{table} 
Table 1: Historical Satellite Revisit Rates. USA) and the Japan Aerospace Exploration Agency (JAXA) (Tokyo, Japan). TRMM aimed to improve understanding of global energy and water cycles by observing the spatial and temporal distribution of tropical rainfall, along with associated hydrometeor structures and heating patterns over tropical and subtropical regions. This was accomplished using onboard instruments such as the precipitation radar (PR), which provided 3D imaging of rainfall structures and vertical distribution, as well as quantitative rainfall measurements over land and ocean. The PR featured a 128-element active phased-array system operating at 13.8 GHz. The system's assembly included a transceiver with 128 solid-state power amplifiers and low-noise amplifiers (LNAs), which were selected at each time step by a circulator that periodically switched between transmission and reception while sharing the same antenna. This was followed by PIN-diode phase shifter elements integrated with dividers/combiners, a 16-branch divider/combiner, an intermediate driver amplifier, and a signal processing subsystem comprising a frequency converter, IF unit, and system control and data processing unit [22]. The NASA GOES-16 satellite, shown in Figure 4, is the first of the GOES-R series of Geostationary Operational Environmental Satellites (GOES), operated also by the National Oceanic and Atmospheric Administration (NOAA). Its Advanced Baseline Imager (ABI) consists of 16 spectral bands at visible and infrared wavelengths, providing high-resolution Geostationary Lightning Mapping (GLM) of the Earth [23]. Its payload consists also Earth and Sun weather monitoring instrumentations. A second instrument, the Microwave Imager (TMI), is a 9-channel radiometer operating at dual-polarized frequencies ranging from 10.7 GHz to 85.5 GHz, with an \(11\text{ km}\times 8\text{ km}\) field of view at 37 GHz and high scanning capability.