## 2 Data Sources
### RSS: MSU Temperature Data
Significant modifications were made to overcome calibration difficulties and time-varying biases [74; 78]. The weighted combinations from multiple MSU channels were used, which depend on the vertical coherence of stratospheric trends to reduce stratospheric cooling [77]. The RSS v3.2 datasets were developed for the lower troposphere (TLT) and middle troposphere (TMT) and were specifically designed to eliminate stratospheric influences [73]. A comprehensive comparison of these datasets was conducted with homogenous radiosonde datasets, revealing a high level of agreement between the two. The present study provides error bounds that define the upper and lower limits of the TLT and TMT trend values to account for the uncertainty introduced by stratospheric contamination, if present. In order to derive extended-term trends in tropospheric temperature using satellite data, it is crucial to remove the diurnally varying component from the observations. This step is essential due to the gradual shifts in the local observation times of the majority of satellites over time. As a result, the temperature measurements can be influenced by the natural daily temperature fluctuations caused by the Earth's rotation and the Sun's heating. A diurnal correction algorithm was derived for the tropics, where decadal-scale temperature changes in the lower troposphere indicated cooling [79]. Analysis revealed that the global trend (70\({}^{\circ}\) S to 82.5\({}^{\circ}\) N) of 0.193 \({}^{\circ}\)K per decade (1979-2003) was approximately 0.1 \({}^{\circ}\)K per decade higher compared to the trend calculated over the same geographical area based on the data [80]. Similarly, the trend observed in the tropics (20 \({}^{\circ}\)S to 20 \({}^{\circ}\)N) of 0.189 \({}^{\circ}\)K per decade was around 0.2 \({}^{\circ}\)K per decade warmer. This study suggested that the tropical troposphere experiences a slightly greater warming rate compared to the surface in most regions, aligning with expectations. Furthermore, the data is consistent with middle tropospheric findings obtained by removing the influence of the stratosphere from MSU2 data using MSU channel 4. This consistency indicates a measure of vertical consistency in RSS data. NOAA's Satellite Applications and Research (STAR) version 3.0 [81] scales the RSS diurnal cycle climatology to generate their version of the MSU/AMSU dataset. The UAH team determines the local diurnal slope by analyzing cross-scan differences [80]. Studies had confirmed that none of the models completely removed the effects of the diurnal cycle [75]. By adjusting GCM-derived diurnal cycles using information derived from comparing satellite observations at various local times, also known as the \"optimized\" or DIUR_OPT approach, an alternative model was used, resulting in the upgrade of the RSS V3.3 datasets to the RSS V4.0 datasets [82; 83]. Long-term stable calibration methods to combine measurements from MSU and AMSU microwave sounders to produce long-term temperature lower troposphere (TLT) and temperature middle troposphere (TMT) products have been described in [72; 73]. The RSS offers regularly updated TLT and TMT products, characterized by consistent and reliable long-term calibration. These products are valuable resources for evaluating climate change over decades.