# Editorial for Special Issue \"Remote Sensing of Precipitation: Part II\"
## 2 Overview of Contributions
[17] performed a comparative analysis of the IMERG high-resolution product and Tropical Rainfall Measuring Mission (TRMM) 3B43 product. These satellite-based precipitation fields were validated against rain gauges over the island of Cyprus for the period from April 2014 to June 2018. Satellite precipitation estimates were compared with the gauge records on a monthly and an annual basis. In an effort to elucidate the strengths and weaknesses of recently released gridded precipitation datasets, [PERSON] et al. [18] conducted a comprehensive evaluation of the performances of several such datasets at daily and monthly timescales. The study was performed over Austria using a dense network of gauges of 882 stations. The evaluation was carried out based on continuous and categorical statistical metrics for the period from June 2014 to December 2015. [PERSON] et al. [19] evaluated four precipitation datasets from the two satellite-based precipitation products, namely IMERG (version 06B) and GSMaP (version 07), against 388 rain gauge observations concerning their spatial and seasonal accuracy over Nepal. Their performances were analyzed for their tendencies and discrepancies depending on the different elevation ranges and relative intensities on a daily and monthly timescale from March 2014 to December 2016. The study by [PERSON] et al. [20] focused on Linear Depolarization Ratio values derived from vertically pointing cloud radars and the distribution of five hydrometeor species during 38 days with thunderstorms that occurred in 2018 and 2019 in Central Europe within the vicinity of the radar used in the study. The study showed improved algorithms for de-aliasing, the derivation of vertical air velocity and the classification of hydrometeors in clouds. The main objectives of the contribution by [PERSON] et al. [21] were (a) to investigate the spatial distribution of precipitation changes using daily, daytime and nighttime records from 2393 weather sites across China; (b) to study the quantification of the performances of selected products in detecting precipitation trends on a sub-daily scale with different validation metrics through a comparison with gauge observations and (c) to identify the metric-based optimal products at a sub-daily scale. In the research by [PERSON] et al. [22], a new downscaling methodology was developed using the Digital Elevation Model to delineate into three geospatial predictors, i.e., elevation,longitude and latitude, in an empirical distribution-based framework (EDBF). Two different satellite-based precipitation datasets, such as the GPM-based multitemporal precipitation data for the prediction of high-resolution downscaled weighted precipitation from 0.1\({}^{\circ}\) to 0.05\({}^{\circ}>\) resolution, and the GPM and the TRMM datasets for the verification of proposed methodology were used over the humid southern region of Mainland China. In the study by [PERSON] et al. [23], an OTT Parsivel-2 (Kempten, Germany) Dischrometer was used to measure raindrop spectra from 10 August 2018 to 10 August 2019 at Yulin Ecohydrological Station, Shaanxi Province, China. The precipitation events obtained were classified as stratiform and convective, based on the rainfall intensity classifying process. The Drop Size Distribution characteristics of Yulin Station were obtained, and the results can help to understand the microphysical characteristics of precipitation and their impact on the mechanism of soil erosivity in the semi-arid area. The study by [PERSON] et al. [24] aimed to evaluate the accuracy of the latest five GPM and TRMM rainfall products across monthly, daily and hourly scales based on ground rain gauge measurements between January 2009 and December 2017 in the Shuaishui River Basin of Eastern-Central China. For the evaluation, a total of four continuous and three categorical metrics were calculated based on satellite precipitation product (SPP) estimates and historical rainfall records at 13 stations over a period of nine years from 2009 to 2017. [PERSON] et al.