# Editorial for Special Issue \"Remote Sensing of Precipitation: Part II\"
## 2 Overview of Contributions  
[PERSON] et al. [1] studied the performance of ensemble forecasts for precipitation estimates by three numerical weather prediction models within THORPEX (The Observing System Research and Predictability Experiment of the World Meteorological Organization), as well as that of the IMERG (Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM)), during severe floods in Iran over the period of March and April 2019. In the paper by [PERSON] et al. [2], precipitation estimates derived from the Italian ground radar network were used in conjunction with measurements from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) to develop an operational-oriented algorithm (RAdar INfrared Blending algorithm for Operational Weather monitoring--RAINBOW) able to provide precipitation pattern and intensity. The algorithm evaluated surface precipitation over five geographical boxes in which the study area was divided. In their study, [PERSON] and [PERSON] [3] assessed the robustness of a probability weighted regional spatial bootstrap approach to estimate precipitation frequencies using radar data. Using the regional spatial bootstrap technique, they investigated two main issues that impact the use of radar-based Quantitative Precipitation Estimations (QPE) in deriving precipitation frequency estimates: (1) the typically short historical records of radar-based QPEs and (2) the effect of outliers in a precipitation maxima series that could possibly cause unrealistic spatial gradients in intensity-duration-frequency relations. [PERSON] et al. [4] contributed with an analysis of the relationship between Z-R (reflectivity and rain rate) parameters and weather types in Central Europe, based on acomprehensive regional dataset of rain microstructure measurements at ten sites in the federal state of Bavaria, Germany. The authors investigated what the effect is of weather types on rain microstructures and whether there is a consistent variation in the Z-R parameters between weather types that would suggest opportunities to improve the QPE with radar-based methods. The study by [PERSON] et al. [5] presented the first attempt for introducing an assimilation of zenith tropospheric delay, derived from more than 48 stations of the Hellenic global navigation satellite systems network, into the operational Numerical Weather Prediction System of the National Observatory of Athens in Greece, which is based on the Mesoscale Weather Research and Forecasting model. The model was applied during seven high-impact precipitation events covering the dry and wet seasons in 2018. The main objective of the study by [PERSON] et al. [6] was to evaluate the performance of multiple Satellite Precipitation Products (SSPs) in depicting the spatiotemporal variations of summer precipitation over Taiwan, using more than 400 local rain gauges for comparison. The authors examined the competence of SSPs in studying the summer connective afternoon rainfall events, which constitute the most frequently observed weather patterns in Taiwan. The analysis mainly focused on the time periods that overlap in all the data investigated--that is, the summers of 2014-2017. Precipitation measurements from a second-generation PARSIVEL dishorometer deployed in Beijing, Northern China, were analyzed by [PERSON] et al. [7] in order to investigate the microphysical structure of raindrop size distribution and its implications on polarimetric radar applications. Rainfall types were classified and analyzed in the domains of the median volume diameter and the normalized intercept parameter. [PERSON] et al. [8] investigated the performance of the Precise Point Positioning technique for the estimation of the zenith tropospheric delays by using a recently introduced low-cost dual-frequency receiver connected to antennas of ranging quality with and without applying relative antenna calibrations.