Instrumentation deployed at three different sites included three vertically pointing Doppler Micro Rain Radar units (one MRR2 and two MRR-Pro) collocated each with a laser disdrometer (PARSIVEL2), plus rain gauges and automated surface observations. The data sets included ground-level drop size distributions recorded by disdrometers, as well as rain gauge and C-band operational data, to study precipitation characteristics, associated microphysical processes and related variables, including convective and stratiform regimes. MRR raw data observations were post-processed with the RaProM and RaProM-Pro methodologies which use spectral reflectivity as input data to compute radar moments and different associated variables such as hydrometeor type (more details and public access to RaProM and RaProm-Pro Python codes are available at https://doi.org/10.3390/rs12244113 and https://doi.org/10.3390/rs13214323).
Results indicated higher rainfall in the eastern (non-irrigated) area during the summer of 2021, similarly as observed during the reference period 2010-2019. This is consistent with the current rain gauge derived climatology available at monthly level exhibiting a zonal gradient of increasing semi-arid conditions from east to west. Seasonal analysis of disdrometer 1-min rainfall rate distributions indicated differences in summer between the irrigated and non-irrigated areas, but not during the other seasons, when surface conditions differed less. MRR vertical profiles of precipitation were examined to assess the possible effect of evaporation, by considering changes of reflectivity, rainfall rate or Liquid Water Content (LWC) at different reference levels when precipitation was present and ground-level relative humidity was about 65%. Preliminary results indicated that, despite the amount of candidate rainfall profiles potentially affected by evaporation was higher in the non-irrigated area, the rate of LWC differences was similar in both areas. Limitations of the methodology and results obtained and possible alternatives, as well as implications for remote sensing of precipitation, are outlined in the presentation. This research was supported by projects WISE-PreP (RTI2018-098693-B-C32) and ARTEMIS (PID2021-124253OB-I00) and the Water Research Institute (IdRA) of the University of Barcelona.

