Analysis of gridded products from passive microwave retrieval algorithms in the GPM era and comparison with global precipitation dataset

Precipitation estimation and evaluation of its distribution are key elements in hydrological applications, water management and for improving flood or droughts monitoring. Satellite-based techniques have allowed precipitation estimation on a global scale with good temporal coverage. Therefore the exploitation of the complete Global Precipitation Measuring (GPM) constellation of passive microwave (PMW) radiometers (providing 3-hourly precipitation coverage over 80 % of the globe) is a crucial need. In this study we show the potentials and limitations of PMW products to effectively monitor precipitation combining all observations available from cross-track and conical scanning radiometers orbiting around the Earth. In this context, we have developed two PMW precipitation retrieval algorithms: the Cloud Dynamics Radiation Database algorithm (CDRD), a physically -based Bayesian algorithm for conically scanning radiometers (i.e., DMSP SSMIS, GMI) and the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross--track scanning radiometers (i.e., NOAA and MetOp-A/B AMSU- -A/MHS, and NPP Suomi ATMS). The algorithms, originally created for applications over Europe and the Mediterranean basin, have been recently extended to Africa and Southern Atlantic for application to the MSG full disk area. Microwave-only gridded data are produced by means of bilinear interpolation of the orbital instantaneous precipitation retrievals from each algorithm. We will show the analysis of surface precipitation at 0.25° x 0.25° resolution at different time scales for the period 2011-2014. A final gridded PMW precipitation product is also obtained by merging retrievals from all available radiometers. The evaluation of consistency of the 15 precipitation patterns and amounts obtained from the two different algorithms has shown a good level of coherence of daily/monthly/seasonal means. Quantitative comparisons with other global gridded dataset of monthly/daily precipitation (single and multiple satellites products, and global raingauge datasets) will be shown. The analysis shows a strong dependence on the number of daily overpasses available from each PMW sensor, and on the ability of each sensor to capture the precipitation climatology of the different regions analyzed, in relation to their environmental and meteorological conditions.