MiRS (Microwave Integrated Retrieval System), which is the official NOAA operational microwave-only retrieval system, is a one-dimensional variational inversion algorithm (1DVAR) (Boukabara et al. 2011, 2013) that employs the Community Radiative Transfer Model (CRTM) as the forward and adjoint operators. It simultaneously solves for surface (Tskin, emissivity), and atmospheric parameters (temperature, water vapor, non-precipitating cloud and hydrometeor profiles). The 1DVAR algorithm uses an iterative approach in which a solution is sought that best fits the observed satellite radiances, subject to other a priori constraints. By explicitly treating the scattering and absorption processes due to both liquid and solid precipitation-sized particles in the forward and adjoint calculation, the MiRS algorithm is able to converge to a realistic solution in rainy as well as non-rainy conditions. A post-processing step is then performed to determine a number of additional derived surface and atmospheric parameters, including precipitation rate. The precipitation rate determination is sensor-independent in that the same relationships (determined off-line using numerical weather prediction model simulations) between the surface precipitation rate and the retrieved vertical hydrometeor profiles are used throughout. MiRS is currently being run operationally at NOAA for Suomi-NPP/ATMS, POES N18, N19, Metop-A, Metop-B/AMSUA-MHS, DMSP-F17, F18/SSMIS, and Megha-Tropiques/SAPHIR. In 2015, an updated version of MiRS (v11.1) was implemented in operational processing of SNPP/ATMS, replacing the previous version which had been run in operations since shortly after the launch of SNPP in 2012. It has also recently been extended to process data from Global Precipitation Mission (GPM)/GMI, and will be further extended to data from JPSS-1(N20)/ATMS in anticipation of launch in Spring 2017.
In this paper we will report on assessment and validation of the MiRS precipitation rate product, including comparisons with ground-based measurements such as the Stage IV radar-gauge product, with a particular emphasis on results from Suomi-NPP/ATMS, and GPM/GMI. Evaluations will be based on performance seen over both short-term (intraseasonal) and longer-term (interseasonal) time periods. Performance assessments at both low and high rain rates, and over land and ocean will be presented. Additionally, contingency-based metrics such as probability of detection and false alarm rate will also be presented. Examination of individual case studies will also highlight the unique capabilities of the MiRS algorithm to characterize the 3-dimensional structure of larger storm systems. Additional discussion will focus on potential avenues for improvement based on results from validation and sensitivity testing.