A One-dimensional Variational (1DVAR) system has been developed at NOAA to process space-borne measurements. It is an iterative physical inversion system that finds a consistent geophysical solution to fit all radiometric measurements simultaneously. One of the particularities of the system is its applicability in cloudy and precipitating conditions. Although valid in principle for all sensors for which the radiative transfer model applies, it has only been tested for passive microwave sensors to date. The Microwave Integrated Retrieval System (MiRS) inverts the radiative transfer equation by finding radiometrically appropriate profiles of temperature, moisture, liquid cloud, hydrometeors as well as the surface emissivity spectrum and skin temperature. Similarly, the inclusion of the cloud and hydrometeor parameters within the inverted state vector makes the assimilation/inversion of cloudy and rainy radiances possible and therefore provides an all-weather capability to the system. Furthermore, MiRS is highly flexible and could be used as a retrieval tool (independent of NWP) or as an assimilation system when combined with a forecast field used as a first guess and/or background. In the MiRS, the fundamental products are inverted first, and then interpreted into secondary or derived products such as sea-ice concentration, snow water equivalent (based on the retrieved emissivity) rainfall rate, total precipitable water (TPW), integrated cloud liquid amount, and ice water path (based on the retrieved atmospheric and hydrometeor products). The MiRS system was implemented operationally at the U.S. National Oceanic and Atmospheric Administration (NOAA) in 2007 for the NOAA-18 satellite. It has since been extended to run for NOAA-19, Metop-A and DMSP-F16 and F18 SSMI/S. This paper gives an overview of the system and presents brief results of the assessment effort for all fundamental products and in particular, the sounding products.