| Abstract: |
The NOAA Microwave Integrated Retrieval System (MiRS) system has been implemented operationally at the U.S. National Oceanic and Atmospheric Administration (NOAA) since 2007 and has been generating many environmental data records (i.e. satellite products) for NOAA-18, NOAA-19, ATMS, Metop-B, SSMIS, AMSR-2, and GMI. The satellite products are atmospheric profiles of temperature and water vapor, cloud liquid water, ice water content, rainfall rate, snow cover and snow water equivalent, snow fall rate, surface temperature and microwave emissivity, and sea ice concentration.
The MiRS is based on 1D-VAR retrieval algorithm which includes the Community Radiative Transfer Model (CRTM) for computing radiances and the gradient of radiance (or Jacobian), and a scheme for minimizing the cost function that weighs the relative contribution of background (a priori) information and satellite observations. 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. In order to be generic, the MiRS system adds a state vector for surface emissivity to automatically consider various surface properties. The inclusion of the emissivity spectrum in the state vector makes the system applicable globally, with the only differences between land, ocean, sea ice, and snow backgrounds residing in the covariance matrix chosen to spectrally constrain the emissivity. 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, it provides an all-weather capability to the system. Furthermore, MiRS is highly flexible, and it could be used as a retrieval tool (independent of numerical weather prediction) or as an assimilation system when combined with a forecast field used as a first guess and/or background.
In this presentation, we will overview the MiRS system, validations, and operational applications. There are a number of recent improvements to the MiRS system. The snow water equivalent retrieval is improved by the implementation of forest fraction emissivity correction. The light rain detection over land is improved by adding cloud liquid water (CLW) and rain water path (RWP) into the rain rate formula. By Implementing new land surface background covariance based on updated CRTM and ECMWF analysis data, the retrieved land surface emissivity are largely improved in comparing with analytical emissivity based on ECMWF data. Both the retrieved temperature and water vapor profiles over ocean are improved by using the atmospheric covariance matrices based on ECMWF 137 level dataset. MiRS is also extended to GPM/GMI. The MiRS retrieval based on GPM/GMI has become operational. TPW retrieval over land based on GPM/GMI data is largely improved by adjusting the MiRS Tuning file.
The MiRS system has also been used in the retrieval of atmospheric parameters for CubeSat. |
