Short-term Prediction Research
and Transition Center

Modeling & Data Assimilation Projects

AIRS Radiance Assimilation

Recently, SPoRT has begun to investigate radiance assimilation within the regional modeling framework. SPoRT, in cooperation with the NASA/NOAA/DoD JCSDA and NCEP/EMC, has begun to utilize the Gridpoint Statistical Interpolation (GSI) 3D-VAR analysis system, which is used operationally by NCEP for the NAM data assimilation system and will shortly be the operational GFS data assimilation system. This system, as well as access to NCEP resources, has allowed for the ability to reproduce an operational run-time environment. The GSI system is a sophisticated 3D-VAR scheme supported by NASA and NOAA. This united effort allows for the accelerated transition of improvements among agencies.

SPoRT efforts in radiance assimilations are focused on the utilization of atmospheric infrared sounder (AIRS) hyperspectral radiance measurements within the regional framework, specifically within that of the WRF-Nonhydrostatic Mesoscale Model (NMM) model, which is the operational North American Modem (NAM). The AIRS instrument is a grating spectrometer measuring 2378 channels from 3.7 to 15.4 µm. This instrument, which is proving measurements used to deduce a far greater analysis of vertical detail of the atmosphere, has shown great improve global forecasts by the JCSDA. SPoRT is working to demonstrate the utility of these measurements in the regional analysis/modeling framework.

In addition to the utility of these measurements, the optimal use of these measurements is being investigated. The CO2 sorting technique has been implemented within the GSI framework to maximize the use of uncontaminated radiances above low-level clouds, where the data within the measurements is most meteorologically significant. Similarly, since the use of the radiances within a regional modeling framework is being considered, spatial thinning methodologies must be addressed. The use of AIRS measurements in the global system imposes thinning methodologies, due to the high volume of AIRS data globally. These methodologies need to be readdressed for use in the NAM domain. A flow chart illustrating the overall scope of this research is shown.