Radiance Simulation System for OSSE

1. Radiance Simulation System for OSSE • Objectives • To evaluate the impact of observing system data under the context of numerical weather analysis and prediction • To access the data impact for those observing systems which are not yet operational. • For satellite observing systems, OSSEs provide a way to evaluate the impact of an instrument while it is still in the design or pre-flight stage • For NWP centers, radiance simulation system for OSSEs help to facilitate the development of the forward operator for the instrument and also helps to shorten the time for the new data type to be used in the current operational data assimilation systems • Progress • Learning and developing radiance simulation system of advanced sounders for OSSEs based on the system built by Kleespies (NESDIS) and Sun (QSS). • Issues • Representativeness of the background cloud information • Modeling cloud optical properties in the radiative transfer model • Modeling instrument noise, both correlated and independent • Validation of simulated radiance • Estimation of observation errors from instrument and radiative transfer model

2. Orbit Simulator • Developed based on the Science Data Processing Toolkit • Geocentric-Equatorial Coordinate System (ECI)-J2000 • Six classical orbit elements (Keplerian) • Provide satellite ephemeris and attitude data (e.g. AIRS) • Orbit is near -polar and sun-synchronous with an inclination of 98.2°. • PM satellite, each time crossing the equator going north at 1:30 P.M. • Altitude is 705 km • Geolocation Simulator • Instrument scan (navigation) pattern simulation (e.g. AIRS) • Generate geodetic latitude and longitude of each FOV • Compute zenith and azimuth of the look vector • Compute solar zenith and solar azimuth angle at the look point • Determine land fraction and surface elevation by sampling • digital elevation model (DEM) within a footprint • Surface Property Simulator • Surface properties (Ts, Ps) from nature run • Surface emissivity and reflectivity are obtained • based on the surface material properties • Seven surface materials are considered: water, ice, • two types of soils, and three types of vegetations • The contribution of each material is determined by: • IGBP land use surface classification for • vegetation types • AVHRR NDVI imagery for vegetation • and water amounts • DEM for land fraction and elevation • Atmospheric Profile Simulator • Validated high resolution atmospheric • profiles from ECMWF (nature run) • Radiative Transfer Model • Currently RTTOV V.7 is used • Will be updated to RTTOV V.8 • Can simulate a more realistic • multilevel infrared cloud • radiance Simulated Radiances

3. Simulated AIRS Observations - Preliminary 651.74 cm-1 871.31 cm-1 1040.26 cm-1 • Atmospheric profiles, surface skin temperature, surface pressure, and cloud information including cloud fraction and cloud liquid water content are provided by the ECMWF nature run (old run) • All clouds are assumed to be opaque and isotropic reflector • Instrument noise: • normal distribution with standard deviation from pre-launch values. • correlated noise is not considered yet. • Need to come up with a validation plan for simulated radiance

4. Open issues • Which instruments to simulate • Each instrument needs orbit, sensor and forward radiative transfer model • Error characteristics • Variance • Correlation • Bias • Calibration strategy • Effects of clouds/aerosol • Generalization to non-NWP instruments

5. Satellite instruments (reference observing system) • TOVS (HIRS/2, MSU, and SSU) • AMSU-A/B • AIRS • IASI • SSM/I • SSMI/S • Windsat • GOES

6. Satellite observations (new observations) • CrIS • GIFTS ? • GOES-R sounder (ABS/HES/etc.) ? • GeoSTAR ?

7. Error modeling and calibration • Variance part relatively easy • correlations and biases are not • Granularity of calibration runs • How many runs and what are the metrics of success?

8. Clouds • Everything is affected by clouds • Satellite radiances • Feature tracking winds • Lidar winds • Which clouds do we use? • RTM capabilities for semi-transparent clouds?

9. Non-NWP instruments • Important to NASA HQ • Atmospheric composition; climate • Much of this is retrieval based, some will be radiance based • Limb sounders?