1 Geostationary Cloud Algorithm Testbed (GEOCAT) Processing Mike Pavolonis and Andy Heidinger (NOAA/NESDIS/STAR) Corey Calvert and William Straka III (UW-CIMSS)

2 Outline History/background Description of Capabilities Limitations Future Plans Availability

3 History/Background GEOCAT was developed by the AWG Cloud Application Team for testing prospective GOES-R cloud algorithms. Cloud algorithms require the use of many channels and much ancillary data. GEOCAT is therefore capable of running many non-cloud algorithms. In recognition of this, other AWG teams are already utilizing GEOCAT for their own development work (e.g. winds, land). We were directed by the AWG to incorporate all compatible CIMSS algorithms into GEOCAT. This work is just beginning. We are considering changing the C in GEOCAT from Cloud to something more general (e.g. Community, Comprehensive, etc…).

4 GEOCAT Capabilities (1) GEOCAT’s Philosophy: Provide navigated and calibrated geostationary imager radiances, ancillary data (e.g. NWP, surface maps, etc…), and fast model generated clear sky radiance data structures to product producing subroutines (e.g. algorithms), and to provide a common algorithm output structure, whose definition is transparent to the algorithm developer. Major benefits of design: 1). Allows for multiple algorithms for the same and/or different products to be processed with a single invocation of the GEOCAT executable. 2). Adding new algorithms is simple. 3). The code is self-optimizing so that no unnecessary calculations or IO are performed. 4). The user specifies which of the available algorithms to run. Supported GEO platforms: GVAR (e.g. GOES 8-15 imagers), MSG (SEVIRI), and MTSAT.

5 Algorithm developer fills out template which passes information to algorithm interface GEOCAT Pointer to algorithm procedure Number of data pointers to allocate Textual algorithm description info. List of pointer names to allocate Output indicator flag Cloud mask and cloud phase dependency NWP and RTM dependency Ancillary data directory path Channel dependency

6 GEOCAT Capabilities (2) Several generic utility functions are available to algorithm developers such as, matrix inversion, interpolation, atmospheric profile utilities, spatial uniformity, etc… Instrument dependant Planck function is available to the algorithm developer. GEOCAT allows data from previous or “future” times to be easily loaded into memory so that algorithms can take advantage of the temporal resolution of geostationary data.

7 Flexible Spatial Domain Full Domain Satellite Zenith Defined Domain Line/Element Defined Domain The spatial domain is defined at run-time

8 GEOCAT Conceptual Model -Satellite Images -Ancillary Data GEOCAT Navigation and Calibration Map ancillary data to pixel level Calculate clear sky radiances (if needed) Execute lower order algorithms Execute higher order algorithms L1 (radiances) L2 (pixel-level products) RTM (clear radiances) Calibrated/navigated radiances and ancillary data are loaded into data structures that can be accessed by algorithms Output from high order algorithms is available to lower level algorithms

9 Ancillary Data Parameter: Global NWP fields (e.g. temperature, water vapor, ozone, etc…) Source: GFS or GDAS Native Spatial Resolution: 0.5 or 1.0 degree Time Resolution: 6-hours Note: The vertical profile variable are interpolated to the standard 101 AIRS levels

10 Ancillary Data Parameter: Surface emissivity (for channels ) Source: Seeman and Borbas (2006) Native Spatial Resolution: 5-km Time Resolution: monthly mean

11 Ancillary Data Parameter: Surface elevation Source: GTOPO-30 Native Spatial Resolution: 8-km Time Resolution: static

12 Ancillary Data Parameter: Surface land type Source: AVHRR-based from UMD Native Spatial Resolution: 1-km Time Resolution: static

13 Ancillary Data Parameter: Snow/ice mask Source: IMS - Northern Hemisphere, SSMI - Southern Hemisphere Native Spatial Resolution: 4-km (Northern Hemisphere), 25-km (Southern Hemisphere) Time Resolution: daily

14 Ancillary Data Parameter: Coast mask Source: NASA Native Spatial Resolution: 1-km Time Resolution: static Notes: Coast mask indicates distance from coast ( km), as sensitivity to coastline will vary from application to application

15 Ancillary Data Parameter: Volcano mask Source: Smithsonian Native Spatial Resolution: 1-km Time Resolution: static Notes: These data indicate how close a given satellite pixel is to a volcano

16 Ancillary Data Parameter: Climatological sea surface temperature Source: OISST Native Spatial Resolution: 1-degree Time Resolution: monthly mean Notes: Higher resolution SST from 0.5 GFS is used when available

17 Infrared Radiative Transfer Model For each channel in memory, the following is available: Clear sky TOA radiances and brightness temperatures Atmospheric transmittances and radiance profiles at 101 levels Currently, only PFAST (Woolf, CIMSS) is available in GEOCAT. We plan on adding the CRTM once shortwave, cloudy RTM, and trace gas updates have been made.

18 RTM Bias Analysis RTM bias analysis shows expected behavior (based on prior experience), which gives confidence that the RTM/NWP fields are implemented properly in GEOCAT. Water Land

19 Example Usage./geocat -verbose -maxsatzen 70 -nscans 200 -use_seebor -use_snow \ -area_dir./ -l1_dir./ -l2_dir./ -dumpch \ -a 2 4 -f met08_disk_1_2006_015_1200.area.gz Command-line arguments are used to specify run-time options. L1 Output L2 Output

20 Known GEOCAT Limitations Limited built-in algorithm precedence No surface reflectance ancillary data No built-in shortwave radiative transfer procedures CRTM is not yet installed in GEOCAT (we are waiting for additional updates - e.g. SW RTM, cloudy RTM, trace gases) GEOCAT does not produce Level 3 (e.g. gridded) data Only tested with Intel Fortran 90 compiler

21 Near-term Plan Our interpretation is that all compatible CIMSS AWG algorithms will be delivered to the AIT via GEOCAT. We are beginning to coordinate this effort with the CIMSS PI’s. At this point, we do not know of any CIMSS algorithms that are not compatible. This will be confirmed when the funding kicks off. We are also beginning to develop GEOCAT documentation. The AIT will determine GEOCAT’s role, beyond delivering CIMSS algorithms.

22 GEOCAT Availability Several groups at CIMSS and the Winds AWG are using GEOCAT. We would prefer non-CIMSS usage to be coordinated through the AIT. The version of GEOCAT used to implement and deliver CIMSS algorithms will be delivered to the AIT. AIT requirements on GEOCAT prior to the delivery of CIMSS algorithms needs to be determined.