Multi-Instrument Intercalibration (MIIC) Framework: Extensions and Deployment

Improving the accuracy of the satellite-based Earth Observing System is a crucial objective for climate science. Climate quality measurements require accurate calibration. Intercalibration ties the calibration of one instrument to a more accurate, preferably SI-traceable, reference instrument by matching measurements in time, space, wavelength, and view angles. The challenge is to find and acquire these matched samples from within the large data volumes distributed across international data centers. For intercalibration typically less than 0.1 % of the data volume are required for analysis. Software tools and networking middleware are needed to intelligently select and acquire matched samples from multiple instruments on separate spacecraft. Matched instantaneous observations are also used in cloud, aerosol, and model comparative analysis studies. The Multi-Instrument Intercalibration (MIIC) Framework is a collection of software to support intercalibration and intercomparison studies within NASA and NOAA data systems.

The World Meteorological Organization (WMO) Global Space based Inter-Calibration System (GSICS) working group analyzes methods and recommends algorithms to improve the calibration of both Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO) instruments. We have implemented a number of the GSICS recommended LEO-LEO and LEO-GEO algorithms as part of the ROSES-2011 Multi-Instrument Intercalibration (MIIC) Framework. We have demonstrated the feasibility and benefit of distributed services built on top of the OPeNDAP networking middleware and server-side functions to support CAL-VAL activities. For this proposal we will extend the features of the MIIC Framework and deploy web services with access to data from both the NASA LaRC Atmospheric Sciences Data Center (ASDC) and the NOAA National Climate Data Center (NCDC) Comprehensive Large Array-data Stewardship System (CLASS). We will leverage the mature capabilities from OPeNDAP, the ASDC, the NCDC, and work performed in the earlier MIIC effort.

The MIIC aggregation services intelligently select and acquire matched data on-the-fly from both data centers. Event Prediction, Data Acquisition, and Analysis web services are used to locate, acquire, and process matched satellite observation data. Users submit instrument sampling and filtering criteria through a web interface or RESTful API. Event Prediction identifies coincident measurements with matched viewing geometries prior to data download using complex orbit propagation and spherical geometry calculations. Data Acquisition communicates with OPeNDAP-MIIC server-side functions to match measurements by resampling data onto common Earth referenced equal angle grids, instrument instantaneous field-of-views (IFOVs), or spectral grids. This combination of intelligent selection and server-side processing significantly reduces network traffic and data to process on local servers. We will demonstrate intercalibration, intercomparison, and model comparison with observations using CERES, CrIS, VIIRS, GOES, SCIAMACHY, and Observing System Simulation Experiments (OSSE) data. The MIIC Framework software will be generalized to support comparative analyses using both Level 1 and Level 2 data parameters. The Event Predictor will be extended to identify satellite instrument data over surface targets such as Libya-4 and Dome C. Histogram data analysis (1D and 2D) and additional atmospheric and surface type filtering will be added. The deployment of the MIIC Framework will enhance access to large distributed collections of multi-mission, multi-instrument data, at both NASA and Non-NASA data centers, in support of intercalibration and other comparative analysis studies.

Chris Currey - PI, Langley Research Center


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