 Establishing state-of-the-art coding, documentation, configuration management standards for the AWG.  Software development process comparable with CMMI level 3 maturity while STAR works toward formal certification  Standards and guidelines are provided on the Quality Assurance page of AWG website NOAA/NESDIS/STAR is taking the lead in the activities to develop, demonstrate and recommend pre-operational algorithms for the GOES-R Level 2 product systems. Fifteen GOES-R Algorithm Working Group (AWG) teams have been formed to select the specialty area algorithms and develop the corresponding product generation systems. The Algorithm Integration Team (AIT) is building a framework that can process all the GOES-R Level 2 products. The framework being built will be used to test the algorithms individually as well as a complete system with all products. To assure the quality of the products and performance of the system in meeting the requirements, datasets and tools for monitoring the system and visualizing the products are under development based on our experience with AIRS, IASI, and GOES products. In this presentation we will describe how AIT will evaluate AWG Level 2 Product Processing System usage, as well as how to monitor, verify, and validate the AWG products. The plan and strategy to compare and integrate products from different satellite platforms will also be addressed. 4. Verification/Validation 1. INTRODUCTION 3. Monitoring/Visualization 2. Quality Standards There are total 5 deliveries to AIT (3 for 80% maturity and 2 for 100% maturity) scheduled for each AWG team. The quality assurance steps and status can be found on the AWG website. Above is an example snap shot of the webpage: Algorithms Acceptance Procedure Standard Documentation:  Algorithm Theoretical Basis Document (ATBD)  Metadata (FGDC guidelines)  Interface Control  System Description  Users Manual  Fortran Programming  C and C++ Programming  Test Plan  Algorithm Implementation Instructions  Latency Reports System Monitoring: IASI example Data Source: Before the real data is available, simulated and proxy data sets will be used for algorithm testing and verification. Matchup data sets, numerical analysis, ground observation, and in-situ campaigns will be used as datasets for validation. Most of our pre-launch algorithm validation is going to be done with products from co-located satellite sensors, such as CALIPSO/CLOUDAT. Develop and implement tools to evaluate AWG Product Processing System usage. Establish a suite of validation tools that will be used by the AWG Product Teams to monitor, verify, and validate the AWG products. Determine ways to compare and integrate products from different satellite platforms – move toward GEOSS. Website: 5. Summary Quality Assurance of the GOES-R AWG Product Processing System L. Zhou 2, Walter Wolf 1, S. Qiu 2, P. Keehn 2, Q. Guo 3, S. Sampson 3, and M. Goldberg 1 1 NOAA/NESDIS/STAR, Camp Springs, MD USA; 2 PSGS, Alexandria, VA 22311, USA; 3 IMSG, Kensington, MD 20895, USA Algorithm Reviews:  Preliminary Design Review (PDR)  Critical Design Review (CDR)  Test Readiness Review (TRR) System Monitoring: We will be running the system in the STAR collaborative environment. Tools will be built to monitor: How many CPUs are in use/idle Memory usage Input/Output usage Status of jobs Diagnostic information of the system Sub-tropical case: IASI gran # 411 and AIRS gran # 234 Techniques has been developed and validated for physical co-location of AIRS/MODIS data.  Spatially convolute MODIS to each AIRS FOV  Spectrally convolute AIRS spectra to MODIS resolution. Physical Co-location of IASI/AVHRR has been developed for METOP GEO/LEO co-location technique will be developed Products Monitoring: AIRS & IASI example Routine Product Monitoring/Visualization: Develop a visualization system to monitor the products in a routine way:  Near Real-Time Display  Daily, Weekly, Monthly Maps  Time Series of Statistics (Mean, StdDev.,RMS)  Diurnal, seasonal variations  Animations