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Measurements of the column CH4, CO and CO2 are high priorities of the NPOESS Pre-Planned Product Improvement (P3I) data sets. Risk reduction for existing NPOESS instruments, including mitigation of daytime CO2 SWIR non-LTE effects, is also a high priority. We have proposed an NPOESS Instrument Of Opportunity (IOO) to address these priorities. It consists of two grating mapping spectrometers (GMSs). One that would acquire measurements with high spectral resolution Δv < 0.13 cm-1 of CH4, CO and H2O absorption lines in reflected sunlight in the VSWIR region 4281 to 4301 cm-1, and another for measurements with Δv < 0.30 cm-1 in the SWIR region 2355 to 2430 cm-1. The IOO will acquire spectra on a crosstrack swath from nadir to 55 degrees (about 1400 km on the ground) on footprints that are about 1.55 and 3.1 km on a side at nadir for the two GMS, respectively. The small footprint facilitates cloud screening, and identification of pollution hotspots. We use linear error analysis (LEA, based on the Rodgers [1] paper) to estimate the proposed IOO's performance. The LEA indicates that the IOO should be able to provide CH4 and CO column retrieval over sunlit land (and from ocean glitter when it is viewed) that satisfies or exceeds NPOESS P3I Environmental Data Records (EDRs) requirements in all aspects except refresh where the IOO would provide every two days vs the once per day requirement. Further, it shows the VSWIR IOO data when used in combination with the NPOESS Cross Track Infrared Sounder (CrIS) [2] data should provide: (a) CO profile data with sensitivity to CO in near surface air that is enhanced compared to that in the current TERRA-MOPITT, ACQUA-AIRS and AURA-TES data sets because these are limited to thermal infrared measurements that lack sensitivity to CO in near surface air layer where there is little contrast between the air temperature and the ground surface temperature, (b) CH4 profile with sensitivity in the near surface air layer that is crucial for identifying CH4 sources/sinks (c) and significant improvement in the CrIS retrieved humidity in the near surface layer of air. We show the SWIR IOO data can be used for CO2 column retrieval with near surface air layer sensitivity in the daytime. And also that in combination with CrIS SWIR data facilitates CO2 SWIR non-LTE mitigation that is required for advanced sounding quality temperature profile (TP) retrieval from CO2 SWIR data in daytime conditions. This provides risk reduction in case of degradation in the CrIS LWIR region data.
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