Assessment of NUCAPS S-NPP CrIS/ATMS Sounding Products Using Reference and Conventional Radiosonde Observations
B. Sun, A. Reale, F. H. Tilley, M. E. Pettey, N. R. Nalli and C. D. Barnet
by IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (IEEE) at 2017-03-08
The NOAA unique combined atmospheric processing system (NUCAPS) sounding products derived from Suomi national polar-orbiting partnership (S-NPP) cross track infrared sounder/advanced technology microwave sounder (CrIS/ATMS) are assessed. This is done using collocated radiosondes from reference sites (i.e., global reference upper air network and satellite synchronized launch sites) and conventional upper air observing sites as the target data. Analysis of satellite retrieval bias and root-mean-square (rms) error, conducted on a global scale and at individual sites with representative climate regimes, indicates the NUCAPS temperature and water vapor retrieval performance meets the operational uncertainty requirements. Caution, however, is needed in this type of approach. In our empirical analyses, we find that the satellite retrieval rms error is sensitive to 1) the time mismatch in radiosonde launch and satellite overpass, particularly near the surface and tropopause for temperature and around the midtroposphere for water vapor, 2) vertical resolution differences between the satellite retrieval and radiosonde that become manifested as a larger rms error in the vicinity of the planetary boundary layer and tropopause, and 3) the accuracy of radiosonde water vapor measurements particularly in the upper troposphere and lower stratosphere where dry bias are prevalent. Examples highlighting these issues in the context of satellite data calibration and validation are provided.
B. Sun, A. Reale, F. H. Tilley, M. E. Pettey, N. R. Nalli and C. D. Barnet, "Assessment of NUCAPS S-NPP CrIS/ATMS Sounding Products Using Reference and Conventional Radiosonde Observations," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 10, no. 6, pp. 2499-2509, June 2017., doi: 10.1109/JSTARS.2017.2670504
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