88th Annual Meeting (20-24 January 2008)

Tuesday, 22 January 2008
NPOESS/VIIRS Cloud Top Temperature - Algorithm Performance Case Study
Exhibit Hall B (Ernest N. Morial Convention Center)
Eric Wong, Northrup Grumman Aerospace Systems, Redondo Beach., CA; and S. C. Ou
This paper describes a comparison study in cloud top temperature (CTT) between the ground based cloud radar measurements and retrieved CTT using the recently developed NPOESS/VIIRS Cloud Top Temperature algorithms for ice cloud, and the Window IR algorithm for daytime water clouds. The cirrus cloud top temperatures are retrieved by solving two nonlinear algebraic equations derived from the theory of radiative transfer for the observed radiances in the 8.55 μm and 12.0 μm bands. For daytime water cloud conditions, the Window IR method employs only the measured radiance in the 10.7 micron band. In this approach, the water cloud top temperature is retrieved by running the OSS radiative transfer model iteratively to match the measured radiance at given input of solar and viewing geometry, atmospheric conditions, cloud optical thickness and effective particle size.

Northrop Grumman Space Technology (NGST) has recently completed functional and initial verification testing of all VIIRS algorithms. Over 40 MODIS 5-minute granules, specifically selected to stress-test the VIIRS algorithms were analyzed along with global synthetic data generated in the NGST Integrated Weather Product Test Bed. Some granules were identified to have satellite overpasses over the ground based measurement sites at the DOE ARM sites and the Cloudnet sites in Europe where cloud data from the radar and/or lidar measurements were obtained. The measured cloud top heights (CTH) were then used to compare with the cloud top temperatures (CTT) retrieved with the VIIRS algorithms. Furthermore, comparisons were also made using cloud top height measurements from the Cloud Physics Lidar (CPL) flown on board of the NASA ER-2 aircraft during the CRYSTAL FACE data collection. Results from the testing of the VIIRS cloud algorithms with these datasets are shown in this presentation.

Supplementary URL: