Abstract
Much of the early record of spectrally broadband earth radiation budget (ERB) measurements was taken by the ERB instrument launched on the Nimbus-7 spacecraft in October 1978. The wide-field-of-view (WFOV) sensors measured the emitted and reflected radiation from November 1978 through January 1993, and the first nine years have been processed into a stable, long-term dataset. However, heating and cooling of the ERB experiment introduced thermal perturbations in the original measurements that were only significant in the shortwave (SW) channels. These sensors were covered by spherical filter domes to absorb incident longwave (LW) radiation. In this paper, a thermal regression model—the thermal calibration adjustment table (CAT)—is developed to track and remove these thermal signals from the SW data. The model relies on instrument temperatures within and near the surface of the ERB instrument, and the observed nonzero nighttime sensor readings represent the thermal signals. Confidence that the model is stable for daytime applications was gained by smoothing the solution using ridge regression and noting the effect on the solution coefficient vector. The bias signal produced by the thermal CAT portrays the balance of instrument heating and cooling within the Nimbus-7 variable external radiation environment. Cooling occurs over about two-thirds of an orbit including satellite night. During the nighttime, the sensor bias change is about 17 W m−2 (compare with mean daytime SW flux of about 200 W m−2) with little seasonal or annual fluctuation. Strong warming takes place during morning and evening twilight when direct solar radiation illuminates the WFOV sensors. This warming effectively compensates for nighttime cooling when the opposite thermal signature is found. Additional daytime warming occurs for satellite positions near the solar declination when the effects of combined LW and SW terrestrial fluxes exceed thermal cooling to space. However, this heating is influenced by the terrestrial scene and so it varies seasonally.
The thermal CAT was one of two semi-independent procedures, each of equal mean accuracy, developed to validate and correct for thermally induced sensor signals. The other, called the global CAT, is described in the second paper in this series. Although the thermal CAT was considered heuristically superior, the global CAT was chosen for the basic calibration work since it was thought to be potentially more stable for the production of a consistent long-term ERB dataset.
