Assimilation of multiresolution radiation products into a downwelling surface radiation model: 1. Prior ensemble implementation

An ensemble-based method for deriving high-resolution estimates of downwelling broadband shortwave and longwave radiation at the Earth's surface via merger of multiresolution (in space and time) satellite-based inputs is presented. An ensemble of data-derived, multiplicative, lognormal perturbations characterizes the uncertainty structure and is subsequently used to perturb nominal estimates of radiation model inputs. The resulting ensemble of model output implicitly contains radiative flux uncertainty associated with uncertain model inputs and explicitly accounts for clear sky versus cloudy sky uncertainties. The perturbations were generated using a two-dimensional conditional turning bands algorithm that accounts for both cross correlations and spatial correlations. Verification studies using independent, ground-based observations show the ensemble to perform well and to encapsulate the majority of observations with relatively little bias. The ensemble-based scheme adequately reproduced hourly downwelling radiative fluxes (and their uncertainty) under diverse atmospheric conditions over a 14 month simulation period in the Southern Great Plains of the United States, and was shown to outperform a more traditional, scalar perturbation approach. The prior ensemble is intended for inclusion into an ensemble-based data assimilation framework presented in part 2 of this study.