###### Abstract  
This experiment is the first ultraviolet radiance assimilation for atmospheric ozone in the troposphere and stratosphere. The experiment has provided better understanding of which observations need to be assimilated, what bias correction scheme may be optimal, and how to obtain surface reflectance. A key element is the extension of the Community Radiative Transfer Model (CRTM) to handle fully polarized radiances, which presents challenges in terms of computational resource requirements. In this study, a scalar (unpolarized) treatment of radiances was used. The surface reflectance plays an important role in assimilating the nadir mapper (NM) radiance of the Ozone Mapping and Profiler Suite (OMPS). Most OMPS NM measurements are affected by the surface reflection of solar radiation. We propose a linear spectral reflectance model that can be determined inline by fitting two OMPS NM channel radiances at 347.6 and 371.8 nm because the two channels have near zero sensitivity on atmospheric ozone. Assimilating a transformed reflectance measurement variable, the \(N\)_value_ can overcome the difficulty in handling the large dynamic range of radiance and normalized radiance across the spectrum of the OMPS NM. It was found that the error in bias correction, surface reflectance, and neglecting polarization in radiative transfer calculations can be largely mitigated by using the two estimated surface reflectance. This study serves as a preliminary demonstration of direct ultraviolet radiance assimilation for total column ozone in the atmosphere. OMPS nadir mapper radiance assimilation; community radiative transfer model (CRTM); retrieval algorithm; surface reflectance +
Footnote †: journal: Remote Sensing  
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(MW) sounding products, which are retrieved from infrared and microwave radiances, have contributed to weather forecasting. Indeed, the algorithm including the cost function and data quality control as well as bias correction in retrieval algorithms are similar to those of direct radiance assimilation systems. However, direct radiance assimilation has two unique advantages: the best prior information and better consistencies among various observations and with the forecast system. Currently, the assimilation of ozone information from satellite-borne ultraviolet (UV) sensors is only conducted in retrieval space because of the challenge of radiative transfer modelling and the lack of accurate knowledge about UV data quality control and bias correction for direct radiance assimilation. However, if difficulties can be overcome, direct UV radiation assimilation offers several advantages compared to retrievals. Reliable prior information on ozone from the NWP 6-h forecast would greatly reduce the uncertainty that exists in retrievals. The determined ozone amount obtained directly from radiances would be more consistent with the NWP model because the NWP 6-h forecast is an important part of the cost function used for minimization. At the same time, there are a number of differences between UV radiance and microwave/infrared radiances. UV radiances are reflected solar radiation from the atmosphere and surface, while microwave and infrared (except for IR shortwave channels) radiances are emitted from the atmosphere/surface themselves. Therefore, UV radiances highly depend on both the zenith and azimuth angles of the sun and the sensor viewing direction. In addition, Solar irradiance can vary with time by 2% at 300 nm [2]. In direct radiance assimilation systems, IR and MW brightness temperatures are actually assimilated. The ratio between the maximum and minimum brightness temperatures is generally less than a factor of 2. However, the ratio between the maximum and minimum radiances for UV sensors can be larger than 100. The large difference in measurements may cause instability in deriving geophysical parameters such as ozone amount in the atmosphere.