Previous analysis of polar mesospheric clouds (PMCs) observed by Solar Backscatter Ultraviolet (SBUV) instruments found that long‐term variations in PMC brightness and occurrence frequency were anticorrelated with solar activity and that an increasing secular trend was present at most latitudes. In this paper, long‐term PMC variations are presented in terms of ice water content (IWC), a physically based variable which is easier to interpret than previously reported UV albedo values. This model‐based conversion from albedo to IWC removes most scattering angle effects. The derived long‐term PMC variations in the SBUV data set are qualitatively the same using either an empirically derived adjustment for local time effects or no adjustment (i.e., assuming cancelation of interannual variations in tidally induced amplitude and/or phase). When we use stratospheric ozone variations as a proxy for mesospheric temperature changes, as suggested by recent model studies, we can explain more of the long‐term IWC variability than if we use a linear trend. These results show that PMC ice water content in bright clouds increased rapidly from 1979 through the late 1990s and has been approximately constant from the late 1990s through 2013. The numerical value and sign of this trend during the last 15 years depend on the choice of end points and latitude band. Simultaneously, the solar response of IWC observed by SBUV has weakened during the most recent cycle in the Northern Hemisphere, but increased in the Southern Hemisphere.

This paper describes the calibration process for the Solar Backscatter Ultraviolet (SBUV) Version 8.6 (V8.6) ozone data product. Eight SBUV instruments have flown on NASA and NOAA satellites since 1970, and a continuous data record is available since November 1978. The accuracy of ozone trends determined from these data depends on the calibration and long-term characterization of each instrument. V8.6 calibration adjustments are determined at the radiance level, and do not rely on comparison of retrieved ozone products with other instruments. The primary SBUV instrument characterization is based on prelaunch laboratory tests and dedicated on-orbit calibration measurements. We supplement these results with "soft" calibration techniques using carefully chosen subsets of radiance data and information from the retrieval algorithm output to validate each instrument's calibration. The estimated long-term uncertainty in albedo is approximately ±0.8–1.2% (1σ) for most of the instruments. The overlap between these instruments and the Shuttle SBUV (SSBUV) data allows us to intercalibrate the SBUV instruments to produce a coherent V8.6 data set covering more than 32 yr. The estimated long-term uncertainty in albedo is less than 3% over this period.

New models of the Sun's irradiance variability are developed from 15 years of direct observations made by the Solar Radiation and Climate Experiment (SORCE) spacecraft from 2003 to 2017 (inclusive). Multiple linear regression parameterizes the observations in terms of facular brightening and sunspot darkening, which are the primary sources of solar irradiance variability. The facular influence is specified as a combination of a linear and nonlinear solar ultraviolet (UV) index; the addition of the nonlinear term allows better reproduction of concurrent solar cycle and rotational variability. The sunspot darkening index is calculated using sunspot observations from both the Debrecen catalog and Air Force Solar Observing Optical Network (SOON) operational sites, the former providing superior model performance. The new model of total solar irradiance variability, NRLTSI3, with the Debrecen sunspot index reproduces the direct Total Irradiance Monitor (TIM) observations better than does the NRLTSI2 model that currently specifies irradiance for the NOAA Climate Data Record (CDR); the correlation of the model and observations increases from 0.956 to 0.971, and the standard deviation of the residuals decreases from 0.124 to 0.100 W m⁻². The new model of solar spectral irradiance variability, NRLSSI3, which extends from 115 to 100,000 nm, reproduces rotational modulation in independent Ozone Monitoring Instrument (OMI) observations at near‐UV and visible wavelengths. The SATIRE model overestimates rotational modulation of near‐UV Fraunhofer spectral features because of excess facular brightness; the EMPIRE model overestimates rotational modulation at all near‐UV wavelengths.

The Earth system responds to solar variability on a wide range of timescales. Knowledge of total solar irradiance (TSI) and solar spectral irradiance (SSI) spanning minutes to centuries is needed by scientists studying a broad array of research applications. For these purposes, the NOAA National Centers for Environmental Information (NCEI) Climate Data Record Program established the Solar Irradiance Climate Data Record. Version 2 of the Naval Research Laboratory's solar variability models that are derived from and demonstrate consistency with irradiance observations specifies TSI and SSI for the Solar Irradiance Climate Data Record. We establish the veracity of the Naval Research Laboratory models on the timescales and over the wavelength range for which the Sun is known to vary and, thereby, specify the utility of these models. Through comparisons with irradiance observations and independent models, we validate NRLTSI2 estimates of TSI on solar rotational (~27‐day), solar cycle (~11‐year), and multidecadal (spacecraft era) variability timescales. Similarly, we validate NRLSSI2 estimates of SSI rotational variability in the ultraviolet through the mid‐visible spectrum. Validation of NRLSSI2 estimates at longer wavelengths, particularly in the near‐infrared, and for the full spectrum at solar cycle timescales and longer is not possible with the current observational record due to instrumental noise and instrument instability. We identify where key new data sets, such as observations from the Total and Spectral Solar Irradiance Sensor‐1, are expected to provide a fuller understanding of total and spectral solar irradiance variability on multiple timescales.