The infrared window region (780-1250 cm-1, 12.8 to 8.0 µm) is of great importance to Earth’s climate due to its high transparency and thermal energy. We present here a new investigation of the transparency of this spectral region based on observations by interferometers of downwelling surface radiance at two DOE Atmospheric Radiation Measurement program sites. We focus on the dominant source of absorption in this region, the water vapor continuum, and derive updated values of spectral absorption coefficients for both the self and foreign continua. Our results show that the self continuum is too strong in the previous version of Mlawer-Tobin_Clough-Kneizys-Davies (MT_CKD) water vapor continuum model, a result that is consistent with other recent analyses, while the foreign continuum is too weak in MT_CKD. In general, the weaker self continuum derived in this study results in an overall increase in atmospheric transparency in the window, although in atmospheres with low amounts of water vapor the transparency may slightly decrease due to the increase in foreign continuum absorption. These continuum changes lead to a significant decrease in downwelling longwave flux at the surface for moist atmospheres and a modest increase in outgoing longwave radiation. The increased fraction of surface-leaving radiation that escapes to space leads to a notable increase (~5-10%) in climate feedback, implying that climate simulations that use the new infrared window continuum will show somewhat less warming than before. This study also points out the possibly important role that aerosol absorption may play in the longwave radiative budget.

Changes in the concentration of greenhouse gases within the atmosphere lead to changes in radiative fluxes throughout the atmosphere. The value of this change, called the instantaneous radiative forcing, varies across climate models, due partly to differences in the distribution of clouds, humidity, and temperature across models, and partly due to errors introduced by approximate treatments of radiative transfer. This paper describes an experiment within the Radiative Forcing Model Intercomparision Project that uses benchmark calculations made with line-by-line models to identify parameterization error in the representation of absorption and emission by greenhouse gases. The clear-sky instantaneous forcing by greenhouse gases to which the world has been subject is computed using a set of 100 profiles, selected from a re-analysis of present-day conditions, that represent the global annual mean forcing with sampling errors of less than 0.01 \si{\watt\per\square\meter}. Six contributing line-by-line models agree in their estimate of this forcing to within 0.025 \si{\watt\per\square\meter} while even recently-developed parameterizations have typical errors four or more times larger, suggesting both that the samples reveal true differences among line-by-line models and that parameterization error will be readily resolved. Agreement among line-by-line models is better in the longwave than in the shortwave where differing treatments of the water vapor vapor continuum affect estimates of forcing by carbon dioxide and methane. The impacts of clouds on instantaneous radiative forcing are roughly estimated, as are adjustments due to stratospheric temperature change. Adjustments are large only for ozone and for carbon dioxide, for which stratospheric cooling introduces modest non-linearity.

This paper describes the initial implementation of a new toolbox that seeks to balance accuracy, efficiency, and flexibility in radiation calculations for dynamical models. The toolbox consists of two related code bases: Radiative Transfer for Energetics (RTE), which computes fluxes given a radiative transfer problem defined in terms of optical properties, boundary conditions and source functions, and RRTM for GCM applications - Parallel (RRTMGP), which combines data and algorithms to map a physical description of the gaseous atmosphere into such a radiative transfer problem. The toolbox is an implementation of well-established ideas, including the use of a k-distribution to represent the spectral variation of absorption by gases and the use of two-stream, plane-parallel methods for solving the radiative transfer equation. The focus is instead on accuracy, by basing the k-distribution on state-of-the-art spectroscopy, and on the sometimes-conflicting goals of flexibility and efficiency. Flexibility is facilitated by making extensive use of computational objects encompassing code and data, the latter provisioned at run time and potentially tailored to specific problems. The computational objects provide robust access to a set of high-efficiency computational kernels that can be adapted to new computational environments. Accuracy is obtained by careful choice of algorithms and through tuning and validation of the k-distribution against benchmark calculations. Flexibility with respect to the host model implies user responsibility for maps between clouds and aerosols and the radiative transfer problem, although comprehensive examples are provided for clouds.