Surface spectral emissivity plays an important role in the polar radiation budget. The significance of surface emissivity in the far‐infrared (far‐IR) has been recognized by recent studies, yet there have been no observations to constrain far‐IR surface spectral emissivity over the entire polar regions. In preparation for the Polar Radiant Energy in the Far‐InfraRed Experiment (PREFIRE) mission, this study develops and assesses an optimal estimation‐based retrieval algorithm to estimate both mid‐IR and far‐IR polar surface emissivity from the future PREFIRE measurements. Synthetic PREFIRE spectra are simulated by feeding the ERA5 reanalysis and a global surface emissivity data set to a radiative transfer model. Information content analysis indicates that the far‐IR surface emissivity retrievals can be more influenced by the atmospheric water vapor abundance than the mid‐IR counterparts. When the total column water vapor is above 1 cm, the far‐IR surface emissivity retrievals largely rely on the a priori constraints. Performance of the optimal‐estimation algorithm is assessed using 960 synthetic PREFIRE clear‐sky radiance spectra over the Arctic. The results based on current best estimate of instrument performance show that all retrievals converge within 15 iterations, the retrieved surface spectral emissivity has a mean bias within ±0.01 and a root‐mean‐square error less than 0.024. The far‐IR surface emissivity retrievals are much more affected by the a priori choice than the mid‐IR ones. A properly constructed a priori covariance can also help to improve the computational efficiency. Influences of other factors for future operational retrievals are also discussed.

The far-IR spectrum plays an important role in the earth’s radiation budget and remote sensing. The authors compare the near-global (80°S–80°N) outgoing clear-sky far-IR flux inferred from the collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations in 2004 with the counterparts computed from reanalysis datasets subsampled along the same satellite trajectories. The three most recent reanalyses are examined: the ECMWF Interim Re-Analysis (ERA-Interim), NASA Modern-Era Retrospective Analysis for Research and Application (MERRA), and NOAA/NCEP Climate Forecast System Reanalysis (CFSR). Following a previous study by X. Huang et al., clear-sky spectral angular distribution models (ADMs) are developed for five of the CERES land surface scene types as well as for the extratropical oceans. The outgoing longwave radiation (OLR) directly estimated from the AIRS radiances using the authors’ algorithm agrees well with the OLR in the collocated CERES ... AbstractThe far-IR spectrum plays an important role in the earth’s radiation budget and remote sensing. The authors compare the near-global (80°S–80°N) outgoing clear-sky far-IR flux inferred from the collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations in 2004 with the counterparts computed from reanalysis datasets subsampled along the same satellite trajectories. The three most recent reanalyses are examined: the ECMWF Interim Re-Analysis (ERA-Interim), NASA Modern-Era Retrospective Analysis for Research and Application (MERRA), and NOAA/NCEP Climate Forecast System Reanalysis (CFSR). Following a previous study by X. Huang et al., clear-sky spectral angular distribution models (ADMs) are developed for five of the CERES land surface scene types as well as for the extratropical oceans. The outgoing longwave radiation (OLR) directly estimated from the AIRS radiances using the authors’ algorithm agrees well with the OLR in the collocated CERES ...

Cloud phase is an important factor affecting cloud contributions to the polar energy budget. Brightness temperature differences (BTDs) between two mid‐infrared (mid‐IR) spectral channels are commonly used in satellite remote sensing to determine the cloud phase, but the mid‐IR has limitations for cloud phase determination in polar regions. This study explores the synergy between the far‐ and mid‐IR for ice cloud phase determinations over polar oceans. A far‐IR BTD test (BTD_449‐521) is developed based on the spectral variations of both ice cloud scattering and absorption properties in the far‐IR “dirty window” region (400–600 cm⁻¹ or 16.7–25 μm). Synthetic IR radiances at 1 cm⁻¹ spectral resolution are generated using ERA5 reanalysis data for both polar regions. A subset of these spectra is used to compare the ice phase determination skill of the far‐IR test with an “AIRS‐Like” mid‐IR BTD test (BTD_1231‐960) for combinations of effective ice particle diameter (D_{eff_ice}), cloud optical depth (COD), and cloud top pressure (CTP). The far‐IR test is performing better for ice clouds with the smallest D_{eff_ice} that we have studied (20 μm) due to the sensitivity of far‐IR scattering to ice particle size. The mid‐IR test was either comparable to or more successful than the far‐IR test for ice clouds with large particle sizes. For all D_{eff_ice}, increasing COD leads to enhanced far‐IR BTD signals due to stronger multiple scattering in the far‐IR than in the mid‐IR. Overall, the variations in far‐IR and mid‐IR BTD test performance are strongly sensitive to D_{eff_ice}, followed by COD and CTP.

Cloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-μm brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat + Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model. Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-μm channel is located at optical depth ~0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between −30 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-μm brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6–10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

Atmospheric Infrared Sounder (AIRS) aboard the National Aeronautics and Space Administration (NASA) Aqua satellite has been operating since September 2002. Its information content, superb instrument performance, and dense sampling pattern make the AIRS radiances an invaluable data set for climate studies. The trends of global‐mean, nadir‐view, clear‐sky AIRS radiances from 2003 to 2020 are studied here, together with the counterparts of synthetic radiances based on two reanalyzes, European Centre for Medium‐Range Weather Forecasts Reanalysis V5 (ECMWF ERA5) and NASA Goddard Earth Observing System V5.4.1 (GEOS‐5.4.1; a reanalysis product without assimilation of hyperspectral radiances such as AIRS). The AIRS observation shows statistically significant negative trends in most of its CO₂ channels, positive but non‐significant trends in the channels over the window regions, and statistically significant positive trends in some of its H₂O channels. The best agreements between observed and simulated radiance trends are seen over the CO₂ tropospheric channels, while the observed and simulated trends over the CO₂ stratospheric channels are opposite. ERA5 results largely agree with the AIRS observation over the H₂O channels. The comparison in the H₂O channels helps reveal a data continuity issue in the GEOS‐5.4.1. Contributions from individual variables to the radiance trends are also assessed by performing separate simulations. This study provides the first synopsis of the global‐mean trend of AIRS radiances over all its thermal‐IR channels.

Greenhouse gas (GHG) additions to Earth's atmosphere initially reduce global outgoing longwave radiation, thereby warming the planet. In select environments with temperature inversions, however, increased GHG concentrations can actually increase local outgoing longwave radiation. Negative top of atmosphere and effective radiative forcing (ERF) from this situation give the impression that local surface temperatures could cool in response to GHG increases. Here we consider an extreme scenario in which GHG concentrations are increased only within the warmest layers of winter near‐surface inversions of the Arctic and Antarctic. We find, using a fully coupled Earth system model, that the underlying surface warms despite the GHG addition exerting negative ERF and cooling the troposphere in the vicinity of the GHG increase. This unique radiative forcing and thermal response is facilitated by the high stability of the polar winter atmosphere, which inhibit thermal mixing and amplify the impact of surface radiative forcing on surface temperature. These findings also suggest that strategies to exploit negative ERF via injections of short‐lived GHGs into inversion layers would likely be unsuccessful in cooling the planetary surface.