A study of the time evolution of GERB shortwave calibration by comparison with CERES Edition-3A data

This study examines the evolution of the GERB-2 and GERB-1 Edition 1 shortwave radiance calibration between 2004-2007 and 2007-2012 respectively, through comparison with CERES instrument FM1 Edition 3A SSF instantaneous radiances. Two periods when simultaneous observations from both GERB-2 and GERB-1 were available, January 13th to February 11th 2007 and May 1st to May 10th 2007, are also compared. For these two overlap periods respectively, averaged over all CERES ‘unfiltered-to-filtered radiance ratio’ subsets, the GERB-1/CERES unfiltered radiance ratio is on average found to be 1.6% and 1.9% lower than the associated GERB-2/CERES unfiltered radiance ratio. Over the two longer time series the GERB/CERES unfiltered radiance ratio shows a general decrease with time for both GERB-2 and GERB-1. The rate of decrease varies through time but no significant seasonal dependence is seen. Averaged over all subsets the GERB-2/CERES unfiltered radiance ratio showed a decrease of 1.9% between June 2004 and June 2006. Between June 2007 and June 2012, the corresponding decrease in the GERB-1/CERES unfiltered radiance ratio was 6.5%. The evolution of the GERB/CERES unfiltered radiance ratio for both GERB-2 and GERB-1 shows a strong dependence on the CERES unfiltered-to-filtered radiance ratio, indicating that it is spectrally dependent. Further time-series analysis and theoretical work using simulated spectral radiance curves suggests that for GERB-1 the evolution is consistent with a darkening in the GERB shortwave spectral response function which is most pronounced at the shortest wavelengths. For GERB-2, no single spectral cause can be identified, suggesting that the evolution is likely due to a combination of several different effects

An assessment of the quality of aerosol retrievals over the Red Sea and evaluation of the climatological cloud-free dust direct radiative effect in the region

Ground-based and satellite observations are used in conjunction with the Rapid Radiative Transfer Model (RRTM) to assess climatological aerosol loading and the associated cloud-free aerosol direct radiative effect (DRE) over the Red Sea. Aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer and Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instruments are first evaluated via comparison with ship-based observations. Correlations are typically better than 0.9 with very small root-mean-square and bias differences. Calculations of the DRE along the ship cruises using RRTM also show good agreement with colocated estimates from the Geostationary Earth Radiation Budget instrument if the aerosol asymmetry parameter is adjusted to account for the presence of large particles. A monthly climatology of AOD over the Red Sea is then created from 5 years of SEVIRI retrievals. This shows enhanced aerosol loading and a distinct north to south gradient across the basin in the summer relative to the winter months. The climatology is used with RRTM to estimate the DRE at the top and bottom of the atmosphere and the atmospheric absorption due to dust aerosol. These climatological estimates indicate that although longwave effects can reach tens of W m−2, shortwave cooling typically dominates the net radiative effect over the Sea, being particularly pronounced in the summer, reaching 60 W m−2 at the surface. The spatial gradient in summertime AOD is reflected in the radiative effect at the surface and in associated differential heating by aerosol within the atmosphere above the Sea. This asymmetric effect is expected to exert a significant influence on the regional atmospheric and oceanic circulation

Cirrus cloud identification from airborne far-infrared and mid-infrared spectra

Airborne interferometric data, obtained from the Cirrus Coupled Cloud-Radiation Experiment (CIRCCREX) and from the PiknMix-F field campaign, are used to test the ability of a machine learning cloud identification and classification algorithm (CIC). Data comprise a set of spectral radiances measured by the Tropospheric Airborne Fourier Transform Spectrometer (TAFTS) and the Airborne Research Interferometer Evaluation System (ARIES). Co-located measurements of the two sensors allow observations of the upwelling radiance for clear and cloudy conditions across the far-and mid-infrared part of the spectrum. Theoretical sensitivity studies show that the performance of the CIC algorithm improves with cloud altitude. These tests also suggest that, for conditions encompassing those sampled by the flight campaigns, the additional information contained within the far-infrared improves the algorithm's performance compared to using mid-infrared data only. When the CIC is applied to the airborne radiance measurements, the classification performance of the algorithm is very high. However, in this case, the limited temporal and spatial variability in the measured spectra results in a less obvious advantage being apparent when using both mid-and far-infrared radiances compared to using mid-infrared information only. These results suggest that the CIC algorithm will be a useful addition to existing cloud classification tools but that further analyses of nadir radiance observations spanning the infrared and sampling a wider range of atmospheric and cloud conditions are required to fully probe its capabilities. This will be realised with the launch of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission, ESA's 9th Earth Explorer

A test of the ability of current bulk optical models to represent the radiative properties of cirrus cloud across the mid-and far-infrared

Measurements of mid- to far-infrared nadir radiances obtained from the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 aircraft during the Cirrus Coupled Cloud-Radiation Experiment (CIRCCREX) are used to assess the performance of various ice cloud bulk optical (single-scattering) property models. Through use of a minimisation approach, we find that the simulations can reproduce the observed spectra in the mid-infrared to within measurement uncertainty but are unable to simultaneously match the observations over the far-infrared frequency range. When both mid and far-infrared observations are used to minimise residuals, first order estimates of the flux differences between the best performing simulations and observations indicate a strong compensation effect between the mid and far infrared such that the absolute broadband difference is < 0.7 W m−2. However, simply matching the spectra using the mid-infrared observations in isolation leads to substantially larger discrepancies, with absolute differences reaching ~ 1.8 W m−2. These results highlight the benefit of far infrared observations for better constraining retrievals of cirrus cloud properties and their radiative impact, and provide guidance for the development of more realistic ice cloud optical models

Retrievals of high latitude surface emissivity across the infrared from high altitude aircraft flights

We present retrievals of infrared spectral surface emissivities spanning the far and mid infrared from aircraft observations over Greenland, taken at an altitude of 9.2 km above sea level. We describe the flight campaign, available measurements and the retrieval method. The principal barriers to reducing uncertainty in the emissivity retrievals are found to be instrumental noise and our ability to simultaneously retrieve the underlying surface temperature. However, our results indicate that using the instrumentation available to us it is possible to retrieve emissivities from altitude with an uncertainty of ~ 0.02 or better across much of the infrared. They confirm that the far‐infrared emissivity of snow and ice surfaces can depart substantially from unity, reaching values as low as 0.9 between 400‐450 cm‐1. They also show good consistency with retrievals from the same flight made from near‐surface observations giving confidence in the methodology used and the results obtained for this more challenging viewing configuration. To the best of our knowledge, this is the first time that far‐infrared surface emissivity has been retrieved from altitude and demonstrates that the methodology has the potential to be extended to planned satellite far‐infrared missions

Cirrus cloud identification from airborne far-infrared and mid-infrared spectra

Airborne interferometric data, obtained from the Cirrus Coupled Cloud-Radiation Experiment (CIRCCREX) and from the PiknMix-F field campaign, are used to test the ability of a machine learning cloud identification and classification algorithm (CIC). Data comprise a set of spectral radiances measured by the Tropospheric Airborne Fourier Transform Spectrometer (TAFTS) and the Airborne Research Interferometer Evaluation System (ARIES). Co-located measurements of the two sensors allow observations of the upwelling radiance for clear and cloudy conditions across the far- and mid-infrared part of the spectrum. Theoretical sensitivity studies show that the performance of the CIC algorithm improves with cloud altitude. These tests also suggest that, for conditions encompassing those sampled by the flight campaigns, the additional information contained within the far-infrared improves the algorithm’s performance compared to using mid-infrared data only. When the CIC is applied to the airborne radiance measurements, the classification performance of the algorithm is very high. However, in this case, the limited temporal and spatial variability in the measured spectra results in a less obvious advantage being apparent when using both mid- and far-infrared radiances compared to using mid-infrared information only. These results suggest that the CIC algorithm will be a useful addition to existing cloud classification tools but that further analyses of nadir radiance observations spanning the infrared and sampling a wider range of atmospheric and cloud conditions are required to fully probe its capabilities. This will be realised with the launch of the Far-infrared Outgoing Radiation Understanding and Monitoring (FORUM) mission, ESA’s 9th Earth Explorer