Establishment of AIRS Climate-Level Radiometric Stability using Radiance Anomaly Retrievals of Minor Gases and SST

Abstract

Abstract. Temperature, H2O, and O3 profiles, as well as CO2, N2O, CH4, CFC12, and SST scalar anomalies are computed using a clear subset of AIRS observations over ocean for the first 16-years of NASA's EOS-AQUA AIRS operation. The AIRS Level 1c radiances are averaged over 16 days and 40 equal-area zonal bins and then converted to brightness temperature anomalies. Geophysical anomalies are retrieved from the brightness temperature anomalies using a relatively standard optimal estimation approach. The CO2, N2O, CH4, and CFC12 anomalies are derived by applying a vertically uniform multiplicative shift to each gas in order to obtain an estimate for the ngas mixing ratio. The minor gas anomalies are compared to the NOAA ESRL in-situ values and used to estimate the radiometric stability of the AIRS radiances. Similarly the retrieved SST anomalies are compared to the SST values used in the ERA-Interim reanalysis and to NOAA's OISST SST product. These inter-comparisons strongly suggest that many AIRS channels are stable to better than 0.02 to 0.03 K/Decade, well below climate trend levels, indicating that the AIRS blackbody is not drifting. However, detailed examination of the anomaly retrieval residuals (observed minus computed) show various small unphysical shifts that correspond to AIRS hardware events (shutdowns, etc.). Some examples are given highlighting how the AIRS radiances stability could be improved, especially for channels sensitive to N2O and CH4. The AIRS short wave channels exhibit larger drifts that make them unsuitable for climate trending, and they are avoided in this work. The AIRS Level 2 surface temperature retrievals only use short wave channels. We summarize how these short wave drifts impacts recently published comparisons of AIRS surface temperature trends to other surface climatologies.

Identification of Short and Long‐Lived Atmospheric Trace Gases From IASI Space Observations

“…In contrast, whitening is immediate, does not require an inverse model nor the ability of a forward model to account for all the observed features, and can be applied on spectral ranges of any size. Likewise, in a more traditional analysis of trends in high resolution infrared spectra (Brindley et al., 2015; Strow & DeSouza‐Machado, 2020), it is very challenging to deal properly with variations of O 3 , CH 4 , CO 2 , or H 2 O due to, for example, natural temporal variations, variations in temperature or sampling biases related to clouds; whereas these are dealt with automatically using the whitening technique.…”

SI-Traceability and Measurement Uncertainty of the Atmospheric Infrared Sounder Version 5 Level 1B Radiances

“…The on-orbit verification and validation of the radiometric calibration of AIRS is performed by comparison of AIRS measurements to scene targets such as sea surface temperature (SST) [30], trace gas concentrations [14], and by comparison to other instruments [31]. In these cases, agreement is seen to be better than 200 mK 1-sigma.…”

“…The AIRS radiances at the 1231 cm -1 window channel show excellent stability relative to independent SST estimates, with a drift of less than 0.2-0.3 mK/decade, from 2002 to 2019 [13]. Using retrievals of trace gases from AIRS compared to in situ measurements allows the estimation of radiance trends of several AIRS channels to as good as 0.02-0.03 mK/decade [14]. Trending over the AIRS timeframe may not require knowledge of the measurement uncertainty; however, when combining AIRS with other data sets, or establishing a benchmark, an estimate of the measurement uncertainty is essential.…”

“…Rigorous quantification of the uncertainties relative to SI standards will enable the benchmarking of the AIRS radiances, enabling trends over long periods, in the event of a break in continuity of similar IR sounder measurements.The AIRS instrument meets the three primary elements identified in the Guidelines for Radiometric Calibration of Electro-Optical Instruments for Remote Sensing [24] as the foundation of an effective calibration: (1) traceability, (2) measurement uncertainty, and (3) verification and validation. Verification and validation of AIRS Level 1B radiances using vicarious calibration of the Earth scene can be found in the literature [13,14]. The SI-traceability, as defined in the Joint Committee for Guides in Metrology (JCGM) the Vocabulaire international de métrologie (VIM) [25] and the Guide to the expression of Uncertainty of Measurement (GUM) [26], requires an unbroken chain of calibrations, each contributing measurement uncertainty.…”

Radiometrically Consistent Climate Fingerprinting Using CrIS and AIRS Hyperspectral Observations

“…An "average-then-retrieve" approach was used by Strow and DeSouza-Machado to derive atmospheric minor gases and ocean skin temperature anomalies from 16 years of real AIRS observations [26]. However, their study was limited to the clear sky subset of AIRS observations.…”