Evaluation of single-footprint AIRS CH<sub>4</sub> Profile Retrieval Uncertainties Using Aircraft Profile Measurements

Abstract

<jats:p>Abstract. We evaluate the uncertainties of methane optimal estimation retrievals from single footprint thermal infrared observations from the Atmospheric Infrared Sounder (AIRS). These retrievals are primarily sensitive to atmospheric methane in the mid-troposphere through the lower stratosphere (~2 to ~17 km). We compare to in situ observations made from aircraft during the Hiaper Pole to Pole Observations (HIPPO), the NASA Atmospheric Tomography Mission (ATom) campaigns, and from the NOAA ESRL aircraft network, between the surface and 5–13 km, across a range of years, latitudes between 60 S to 80 N, and over land and ocean. After a global, pressure dependent bias correction, we find that the land and ocean have similar biases and that the reported observation error (combined measurement and interference errors) of ~27 ppb is consistent with the standard deviation between aircraft and individual AIRS observations. A single measurement has measurement (noise related) uncertainty of ~17 ppb, a ~20 ppb uncertainty from radiative interferences (e.g. from water, temperature, etc.), and ~ 30 ppb due to smoothing error, which is partially removed when making comparisons to in situ measurements or models in a way that account for this regularization. We estimate a 16 ppb validation error because the aircraft typically did not measure methane at altitudes where the AIRS measurements have some sensitivity, e.g. the stratosphere. Daily averaged AIRS measurements of at least 9 observations over spatio-temporal domains of </jats:p>

Downward Trend in Methane Detected in a Northern Colorado Oil and Gas Production Region Using AIRS Satellite Data

“…Kulawik et al. (2021) report decreases in AIRS CH 4 errors with increasing averaging times, and for a single footprint uncertainty decreases significantly for seasonal averages. They used the MUlti‐SpEctra, MUlti‐SpEcies, MUlti‐Sensors (MUSES) retrieval algorithm in their study, which differs from the algorithm used in Version 7, but a reduction in uncertainties associated with seasonal averages and multiple footprints should apply to Version 7 data as well simply because of the benefits of increased spatial and temporal sample sizes.…”

“…In their Figure 2, Kulawik et al. (2021) show the averaging kernels for nominal AIRS altitude levels for a tropical location based on the MUSES retrieval algorithm. Figure 2 from Xiong et al.…”

“…A comprehensive uncertainty analysis with a data correction such as the one described by Kulawik et al. (2021) for the MUSES retrieval was beyond the scope of our study.…”

Amazonian terrestrial water balance inferred from satellite-derived water vapor isotopes

“…The scatter in the deuterium content versus TWS/river discharge data are also likely driven by uncertainties in the river discharge data which are assumed to be 20% or larger. That said, uncertainties related to the deuterium content and gravity measurements are small relative to the other uncertainties mentioned since both are effectively precision limited, meaning that monthly averaging reduces their uncertainties 15,31,32,36 . These different effects are discussed in more detail in Methods.…”

“…The precision of a single observation of the integrated free-tropospheric deuterium content in the tropics is approximately 25 per mil 31 . Singleday averages over a ~2° latitude ×2° longitude have an uncertainty of ~8 per mil; the uncertainties in the data are somewhat correlated primarily due to the effects of temperature on the deuterium content retrieval 36 . However, further averaging is possible at monthly to seasonal time scales such that we expect the accuracy of averaged values at monthly time scales to be better than ~4 permil.…”