Estimate of bias in Aura TES HDO/H2O profiles from comparison of TES and in situ HDO/H2O measurements at the Mauna Loa observatory
Abstract. The Aura satellite Tropospheric Emission Spectrometer (TES) instrument is capable of measuring the HDO/H2O ratio in the lower troposphere using thermal infrared radiances between 1200 and 1350 cm−1. However, direct validation of these measurements is challenging due to a lack of in situ measured vertical profiles of the HDO/H2O ratio that are spatially and temporally co-located with the TES observations. From 11 October through 5 November 2008, we undertook a campaign to measure HDO and H2O at the Mauna Loa observatory in Hawaii for comparison with TES observations. The Mauna Loa observatory is situated at 3.1 km above sea level or approximately 680 hPa, which is approximately the altitude where the TES HDO/H2O observations show the most sensitivity. Another advantage of comparing in situ data from this site to estimates derived from thermal IR radiances is that the volcanic rock is heated by sunlight during the day, thus providing significant thermal contrast between the surface and atmosphere; this thermal contrast increases the sensitivity to near surface estimates of tropospheric trace gases. The objective of this inter-comparison is to better characterize a bias in the TES HDO data, which had been previously estimated to be approximately 5 % too high for a column integrated value between 850 hPa and 500 hPa. We estimate that the TES HDO profiles should be corrected downwards by approximately 4.8 % and 6.3 % for Versions 3 and 4 of the data respectively. These corrections must account for the vertical sensitivity of the TES HDO estimates. We estimate that the precision of this bias correction is approximately 1.9 %. The accuracy is driven by the corrections applied to the in situ HDO and H2O measurements using flask data taken during the inter-comparison campaign and is estimated to be less than 1 %. Future comparisons of TES data to accurate vertical profiles of in situ measurements are needed to refine this bias estimate.