Validation and Error Estimation of AIRS MUSES CO Profiles with HIPPO, ATom and NOAA ESRL Aircraft Observations
Abstract
In this study we examine the uncertainties and errors in carbon monoxide (CO) retrievals from Atmospheric Infrared Sounder (AIRS) single footprint, non-cloud cleared radiances using aircraft observations. The aircraft observations are from the HIAPER Pole-to-Pole (HIPPO, 2009 - 2011) and the first three Atmospheric Tomography Mission (ATom, 2016 -2017) campaigns as well as the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL) aircraft network, taken between 2006 and 2017.
The retrievals are obtained using an optimal estimation approach using the MUlti-SpEctra, MUlti-SpEcies, MUlti-Sensors (MUSES) algorithm. MUSES leverages retrieval algorithms developed to use radiances from the Tropospheric Emissions Spectrometer (TES) on board the AURA satellite. MUSES is capable of using radiances from either one or multiple instruments. The optimal estimation method it employs provides a measure of the vertical sensitivity through the averaging kernel matrix and estimates of the uncertainties due to noise and radiative interferences from other geophysical parameters such as temperature and water vapor. Our validation methodology examines these uncertainties across a range of latitudes from the sub-polar to tropical regions over both ocean and land points. In addition, we examine the empirical and theoretical errors for select plume and background cases calculated from an ensemble of AIRS retrievals collocated with individual aircraft profiles. The main goals of this evaluation are to determine the suitability of these CO retrievals for use in monitoring global CO budgets and to reduce biases and uncertainties in chemical transport modeling studies.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMA031.0017H
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0345 Pollution: urban and regional;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 0365 Troposphere: composition and chemistry;
- ATMOSPHERIC COMPOSITION AND STRUCTURE;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES