Evaluation of MOPITT Version 7 joint TIR–NIR XCOretrievals with TCCON

Atmospheric Measurement Techniques

Helen M. Worden¹  Rebecca R. Buchholz¹  Nicholas M. Deutscher²  David W. T. Griffith²  Voltaire A. Velazco³  Bianca C. Baier⁴  Colm Sweeney⁴  Sébastien Roche⁵  Kimberly Strong⁵  Tai-Long He⁵  Debra Wunch⁵  Dylan B. A. Jones⁵  Jacob K. Hedelius⁵  Coleen M. Roehl⁶  Paul O. Wennberg⁷  Matthäus Kiel⁸  Manvendra K. Dubey⁹  Rigel Kivi^1,10  Justus Notholt^1,11  Matthias Schneider^1,12  Frank Hase^1,12  Markus Rettinger^1,13  Ralf Sussmann^1,13  Kei Shiomi^1,14  Wei Wang^1,15  Pascal Jeseck^1,16  Yao Té^1,16  Dietrich G. Feist^1,17  Laura T. Iraci^1,18  Isamu Morino^1,19  Hirofumi Ohyama^1,19  Thorsten Warneke^1,19  Young-Suk Oh^2,20  David F. Pollard^2,21  Martine De Mazière^2,22  Osamu Uchino^2,23  Cheng Liu^2,23 

[1]Atmospheric Chemistry Observations & Modeling, National Center for Atmospheric Research, Boulder, Colorado, USA

[2]Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Northfields Ave., Wollongong, NSW 2522, Australia

[3]Centre for Atmospheric Chemistry, School of Earth, Atmospheric and Life Sciences, University of Wollongong, Northfields Ave., Wollongong, NSW 2522, Australia

[4]Oscar M. Lopez Center for Climate Change Adaptation and Disaster Risk Management Foundation, Inc., Pasig City, Philippines

[5]Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado, USA

[6]NOAA Earth System Research Laboratory, Boulder, Colorado, USA

[7]Department of Physics, University of Toronto, Toronto, Canada

[8]Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA

[9]Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA

[10]Division of Engineering and Applied Science, California Institute of Technology, Pasadena, California, USA

[11]Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USA

[12]Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA

[13]Earth and Environmental Sciences, Los Alamos National Laboratory, Los Alamos, New Mexico, USA

[14]Finnish Meteorological Institute, Sodankylä, Finland

[15]Institute of Environmental Physics, University of Bremen, Bremen, Germany

[16]Institute of Meteorology and Climate Research (IMK-ASF), Karlsruhe Institute of Technology, Karlsruhe, Germany

[17]Institute of Meteorology and Climate Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany

[18]Japan Aerospace Exploration Agency, 2-1-1 Sengen, Tsukuba, Ibaraki, Japan

[19]Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei, 230031, China

[20]LERMA-IPSL, Sorbonne Université, CNRS, Observatoire de Paris, PSL Université, 75005, Paris, France

[21]Lehrstuhl für Physik der Atmosphäre, Ludwig-Maximilians-Universität München, Munich, Germany

[22]Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt, Oberpfaffenhofen, Germany

[23]Max Planck Institute for Biogeochemistry, Jena, Germany

[24]NASA Ames Research Center, Mountain View, California, USA

[25]National Institute for Environmental Studies (NIES), Tsukuba, Japan

[26]National Institute of Meteorological Sciences 33, Seohobuk-ro, Seogwipo-si, Jeju-do 63568, Republic of Korea

[27]National Institute of Water and Atmospheric Research, Lauder, New Zealand

[28]Royal Belgian Institute for Space Aeronomy (BIRA-IASB), Brussels, 1180, Belgium

[29]School of Earth and Space Sciences, University of Science and Technology of China, Hefei, 230026, China

DOI  :  10.5194/amt-12-5547-2019

来源: publisher

【 摘 要 】

Observations of carbon monoxide (CO) from the Measurements Of Pollution In The Troposphere (MOPITT) instrument aboard the Terra spacecraft were expected to have an accuracy of 10 % prior to the launch in 1999. Here we evaluate MOPITT Version 7 joint (V7J) thermal-infrared and near-infrared (TIR–NIR) retrieval accuracy and precision and suggest ways to further improve the accuracy of the observations. We take five steps involving filtering or bias corrections to reduce scatter and bias in the data relative to other MOPITT soundings and ground-based measurements. (1) We apply a preliminary filtering scheme in which measurements over snow and ice are removed. (2) We find a systematic pairwise bias among the four MOPITT along-track detectors (pixels) on the order of 3–4 ppb with a small temporal trend, which we remove on a global scale using a temporally trended bias correction. (3) Using a small-region approximation (SRA), a new filtering scheme is developed and applied based on additional quality indicators such as the signal-to-noise ratio (SNR). After applying these new filters, the root-mean-squared error computed using the local median from the SRA over 16 years of global observations decreases from 3.84 to 2.55 ppb. (4) We also use the SRA to find variability in MOPITT retrieval anomalies that relates to retrieval parameters. We apply a bias correction to one parameter from this analysis. (5) After applying the previous bias corrections and filtering, we compare the MOPITT results with the GGG2014 ground-based Total Carbon Column Observing Network (TCCON) observations to obtain an overall global bias correction. These comparisons show that MOPITT V7J is biased high by about 6 %–8 %, which is similar to past studies using independent validation datasets on V6J. When using TCCON spectrometric column retrievals without the standard airmass correction or scaling to aircraft (WMO scale), the ground- and satellite-based observations overall agree to better than 0.5 %. GEOS-Chem data assimilations are used to estimate the influence of filtering and scaling to TCCON on global CO and tend to pull concentrations away from the prior fluxes and closer to the truth. We conclude with suggestions for further improving the MOPITT data products.

【 授权许可】

Unknown