Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 3.248 IF 3.248
  • IF 5-year value: 3.650 IF 5-year 3.650
  • CiteScore value: 3.37 CiteScore 3.37
  • SNIP value: 1.253 SNIP 1.253
  • SJR value: 1.869 SJR 1.869
  • IPP value: 3.29 IPP 3.29
  • h5-index value: 47 h5-index 47
  • Scimago H index value: 60 Scimago H index 60
Volume 10, issue 7 | Copyright

Special issue: Ten years of Ozone Monitoring Instrument (OMI) observations...

Atmos. Meas. Tech., 10, 2455-2475, 2017
https://doi.org/10.5194/amt-10-2455-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 13 Jul 2017

Research article | 13 Jul 2017

Validation of 10-year SAO OMI Ozone Profile (PROFOZ) product using ozonesonde observations

Guanyu Huang1, Xiong Liu1, Kelly Chance1, Kai Yang2, Pawan K. Bhartia3, Zhaonan Cai1, Marc Allaart4, Gérard Ancellet5, Bertrand Calpini6, Gerrie J. R. Coetzee7, Emilio Cuevas-Agulló8, Manuel Cupeiro9, Hugo De Backer10, Manvendra K. Dubey11, Henry E. Fuelberg12, Masatomo Fujiwara13, Sophie Godin-Beekmann5, Tristan J. Hall12, Bryan Johnson14, Everette Joseph15, Rigel Kivi16, Bogumil Kois17, Ninong Komala18, Gert König-Langlo19, Giovanni Laneve20, Thierry Leblanc21, Marion Marchand5, Kenneth R. Minschwaner22, Gary Morris23, Michael J. Newchurch24, Shin-Ya Ogino25, Nozomu Ohkawara26, Ankie J. M. Piters4, Françoise Posny27, Richard Querel28, Rinus Scheele4, Frank J. Schmidlin3, Russell C. Schnell14, Otto Schrems19, Henry Selkirk29, Masato Shiotani30, Pavla Skrivánková31, René Stübi6, Ghassan Taha29, David W. Tarasick32, Anne M. Thompson3, Valérie Thouret33, Matthew B. Tully34, Roeland Van Malderen10, Holger Vömel35, Peter von der Gathen36, Jacquelyn C. Witte37, and Margarita Yela38 Guanyu Huang et al.
  • 1Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA
  • 2Department of Atmospheric and Oceanic Science, University of Maryland, College Park, Maryland, USA
  • 3NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
  • 4Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
  • 5LATMOS-ISPL, Université Paris 6 Pierre-et-Marie-Curie, Paris, France
  • 6MeteoSwiss Aerological Station, Federal Office of Meteorology and Climatology MeteoSwiss, Payerne, Switzerland
  • 7South African Weather Service, Pretoria, South Africa
  • 8Izana Atmospheric Research Center, Meteorological State Agency of Spain, Santa Cruz de Tenerife, Spain
  • 9National Meteorological Service, Ushuaia, Tierra del Fuego, Argentina
  • 10Royal Meteorological Institute of Belgium, Brussels, Belgium
  • 11Los Alamos National Laboratory, Los Alamos, NM, USA
  • 12Earth, Ocean and Atmospheric Sciences, Florida State University, Tallahassee, FL, USA
  • 13Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Japan
  • 14NOAA/ESRL Global Monitoring Division, Boulder, CO, USA
  • 15Atmospheric Sciences Research Center, SUNY at Albany, Albany, NY, USA
  • 16Finnish Meteorological Institute, Sodankylä, Finland
  • 17The Institute of Meteorology and Water Management, National Research Institute, Warsaw, Poland
  • 18Indonesian Institute of Aeronautics and Space (LAPAN), Bandung, Indonesia
  • 19Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
  • 20Earth Observation Satellite Images Applications Lab (EOSIAL), Università di Roma “La Sapienza”, Rome, Italy
  • 21Jet Propulsion Laboratory, California Institute of Technology, Wrightwood, CA, USA
  • 22Department of Physics, New Mexico Institute of Mining and Technology, Socorro, NM, USA
  • 23St. Edward's University, Austin, TX, USA
  • 24Department of Atmospheric Science, University of Alabama in Huntsville, Huntsville, AL, USA
  • 25Department of Coupled Ocean-Atmosphere-Land Processes Research, Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan
  • 26Global Environment and Marine Department, Japan Meteorological Agency, Tokyo, Japan
  • 27Université de la Réunion, Saint Denis, France
  • 28National Institute of Water and Atmospheric Research, Lauder, Central Otago, New Zealand
  • 29Universities Space Research Association, Greenbelt, MD, USA
  • 30Research Institute for Sustainable Humanosphere, Kyoto University, Kyoto, Japan
  • 31Upper Air and Surface Observation Department, Czech Hydrometeorological Institute, Prague, Czech Republic
  • 32Air Quality Research Division, Environment & Climate Change Canada, Downsview, ON, Canada
  • 33Laboratoire d'Aérologie, Université de Toulouse, CNRS, UPS, Toulouse, France
  • 34Bureau of Meteorology, Melbourne, Victoria, Australia
  • 35Earth Observing Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
  • 36Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany
  • 37Science Systems and Applications Inc., Greenbelt, MD, USA
  • 38Atmospheric Research and Instrumentation Branch, National Institute for Aerospace Technology (INTA), Madrid, Spain

Abstract. We validate the Ozone Monitoring Instrument (OMI) Ozone Profile (PROFOZ) product from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against ozonesonde observations. We also evaluate the effects of OMI row anomaly (RA) on the retrieval by dividing the dataset into before and after the occurrence of serious OMI RA, i.e., pre-RA (2004–2008) and post-RA (2009–2014). The retrieval shows good agreement with ozonesondes in the tropics and midlatitudes and for pressure  < ∼ 50hPa in the high latitudes. It demonstrates clear improvement over the a priori down to the lower troposphere in the tropics and down to an average of ∼550 (300)hPa at middle (high) latitudes. In the tropics and midlatitudes, the profile mean biases (MBs) are less than 6%, and the standard deviations (SDs) range from 5 to 10% for pressure  < ∼ 50hPa to less than 18% (27%) in the tropics (midlatitudes) for pressure  > ∼ 50hPa after applying OMI averaging kernels to ozonesonde data. The MBs of the stratospheric ozone column (SOC, the ozone column from the tropopause pressure to the ozonesonde burst pressure) are within 2% with SDs of  < 5% and the MBs of the tropospheric ozone column (TOC) are within 6% with SDs of 15%. In the high latitudes, the profile MBs are within 10% with SDs of 5–15% for pressure  < ∼50hPa but increase to 30% with SDs as great as 40% for pressure  > ∼50hPa. The SOC MBs increase up to 3% with SDs as great as 6% and the TOC SDs increase up to 30%. The comparison generally degrades at larger solar zenith angles (SZA) due to weaker signals and additional sources of error, leading to worse performance at high latitudes and during the midlatitude winter. Agreement also degrades with increasing cloudiness for pressure  > ∼ 100hPa and varies with cross-track position, especially with large MBs and SDs at extreme off-nadir positions. In the tropics and midlatitudes, the post-RA comparison is considerably worse with larger SDs reaching 2% in the stratosphere and 8% in the troposphere and up to 6% in TOC. There are systematic differences that vary with latitude compared to the pre-RA comparison. The retrieval comparison demonstrates good long-term stability during the pre-RA period but exhibits a statistically significant trend of 0.14–0.7%year−1 for pressure  < ∼80hPa, 0.7DUyear−1 in SOC, and −0. 33DUyear−1 in TOC during the post-RA period. The spatiotemporal variation of retrieval performance suggests the need to improve OMI's radiometric calibration especially during the post-RA period to maintain the long-term stability and reduce the latitude/season/SZA and cross-track dependency of retrieval quality.

Publications Copernicus
Special issue
Download
Short summary
It is essential to understand the data quality of +10-year OMI ozone product and impacts of the “row anomaly” (RA). We validate the OMI Ozone Profile (PROFOZ) product from Oct 2004 to Dec 2014 against ozonesonde observations globally. Generally, OMI has good agreement with ozonesondes. The spatiotemporal variation of retrieval performance suggests the need to improve OMI’s radiometric calibration especially during the post-RA period to maintain the long-term stability.
It is essential to understand the data quality of +10-year OMI ozone product and impacts of the...
Citation
Share