scholarly journals Retrievals of tropospheric ozone profiles from the synergism of AIRS and OMI: methodology and validation

2018 ◽  
Vol 11 (10) ◽  
pp. 5587-5605 ◽  
Author(s):  
Dejian Fu ◽  
Susan S. Kulawik ◽  
Kazuyuki Miyazaki ◽  
Kevin W. Bowman ◽  
John R. Worden ◽  
...  
Keyword(s):  
Measurement Error ◽  
Tropospheric Ozone ◽  
Retrieval Algorithm ◽  
Vertical Resolution ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Data Set ◽  
Global Coverage ◽  
Ozone Monitoring ◽  
Wide Swath

Abstract. The Tropospheric Emission Spectrometer (TES) on the A-Train Aura satellite was designed to profile tropospheric ozone and its precursors, taking measurements from 2004 to 2018. Starting in 2008, TES global sampling of tropospheric ozone was gradually reduced in latitude, with global coverage stopping in 2011. To extend the record of TES, this work presents a multispectral approach that will provide O3 data products with vertical resolution and measurement error similar to TES by combining the single-footprint thermal infrared (TIR) hyperspectral radiances from the Aqua Atmospheric Infrared Sounder (AIRS) instrument and the ultraviolet (UV) channels from the Aura Ozone Monitoring Instrument (OMI). The joint AIRS+OMI O3 retrievals are processed through the MUlti-SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) retrieval algorithm. Comparisons of collocated joint AIRS+OMI and TES to ozonesonde measurements show that both systems have similar errors, with mean and standard deviation of the differences well within the estimated measurement error. AIRS+OMI and TES have slightly different biases (within 5 parts per billion) vs. the sondes. Both AIRS and OMI have wide swath widths (∼1650 km for AIRS; ∼2600 km for OMI) across satellite ground tracks. Consequently, the joint AIRS+OMI measurements have the potential to maintain TES vertical sensitivity while increasing coverage by 2 orders of magnitude, thus providing an unprecedented new data set with which to quantify the evolution of tropospheric ozone.

scholarly journals Retrievals of Tropospheric Ozone Profiles from the Synergic Observation of AIRS and OMI: Methodology and Validation

2018 ◽  
Author(s):  
Dejian Fu ◽  
Susan S. Kulawik ◽  
Kazuyuki Miyazaki ◽  
Kevin W. Bowman ◽  
John R. Worden ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Measurement Uncertainty ◽  
Tropospheric Ozone ◽  
Retrieval Algorithm ◽  
Vertical Resolution ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Global Coverage ◽  
Ozone Monitoring ◽  
Wide Swath

Abstract. The Tropospheric Emission Spectrometer (TES) on the A-Train Aura satellite was designed to profile tropospheric ozone and its precursors, taking measurements from 2004 to 2018. Starting in 2008, TES global sampling of tropospheric ozone was gradually reduced in latitude with global coverage stopping in 2011. To extend the record of TES, this work presents a multispectral approach that will provide O3 data products with vertical resolution and measurement uncertainty similar to TES by combining the single-footprint thermal infrared (TIR) hyperspectral radiances from the Aqua Atmospheric Infrared Sounder (AIRS) instrument and the ultraviolet (UV) channels from the Aura Ozone Monitoring Instrument (OMI). The joint AIR+OMI O3 retrievals are processed through the MUlti-SpEctra, MUlti-SpEcies, MUlti-SEnsors (MUSES) retrieval algorithm. Comparisons of collocated joint AIRS+OMI and TES to ozonesonde measurements show that both systems have similar errors, with mean and standard deviation of the differences well within the estimated measurement uncertainty. AIRS+OMI and TES have slightly different biases (within 5 parts per billion) versus the sondes. Both AIRS and OMI have wide swath widths (~ 1,650 km for AIRS; ~ 2,600 km for OMI) across satellite ground tracks. Consequently, the joint AIRS+OMI measurements have the potential to maintain TES vertical sensitivity while increasing coverage by two orders of magnitude, thus providing an unprecedented new dataset to quantify the evolution of tropospheric ozone.

scholarly journals Tropospheric ozone column retrieval at northern mid-latitudes from the Ozone Monitoring Instrument by means of a neural network algorithm

2011 ◽  
Vol 4 (11) ◽  
pp. 2375-2388 ◽  
Author(s):  
P. Sellitto ◽  
B. R. Bojkov ◽  
X. Liu ◽  
K. Chance ◽  
F. Del Frate
Keyword(s):  
Neural Network ◽  
Test Data ◽  
Tropospheric Ozone ◽  
Optimal Estimation ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Monitoring Instrument ◽  
Network Algorithm ◽  
Neural Network Algorithm ◽  
Ozone Monitoring

Abstract. Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a neural network algorithm. An extended set of ozone sonde measurements at northern mid-latitudes for the years 2004–2008 has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.

scholarly journals Tropospheric ozone column retrieval from the Ozone Monitoring Instrument by means of a neural network algorithm

2011 ◽  
Vol 4 (3) ◽  
pp. 2491-2524 ◽  
Author(s):  
P. Sellitto ◽  
B. R. Bojkov ◽  
X. Liu ◽  
K. Chance ◽  
F. Del Frate
Keyword(s):  
Neural Network ◽  
Test Data ◽  
Tropospheric Ozone ◽  
Optimal Estimation ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Monitoring Instrument ◽  
Neural Network Algorithm ◽  
Ozone Monitoring ◽  
Boundary Layer Ozone

Abstract. Monitoring tropospheric ozone from space is of critical importance in order to gain more thorough knowledge on phenomena affecting air quality and the greenhouse effect. Deriving information on tropospheric ozone from UV/VIS nadir satellite spectrometers is difficult owing to the weak sensitivity of the measured radiance spectra to variations of ozone in the troposphere. Here we propose an alternative method of analysis to retrieve tropospheric ozone columns from Ozone Monitoring Instrument radiances by means of a Neural Network algorithms. An extended set of ozone sonde measurements at northern mid-latitudes has been considered as the training and test data set. The design of the algorithm is extensively discussed. Our retrievals are compared to both tropospheric ozone residuals and optimal estimation retrievals over a similar independent test data set. Results show that our algorithm has comparable accuracy with respect to both correlative methods and its performance is slightly better over a subset containing only European ozone sonde stations. Possible sources of errors are analyzed. Finally, the capabilities of our algorithm to derive information on boundary layer ozone are studied and the results critically discussed.

scholarly journals Comparison of GOME-2/Metop-A ozone profiles with GOMOS, OSIRIS and MLS measurements

2015 ◽  
Vol 8 (7) ◽  
pp. 7663-7695
Author(s):  
A. Määttä ◽  
O. N. E. Tuinder ◽  
S. Tukiainen ◽  
V. Sofieva ◽  
J. Tamminen
Keyword(s):  
Reference Data ◽  
Retrieval Algorithm ◽  
Vertical Resolution ◽  
Infrared Imager ◽  
Ozone Profile ◽  
High Vertical Resolution ◽  
Global Coverage ◽  
Ozone Monitoring ◽  
Vertical Ozone ◽  
Vertical Ozone Profiles

Abstract. This paper presents a comparison of vertical ozone profiles retrieved by the Ozone ProfilE Retrieval Algorithm (OPERA) from the Global Ozone Monitoring Experiment 2 (GOME-2) measurements on board Metop-A with high-vertical-resolution ozone profiles by Global Ozone Monitoring by Occultation of Stars (GOMOS), Optical Spectrograph and Infrared Imager System (OSIRIS) and Microwave Limb Sounder (MLS). The comparison, with global coverage, focuses on the stratosphere and the lower mesosphere and covers the period from March 2008 until the end of 2011. The comparison shows an agreement of the GOME-2 ozone profiles with those of GOMOS, OSIRIS and MLS within ±15 % in the altitude range from 15 km up to ~ 35–40 km depending on latitude. The GOME-2 ozone profiles from non-degradation corrected radiances have a tendency to a systematic negative bias with respect to the reference data above ~ 30 km. The GOME-2 bias with respect to the high-vertical resolution instruments depends on season, with the strongest dependence observed at high latitudes.

Evaluation of tropospheric ozone residual measurements derived from TOMS-V9 and hyper-spectral total ozone algorithms

2021 ◽  
Author(s):  
Jerry Ziemke ◽  
Natalya Kramarova ◽  
Dave Haffner ◽  
Pawan Bhartia
Keyword(s):  
Tropospheric Ozone ◽  
Total Ozone ◽  
Model Simulation ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Total Column Ozone ◽  
Hyper Spectral ◽  
Order Of Magnitude ◽  
Boundary Layer Ozone ◽  
Column Ozone

<p>The NASA TOMS V9 (TOMS-V9) total ozone retrieval algorithm is tested<br>for sensitvity to boundary-layer ozone and suitability to make daily<br>maps of tropospheric ozone residual (TOR).  Daily maps of TOR are<br>derived by differencing co-located MERRA-2 assimilated MLS<br>stratospheric column ozone (SCO) from total column ozone from the Aura<br>Ozone Monitoring Instrument (OMI).  The TOMS-V9 algorithm uses a few<br>discrete channels with an order of magnitude range in ozone<br>senstivity. We compare the TOR results from TOMS-V9 with results from<br>several hyper-spectral total ozone retrievals: GODFIT v4 (BIRA-IASB),<br>OMI-DOAS (KNMI), and total ozone from the SAO PROFOZ algorithm. We<br>compare all satellite-retrieved TOR with TOR derived from ozonesondes,<br>lidar, and the Goddard Modeling Initiative (GMI) model simulation.</p><p> </p><p> </p>

scholarly journals Trends of tropical tropospheric ozone from 20 years of European satellite measurements and perspectives for the Sentinel-5 Precursor

2016 ◽  
Vol 9 (10) ◽  
pp. 5037-5051 ◽  
Author(s):  
Klaus-Peter Heue ◽  
Melanie Coldewey-Egbers ◽  
Andy Delcloo ◽  
Christophe Lerot ◽  
Diego Loyola ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Total Ozone ◽  
Atlantic Coast ◽  
Convective Cloud ◽  
Differential Method ◽  
Retrieval Algorithm ◽  
Data Set ◽  
Cloud Data ◽  
The Individual ◽  
Column Ozone

Abstract. In preparation of the TROPOMI/S5P launch in early 2017, a tropospheric ozone retrieval based on the convective cloud differential method was developed. For intensive tests we applied the algorithm to the total ozone columns and cloud data of the satellite instruments GOME, SCIAMACHY, OMI, GOME-2A and GOME-2B. Thereby a time series of 20 years (1995–2015) of tropospheric column ozone was generated. To have a consistent total ozone data set for all sensors, one common retrieval algorithm, namely GODFITv3, was applied and the L1 reflectances were also soft calibrated. The total ozone columns and the cloud data were input into the tropospheric ozone retrieval. However, the tropical tropospheric column ozone (TCO) for the individual instruments still showed small differences and, therefore, we harmonised the data set. For this purpose, a multilinear function was fitted to the averaged difference between SCIAMACHY's TCO and those from the other sensors. The original TCO was corrected by the fitted offset. GOME-2B data were corrected relative to the harmonised data from OMI and GOME-2A. The harmonisation leads to a better agreement between the different instruments. Also, a direct comparison of the TCO in the overlapping periods proves that GOME-2A agrees much better with SCIAMACHY after the harmonisation. The improvements for OMI were small. Based on the harmonised observations, we created a merged data product, containing the TCO from July 1995 to December 2015. A first application of this 20-year record is a trend analysis. The tropical trend is 0.7 ± 0.12 DU decade−1. Regionally the trends reach up to 1.8 DU decade−1 like on the African Atlantic coast, while over the western Pacific the tropospheric ozone declined over the last 20 years with up to 0.8 DU decade−1. The tropical tropospheric data record will be extended in the future with the TROPOMI/S5P data, where the TCO is part of the operational products.

scholarly journals A scientific algorithm to simultaneously retrieve carbon monoxide and methane from TROPOMI onboard Sentinel-5 Precursor

2019 ◽  
Vol 12 (12) ◽  
pp. 6771-6802 ◽  
Author(s):  
Oliver Schneising ◽  
Michael Buchwitz ◽  
Maximilian Reuter ◽  
Heinrich Bovensmann ◽  
John P. Burrows ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Air Quality ◽  
Systematic Error ◽  
Random Error ◽  
Optical Absorption Spectroscopy ◽  
Retrieval Algorithm ◽  
Validation Data ◽  
Data Set ◽  
Airborne Measurements ◽  
Global Coverage

Abstract. Carbon monoxide (CO) is an important atmospheric constituent affecting air quality, and methane (CH4) is the second most important greenhouse gas contributing to human-induced climate change. Detailed and continuous observations of these gases are necessary to better assess their impact on climate and atmospheric pollution. While surface and airborne measurements are able to accurately determine atmospheric abundances on local scales, global coverage can only be achieved using satellite instruments. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor satellite, which was successfully launched in October 2017, is a spaceborne nadir-viewing imaging spectrometer measuring solar radiation reflected by the Earth in a push-broom configuration. It has a wide swath on the terrestrial surface and covers wavelength bands between the ultraviolet (UV) and the shortwave infrared (SWIR), combining a high spatial resolution with daily global coverage. These characteristics enable the determination of both gases with an unprecedented level of detail on a global scale, introducing new areas of application. Abundances of the atmospheric column-averaged dry air mole fractions XCO and XCH4 are simultaneously retrieved from TROPOMI's radiance measurements in the 2.3 µm spectral range of the SWIR part of the solar spectrum using the scientific retrieval algorithm Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). This algorithm is intended to be used with the operational algorithms for mutual verification and to provide new geophysical insights. We introduce the algorithm in detail, including expected error characteristics based on synthetic data, a machine-learning-based quality filter, and a shallow learning calibration procedure applied in the post-processing of the XCH4 data. The quality of the results based on real TROPOMI data is assessed by validation with ground-based Fourier transform spectrometer (FTS) measurements providing realistic error estimates of the satellite data: the XCO data set is characterised by a random error of 5.1 ppb (5.8 %) and a systematic error of 1.9 ppb (2.1 %); the XCH4 data set exhibits a random error of 14.0 ppb (0.8 %) and a systematic error of 4.3 ppb (0.2 %). The natural XCO and XCH4 variations are well-captured by the satellite retrievals, which is demonstrated by a high correlation with the validation data (R=0.97 for XCO and R=0.91 for XCH4 based on daily averages). We also present selected results from the mission start until the end of 2018, including a first comparison to the operational products and examples of the detection of emission sources in a single satellite overpass, such as CO emissions from the steel industry and CH4 emissions from the energy sector, which potentially allows for the advance of emission monitoring and air quality assessments to an entirely new level.

scholarly journals Validation and update of OMI Total Column Water Vapor product

2016 ◽  
Vol 16 (17) ◽  
pp. 11379-11393 ◽  
Author(s):  
Huiqun Wang ◽  
Gonzalo Gonzalez Abad ◽  
Xiong Liu ◽  
Kelly Chance
Keyword(s):  
Water Vapor ◽  
Liquid Water ◽  
Retrieval Algorithm ◽  
Ozone Monitoring Instrument ◽  
Validation Data ◽  
Data Set ◽  
Wide Range ◽  
Key Factor ◽  
The Mean ◽  
Total Column

Abstract. The collection 3 Ozone Monitoring Instrument (OMI) Total Column Water Vapor (TCWV) data generated by the Smithsonian Astrophysical Observatory's (SAO) algorithm version 1.0 and archived at the Aura Validation Data Center (AVDC) are compared with NCAR's ground-based GPS data, AERONET's sun-photometer data, and Remote Sensing System's (RSS) SSMIS data. Results show that the OMI data track the seasonal and interannual variability of TCWV for a wide range of climate regimes. During the period from 2005 to 2009, the mean OMI−GPS over land is −0.3 mm and the mean OMI−AERONET over land is 0 mm. For July 2005, the mean OMI−SSMIS over the ocean is −4.3 mm. The better agreement over land than over the ocean is corroborated by the smaller fitting residuals over land and suggests that liquid water is a key factor for the fitting quality over the ocean in the version 1.0 retrieval algorithm. We find that the influence of liquid water is reduced using a shorter optimized retrieval window of 427.7–465 nm. As a result, the TCWV retrieved with the new algorithm increases significantly over the ocean and only slightly over land. We have also made several updates to the air mass factor (AMF) calculation. The updated version 2.1 retrieval algorithm improves the land/ocean consistency and the overall quality of the OMI TCWV data set. The version 2.1 OMI data largely eliminate the low bias of the version 1.0 OMI data over the ocean and are 1.5 mm higher than RSS's “clear” sky SSMIS data in July 2005. Over the ocean, the mean of version 2.1 OMI−GlobVapour is 1 mm for July 2005 and 0 mm for January 2005. Over land, the version 2.1 OMI data are about 1 mm higher than GlobVapour when TCWV  <  15 mm and about 1 mm lower when TCWV  >  15 mm.

scholarly journals Global ozone–CO correlations from OMI and AIRS: constraints on tropospheric ozone sources

2013 ◽  
Vol 13 (4) ◽  
pp. 8901-8937 ◽  
Author(s):  
P. S. Kim ◽  
D. J. Jacob ◽  
X. Liu ◽  
J. X. Warner ◽  
K. Yang ◽  
...  
Keyword(s):  
Tropospheric Ozone ◽  
Transport Model ◽  
General Structure ◽  
Deep Convection ◽  
Chemical Transport Model ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Tropical Regions ◽  
Ozone Maximum ◽  
Regression Slopes

Abstract. We present a global data set of free tropospheric ozone–CO correlations with 2° × 2.5° spatial resolution from the Ozone Monitoring Instrument (OMI) and Atmospheric Infrared Sounder (AIRS) satellite instruments for each season of 2008. OMI and AIRS have near daily global coverage of ozone and CO respectively and observe coincident scenes with similar vertical sensitivities. The resulting ozone–CO correlations are highly statistically significant (positive or negative) in most regions of the world, and are less noisy than previous satellite-based studies that used sparser data. We interpret the observed ozone–CO correlations with the GEOS-Chem chemical transport model to infer constraints on ozone sources. Driving GEOS-Chem with different meteorological fields generally shows consistent ozone–CO correlation patterns, except in some tropical regions where the correlations are strongly sensitive to model transport error associated with deep convection. GEOS-Chem reproduces the general structure of the observed ozone–CO correlations and regression slopes (dO3/dCO), although there are some large regional discrepancies. We examine the model sensitivity of dO3/dCO to different ozone sources (combustion, biosphere, stratosphere, and lightning NOx) by correlating the ozone change from that source to CO from the standard simulation. The model reproduces the observed positive dO3/dCO in the extratropical Northern Hemisphere in spring–summer, driven by combustion sources. Stratospheric influence there is also associated with a positive dO3/dCO because of the interweaving of stratospheric downwelling with continental outflow. The well-known ozone maximum over the tropical South Atlantic is associated with negative dO3/dCO in the observations; this feature is reproduced in GEOS-Chem and supports a dominant contribution from lightning to the ozone maximum. A~major model discrepancy is found over the Northeast Pacific in summer-fall where dO3/dCO is positive in the observations but negative in the model, for all ozone sources. We suggest that this reflects a model overestimate of lightning at northern mid-latitudes combined with an underestimate of the East Asian CO source.

scholarly journals Improvements to the OMI near UV aerosol algorithm using A-train CALIOP and AIRS observations

2013 ◽  
Vol 6 (3) ◽  
pp. 5621-5652 ◽  
Author(s):  
O. Torres ◽  
C. Ahn ◽  
Z. Chen
Keyword(s):  
Retrieval Algorithm ◽  
Orthogonal Polarization ◽  
Aerosol Layer ◽  
Carbonaceous Aerosols ◽  
Ozone Monitoring Instrument ◽  
Atmospheric Infrared Sounder ◽  
Layer Height ◽  
Aerosol Retrieval ◽  
Polarization Sensor ◽  
Aerosol Properties

Abstract. The height of desert dust and carbonaceous aerosols layers and, to a lesser extent, the difficulty in determining the predominant size mode of these absorbing aerosol types, are sources of uncertainty in the retrieval of aerosol properties from near UV satellite observations. The availability of independent, near-simultaneous measurements of aerosol layer height, and aerosol-type related parameters derived from observations by other A-train sensors, makes possible the use of this information as input to the OMI (Ozone Monitoring Instrument) near UV aerosol retrieval algorithm (OMAERUV). A monthly climatology of aerosol layer height derived from observations by the CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) sensor, and real-time AIRS (Atmospheric Infrared Sounder) CO observations are used in an upgraded version of the OMAERUV algorithm. AIRS CO measurements are used as a reliable tracer of carbonaceous aerosols, which allows the identification of smoke layers in regions and seasons when the dust-smoke differentiation is difficult in the near-UV. The use of CO measurements also enables the identification of elevated levels of boundary layer pollution undetectable by near UV observations alone. In this paper we discuss the combined use of OMI, CALIOP and AIRS observations for the characterization of aerosol properties, and show an improvement in OMI aerosol retrieval capabilities.

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