On the derivation of tropospheric column ozone from radiances measured by the total ozone mapping spectrometer

1995 ◽  
Vol 100 (D6) ◽  
pp. 11137 ◽  
Author(s):  
Robert D. Hudson ◽  
Jae-Hwan Kim ◽  
Anne M. Thompson
Keyword(s):  
Total Ozone ◽  
Total Ozone Mapping Spectrometer ◽  
Column Ozone

scholarly journals Validation of the Suomi NPP Ozone Mapping and Profiler Suite total column ozone using Brewer and Dobson spectrophotometers

2013 ◽  
Vol 6 (3) ◽  
pp. 4577-4605 ◽  
Author(s):  
K. Bai ◽  
C. Liu ◽  
R. Shi ◽  
W. Gao
Keyword(s):  
Standard Deviation ◽  
Total Ozone ◽  
Daily Basis ◽  
Total Ozone Mapping Spectrometer ◽  
Total Column Ozone ◽  
Ozone Profile ◽  
Column Ozone ◽  
Relative Differences ◽  
Dependent Error ◽  
Total Column

Abstract. This study mainly focuses on the validation of total column (TC) ozone data derived from the Ozone Mapping and Profiler Suite (OMPS) on board the NASA's Suomi National Polar-orbiting Partnership satellite (NPP). OMPS is an advanced suite of three hyperspectral instruments that maps global ozone on a daily basis and extends the more than 30 yr total ozone and ozone profile records. The algorithm used to derive OMPS TC ozone is adapted from the heritage of Total Ozone Mapping Spectrometer (TOMS) Version 7 algorithm but with a number of enhancements. Validation is primarily performed through comparisons with an ensemble of 74 global distributed Brewer and Dobson spectrophotometers measurements. Linear regression performs fair agreement between OMPS TC ozone and ground-based TC ozone measurements with root mean square error (RMSE) around of 3% (10 DU). Comparison shows that OMPS TC ozone estimates 0.21% higher than Brewer measurements average, with station-to-station standard deviation of 3.14%. As comparing with Dobson measurements, OMPS TC ozone averages 0.86% higher than the station average with standard deviation of 3.05%. The relative differences between OMPS and ground TC ozone were analysed varying with latitude and time as well as viewing geometry respectively. Comparisons show relative differences within 2% over most of latitude and viewing conditions. Only comparing with Brewer measurements did it show an OMPS TC ozone dependent error, large negative bias was observed as OMPS TC ozone below 220 DU and positive bias shown above 460 DU.

scholarly journals Comparison of profile total ozone from SBUV(v8.6) with GOME-type and ground-based total ozone for 16-yr period (1996 to 2011)

2013 ◽  
Vol 6 (6) ◽  
pp. 10081-10115 ◽  
Author(s):  
E. W. Chiou ◽  
P. K. Bhartia ◽  
R. D. McPeters ◽  
D. G. Loyola ◽  
M. Coldewey-Egbers ◽  
...  
Keyword(s):  
Strong Evidence ◽  
Total Ozone ◽  
Time Dependent ◽  
Total Column Ozone ◽  
Monthly Data ◽  
Latitude Band ◽  
Ozone Data ◽  
Standard Deviations ◽  
Column Ozone ◽  
Total Column

Abstract. This paper describes the comparison of the variability of total column ozone inferred from the three independent multi-year data records, namely, (i) SBUV(v8.6) profile total ozone, (ii) GTO(GOME-Type total ozone), and (iii) Ground-based total ozone data records covering the 16-yr overlap period (March 1996 through June 2011). Analyses are conducted based on area weighted zonal means for (0–30° S), (0–30° N), (50–30° S), and (30–60° N). It has been found that on average, the differences in monthly zonal mean total ozone vary between −0.32 to 0.76 % and are well within 1%. For "GTO minus SBUV", the standard deviations and ranges (maximum minus minimum) of the differences regarding monthly zonal mean total ozone vary between 0.58 to 0.66% and 2.83 to 3.82% respectively, depending on the latitude band. The corresponding standard deviations and ranges regarding the differences in monthly zonal mean anomalies show values between 0.40 to 0.59% and 2.19 to 3.53%. The standard deviations and ranges of the differences "Ground-based minus SBUV" regarding both monthly zonal means and anomalies are larger by a factor of 1.4 to 2.9 in comparison to "GTO minus SBUV". The Ground-based zonal means, while show no systematic differences, demonstrate larger scattering of monthly data compared to satellite-based records. The differences in the scattering are significantly reduced if seasonal zonal averages are analyzed. The trends of the differences "GTO minus SBUV" and "Ground-based minus SBUV" are found to vary between −0.04 and 0.12% yr−1 (−0.11 and 0.31 DU yr−1). These negligibly small trends have provided strong evidence that there are no significant time dependent differences among these multi-year total ozone data records. Analyses of the deviations from pre-1980 level indicate that for the overlap period of 1996 to 2010, all three data records show gradual recovery at (30–60° N) from −5% in 1996 to −2% in 2010. The corresponding recovery at (50–30° S) is not as obvious until after 2006.

The Solar Backscatter Ultraviolet and Total Ozone Mapping Spectrometer (SBUV/TOMS) for NIMBUS G

1975 ◽  
Vol 14 (4) ◽  
Author(s):  
D. F. Heath ◽  
A. J. Krueger ◽  
H. A. Roeder ◽  
B. D. Henderson
Keyword(s):  
Total Ozone ◽  
Total Ozone Mapping Spectrometer

scholarly journals Tropical tropospheric ozone derived using Clear-Cloudy Pairs (CCP) of TOMS measurements

2003 ◽  
Vol 3 (1) ◽  
pp. 225-252 ◽  
Author(s):  
M. J. Newchurch ◽  
D. Sun ◽  
J. H. Kim ◽  
X. Liu
Keyword(s):  
High Altitude ◽  
Tropospheric Ozone ◽  
Total Ozone ◽  
Stratospheric Ozone ◽  
Lower Troposphere ◽  
Total Ozone Mapping Spectrometer ◽  
Significant Difference ◽  
Retrieval Efficiency ◽  
Retrieval Errors ◽  
Low Altitude

Abstract. Using TOMS total-ozone measurements over high-altitude cloud locations and nearby paired clear locations, we describe the Clear-Cloudy Pairs (CCP) method for deriving tropical tropospheric ozone. The high-altitude clouds are identified by measured 380 nm reflectivities greater than 80% and Temperature Humidity InfraRed (THIR) measured cloud-top pressures less than 200 hPa. To account for locations without high-altitude clouds, we apply a zonal sine fitting to the stratospheric ozone derived from available cloudy points, resulting in a wave-one amplitude of about 4 DU. THIR data is unavailable after November 1984, so we extend the CCP method by using a reflectivity threshold of 90% to identify high-altitude clouds and remove the influence of high-reflectivity-but-low-altitude clouds with a lowpass frequency filter. We correct ozone retrieval errors associated with clouds, and ozone retrieval errors due to sun glint and aerosols. Comparing CCP results with Southern Hemisphere ADditional OZonesondes (SHADOZ) tropospheric ozone indicates that CCP tropospheric ozone and ozonesonde measurements are highly consistent. The most significant difference between CCP and ozonesonde tropospheric ozone can be explained by the low Total Ozone Mapping Spectrometer (TOMS) retrieval efficiency of ozone in the lower troposphere.

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.

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