scholarly journals Extended and refined multi sensor reanalysis of total ozone for the period 1970–2012

2015 ◽  
Vol 8 (3) ◽  
pp. 3283-3319 ◽  
Author(s):  
R. J. van der A ◽  
M. A. F. Allaart ◽  
H. J. Eskes
Keyword(s):  
Data Assimilation ◽  
Total Ozone ◽  
Transport Model ◽  
Forecast Error ◽  
Satellite Observations ◽  
Weather Forecasts ◽  
Stratospheric Temperature ◽  
The Individual ◽  
Data Assimilation Technique ◽  
Ozone Column

Abstract. The ozone multi-sensor reanalysis (MSR) is a multi-decadal ozone column data record constructed using all available ozone column satellite datasets, surface Brewer and Dobson observations and a data assimilation technique with detailed error modelling. The result is a high-resolution time series of 6 hourly global ozone column fields and forecast error fields that may be used for ozone trend analyses as well as detailed case studies. The ozone MSR is produced in two steps. First, the latest reprocessed versions of all available ozone column satellite datasets are collected, and are corrected for biases as function of solar zenith angle, viewing angle, time (trend), and stratospheric temperature using Brewer/Dobson ground measurements from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC; http://www.woudc.org/). Subsequently the debiased satellite observations are assimilated within the ozone chemistry and data assimilation model TMDAM driven by meteorological analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF). The MSR2 (MSR version 2) reanalysis upgrade described in this paper consists of an ozone record for the 43 year period 1970–2012. The chemistry-transport model and data assimilation system have been adapted to improve the resolution, error modelling and processing speed. BUV satellite observations have been included for the period 1970–1977. The total record is extended with 13 years compared to the first version of the ozone multi sensor reanalysis, the MSR1. The latest total ozone retrievals of 15 satellite instruments are used: BUV-Nimbus4, TOMS-Nimbus7, TOMS-EP, SBUV-7, -9, -11, -14, -16, -17, -18, -19, GOME, SCIAMACHY, OMI and GOME-2. The resolution of the model runs, assimilation and output is increased from 2° x 3° to 1° x 1°. The analysis is driven by three-hourly meteorology from the ERA-interim reanalysis of ECMWF starting from 1979, and ERA-40 before that date. The chemistry parameterization has been updated. The performance of the MSR2 analysis is studied with the help of observation-minus-forecast (OmF) departures from the data assimilation, by comparisons with the individual station observations and with ozone sondes. The OmF statistics show that the mean bias of the MSR2 analyses is less than 1% with respect to debiased satellite observations after 1979.

scholarly journals Extended and refined multi sensor reanalysis of total ozone for the period 1970–2012

2015 ◽  
Vol 8 (7) ◽  
pp. 3021-3035 ◽  
Author(s):  
R. J. van der A ◽  
M. A. F. Allaart ◽  
H. J. Eskes
Keyword(s):  
Data Assimilation ◽  
Satellite Data ◽  
Zenith Angle ◽  
Total Ozone ◽  
Transport Model ◽  
Forecast Error ◽  
Satellite Observations ◽  
Data Sets ◽  
Stratospheric Temperature ◽  
Ozone Column

Abstract. The ozone multi-sensor reanalysis (MSR) is a multi-decadal ozone column data record constructed using all available ozone column satellite data sets, surface Brewer and Dobson observations and a data assimilation technique with detailed error modelling. The result is a high-resolution time series of 6-hourly global ozone column fields and forecast error fields that may be used for ozone trend analyses as well as detailed case studies. The ozone MSR is produced in two steps. First, the latest reprocessed versions of all available ozone column satellite data sets are collected and then are corrected for biases as a function of solar zenith angle (SZA), viewing zenith angle (VZA), time (trend), and stratospheric temperature using surface observations of the ozone column from Brewer and Dobson spectrophotometers from the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Subsequently the de-biased satellite observations are assimilated within the ozone chemistry and data assimilation model TMDAM. The MSR2 (MSR version 2) reanalysis upgrade described in this paper consists of an ozone record for the 43-year period 1970–2012. The chemistry transport model and data assimilation system have been adapted to improve the resolution, error modelling and processing speed. Backscatter ultraviolet (BUV) satellite observations have been included for the period 1970–1977. The total record is extended by 13 years compared to the first version of the ozone multi sensor reanalysis, the MSR1. The latest total ozone retrievals of 15 satellite instruments are used: BUV-Nimbus4, TOMS-Nimbus7, TOMS-EP, SBUV-7, -9, -11, -14, -16, -17, -18, -19, GOME, SCIAMACHY, OMI and GOME-2. The resolution of the model runs, assimilation and output is increased from 2° × 3° to 1° × 1°. The analysis is driven by 3-hourly meteorology from the ERA-Interim reanalysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) starting from 1979, and ERA-40 before that date. The chemistry parameterization has been updated. The performance of the MSR2 analysis is studied with the help of observation-minus-forecast (OmF) departures from the data assimilation, by comparisons with the individual station observations and with ozone sondes. The OmF statistics show that the mean bias of the MSR2 analyses is less than 1 % with respect to de-biased satellite observations after 1979.

scholarly journals Multi sensor reanalysis of total ozone

2010 ◽  
Vol 10 (4) ◽  
pp. 11401-11448 ◽  
Author(s):  
R. J. van der A ◽  
M. A. F. Allaart ◽  
H. J. Eskes
Keyword(s):  
Data Assimilation ◽  
Total Ozone ◽  
Transport Model ◽  
Chemical Transport ◽  
Satellite Observations ◽  
Chemical Transport Model ◽  
Model Driven ◽  
Stratospheric Temperature ◽  
Near Ultraviolet ◽  
Time Period

Abstract. A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe), SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16), GOME (ERS-2), SCIAMACHY (Envisat), OMI (EOS-Aura), and GOME-2 (Metop-A) have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based on independent ground-based total ozone data from the World Ozone and Ultraviolet Data Center. The correction is a function of solar zenith angle, viewing angle, time (trend), and stratospheric temperature. As second step data assimilation was applied to create a global dataset of total ozone analyses. The data assimilation method is a sub-optimal implementation of the Kalman filter technique, and is based on a chemical transport model driven by ECMWF meteorological fields. The chemical transport model provides a detailed description of (stratospheric) transport and uses parameterisations for gas-phase and ozone hole chemistry. The MSR dataset results from a 30-year data assimilation run with the 14 corrected satellite datasets as input, and is available on a grid of 1×1½ degrees with a sample frequency of 6 h for the complete time period (1978–2008). The Observation-minus-Analysis (OmA) statistics show that the bias of the MSR analyses is less than 1 percent with an RMS standard deviation of about 2 percent as compared to the corrected satellite observations used.

scholarly journals Multi sensor reanalysis of total ozone

2010 ◽  
Vol 10 (22) ◽  
pp. 11277-11294 ◽  
Author(s):  
R. J. van der A ◽  
M. A. F. Allaart ◽  
H. J. Eskes
Keyword(s):  
Data Assimilation ◽  
Total Ozone ◽  
Transport Model ◽  
Chemical Transport ◽  
Satellite Observations ◽  
Chemical Transport Model ◽  
Model Driven ◽  
Near Ultraviolet ◽  
Time Period ◽  
Sample Frequency

Abstract. A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe), SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16), GOME (ERS-2), SCIAMACHY (Envisat), OMI (EOS-Aura), and GOME-2 (Metop-A) have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based on independent ground-based total ozone data from the World Ozone and Ultraviolet Data Center. The correction is a function of solar zenith angle, viewing angle, time (trend), and effective ozone temperature. As second step data assimilation was applied to create a global dataset of total ozone analyses. The data assimilation method is a sub-optimal implementation of the Kalman filter technique, and is based on a chemical transport model driven by ECMWF meteorological fields. The chemical transport model provides a detailed description of (stratospheric) transport and uses parameterisations for gas-phase and ozone hole chemistry. The MSR dataset results from a 30-year data assimilation run with the 14 corrected satellite datasets as input, and is available on a grid of 1× 1 1/2° with a sample frequency of 6 h for the complete time period (1978–2008). The Observation-minus-Analysis (OmA) statistics show that the bias of the MSR analyses is less than 1% with an RMS standard deviation of about 2% as compared to the corrected satellite observations used.

scholarly journals Changes in Power Plant NOx Emissions over Northwest Greece Using a Data Assimilation Technique

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 900
Author(s):  
Ioanna Skoulidou ◽  
Maria-Elissavet Koukouli ◽  
Arjo Segers ◽  
Astrid Manders ◽  
Dimitris Balis ◽  
...  
Keyword(s):  
Power Plant ◽  
Data Assimilation ◽  
Energy Production ◽  
Power Plants ◽  
Transport Model ◽  
A Priori ◽  
Filter Method ◽  
Nox Emissions ◽  
A Posteriori ◽  
Data Assimilation Technique

In this work, we investigate the ability of a data assimilation technique and space-borne observations to quantify and monitor changes in nitrogen oxides (NOx) emissions over Northwestern Greece for the summers of 2018 and 2019. In this region, four lignite-burning power plants are located. The data assimilation technique, based on the Ensemble Kalman Filter method, is employed to combine space-borne atmospheric observations from the high spatial resolution Sentinel-5 Precursor (S5P) Tropospheric Monitoring Instrument (TROPOMI) and simulations using the LOTOS-EUROS Chemical Transport model. The Copernicus Atmosphere Monitoring Service-Regional European emissions (CAMS-REG, version 4.2) inventory based on the year 2015 is used as the a priori emissions in the simulations. Surface measurements of nitrogen dioxide (NO2) from air quality stations operating in the region are compared with the model surface NO2 output using either the a priori (base run) or the a posteriori (assimilated run) NOx emissions. Relative to the a priori emissions, the assimilation suggests a strong decrease in concentrations for the station located near the largest power plant, by 80% in 2019 and by 67% in 2018. Concerning the estimated annual a posteriori NOx emissions, it was found that, for the pixels hosting the two largest power plants, the assimilated run results in emissions decreased by ~40–50% for 2018 compared to 2015, whereas a larger decrease, of ~70% for both power plants, was found for 2019, after assimilating the space-born observations. For the same power plants, the European Pollutant Release and Transfer Register (E-PRTR) reports decreased emissions in 2018 and 2019 compared to 2015 (−35% and −38% in 2018, −62% and −72% in 2019), in good agreement with the estimated emissions. We further compare the a posteriori emissions to the reported energy production of the power plants during the summer of 2018 and 2019. Mean decreases of about −35% and−63% in NOx emissions are estimated for the two larger power plants in summer of 2018 and 2019, respectively, which are supported by similar decreases in the reported energy production of the power plants (~−30% and −70%, respectively).

scholarly journals First steps towards the assimilation of IASI ozone data into the MOCAGE-PALM system

2009 ◽  
Vol 9 (2) ◽  
pp. 6691-6737 ◽  
Author(s):  
S. Massart ◽  
C. Clerbaux ◽  
D. Cariolle ◽  
A. Piacentini ◽  
S. Turquety ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Total Ozone ◽  
Transport Model ◽  
Polar Regions ◽  
Observation Error ◽  
Random Errors ◽  
Chemistry Transport Model ◽  
Ozone Data ◽  
The One ◽  
New Generation

Abstract. The Infrared Atmospheric Sounding Interferometer (IASI) is one of the five European new generation instruments carried by the polar-orbiting MetOp-A satellite. Data assimilation is a powerful tool to combine these data with a numerical model. This paper presents the first steps made towards the assimilation of the total ozone columns from the IASI measurements into a chemistry transport model. The IASI ozone data used are provided by an inversion of radiances performed at the LATMOS (Laboratoire Atmosphères, Milieux, Observations Spatiales). As a contribution to the validation of this dataset, the LATMOS-IASI data are compared to a four dimensional ozone field, with low systematic and random errors compared to ozonesondes and OMI-DOAS data. This field results from the combined assimilation of ozone profiles from the MLS instrument and of total ozone columns from the SCIAMACHY instrument. It is found that on average, the LATMOS-IASI data tends to overestimate the total ozone columns by 2% to 8%. The random observation error of the LATMOS-IASI data is estimated to about 6%, except over polar regions and deserts where it is higher. Using this information, the LATMOS-IASI data are then assimilated, combined with the MLS data. This first LATMOS-IASI data assimilation experiment shows that the resulting analysis is quite similar to the one obtained from the combined MLS and SCIAMACHY data assimilation.

Assimilation of GOME total-ozone satellite observations in a three-dimensional tracer-transport model

2003 ◽  
Vol 129 (590) ◽  
pp. 1663-1681 ◽  
Author(s):  
H. J. Eskes ◽  
P. F. J. Van Velthoven ◽  
P. J. M. Valks ◽  
H. M. Kelder
Keyword(s):  
Total Ozone ◽  
Transport Model ◽  
Three Dimensional ◽  
Satellite Observations ◽  
Tracer Transport

scholarly journals Relations between erythemal UV dose, global solar radiation, total ozone column and aerosol optical depth at Uccle, Belgium

2014 ◽  
Vol 14 (22) ◽  
pp. 12251-12270 ◽  
Author(s):  
V. De Bock ◽  
H. De Backer ◽  
R. Van Malderen ◽  
A. Mangold ◽  
A. Delcloo
Keyword(s):  
Time Series ◽  
Solar Radiation ◽  
Aerosol Optical Depth ◽  
Change Point ◽  
Regression Models ◽  
Total Ozone ◽  
Global Solar Radiation ◽  
Uv Dose ◽  
The Individual ◽  
Ozone Column

Abstract. At Uccle, Belgium, a long time series (1991–2013) of simultaneous measurements of erythemal ultraviolet (UV) dose (Sery), global solar radiation (Sg), total ozone column (Q_{O3}$) and aerosol optical depth (τaer) (at 320.1 nm) is available, which allows for an extensive study of the changes in the variables over time. Linear trends were determined for the different monthly anomalies time series. Sery, Sg and QO3 all increase by respectively 7, 4 and 3% per decade. τaer shows an insignificant negative trend of −8% per decade. These trends agree with results found in the literature for sites with comparable latitudes. A change-point analysis, which determines whether there is a significant change in the mean of the time series, is applied to the monthly anomalies time series of the variables. Only for Sery and QO3, was a significant change point present in the time series around February 1998 and March 1998, respectively. The change point in QO3 corresponds with results found in the literature, where the change in ozone levels around 1997 is attributed to the recovery of ozone. A multiple linear regression (MLR) analysis is applied to the data in order to study the influence of Sg, QO3 and τaer on Sery. Together these parameters are able to explain 94% of the variation in Sery. Most of the variation (56%) in Sery is explained by Sg. The regression model performs well, with a slight tendency to underestimate the measured Sery values and with a mean absolute bias error (MABE) of 18%. However, in winter, negative Sery are modeled. Applying the MLR to the individual seasons solves this issue. The seasonal models have an adjusted R2 value higher than 0.8 and the correlation between modeled and measured Sery values is higher than 0.9 for each season. The summer model gives the best performance, with an absolute mean error of only 6%. However, the seasonal regression models do not always represent reality, where an increase in Sery is accompanied with an increase in QO3 and a decrease in τaer. In all seasonal models, Sg is the factor that contributes the most to the variation in Sery, so there is no doubt about the necessity to include this factor in the regression models. The individual contribution of τaer to Sery is very low, and for this reason it seems unnecessary to include τaer in the MLR analysis. Including QO3, however, is justified to increase the adjusted R2 and to decrease the MABE of the model.

scholarly journals NDACC UV-visible total ozone measurements: improved retrieval and comparison with correlative satellite and ground-based observations

2010 ◽  
Vol 10 (8) ◽  
pp. 20405-20460
Author(s):  
F. Hendrick ◽  
J.-P. Pommereau ◽  
F. Goutail ◽  
R. D. Evans ◽  
D. Ionov ◽  
...  
Keyword(s):  
Cross Sections ◽  
Total Ozone ◽  
Complete Removal ◽  
Temperature Correction ◽  
Atmospheric Composition ◽  
Vertical Column ◽  
Stratospheric Temperature ◽  
Uv Visible ◽  
Ozone Column

Abstract. Accurate long-term monitoring of total ozone is one of the most important requirements for identifying possible natural or anthropogenic changes in the composition of the stratosphere. For this purpose, the NDACC (Network for the Detection of Atmospheric Composition Change) UV-visible Working Group has made recommendations for improving and homogenizing the retrieval of total ozone columns from twilight zenith-sky visible spectrometers. These instruments, deployed all over the world in about 35 stations, allow measurements of total ozone twice daily with little sensitivity to stratospheric temperature and cloud cover. The NDACC recommendations address both the DOAS retrieval parameters and the calculation of air mass factors (AMF) needed for the conversion of O3 slant column densities into vertical column amounts. The most important improvement is the use of O3 AMF look-up tables calculated using the TOMS V8 O3 profile climatology, that allows accounting for the dependence of the O3 AMF on the seasonal and latitudinal variations of the O3 vertical distribution. To investigate their impact on the retrieved ozone columns, the recommendations have been applied to measurements from the NDACC/SAOZ (Système d'Analyse par Observation Zénithale) network. The revised SAOZ ozone data from eight stations covering all latitude regions have been compared to TOMS, GOME-GDP4, SCIAMACHY-TOSOMI, OMI-TOMS, and OMI-DOAS satellite overpass observations, as well as to those of collocated Dobson and Brewer instruments. A significant improvement is obtained after applying the new O3 AMFs, although systematic seasonal differences between SAOZ and all other instruments remain. These are shown to mainly originate from i) the temperature dependence of the ozone absorption cross sections in the UV being not or improperly corrected by some retrieval algorithms, and ii) the longitudinal differences in tropospheric ozone column being ignored by zonal climatologies. For those measurements sensitive to stratospheric temperature like TOMS, OMI-TOMS, Dobson and Brewer, the application of a temperature correction results in the almost complete removal of the seasonal difference with SAOZ, improving significantly the consistency between all ground-based and satellite total ozone observations.

scholarly journals Total ozone column intercomparison of Brewers, Dobsons, and BTS-Solar at Hohenpeißenberg and Davos in 2019/2020

2021 ◽  
Vol 14 (7) ◽  
pp. 4915-4928
Author(s):  
Ralf Zuber ◽  
Ulf Köhler ◽  
Luca Egli ◽  
Mario Ribnitzky ◽  
Wolfgang Steinbrecht ◽  
...  
Keyword(s):  
Seasonal Variation ◽  
Standard Deviation ◽  
Total Ozone ◽  
Retrieval Algorithm ◽  
Measurement Campaign ◽  
Total Ozone Column ◽  
Stratospheric Temperature ◽  
Retrieval Algorithms ◽  
Double Monochromator ◽  
Ozone Column

Abstract. During the 2019/2020 measurement campaign at Hohenpeißenberg (Germany) and Davos (Switzerland) we compared the well-established Dobson and Brewer spectrometers (single- and double-monochromator Brewer) with newer BTS array-spectroradiometer-based systems in terms of total ozone column (TOC) determination. The aim of this study is to validate the BTS performance in a longer-term TOC analysis over more than 1 year with seasonal and weather influences. Two different BTS setups have been used – a fibre-coupled entrance optic version by PMOD/WRC called Koherent and a diffusor optic version from Gigahertz Optik GmbH called BTS-Solar, which proved to be simpler in terms of calibration. The array-spectrometer-based BTS systems have been calibrated with traceability to NMI, and both versions of TOC retrieval algorithms are based on spectral measurements in the range of 305 to 350 nm instead of single-wavelength or wavelength pair measurements as per Brewer or Dobson. The two BTS-based systems, however, used fundamentally different retrieval algorithms for the TOC assessment, whereby the retrieval of the BTS-Solar turned out to achieve significantly smaller seasonal drifts. The intercomparison showed a difference of the BTS-Solar to Brewers of < 0.1 % with an expanded standard deviation (k=2) of < 1.5 % over the whole measurement campaign. Koherent showed a difference of 1.7 % with an expanded standard deviation (k=2) of 2.7 % mostly caused by a significant seasonal variation. To summarize, the BTS-Solar performed at the level of Brewers in the comparison in Hohenpeißenberg. The BTS-Solar showed very small dependence on the slant path column compared to the double-monochromator Brewer and performed better than the single-monochromator Brewer. Koherent showed a strong seasonal variation in Davos due to the sensitivity of its ozone retrieval algorithm to stratospheric temperature.

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