Tropical Tropospheric Ozone Columns Research Articles

TROPOMI tropospheric ozone column data: geophysical assessment and comparison to ozonesondes, GOME-2B and OMI

Abstract. Ozone in the troposphere affects humans and ecosystems as a pollutant and as a greenhouse gas. Observing, understanding and modelling this dual role, as well as monitoring effects of international regulations on air quality and climate change, however, challenge measurement systems to operate at opposite ends of the spatio-temporal scale ladder. Aboard the ESA/EU Copernicus Sentinel-5 Precursor (S5P) satellite launched in October 2017, the TROPOspheric Monitoring Instrument (TROPOMI) aspires to take the next leap forward by measuring ozone and its precursors at unprecedented horizontal resolution until at least the mid-2020s. In this work, we assess the quality of TROPOMI's first release (V01.01.05–08) of tropical tropospheric ozone column (TrOC) data. Derived with the convective cloud differential (CCD) method, TROPOMI daily TrOC data represent the 3 d moving mean ozone column between the surface and 270 hPa under clear-sky conditions gridded at 0.5∘ latitude by 1∘ longitude resolution. Comparisons to almost 2 years of co-located SHADOZ ozonesonde and satellite data (Aura OMI and MetOp-B GOME-2) conclude to TROPOMI biases between −0.1 and +2.3 DU (<+13 %) when averaged over the tropical belt. The field of the bias is essentially uniform in space (deviations <1 DU) and stable in time at the 1.5–2.5 DU level. However, the record is still fairly short, and continued monitoring will be key to clarify whether observed patterns and stability persist, alter behaviour or disappear. Biases are partially due to TROPOMI and the reference data records themselves, but they can also be linked to systematic effects of the non-perfect co-locations. Random uncertainty due to co-location mismatch contributes considerably to the 2.6–4.6 DU (∼14 %–23 %) statistical dispersion observed in the difference time series. We circumvent part of this problem by employing the triple co-location analysis technique and infer that TROPOMI single-measurement precision is better than 1.5–2.5 DU (∼8 %–13 %), in line with uncertainty estimates reported in the data files. Hence, the TROPOMI precision is judged to be 20 %–25 % better than for its predecessors OMI and GOME-2B, while sampling at 4 times better spatial resolution and almost 2 times better temporal resolution. Using TROPOMI tropospheric ozone columns at maximal resolution nevertheless requires consideration of correlated errors at small scales of up to 5 DU due to the inevitable interplay of satellite orbit and cloud coverage. Two particular types of sampling error are investigated, and we suggest how these can be identified or remedied. Our study confirms that major known geophysical patterns and signals of the tropical tropospheric ozone field are imprinted in TROPOMI's 2-year data record. These include the permanent zonal wave-one pattern, the pervasive annual and semiannual cycles, the high levels of ozone due to biomass burning around the Atlantic basin, and enhanced convective activity cycles associated with the Madden–Julian Oscillation over the Indo-Pacific warm pool. TROPOMI's combination of higher precision and higher resolution reveals details of these patterns and the processes involved, at considerably smaller spatial and temporal scales and with more complete coverage than contemporary satellite sounders. If the accuracy of future TROPOMI data proves to remain stable with time, these hold great potential to be included in Climate Data Records, as well as serve as a travelling standard to interconnect the upcoming constellation of air quality satellites in geostationary and low Earth orbits.

FULL-PHYSICS INVERSE LEARNING MACHINE FOR SATELLITE REMOTE SENSING OF OZONE PROFILE SHAPES AND TROPOSPHERIC COLUMNS

Abstract. Characterizing vertical distributions of ozone from nadir-viewing satellite measurements is known to be challenging, particularly the ozone information in the troposphere. A novel retrieval algorithm called Full-Physics Inverse Learning Machine (FP-ILM), has been developed at DLR in order to estimate ozone profile shapes based on machine learning techniques. In contrast to traditional inversion methods, the FP-ILM algorithm formulates the profile shape retrieval as a classification problem. Its implementation comprises a training phase to derive an inverse function from synthetic measurements, and an operational phase in which the inverse function is applied to real measurements. This paper extends the ability of the FP-ILM retrieval to derive tropospheric ozone columns from GOME- 2 measurements. Results of total and tropical tropospheric ozone columns are compared with the ones using the official GOME Data Processing (GDP) product and the convective-cloud-differential (CCD) method, respectively. Furthermore, the FP-ILM framework will be used for the near-real-time processing of the new European Sentinel sensors with their unprecedented spectral and spatial resolution and corresponding large increases in the amount of data.

Tropical tropospheric ozone columns from nadir retrievals of GOME-1/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A (1996–2012)

Abstract. Tropical tropospheric ozone columns are retrieved with the convective cloud differential (CCD) technique using total ozone columns and cloud parameters from different European satellite instruments. Monthly-mean tropospheric column amounts [DU] are calculated by subtracting the above-cloud ozone column from the total column. A CCD algorithm (CCD_IUP) has been developed as part of the verification algorithm developed for TROPOspheric Monitoring Instrument (TROPOMI) on Sentinel 5-precursor (S5p) mission, which was applied to GOME/ERS-2 (1995–2003), SCIAMACHY/Envisat (2002–2012), and GOME-2/MetOp-A (2007–2012) measurements. Thus a unique long-term record of monthly-mean tropical tropospheric ozone columns (20° S–20° N) from 1996 to 2012 is now available. An uncertainty estimation has been performed, resulting in a tropospheric ozone column uncertainty less than 2 DU ( < 10 %) for all instruments. The dataset has not been yet harmonised into one consistent; however, comparison between the three separate datasets (GOME/SCIAMACHY/GOME-2) shows that GOME-2 overestimates the tropical tropospheric ozone columns by about 8 DU, while SCIAMACHY and GOME are in good agreement. Validation with Southern Hemisphere ADditional OZonesondes (SHADOZ) data shows that tropospheric ozone columns from the CCD_IUP technique and collocated integrated ozonesonde profiles from the surface up to 200 hPa are in good agreement with respect to range, interannual variations, and variances. Biases within ±5 DU and root-mean-square (RMS) deviation of less than 10 DU are found for all instruments. CCD comparisons using SCIAMACHY data with tropospheric ozone columns derived from limb/nadir matching have shown that the bias and RMS deviation are within the range of the CCD_IUP comparison with the ozonesondes. The 17-year dataset can be helpful for evaluating chemistry models and performing climate change studies.

Tropical tropospheric ozone column retrieval for GOME-2

Abstract. This paper presents the operational retrieval of tropical tropospheric ozone columns (TOCs) from the Second Global Ozone Monitoring Experiment (GOME-2) instruments using the convective-cloud-differential (CCD) method. The retrieval is based on total ozone and cloud property data provided by the GOME Data Processor (GDP) 4.7, and uses above-cloud and clear-sky ozone column measurements to derive a monthly mean TOC between 20° N and 20° S. Validation of the GOME-2 TOC with several tropical ozonesonde sites shows good agreement, with a high correlation between the GOME-2 and sonde measurements, and small biases within ~ 3 DU. The TOC data have been used in combination with tropospheric NO2 measurements from GOME-2 to analyse the effect of the 2009–2010 El Niño–Southern Oscillation (ENSO) on the tropospheric ozone distribution in the tropics. El Niño induced dry conditions in September–October 2009 resulted in relatively high tropospheric ozone columns over the southern Indian Ocean and northern Australia, while La Niña conditions in September–October 2010 resulted in a strong increase in tropospheric NO2 in South America, and enhanced ozone in the eastern Pacific and South America. Comparisons of the GOME-2 tropospheric ozone data with simulations of the ECHAM/MESSy Atmospheric Chemistry (EMAC) model for 2009 El Niño conditions illustrate the usefulness of the GOME-2 TOC measurements in evaluating chemistry climate models (CCMs). Evaluation of CCMs with appropriate satellite observations helps to identify strengths and weaknesses of the model systems, providing a better understanding of driving mechanisms and adequate relations and feedbacks in the Earth atmosphere, and finally leading to improved models.

Estimating the climate significance of halogen-driven ozone loss in the tropical marine troposphere

Abstract. We have integrated observations of tropospheric ozone, very short-lived (VSL) halocarbons and reactive iodine and bromine species from a wide variety of tropical data sources with the global CAM-Chem chemistry-climate model and offline radiative transfer calculations to compute the contribution of halogen chemistry to ozone loss and associated radiative impact in the tropical marine troposphere. The inclusion of tropospheric halogen chemistry in CAM-Chem leads to an annually averaged depletion of around 10% (~2.5 Dobson units) of the tropical tropospheric ozone column, with largest effects in the middle to upper troposphere. This depletion contributes approximately −0.10 W m−2 to the radiative flux at the tropical tropopause. This negative flux is of similar magnitude to the ~0.33 W m−2 contribution of tropospheric ozone to present-day radiative balance as recently estimated from satellite observations. We find that the implementation of oceanic halogen sources and chemistry in climate models is an important component of the natural background ozone budget and we suggest that it needs to be considered when estimating both preindustrial ozone baseline levels and long term changes in tropospheric ozone.

The influence of biogenic emissions from Africa on tropical tropospheric ozone during 2006: a global modeling study

Abstract. We have performed simulations using a 3-D global chemistry-transport model to investigate the influence that biogenic emissions from the African continent exert on the composition of the troposphere in the tropical region. For this purpose we have applied two recently developed biogenic emission inventories provided for use in large-scale global models (Granier et al., 2005; Lathière et al., 2006) whose seasonality and temporal distribution for biogenic emissions of isoprene, other volatile organic compounds and NO is markedly different. The use of the 12 year average values for biogenic emissions provided by Lathière et al. (2006) results in an increase in the amount of nitrogen sequestrated into longer lived reservoir compounds which contributes to the reduction in the tropospheric ozone burden in the tropics. The associated re-partitioning of nitrogen between PAN, HNO3 and organic nitrates also results in a ~5% increase in the loss of nitrogen by wet deposition. At a global scale there is a reduction in the oxidizing capacity of the model atmosphere which increases the atmospheric lifetimes of CH4 and CO by ~1.5% and ~4%, respectively. Comparisons against a range of different measurements indicate that applying the 12 year average of Lathière et al. (2006) improves the performance of TM4_AMMA for 2006 in the tropics. By the use of sensitivity studies we show that the release of NO from soils in Africa accounts for between ~2–45% of tropospheric ozone in the African troposphere, ~10% in the upper troposphere and between ~5–20% of the tropical tropospheric ozone column over the tropical Atlantic Ocean. The subsequent reduction in OH over the source regions allows enhanced transport of CO out of the region. For biogenic volatile organic C1 to C3 species released from Africa, the effects on tropical tropospheric ozone are rather limited, although this source contributes to the global burden of VOC by between ~2–4% and has a large influence on the organic composition of the troposphere over the tropical Atlantic Ocean.

Tropospheric ozone over a tropical Atlantic station in the Northern Hemisphere: Paramaribo, Surinam (6¼N, 55¼W)

We present an analysis of 2.5 yr of weekly ozone soundings conducted at a new monitoring station in Paramaribo, Surinam (6¼N, 55¼W). This is currently one of only three ozone sounding stations in the Northern Hemisphere (NH) tropics, and the only one in the equatorial Atlantic region. Paramaribo is part of the Southern Hemisphere Additional Ozone Sounding program (SHADOZ). Owing to its position close to the equator, the inter-tropical convergence zone (ITCZ) passes over Paramaribo twice per year, which results in a semi-annual seasonality of many parameters including relative humidity and ozone. The dataset from Paramaribo is used to: (1) evaluate the ozone variability relative to precipitation, atmospheric circulation patterns and biomass burning; (2) contrast ozone at the NH equatorial Atlantic with that at nearby Southern Hemisphere (SH) stations Natal (6¼S, 35¼W) and Ascension (8¼S, 14¼W); (3) compare the seasonality of tropospheric ozone with a satellite-derived ozone product: tropical tropospheric ozone columns from the modified residual method (MR-TTOC). We find that Paramaribo is a distinctly Atlantic station. Despite its position north of the equator, it resembles nearby SH stations during most of the year. Transport patterns in the lower and middle troposphere during February and March differ from SH stations, which leads to a seasonality of ozone with two maxima. MR-TTOC over Paramaribo does not match the observed seasonality of ozone due to the use of a SH ozone sonde climatology in the MR method. The Paramaribo ozone record is used to suggest an improvement for Northern Hemisphere MR-TTOC retrievals. We conclude that station Paramaribo shows unique features in the region, and clearly adds new information to the existing SHADOZ record.

Variability in tropical tropospheric ozone: Analysis with Global Ozone Monitoring Experiment observations and a global model

Tropical tropospheric ozone columns (TTOCs) have been determined with a convective‐cloud‐differential (CCD) method, using ozone column and cloud measurements from the Global Ozone Monitoring Experiment (GOME) instrument. GOME cloud top pressures, derived with the Fast Retrieval Scheme for Clouds from the Oxygen A‐band (FRESCO) method, indicate that most convective cloud top levels are between 300 and 500 hPa and do not extend to the tropical tropopause. The new GOME‐CCD method takes this tropical transition layer below the tropopause into account and uses above‐cloud and clear‐sky ozone column measurements to derive a monthly mean TTOC below 200 hPa. Validation of the GOME‐TTOCs with seven Southern Hemisphere Additional Ozonesondes (SHADOZ) sites shows good agreement, with an RMS difference of about 5 Dobson units. In the northern tropics the GOME‐TTOC compares most of the time well with in situ measurements at Paramaribo (6°N, 55°W) and Abidjan (5°N, 4°W). Analysis of the GOME‐TTOCs for 2000 and 2001, with the aid of the chemistry‐transport model TM3, illustrates that the variability in the TTOC depends on a complex interaction of several processes, including biomass burning, lightning, and large‐scale transport. The much larger extent of the South Atlantic TTOC maximum in September–October 2001, compared to September–October 2000, can be attributed to differences in large‐scale transport. An exceptional situation in the northern tropics occurred during the biomass burning season December 2001 to January 2002, when there were almost no fires over northern Africa. This resulted in strongly reduced TTOCs over the Atlantic between the equator and 10°N.

Interpretation of TOMS observations of tropical tropospheric ozone with a global model and in situ observations

We interpret the distribution of tropical tropospheric ozone columns (TTOCs) from the Total Ozone Mapping Spectrometer (TOMS) by using a global three‐dimensional model of tropospheric chemistry (GEOS‐CHEM) and additional information from in situ observations. The GEOS‐CHEM TTOCs capture 44% of the variance of monthly mean TOMS TTOCs from the convective cloud differential method (CCD) with no global bias. Major discrepancies are found over northern Africa and south Asia where the TOMS TTOCs do not capture the seasonal enhancements from biomass burning found in the model and in aircraft observations. A characteristic feature of these northern tropical enhancements, in contrast to southern tropical enhancements, is that they are driven by the lower troposphere where the sensitivity of TOMS is poor due to Rayleigh scattering. We develop an efficiency correction to the TOMS retrieval algorithm that accounts for the variability of ozone in the lower troposphere. This efficiency correction increases TTOCs over biomass burning regions by 3–5 Dobson units (DU) and decreases them by 2–5 DU over oceanic regions, improving the agreement between CCD TTOCs and in situ observations. Applying the correction to CCD TTOCs reduces by ∼5 DU the magnitude of the “tropical Atlantic paradox” [Thompson et al., 2000], i.e. the presence of a TTOC enhancement over the southern tropical Atlantic during the northern African biomass burning season in December–February. We reproduce the remainder of the paradox in the model and explain it by the combination of upper tropospheric ozone production from lightning NOx, persistent subsidence over the southern tropical Atlantic as part of the Walker circulation, and cross‐equatorial transport of upper tropospheric ozone from northern midlatitudes in the African “westerly duct.” These processes in the model can also account for the observed 13–17 DU persistent wave‐1 pattern in TTOCs with a maximum over the tropical Atlantic and a minimum over the tropical Pacific during all seasons. The photochemical effects of mineral dust have only a minor role on the modeled distribution of TTOCs, including over northern Africa, due to multiple competing effects. The photochemical effects of mineral dust globally decrease annual mean OH concentrations by 9%. A global lightning NOx source of 6 Tg N yr−1 in the model produces a simulation that is most consistent with TOMS and in situ observations.

Chemistry-transport modeling of the satellite observed distribution of tropical troposheric ozone

Abstract. We have compared the 14-year record of satellite derived tropical tropospheric ozone columns (TTOC) from the NIMBUS--7 Total Ozone Mapping Spectrometer (TOMS) to TTOC calculated by achemistry-transport model (CTM). An objective measure of error, based on the zonal distribution of TTOC in the tropics, is applied to perform this comparison systematically. In addition, the sensitivity of the model to several key processes in the tropics is quantified to select directions for future improvements. The comparisons indicate a widespread, systematic (20%) discrepancy over the tropical Atlantic Ocean, which maximizes during austral Spring. Although independent evidence from ozonesondes shows that some of the disagreement is due to satellite overestimate of TTOC, the Atlantic mismatch is largely due to a misrepresentation of seasonally recurring processes in the model. Only minor differences between the model and observations over the Pacific occur, mostly due to interannual variability not captured by the model. Although chemical processes determine the TTOC extent, dynamical processes dominate the TTOC distribution, as the use of actual meteorology pertaining to the year of observations always leads to a better agreement with TTOC observations than using a random year or a climatology. The modeled TTOC is remarkably insensitive to many model parameters due to efficient feedbacks in the ozone budget. Nevertheless, the simulations would profit from an improved biomass burning calendar, as well as from an increase in NOx abundances in free tropospheric biomass burning plumes. The model showed the largest response to lightning NOx emissions, but systematic improvements could not be found. The use of multi-year satellite derived tropospheric data to systematically test and improve a CTM is a promising new addition to existing methods of model validation, and is a first step to integrating tropospheric satellite observations into global ozone modeling studies. Conversely, the CTM may suggest improvements to evolving satellite retrievals for tropospheric ozone.

Distribution of Tropical Tropospheric Ozone Determined by the Scan-Angle Method Applied to TOMS Measurements

Abstract This work describes the first method to determine the tropical tropospheric ozone column directly from the Total Ozone Mapping Spectrometer (TOMS) space-borne instrument based on the physical differences in ozone-column detection as a function of its scan-angle geometry. Comparisons to tropical ozonesonde observations suggest the accuracy of these retrievals is ∼20%. Tropospheric ozone derived from this scan-angle method (SAM) exhibits a broad enhancement over South America, the southern Atlantic Ocean, and western South Africa and a minimum over the central Pacific Ocean in September–October. An ozone enhancement in equatorial North Africa is seen in March, the northern burning season. This ozone abundance is not detected by other retrieval methods. The magnitude of the ozone enhancement south of the equator is greater than the enhancement north of the equator. Abnormally high tropospheric ozone occurs over the western Pacific Ocean during the El Nino season when the ozone amounts are as high as...

Identification of an El Niño‐Southern Oscillation signal in a multiyear global simulation of tropospheric ozone

We present the first study of the El Niño‐Southern Oscillation (ENSO) interannual variability in tropical tropospheric ozone in a multiyear simulation with a global three‐dimensional chemistry‐transport model. A 15‐year period (1979–1993) was simulated using European Centre for Medium‐Range Weather Forecasts meteorological reanalysis data and a time‐varying emission data set. A comparison of model calculations with observations shows good agreement for surface ozone, seasonal cycles, and ozone concentrations at remote stations, but reveals an underestimate of ozone in the free troposphere, which is most pronounced during biomass burning seasons. The ENSO signal is the most important component of interannual variability in tropical tropospheric ozone columns (TTOC), being responsible for nearly 25% of the total interannual variability of ozone in the tropics. The amplitude of the modeled ENSO signal in TTOC is 3 Dobson units, in close agreement with satellite observations. This signal is evenly distributed with height, indicating that rapid vertical transport plays an important role. The ENSO signal is also detectable at the surface, for example at the Pacific island Samoa, for which model‐calculated and measured ozone agree well.

Detection of a lightning influence on tropical tropospheric ozone

Empirical orthogonal functions (EOFs) are used to analyze a 14‐year record of tropical tropospheric ozone columns (TTOCs) determined from satellite measurements. The first EOF explains 54% of TTOC variance and represents biomass burning in Africa and South America. The second EOF explains 20% of the variance and has a distinct lightning signature.