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NASA NTRS2007

Air Quality Research and Applications Using AURA OMi Data

The Ozone Monitoring Instrument (OMI) on EOS Aura is a new generation of satellite remote sensing instrument designed to measure trace gas and aerosol absorption at the UV and blue wavelengths. These measurements are made globally at urban scale resolution with no inter-orbital gaps that make them potentially very useful for air quality research, such as the determination of the sources and processes that affect global and regional air quality, and to develop applications such as air quality forecast. However, the use of satellite data for such applications is not as straight forward as satellite data have been for stratospheric research. There is a need for close interaction between the satellite product developers, in-situ measurement programs, and the air quality research community to overcome some of the inherent difficulties in interpreting data from satellite-based remote sensing instruments. In this talk we will discuss the challenges and opportunities in using OMI products for air quality research and applications. A key conclusion of this work is that to realize the full potential of OMI measurements it will be necessary to combine OMI data with data from instruments such as MLS, MODIS, AIRS, and CALIPSO that are currently flying in the "A-train" satellite constellation. In addition similar data taken by satellites crossing the earth at different local times than the A-train (e.g., the recently MetOp satellite) would need to be processed in a consistent manner to study diurnal variability, and to capture the effects on air quality of rapidly changing events such as wild fires.

Bhartia, P.K.↗
NASA NTRSDate not supplied

Assessment of Long-term Trends in the Collection 4 Total Ozone Record from the Ozone Monitoring Instrument

Long-term changes in total ozone affect the amount of harmful UV radiation reaching Earth’s surface and reflect progress made towards recovery of stratospheric ozone. Satellite total ozone data are also used to estimate long-term trends in tropospheric ozone, a reactive and potent greenhouse gas, by subtracting the stratospheric column timeseries from that of total ozone. For these scientific applications, the long-term stability should be better than 1%. Left unchecked, instrument calibration drift can produce a trend of this magnitude or greater. NASA has produced nearly twenty years of total ozone data from the Ozone Monitoring Instrument (OMI) using the Total Ozone Mapping Spectrometer (TOMS) algorithm. The drift in the OMI instrument as monitored by ice radiance calibration has been relatively slow, but it has reached a level of ~3% over the mission lifetime. This drift was corrected in the recently released Collection 4 OMI calibrated radiances, updating the Collection 3 calibration released in 2006. We have reprocessed the OMI total ozone record using the Collection 4 calibration and updates to the TOMS algorithm. We summarize these changes and evaluate their impact by comparing to the previous Collection 3 OMI dataset, the Suomi NPP Ozone Mapping and Profiler Suite Nadir Mapper (OMPS-NM) and Solar Backscatter UV (SBUV) Merged Ozone Dataset (MOD) total ozone records and other independent satellite total ozone datasets. Climatological radiance residuals from OMI and OMPS-NM are calculated and compared to investigate differences in spectral calibration that can cause drifts in long-term total ozone trends. We also analyze the tropospheric ozone record produced using the Collection 4 OMI total ozone and stratospheric column ozone from MLS. Collection 3 OMI data processed with the TOMS algorithm show a positive drift relative to other satellite and ground-based data of 1-2 DU per decade. Initial results show that this drift is reduced in Collection 4 OMI, due to the updated OMI calibration. In this work we will quantify the improvements in Collection 4 OMI relative to independent data sources at both the ozone and radiance level

Collection 4 OMI Total Ozone↗
NASA NTRSDate not supplied

Tropospheric Ozone in the NASA GEOS Model: Effects of Satellite NO2 Data Assimilation and Improvements in Background NOx Chemistry

Tropospheric ozone is a major atmospheric oxidant, the primary source of the hydroxyl radical, and a greenhouse gas. In the troposphere, it is produced from the oxidation of carbon monoxide and volatile organic compounds in the presence of nitrogen oxides (NOx=NO+NO2) or has its origins in the stratosphere. The tropospheric ozone burdens in global atmospheric chemistry models disagree by a factor of 1.5, indicating an incomplete understanding of ozone sources and sinks. Here we examine the tropospheric ozone simulation in NASA Global Modeling and Assimilation Office’s (GMAO’s) GEOS model with the GEOS-Chem chemistry mechanism (version 14.2), using observations from satellites, aircraft, ozonesondes, and surface sites. This modeling framework is used to produce GMAO’s GEOS Composition Forecasts (GEOS-CF), and it has been updated extensively with new emission inventories, improved model physics, satellite data assimilation capability, and an up-to-date chemical mechanism that includes tropospheric halogen chemistry and NOx recycling from particulate nitrate. Earlier versions of the model using GEOS-Chem version 12.0 showed an underestimate in tropospheric ozone in the northern hemisphere. We evaluate the ozone simulation in the updated model, focusing on the effects of assimilating satellite NO2 data from the Ozone Monitoring Instrument (OMI), constraining stratospheric ozone to satellite data, and updates to the NOx chemistry. We will examine changes in the vertical profiles of tropospheric ozone over the US in support of the Tropospheric Emissions: Monitoring of Pollution (TEMPO), and discuss implications for the tropospheric ozone budget.

V. Shah↗
NASA NTRSDate not supplied

Tropospheric Ozone in the NASA GEOS Model: Effects of Satellite Data Assimilation and Improvements in Background NO x Chemistry

Tropospheric ozone is a major atmospheric oxidant, the primary source of the hydroxyl radical, and a greenhouse gas. In the troposphere, it is produced from the oxidation of carbon monoxide and volatile organic compounds in the presence of nitrogen oxides (NO x =NO+NO 2 ) or has its origins in the stratosphere. The tropospheric ozone burdens in global atmospheric chemistry models disagree by a factor of 1.5, indicating an incomplete understanding of ozone sources and sinks. Here we examine the tropospheric ozone simulation in NASA Global Modeling and Assimilation Office’s (GMAO’s) GEOS model with the GEOS-Chem chemistry mechanism (version 14.2), using observations from satellites, aircraft, ozonesondes, and surface sites. This modeling framework is used to produce GMAO’s GEOS Composition Forecasts (GEOS-CF), and it has been updated extensively with new emission inventories, improved model physics, satellite data assimilation capability, and an up-to-date chemical mechanism that includes tropospheric halogen chemistry and NOx recycling from particulate nitrate. Earlier versions of the model using GEOS-Chem version 12.0 showed an underestimate in tropospheric ozone in the northern hemisphere. We evaluate the ozone simulation in the updated model, focusing on the effects of assimilating satellite NO 2 data from the Ozone Monitoring Instrument (OMI), constraining stratospheric ozone to satellite data, and updates to the NOx chemistry. We will examine changes in the vertical profiles of tropospheric ozone over the US in support of the Tropospheric Emissions: Monitoring of Pollution (TEMPO), and discuss implications for the tropospheric ozone budget.

Viral Shah↗
NASA NTRS2006

Tropospheric and stratospheric ozone from assimilation of Aura data

Ozone is an atmospheric trace gas with multiple impacts on the environment. Global ozone fields are needed for air quality predictions, estimation of the ultraviolet radiation reaching the surface, climate-radiation studies, and may also have an impact on longer-term weather predictions. We estimate global ozone fields in the stratosphere and troposphere by combining the data from EOS Aura satellite with an ozone model using data assimilation. Ozone exhibits a large temporal variability in the lower stratosphere. Our previous work showed that assimilation of satellite data from limb-sounding geometry helps constrain ozone profiles in that region. We assimilated ozone data from the Aura Microwave Limb Sounder (MLS) and the Ozone Monitoring Instrument (OMI) into the ozone system at NASA's Global Modeling and Assimilation Office (GMAO). Ozone is transported within a general circulation model (GCM) which includes parameterizations for stratospheric photochemistry, tropospheric chemistry, and a simple scheme for heterogeneous ozone loss. The focus of this study is on the representation of ozone in the lower stratosphere and tropospheric ozone columns. We plan to extend studies of tropospheric ozone distribution through assimilation of ozone data from the Tropospheric Emission Spectrometer (TES). Comparisons with ozone sondes and occultation data show that assimilation of Aura data reproduces ozone gradients and variability in the lower stratosphere well. We proceed by separating the contributions to temporal changes in the ozone field into those that are due to the model and those that are due to the assimilation of Aura data. The impacts of Aura data are illustrated and their role in the representation of ozone variability in the lower stratosphere and troposphere is shown.

Stajner, I.↗
NASA NTRS2005

Assimilation of MLS and OMI Ozone Data

Ozone data from Aura Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) were assimilated into the ozone model at NASA's Global Modeling and Assimilation Office (GMAO). This assimilation produces ozone fields that are superior to those from the operational GMAO assimilation of Solar Backscatter Ultraviolet (SBUV/2) instrument data. Assimilation of Aura data improves the representation of the "ozone hole" and the agreement with independent Stratospheric Aerosol and Gas Experiment (SAGE) III and ozone sonde data. Ozone in the lower stratosphere is captured better: mean state, vertical gradients, spatial and temporal variability are all improved. Inclusion of OMI and MLS data together, or separately, in the assimilation system provides a way of checking how consistent OMI and MLS data are with each other, and with the ozone model. We found that differences between OMI total ozone column data and model forecasts decrease after MLS data are assimilated. This indicates that MLS stratospheric ozone profiles are consistent with OMI total ozone columns. The evaluation of error characteristics of OMI and MLS ozone will continue as data from newer versions of retrievals becomes available. We report on the initial step in obtaining global assimilated ozone fields that combine measurements from different Aura instruments, the ozone model at the GMAO, and their respective error characteristics. We plan to use assimilated ozone fields in estimation of tropospheric ozone. We also plan to investigate impacts of assimilated ozone fields on numerical weather prediction through their use in radiative models and in the assimilation of infrared nadir radiance data from NASA's Advanced Infrared Sounder (AIRS).

Stajner, I.↗
NASA NTRS2017

Optimal A-Train Data Utilization: A Use Case of Aura OMI L2G and MERRA-2 Aerosol Products

Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission measures ozone column and profile, aerosols, clouds, surface UV irradiance, and the trace gases including NO2, SO2, HCHO, BrO, and OClO using UltraViolet electromagnetic spectrum (280 - 400 nm) with a daily global coverage and a pixel spatial resolution of 13 km × 24 km at nadir, and it's been one of the key instruments to study the Earth's atmospheric composition and chemistry. The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is NASA's atmospheric reanalysis using an upgraded version of Goddard Earth Observing System Model, version 5 (GEOS-5) data assimilation system. Compared to its predecessor MERRA, MERRA-2 is enhanced with more aspects of the Earth system among which is aerosol assimilation. When comparing between satellite pixel measurements and modeled grid data, how to properly handle counterpart pairing is critical considering their spatial and temporal variations. The comparison between satellite and model data by simply using Level 3 (L3) products may result biases due to lack of detailed temporal information. It has been preferred to inter-compare or implement satellite derived physical quantity (i.e., Level 2 (L2) Swath type) directly with/to model measurements with higher temporal and spatial resolution as possible. However, this has posed a challenge in the community to handle. Rather than directly handling the L2 or L3 data, there is a Level 2G (L2G) product conserving L2 pixel scientific data quality but in Grid type with the global coverage. In this presentation, we would like to demonstrate the optimal utilization of OMI L2G daily aerosol products by comparing with MERRA-2 hourly aerosol simulations matched well in both space and time.

MERRA-2 reanalysis↗
NASA NTRS2016

Tropospheric Column Ozone Response to ENSO in GEOS-5 Assimilation of OMI and MLS Ozone Data

We use GEOS-5 analyses of Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) ozone observations to investigate the magnitude and spatial distribution of the El Nino Southern Oscillation (ENSO) influence on tropospheric column ozone (TCO) into the middle latitudes. This study provides the first explicit spatially resolved characterization of the ENSO influence and demonstrates coherent patterns and teleconnections impacting the TCO in the extratropics. The response is evaluated and characterized by both the variance explained and sensitivity of TCO to the Nino 3.4 index. The tropospheric response in the tropics agrees well with previous studies and verifies the analyses. A two-lobed response symmetric about the Equator in the western Pacific/Indonesian region seen in some prior studies and not in others is confirmed here. This two-lobed response is consistent with the large-scale vertical transport. We also find that the large-scale transport in the tropics dominates the response compared to the small-scale convective transport. The ozone response is weaker in the middle latitudes, but a significant explained variance of the TCO is found over several small regions, including the central United States. However, the sensitivity of TCO to the Nino 3.4 index is statistically significant over a large area of the middle latitudes. The sensitivity maxima and minima coincide with anomalous anti-cyclonic and cyclonic circulations where the associated vertical transport is consistent with the sign of the sensitivity. Also, ENSO related changes to the mean tropopause height can contribute significantly to the midlatitude response. Comparisons to a 22-year chemical transport model simulation demonstrate that these results from the 9- year assimilation are representative of the longer term. This investigation brings insight to several seemingly disparate prior studies of the El Nino influence on tropospheric ozone in the middle latitudes.

ML↗
NASA NTRS2014

Development and Testing of the New Surface LER Climatology for OMI UV Aerosol Retrievals

Ozone Monitoring Instrument (OMI) onboard Aura satellite retrieved aerosols properties using UV part of solar spectrum. The OMI near UV aerosol algorithm (OMAERUV) is a global inversion scheme which retrieves aerosol properties both over ocean and land. The current version of the algorithm makes use of TOMS derived Lambertian Equivalent Reflectance (LER) climatology. A new monthly climatology of surface LER at 354 and 388 nm have been developed. This will replace TOMS LER (380 nm and 354nm) climatology in OMI near UV aerosol retrieval algorithm. The main objectives of this study is to produce high resolution (quarter degree) surface LER sets as compared to existing one degree TOMS surface LERs, to product instrument and wavelength consistent surface climatology. Nine years of OMI observations have been used to derive monthly climatology of surface LER. MODIS derived aerosol optical depth (AOD) have been used to make aerosol corrections on OMI wavelengths. MODIS derived BRDF adjusted reflectance product has been also used to capture seasonal changes in the surface characteristics. Finally spatial and temporal averaging techniques have been used to fill the gaps around the globes, especially in the regions with consistent cloud cover such as Amazon. After implementation of new surface data in the research version of algorithm, comparisons of AOD and single scattering albedo (SSA) have been performed over global AERONET sites for year 2007. Preliminary results shows improvements in AOD retrievals globally but more significance improvement were observed over desert and bright locations. We will present methodology of deriving surface data sets and will discuss the observed changes in retrieved aerosol properties with respect to reference AERONET measurements.

Aerosol↗
NASA NTRS2014

Assessment of 10 Year Record of Aerosol Optical Depth from OMI UV Observations

The Ozone Monitoring Instrument (OMI) onboard the EOS-Aura satellite provides information on aerosol optical properties by making use of the large sensitivity to aerosol absorption in the near-ultraviolet (UV) spectral region. Another important advantage of using near UV observations for aerosol characterization is the low surface albedo of all terrestrial surfaces in this spectral region that reduces retrieval errors associated with land surface reflectance characterization. In spite of the 13 × 24 square kilometers coarse sensor footprint, the OMI near UV aerosol algorithm (OMAERUV) retrieves aerosol optical depth (AOD) and single-scattering albedo under cloud-free conditions from radiance measurements at 354 and 388 nanometers. We present validation results of OMI AOD against space and time collocated Aerosol Robotic Network measured AOD values over multiple stations representing major aerosol episodes and regimes. OMAERUV's performance is also evaluated with respect to those of the Aqua-MODIS Deep Blue and Terra-MISR AOD algorithms over arid and semi-arid regions in Northern Africa. The outcome of the evaluation analysis indicates that in spite of the "row anomaly" problem, affecting the sensor since mid-2007, the long-term aerosol record shows remarkable sensor stability.

aerosol optical depth↗
NASA NTRSDate not supplied

Multi-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS) Datasets Released by NASA GES DISC and Their Applications for Air Quality

Nitrogen dioxide (NO2), a pervasive air pollutant, comes from vehicles, power plants, industrial emissions, and off-road sources such as construction or lawn and gardening equipment. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) curates many remote sensing datasets with NO2 retrievals, which have been utilized for air quality research and applications. The remotely-sensed datasets include those generated by the Ozone Monitoring Instrument (OMI) on the Aura satellite, the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S5P), and the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi National Polar-orbiting Partnership (S- NPP). In collaboration with the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Multi-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS) project, the GES DISC recently released MINDS datasets. The NASA MEaSUREs MINDS project aims to develop long-term NO2 global data records by adapting a consistent retrieval algorithm to multiple instrument measurements. Long-term data records will be achieved by applying consistent retrieval approaches to multiple satellite instruments, including OMI (2004 - ); the Global Ozone Monitoring Experiment (GOME, 1995-2011) onboard the second European Remote Sensing satellite (ERS-2); the Scanning Imaging Spectrometer for Atmospheric Cartography (SCIAMACHY, 2002-2012) onboard the ENVIronmental SATellite (ENVISAT); GOME-2 on the Meteorological Operational satellites (MetOp-A and MetOp-B, 2006 - ); and TROPOMI onboard the Copernicus S5P (2017 - ). The long-term record (1995 to present) of MINDS datasets makes them very useful for air quality trend studies. Some MINDS datasets with high spatial resolution of only a few kilometers can be used for air quality research and applications at regional scales. In this presentation, we will introduce all of the MINDS products and services, and demonstrate use cases of MINDS data for studying air quality. We will also present a few other NO2 datasets acquired from NASA’s Health and Air Quality Applied Sciences Team (HAQAST), to be archived and distributed by the GES DISC, and highlight some of their applications for air quality and health.

Feng Ding↗
NASA NTRSDate not supplied

Comparing Satellite Measurements of Volcanic SO2 Mass from OMI, OMPS and TROPOMI

Sulfur dioxide (SO2) is a major air pollutant that contributes to acid rain and aerosol formation (e.g., sulfates), adversely affects the environment and human health, and explosive volcanic SO2 emissions can impact climate. The majority of SO2 emissions are related to anthropogenic processes (e.g., fossil fuel burning, metal ore smelting operations), although natural processes such as volcanic eruptions and degassing also play an important role as anthropogenic SO2 emissions continue to decline. Generally, the most interest in volcanoes occurs during major eruptions. We will focus on comparing volcanic SO2 outgassing that occurs on an almost daily basis from lesser known volcanoes using satellite data. At NASA’s Global Sulfur Dioxide Monitoring Home page (https://so2.gsfc.nasa.gov/), we have been posting daily SO2 maps from 40 volcanic and industrial regions around the world using measurements from three satellite instruments; the Ozone Monitoring Instrument (OMI) onboard NASA’s Earth Observing System Aura satellite, the Ozone Monitoring and Profiler Suite (OMPS) onboard the NASA-NOAA Suomi National Polar-orbiting Partnership (NPP) satellite, and the TROPOspheric Monitoring Instrument (TROPOMI) onboard the ESA/Copernicus Sentinel-5 Precursor satellite. These instruments in low Earth sun-synchronous polar orbits with 1:30-2:00 pm equator crossing local time provide daily SO2 maps at different spatial resolutions: 13 x 24 km2, 50 x 50 km2 and 5.5 x 3.5 km2 for OMI, OMPS and TROPOMI respectively. Data from OMI are available since October 2004 (partial coverage since 2008), from OMPS since 2012 and from TROPOMI since 2018. We will present comparative SO2 mass time-series (see Hunga-Tonga plot) and statistical analyses of recent eruptions that have data from all the instruments.

SO2↗
NASA NTRS2022

Out of the blue: volcanic SO e2 emissions during the 2021–2022 eruptions of Hunga Tonga – Hunga Ha'apai (Tonga)

Most volcanism on Earth is submarine, but volcanic gas emissions by submarine eruptions are rarely observed and hence largely unquantified. On January 15, 2022 a submarine eruption of Hunga Tonga-Hunga Ha'apai (HTHH) volcano (Tonga) generated an explosion of historic magnitude, and was preceded by ≈1 month of Surtseyan eruptive activity and two precursory explosive eruptions. We present an analysis of ultraviolet (UV) satellite measurements of volcanic sulfur dioxide (SO 2 ) between December 2021 and the climactic January 15, 2022 eruption, comprising an unprecedented record of Surtseyan eruptive emissions. UV measurements from the Ozone Monitoring Instrument (OMI) on NASA’s Aura satellite, the Ozone Mapping and Profiler Suite (OMPS) on Suomi-NPP, the Tropospheric Monitoring Instrument (TROPOMI) on ESA’s Sentinel-5P, and the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) are combined to yield a consistent multi-sensor record of eruptive degassing. We estimate SO 2 emissions during the eruption’s key phases: the initial December 19, 2021 eruption (≈0.01 Tg SO 2 ); continuous SO 2 emissions from December 20, 2021 – early January 2022 (≈0.12 Tg SO 2 ); the January 13, 2022 stratospheric eruption (0.06 Tg SO 2 ); and the paroxysmal January 15, 2022 eruption (≈0.4-0.5 Tg SO 2 ); yielding a total SO 2 emission of ≈0.60.7 Tg SO 2 for the eruptive episode. We interpret the vigorous SO 2 emissions observed prior to the January 2022 eruptions, which were significantly higher than measured in the 2009 and 2014 HTHH eruptions, as strong evidence for a rejuvenated magmatic system. High cadence DSCOVR/EPIC SO 2 imagery permits the first UV-based analysis of umbrella cloud spreading and volume flux in the January 13, 2022 eruption, and also tracks early dispersion of the stratospheric SO 2 cloud injected on January 15. The ≈0.4-0.5 Tg SO 2 discharged by the paroxysmal January 15, 2022 HTHH eruption is low relative to other eruptions of similar magnitude, and a review of other submarine eruptions in the satellite era indicates that modest SO 2 yields may be characteristic of submarine volcanism, with the emissions and atmospheric impacts likely dominated by water vapor. The origin of the low SO 2 loading awaits further investigation but scrubbing of SO 2 in the water-rich eruption plumes and rapid conversion to sulfate aerosol are plausible, given the exceptional water emission by the January 15, 2022 HTHH eruption.

Volcanoes↗
NASA NTRS2017

The Version 3 OMI NO2 Standard Product

We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2) products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO2 slant column density (SCD) retrieval and (2) higher-resolution (1° latitude and 1.25° longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry–transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by ∼10-40%) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite- and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots.

Ozone Monitoring Instrument (OMI)↗
NASA NTRS2013

Application of OMI, SCIAMACHY and GOME-2 Satellite SO2 Retrievals for Detection of Large Emission Sources

Retrievals of sulfur dioxide (SO2) from space-based spectrometers are in a relatively early stage of development. Factors such as interference between ozone and SO2 in the retrieval algorithms often lead to errors in the retrieved values. Measurements from the Ozone Monitoring Instrument (OMI), Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY), and Global Ozone Monitoring Experiment-2 (GOME-2) satellite sensors, averaged over a period of several years, were used to identify locations with elevated SO2 values and estimate their emission levels. About 30 such locations, detectable by all three sensors and linked to volcanic and anthropogenic sources, were found after applying low and high spatial frequency filtration designed to reduce noise and bias and to enhance weak signals to SO2 data from each instrument. Quantitatively, the mean amount of SO2 in the vicinity of the sources, estimated from the three instruments, is in general agreement. However, its better spatial resolution makes it possible for OMI to detect smaller sources and with additional detail as compared to the other two instruments. Over some regions of China, SCIAMACHY and GOME-2 data show mean SO2 values that are almost 1.5 times higher than those from OMI, but the suggested spatial filtration technique largely reconciles these differences.

SO2 retrievals↗
NASA NTRS2011

A Global Climatology of Tropospheric and Stratospheric Ozone Derived from Aura OMI and MLS Measurements

A global climatology of tropospheric and stratospheric column ozone is derived by combining six years of Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) ozone measurements for the period October 2004 through December 2010. The OMI/MLS tropospheric ozone climatology exhibits large temporal and spatial variability which includes ozone accumulation zones in the tropical south Atlantic year-round and in the subtropical Mediterranean! Asia region in summer months. High levels of tropospheric ozone in the northern hemisphere also persist in mid-latitudes over the eastern North American and Asian continents extending eastward over the Pacific Ocean. For stratospheric ozone climatology from MLS, largest ozone abundance lies in the northern hemisphere in the latitude range 70degN-80degN in February-April and in the southern hemisphere around 40degS-50degS during months August-October. The largest stratospheric ozone abundances in the northern hemisphere lie over North America and eastern Asia extending eastward across the Pacific Ocean and in the southern hemisphere south of Australia extending eastward across the dateline. With the advent of many newly developing 3D chemistry and transport models it is advantageous to have such a dataset for evaluating the performance of the models in relation to dynamical and photochemical processes controlling the ozone distributions in the troposphere and stratosphere.

Ziemke, J.R.↗
NASA NTRS2004

The Antarctic Ozone Hole: Initial Results from Aura / OMI Compared with TOMS

A series of TOMS instruments (on November 7 , Meteor 3, and Earth Probe) has been monitoring the annual development of the Antarctic ozone hole since the 1980s. The ozone mapping instrument on Aura, OMI, is expected to take over this record of observation from the aging Earth Probe TOMS instrument. The area of the ozone hole can be taken as a sensitive indicator of the magnitude of ozone destruction each year. The timing of initial formation of the ozone hole and its duration are sensitive to the atmospheric dynamics of the southern polar regions. The entire TOMS data record (1978 - 2004) has recently been reprocessed with the new version 8 algorithm, which includes a revised calibration. The effect has been to slightly increase ozone hole area over earlier estimates, but only by 23%. OMI (ozone monitoring instrument) on Aura is a hyperspectral imaging instrument that operates in a pushbroom mode to measure solar backscattered radiation in the ultraviolet and visible. OMI has higher spatial resolution than TOMS - 14 x 24 km versus 38 km x 38 km from TOMS. OMI has now begin mapping total column ozone on a global basis in a measurement similar to TOMS. The ozone hole measurements for 2003 are compared with those from Earth Probe TOMS.

McPeters, R.↗
NASA NTRS2016

Solar Spectral Irradiance Variability in Cycle 24: Model Predictions and OMI Observations

Utilizing the excellent stability of the Ozone Monitoring Instrument (OMI), we characterize both short-term (solar rotation) and long-term (solar cycle) changes of the solar spectral irradiance (SSI) between 265-500 nanometers during the ongoing Cycle 24. We supplement the OMI data with concurrent observations from the GOME-2 (Global Ozone Monitoring Experiment - 2) and SORCE (Solar Radiation and Climate Experiment) instruments and find fair-to-excellent agreement between the observations and predictions of the NRLSSI2 (Naval Research Laboratory Solar Spectral Irradiance - post SORCE) and SATIRE-S (the Naval Research Laboratory's Spectral And Total Irradiance REconstruction for the Satellite era) models.

Sun↗