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NASA NTRS2016

Comparison of OMI NO2 Observations and Their Seasonal and Weekly Cycles with Ground-Based Measurements in Helsinki

We present the comparison of satellite-based OMI (Ozone Monitoring Instrument) NO2 products with ground-based observations in Helsinki. OMI NO2 total columns, available from standard product (SP) and DOMINO algorithm, are compared with the measurements performed by the Pandora spectrometer in Helsinki in 2012. The relative difference between Pandora 21 and OMI SP retrievals is 4 and 6 for clear sky and all sky conditions, respectively. DOMINO NO2 retrievals showed slightly lower total columns with median differences about 5 and 14 for clear sky and all sky conditions, respectively. Large differences often correspond to cloudy autumn-winter days with solar zenith angles above 65. Nevertheless, the differences remain within the retrieval uncertainties. Furthermore, the weekly and seasonal cycles from OMI, Pandora and NO2 surface concentrations are compared. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as result of reduced emissions from traffic and industrial activities. Also the seasonal cycle shows a similar behavior, even though the results are affected by the fact that most of the data are available during spring-summer because of cloud cover in other seasons. This is one of few works in which OMI NO2 retrievals are evaluated in an urban site at high latitudes (60N). Despite the city of Helsinki having relatively small pollution sources, OMI retrievals have proved to be able to describe air quality features and variability similar to surface observations. This adds confidence in using satellite observations for air quality monitoring also at high latitudes.

Validation↗

NASA NTRS2019

A New Discrete Wavelength BUV Algorithm for Consistent Volcanic SO2 Retrievals from Multiple Satellite Missions

This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, and Lambertian effective reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) onboard NASA's Nimbus-7 satellite (N7/TOMS: 1978-1993) and from the current Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory (DSCOVR: 2015-) from the Earth-Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were assessed using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as the Ozone Monitoring Instrument (OMI) onboard NASA's Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) onboard NASA-NOAA Suomi National Polar Partnership (SNPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus-7/TOMS instrument, described in Sect. S1 of the Supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as the 1991 Pinatubo eruption. To estimate SO2 retrieval systematic uncertainties, we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.

Bradford L Fisher↗

NASA NTRS2010

Current Applications of OMI Tropospheric NO2 Data for Air Quality and a Look to the Future

Ozone Monitoring Instrument (OMI) Tropospheric NO2 products are being used to enhance the ability to monitor changes in NO2 air quality, update emission inventories, and evaluate regional air quality models. Trends in tropospheric column NO2 have been examined over the eastern United States in relation to emissions changes mandated by regulatory actions. Decreases of 20 to 40 percent over the period 2005 to 2008 were noted, largely in response to major emission reductions at power plants. The OMI data have been used to identify regions in which the opposite trend has been found. We have also used OMI NO2 in efforts to improve emission inventories for NOx emissions from soil. Lightning NOx emissions have been added to CMAQ, the US Environmental Protection Agency's regional air quality model. Evaluation of the resulting NO2 columns in the model is being conducted using the OMI NO2 observations. Community Multiscale Air Quality (CMAQ) together with the OMI NO2 data comprise a valuable tool for monitoring and predicting air quality. Looking to the future, we expect that the combination of Global Ozone Monitoring Experiment-2 (GOME-2) (morning) and OMI (afternoon) data sets obtained through use of the same retrieval algorithms will substantially increase the possibility of successful integration of satellite information into regional air quality forecast models. Farther down the road, we anticipate the Geostationary Coastal and Air Pollution Events (GEO-CAPE) platform to supply data possibly on an hourly basis, allowing much more comprehensive analysis of air quality from space.

Pickering, Kenneth E.↗

NASA NTRS2023

Satellite Remote-Sensing Capability to Assess Tropospheric-Column Ratios of Formaldehyde and Nitrogen Dioxide: Case Study During the Long Island Sound Tropospheric Ozone Study 2018 (LISTOS 2018) Field Campaign

Satellite retrievals of tropospheric-column formaldehyde (HCHO) and nitrogen dioxide (NO 2 ) are frequently used to investigate the sensitivity of ozone (O 3 ) production to emissions of nitrogen oxides and volatile organic carbon compounds. This study inter-compared the systematic biases and uncertainties in retrievals of NO 2 and HCHO, as well as resulting HCHO–NO 2 ratios (FNRs), from two commonly applied satellite sensors to investigate O 3 production sensitivities (Ozone Monitoring Instrument, OMI, and TROPOspheric Monitoring Instrument, TROPOMI) using airborne remote-sensing data taken during the Long Island Sound Tropospheric Ozone Study 2018 between 25 June and 6 September 2018. Compared to aircraft-based HCHO and NO 2 observations, the accuracy of OMI and TROPOMI were magnitude-dependent with high biases in clean environments and a tendency towards more accurate comparisons to even low biases in moderately polluted to polluted regions. OMI and TROPOMI NO 2 systematic biases were similar in magnitude (normalized median bias, NMB = 5 %–6 %; linear regression slope ≈ 0.5–0.6), with OMI having a high median bias and TROPOMI resulting in small low biases. Campaign-averaged uncertainties in the three satellite retrievals (NASA OMI; Quality Assurance for Essential Climate Variables, QA4ECV OMI; and TROPOMI) of NO 2 were generally similar, with TROPOMI retrievals having slightly less spread in the data compared to OMI. The three satellite products differed more when evaluating HCHO retrievals. Campaign-averaged tropospheric HCHO retrievals all had linear regression slopes ∼0.5 and NMBs of 39 %, 17 %, 13 %, and 23 % for NASA OMI, QA4ECV OMI, and TROPOMI at finer (0.05° x 0.05°) and coarser (0.15° x 0.15°) spatial resolution, respectively. Campaign-averaged uncertainty values (root mean square error, RMSE) in NASA and QA4ECV OMI HCHO retrievals were ~9.0 x 10 15 molecules cm –2 (∼ 50 %–55 % of mean column abundance), and the higher-spatial-resolution retrievals from TROPOMI resulted in RMSE values ∼30 % lower. Spatially averaging TROPOMI tropospheric-column HCHO, along with NO 2 and FNRs, to resolutions similar to the OMI reduced the uncertainty in these retrievals. Systematic biases in OMI and TROPOMI NO 2 and HCHO retrievals tended to cancel out, resulting in all three satellite products comparing well to observed FNRs. However, while satellite-derived FNRs had minimal campaign-averaged median biases, unresolved errors in the indicator species did not cancel out in FNR calculations, resulting in large RMSE values compared to observations. Uncertainties in HCHO retrievals were determined to drive the unresolved biases in FNR retrievals.

Matthew S. Johnson↗

NASA NTRS2006

Observations over Hurricanes from the Ozone Monitoring Instrument

There is an apparent inconsistency between the total column ozone derived from the total ozone mapping spectrometer (TOMS) and aircraft observations within the eye region of tropical cyclones. The higher spectral resolution, coverage, and sampling of the ozone monitoring instrument (OMI) on NASA s Aura satellite as compared with TOMS allows for improved ozone retrievals by including estimates of cloud pressure derived simultaneously using the effects of rotational Raman scattering. The retrieved cloud pressures from OM1 are more appropriate than the climatological cloud-top pressures based on infrared measurements used in the TOMS and initial OM1 algorithms. We find that total ozone within the eye of hurricane Katrina is significantly overestimated when we use climatological cloud pressures. Using OMI-retrieved cloud pressures, total ozone in the eye is similar to that in the surrounding area. The corrected total ozone is in better agreement with aircraft measurements that imply relatively small or negligible amounts of stratospheric intrusion into the eye region of tropical cyclones.

Joiner, J.↗

NASA NTRS2022

Change in Tropospheric Ozone in the Recent Decades and its Contribution to Global Total Ozone

Tropospheric ozone is a key chemically active trace gas and radiative forcer. Understanding its long-term changes is important to properly interpret observed changes in total column ozone and stratospheric ozone recovery. We investigate global and regional tropospheric ozone changes and their impact on total column ozone during 2005-2018 using satellite measurements and the NASA Goddard Earth Observing System Chemistry Climate Model (GEOSCCM). Global total ozone increased ~4 DU during 2005-2018 (+0.28±0.06 DU yr(exp -1)) as inferred from Ozone Monitoring Instrument (OMI). Consistent with previous studies, the OMI/MLS (Microwave Limb Sounder) derived global tropospheric ozone increased 2.2 DU during this period, 60% of the global total column ozone increase. While GEOSCCM reproduces reasonably well the total column increase, it overestimates the stratospheric ozone increase and underestimates the tropospheric ozone increase. We find that the tropospheric ozone increases are likely attributed to a growth of regional emissions of key ozone precursors, especially volatile organic compounds (VOCs) as reflected by the positive trends in formaldehyde (CH2O). Although carbon monoxide (CO) has been decreasing everywhere around the globe, it has relatively small impact on the tropospheric ozone trend. Trends in nitrogen dioxide (NO2) vary with regions, and these changes counteract or reinforce the positive effects of CH2O on the tropospheric ozone increases. The model underestimates the observed tropospheric ozone increase, especially over the US and Europe, because of underestimated NO2 emissions changes used in the model. The stratospheric ozone contribution increases during this period in the Northern Hemisphere and contributes to the tropospheric ozone increase.

Atmospheric chemistry↗

NASA NTRS2014

Next Generation Aura-OMI SO2 Retrieval Algorithm: Introduction and Implementation Status

We introduce our next generation algorithm to retrieve SO2 using radiance measurements from the Aura Ozone Monitoring Instrument (OMI). We employ a principal component analysis technique to analyze OMI radiance spectral in 310.5-340 nm acquired over regions with no significant SO2. The resulting principal components (PCs) capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering, and ozone absorption) and measurement artifacts, enabling us to account for these various interferences in SO2 retrievals. By fitting these PCs along with SO2 Jacobians calculated with a radiative transfer model to OMI-measured radiance spectra, we directly estimate SO2 vertical column density in one step. As compared with the previous generation operational OMSO2 PBL (Planetary Boundary Layer) SO2 product, our new algorithm greatly reduces unphysical biases and decreases the noise by a factor of two, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing long-term, consistent SO2 records for air quality and climate research. We have operationally implemented this new algorithm on OMI SIPS for producing the new generation standard OMI SO2 products.

Sulfur dioxide↗

NASA NTRS2007

Identification of Stratospheric Waves in Ozone in the Tropics from OMI High Spectral Resolution Measurements

Previous studies using Total Ozone Mapping Spectrometer (TOMS) measurements have identified several types of tropical waves in the stratosphere. These waves include Kelvin waves, mixed Rossby-gravity waves, equatorial Rossby waves, and global normal modes. All of these detected waves occur when their zonal phase speeds are opposite the zonal winds in the low-mid stratosphere associated with the Quasi-biennial Oscillation (QBO). Peak-to-peak amplitudes in all cases are typically 5 DU. While total ozone data from TOMS is sensitive in detecting these tropical waves, they provide each day only a single horizontal cross-sectional map. The high spatial and spectral resolution of the Aura Ozone Monitoring Instrument (OMI) provides a unique means to evaluate 3D structure in these waves including their propagation characteristics. Ozone profiles retrieved from OMI radiances for wavelengths 270-310 nm are utilized to examine the nature of these wave disturbances extending from the lower to upper stratosphere.

Ziemke, J. R.↗

NASA NTRS2007

SHADOZ in the Aura Era

We present comparisons of observed tropical and sub-tropical ozone from the Southern Hemisphere Additional Ozonesondes (SHADOZ) project with satellite measurements using Aura's Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) instruments. Satellite products of total and derived tropospheric column ozone from OMI and profiles of ozone in the UT/LS region from MLS are used.

Witte, J. C.↗

NASA NTRS2008

Impact of Surface Emissions to the Zonal Variability of Tropical Tropospheric Ozone and Carbon Monoxide for November 2004

The chemical and dynamical processes governing the zonal variability of tropical tropospheric ozone and carbon monoxide are investigated for November 2004 using satellite observations, in-situ measurements, and chemical transport models in conjunction with inverse-estimated surface emissions. Vertical ozone profile estimates from the Tropospheric Emission Spectrometer (TES) and ozone sonde measurements from the Southern Hemisphere Additional Ozonesondes (SHADOZ) network show the so called zonal 'wave-one' pattern, which is characterized by peak ozone concentrations (70-80 ppb) centered over the Atlantic, as well as elevated concentrations of ozone over Indonesia and Australia (60-70 ppb) in the lower troposphere. Observational evidence from TES CO vertical profiles and Ozone Monitoring Instrument (OMI) NO2 columns point to regional surface emissions as an important contributor to the elevated ozone over Indonesia. This contribution is investigated with the GEOS-Chem chemistry and transport model using surface emission estimates derived from an optimal inverse model, which was constrained by TES and Measurements Of Pollution In The Troposphere (MOPITT) CO profiles (Jones et al., 2007). These a posteriori estimates, which were over a factor of 2 greater than climatological emissions, reduced differences between GEOS-Chem and TES ozone observations by 30-40% and led to changes in GEOS-Chem upper tropospheric ozone of up to 40% over Indonesia. The remaining residual differences can be explained in part by upper tropospheric ozone produced from lightning NOx in the South Atlantic. Furthermore, model simulations from GEOS-Chem indicate that ozone over Indonesian/Australian is more sensitive to changes in surface emissions of NOx than ozone over the tropical Atlantic.

tropical tropospheric ozone↗

NASA NTRS2012

Global Assimilation of EOS-Aura Data as a Means of Mapping Ozone Distribution in the Lower Stratosphere and Troposphere

Ozone in the lower stratosphere and the troposphere plays an important role in forcing the climate. However, the global ozone distribution in this region is not well known because of the sparse distribution of in-situ data and the poor sensitivity of satellite based observations to the lowermost of the atmosphere. The Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) instruments on EOS-Aura provide information on the total ozone column and the stratospheric ozone profile. This data has been assimilated into NASA s Global Earth Observing System, Version 5 (GEOS-5) data assimilation system (DAS). We will discuss the results of assimilating three years of OMI and MLS data into GEOS-5. This data was assimilated alongside meteorological observations from both conventional sources and satellite instruments. Previous studies have shown that combining observations from these instruments through the Trajectory Tropospheric Ozone Residual methodology (TTOR) or using data assimilation can yield useful, yet low biased, estimates of the tropospheric ozone budget. We show that the assimilated ozone fields in this updated version of GEOS-5 exhibit an excellent agreement with ozone sonde and High Resolution Dynamics Limb Sounder (HIRDLS) data in the lower stratosphere in terms of spatial and temporal variability as well as integrated ozone abundances. Good representation of small-scale vertical features follows from combining the MLS data with the assimilated meteorological fields. We then demonstrate how this information can be used to calculate the Stratosphere - Troposphere Exchange of ozone and its contribution to the tropospheric ozone column in GEOS-5. Evaluations of tropospheric ozone distributions from the assimilation will be made by comparisons with sonde and other in-situ observations.

Wargan, Krzysztof↗

NASA NTRS2018

Global Changes in the Diurnal Cycle of Surface Ozone

Changing emissions of NOx and other ozone precursors drive trends in both production and loss of surface ozone, leading to surface ozone trends that differ according to the time of day. Consequently, the magnitude of the diurnal cycle in surface ozone is changing in several regions of the world. Changes in the diurnal cycle of ozone have implications for the metrics used to assess the impact of ozone on human health and vegetation, since different metrics are sensitive to different portions of the diurnal cycle. We use a high resolution model simulation to examine global changes in the magnitude of the diurnal cycle of O3 between 1980 and 2015. The simulation reproduces the negative trends in the tropospheric NO2 column over the eastern United States and Europe, and the positive trends over East Asia, seen by the Ozone Monitoring Instrument (OMI). It also gives a reasonable reproduction of the change in the diurnal cycle of surface ozone seen at rural sites in the eastern United States between the 1990s and 2000s. The simulation shows that the magnitude of the surface O3 diurnal cycle is increasing in regions with positive changes in NOx emissions, such as South and East Asia, and decreasing in regions with reductions in NOx emissions. It also shows changes in the diurnal cycle of the tropospheric ozone column, although these have fewer regions with statistically significant trends. These changes suggest that daily mean ozone is responding less than the mid-day ozone measured by the Total Ozone Mapping Spectrometer (TOMS) and OMI.

Trends↗

NASA NTRS2006

First Results from the OMI Rotational Raman Scattering Cloud Pressure Algorithm

We have developed an algorithm to retrieve scattering cloud pressures and other cloud properties with the Aura Ozone Monitoring Instrument (OMI). The scattering cloud pressure is retrieved using the effects of rotational Raman scattering (RRS). It is defined as the pressure of a Lambertian surface that would produce the observed amount of RRS consistent with the derived reflectivity of that surface. The independent pixel approximation is used in conjunction with the Lambertian-equivalent reflectivity model to provide an effective radiative cloud fraction and scattering pressure in the presence of broken or thin cloud. The derived cloud pressures will enable accurate retrievals of trace gas mixing ratios, including ozone, in the troposphere within and above clouds. We describe details of the algorithm that will be used for the first release of these products. We compare our scattering cloud pressures with cloud-top pressures and other cloud properties from the Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. OMI and MODIS are part of the so-called A-train satellites flying in formation within 30 min of each other. Differences between OMI and MODIS are expected because the MODIS observations in the thermal infrared are more sensitive to the cloud top whereas the backscattered photons in the ultraviolet can penetrate deeper into clouds. Radiative transfer calculations are consistent with the observed differences. The OMI cloud pressures are shown to be correlated with the cirrus reflectance. This relationship indicates that OMI can probe through thin or moderately thick cirrus to lower lying water clouds.

Joiner, Joanna↗

NASA NTRS2007

What You Need to Know About the OMI NO2 Data Product for Air Quality Studies

The standard nitrogen dioxide (NO2) data product, produced from measurements by the Ozone Monitoring Instrument (OMI), are publicly available online from the NASA GESDISC facility. Important data fields include total and tropospheric column densities, as well as collocated data for cloud fraction and cloud top height, surface albedo and snow/ice coverage, at the resolution of the OMI instrument (12 km x 26 km, at nadir). The retrieved NO2 data have been validated, principally under clear-sky conditions. The first public-release version has been available since September 2006. An improved version of the data product, which includes a number of new data fields, and improved estimates of the retrieval uncertainties will be released by the end of 2007. This talk will describe the standard NO2 data product, including details that are essential for the use of the data for air quality studies. We will also describe the principal improvements with the new version of the data product.

Celarier, E. A.↗

NASA NTRSDate not supplied

Verification of TROPOMI NO2 Product Using OMI NO2 algorithm

We evaluated S5P TROPOspheric Monitoring Instrument (TROPOMI) operational nitrogen dioxide (NO2) product by comparing with the NO2 retrievals from Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite. We compared spatially matched NO2 vertical column density (VCD) data from OMI and TROPOMI to identify any discrepancies between the two operational products. We also applied OMI Air-Mass Factor (AMF) algorithm to TROPOMI Slant Column Density (SCD) data (v02.03.01) aiming to create long-term merged NO2 Earth Science Data Record (https://disc.gsfc.nasa.gov/datasets/TROPOMI_MINDS_NO2_1.1/summary ). The algorithm (version 4.0) uses new Geometry-dependent Lambertian Equivalent surface Reflectivity (GLER) product available for each TROPOMI pixel. GLER is pre-calculated using the vector linearized discrete ordinate radiative transfer (VLIDORT) model, which uses as input high-resolution bidirectional reflectance distribution function (BRDF) information from NASA's Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the wind-dependent Cox–Munk wave-facet slope distribution over water, the latter with a contribution from the water-leaving radiance based on MODIS gap-filled in-water chlorophyll-a data. The GLER data, combined with consistently retrieved cloud parameters, provide improved information for the calculation of the scattering weight profiles. Additional AMF improvements result from using high resolution (0.25o latitude x 0.25o longitude) a priori NO2 profile shapes and other auxiliary information from the Global Modeling Initiative (GMI) Replay simulation sampled using S5P orbital simulator. Our TROPOMI_MINDS_NO2 algorithm employs the stratosphere-troposphere separation scheme, de-striping, and surface snow/ice treatment consistently with the latest OMI NO2 re-processing (version 4). We evaluate the TROPOMI_MINDS_NO2 product by comparing with the S5P operational NO2 product as well as with independent NO2 observations from ground-based Pandora and aircraft observations. Our results indicate that the new TROPOMI_MINDS_NO2 retrievals are generally higher than the S5P operational NO2 product over polluted regions and show improved agreement with independent validation data.

TROPOMI↗

NASA NTRS2017

Effects of Surface BRDF on the OMI Cloud and NO2 Retrievals: A New Approach Based on Geometry-Dependent Lambertian Equivalent Reflectivity (GLER) Derived from MODIS

The Ozone Monitoring Instrument (OMI) cloud and NO2 algorithms use a monthly gridded surface reflectivity climatology that does not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (GLER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. GLER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from MODIS over land and the Cox Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare GLER and climatological LER at 466 nm, which is used in the OMI O2-O2cloud algorithm to derive effective cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and GLERs is carried out. GLER and corresponding retrieved cloud products are then used as input to the OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with GLERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

MODIS BRDF OMI clouds NO2 GLER↗

NASA NTRS2016

Highlights from the 11-Year Record of Tropospheric Ozone from OMI/MLS and Continuation of that Long Record Using OMPS Measurements

Since October 2004 the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) onboard the Aura satellite have provided over 11 years of continuous tropospheric ozone measurements. These OMI/MLS measurements have been used in many studies to evaluate dynamical and photochemical effects caused by ENSO, the Madden-Julian Oscillation (MJO) and shorter timescales, as well as long-term trends and the effects of deep convection on tropospheric ozone. Given that the OMI and MLS instruments have now extended well beyond their expected lifetimes, our goal is to continue their long record of tropospheric ozone using recent Ozone Mapping Profiler Suite (OMPS) measurements. The OMPS onboard the Suomi National Polar-orbiting Partnership NPP satellite was launched on October 28, 2011 and is comprised of three instruments: the nadir mapper, the nadir profiler, and the limb profiler. Our study combines total column ozone from the OMPS nadir mapper with stratospheric column ozone from the OMPS limb profiler to measure tropospheric ozone residual. The time period for the OMPS measurements is March 2012 present. For the OMPS limb profiler retrievals, the OMPS v2 algorithm from Goddard is tested against the University of Saskatchewan (USask) Algorithm. The retrieved ozone profiles from each of these algorithms are evaluated with ozone profiles from both ozonesondes and the Aura Microwave Limb Sounder (MLS). Effects on derived OMPS tropospheric ozone caused by the 2015-2016 El Nino event are highlighted. This recent El Nino produced anomalies in tropospheric ozone throughout the tropical Pacific involving increases of approximately 10 DU over Indonesia and decreases approximately 5-10 DU in the eastern Pacific. These changes in ozone due to El Nino were predominantly dynamically-induced, caused by the eastward shift in sea-surface temperature and convection from the western to the eastern Pacific.

MJO↗

NASA NTRS2013

Modeling of 2008 Kasatochi Volcanic Sulfate Direct Radiative Forcing: Assimilation of OMI SO2 Plume Height Data and Comparison with MODIS and CALIOP Observations

Volcanic SO2 column amount and injection height retrieved from the Ozone Monitoring Instrument (OMI) with the Extended Iterative Spectral Fitting (EISF) technique are used to initialize a global chemistry transport model (GEOS-Chem) to simulate the atmospheric transport and lifecycle of volcanic SO2 and sulfate aerosol from the 2008 Kasatochi eruption, and to subsequently estimate the direct shortwave, top-of-the-atmosphere radiative forcing of the volcanic sulfate aerosol. Analysis shows that the integrated use of OMI SO2 plume height in GEOS-Chem yields: (a) good agreement of the temporal evolution of 3-D volcanic sulfate distributions between model simulations and satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP), and (b) an e-folding time for volcanic SO2 that is consistent with OMI measurements, reflecting SO2 oxidation in the upper troposphere and stratosphere is reliably represented in the model. However, a consistent (approx. 25 %) low bias is found in the GEOS-Chem simulated SO2 burden, and is likely due to a high (approx.20 %) bias of cloud liquid water amount (as compared to the MODIS cloud product) and the resultant stronger SO2 oxidation in the GEOS meteorological data during the first week after eruption when part of SO2 underwent aqueous-phase oxidation in clouds. Radiative transfer calculations show that the forcing by Kasatochi volcanic sulfate aerosol becomes negligible 6 months after the eruption, but its global average over the first month is -1.3W/sq m, with the majority of the forcing-influenced region located north of 20degN, and with daily peak values up to -2W/sq m on days 16-17. Sensitivity experiments show that every 2 km decrease of SO2 injection height in the GEOS-Chem simulations will result in a approx.25% decrease in volcanic sulfate forcing; similar sensitivity but opposite sign also holds for a 0.03 m increase of geometric radius of the volcanic aerosol particles. Both sensitivities highlight the need to characterize the SO2 plume height and aerosol particle size from space. While more research efforts are warranted, this study is among the first to assimilate both satellite-based SO2 plume height and amount into a chemical transport model for an improved simulation of volcanic SO2 and sulfate transport.

Wang, J.↗