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NASA NTRS1994

Ozone determinations with the NOAA SBUV/2 system

The NOAA satellite ozone monitoring program was initiated by the National Environmental Satellite Data and Information Service (NESDIS) in December 1984, with the launch of the NOAA-9 spacecraft carrying the first operational Solar Backscatter Ultraviolet Spectrometer (SBUV/2). This instrument and its successor on NOAA-11, launched in 1988, are similar to the SBUV instrument launched by the NASA in 1978 on the Nimbus-7 research spacecraft. Measurements by the SBUV and SBUV/2 instruments overlap beginning in 1985. These instruments use measurements of the reflected ultraviolet solar radiation from the atmosphere to derive total ozone amounts and ozone vertical profiles. Since launch, the NOAA instruments and the derived products have been undergoing extensive evaluation by scientists of NOAA and NASA. Measurements obtained with these instruments are processed in real time by the NESDIS. These are reprocessed as the SBUV/2 instrument characterization is refined and as the retrieval algorithm for processing the data is improved. The NOAA-9 ozone data archive begins in March 1985 and continues through October 1990. The archive of NOAA-11 data begins in January 1989 and the data continues to be acquired in 1992.

Planet, Walter G.↗
NASA NTRS1988

Nimbus-7 global cloud climatology. I - Algorithms and validation

An improved version of the Nimbus-7 cloud retrieval algorithm was validated using data from Nimbus-7 Temperature Humidity Infrared Radiometer and Total Ozone Mapping Spectrometer to determine cloudiness parameters for the globe. Quantitative validation of total cloud amount was performed by comparing the algorithm results with estimates derived from GOES images and auxiliary meteorological data. The systematic errors of the Nimbus-7 total cloud-amount algorithm, relative to the GOES-derived estimates, were found to be less than 10 percent. The random errors of daily estimates ranged between 7 and 16 percent, day or night.

Stowe, L. L.↗
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 NTRS2024

Decade-Long Ozone Profile Record from Suomi NPP OMPS Limb Profiler: Assessment of Version 2.6 Data

We evaluate a decadal ozone profile record derived from the Suomi National Polar-orbiting Partnership (SNPP) Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) satellite instrument. In 2023, the OMPS LP data were re-processed with the new version 2.6 retrieval algorithm that combines measurements from the ultraviolet (UV) and visible (VIS) parts of the spectra and employs the second order Tikhonov regularization to retrieve a single vertical ozone profile between 12.5 km (or cloud tops) and 57.5 km with the vertical resolution of about 1.9 - 2.5 km between 20-55 km. The algorithm uses radiances measured at six UV ozone-sensitive wavelengths (295, 302, 306, 312, 317 and 322 nm) paired with 353 nm, and one VIS wavelength at 606 nm combined with 510 nm and 675 nm to form a triplet. Each wavelength pair or triplet is used over a limited range of tangent altitudes where the sensitivity to ozone changes are strongest. A new implemented aerosol correction scheme is based on a gamma-function particle size distribution. Numerous calibration changes that affected ozone retrievals were also applied to measured LP radiances, including updates in altitude registration, radiometric calibration, stray light, and spectral registration. The key version 2.6 improvement is the reduction in relative drifts between LP ozone and correlative measurements, linked previously to a drift in the version 2.5 LP altitude registration. We compare LP ozone profiles with those from Aura Microwave Limb Sensor (MLS) to quantify ozone changes in version 2.6.

Limb scattering↗
NASA NTRS1994

Participation in TOMS missions

In the past year we have been investigating a new algorithm for the derivation of column sulfur dioxide, column ozone, and aerosol optical depth from the Total Ozone Mapping Spectrometer (TOMS) High Density TOMS (HDT) archived albedos. Simulations of the measured albedos were made using a radiative transfer model, and a technique developed to separate the effects of the aerosol optical depth from the absorption optical depth. The retrieval adopted obtained values from the three parameters with high accuracy. This retrieval was then applied to the TOMS data.

Hudson, Robert D.↗
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 NTRS1998

Estimation of 3-D Cloud Effects on TOMS Satellite Retrieval of Surface UV Irradiance

To improve surface UV irradiance retrieval from the Total Ozone Mapping Spectrometer (TOMS) we simulate errors of the TOMS cloud correction algorithm for summertime broken cloud conditions. Cloud scenes (50 km by 50 km) are modeled by a normal random (Gaussian) field with a fixed lower boundary and conservative scattering. The model relates stochastic field characteristics with the cloud amount, mean cloud diameter and aspect ratio. Clouds are embedded into Rayleigh atmosphere with standard ozone profile. Radiative transfer calculations of the radiance at the top of the atmosphere and irradiance at the surface were performed using 3-D Monte Carlo (MC) code. The results are averaged over the satellite field of view on the surface (50 km by 50 km) and compared with TOMS predicted surface irradiance for the same scene reflectance. The TOMS algorithm assumes horizontally homogeneous Cl-type cloud between 3 km and 5.5 km. The effective optical depth is determined by fitting observed (MC) radiance at 380 nm. Having the same radiance at the satellite the homogeneous and broken cloud models predict different average irradiances at the surface. This is due to the differences in Bidirectional Reflection Distribution Function (BRDF) for homogeneous and broken cloud scenes with the same hemispherical albedo. For typical TOMS observational geometry at mid-latitudes the simulated single pixels errors may be as large as +/- 20%. Qualitatively these errors are due to the dominance of the non-horizontal cloud surfaces, which are not accounted for in the homogeneous cloud model. However, due to high variability of the real cloud shapes and types it is unclear how these single pixel errors would affect TOMS time-integrated UV exposure over extended periods (weeks to months) for different regions.

Krotkov, Nickolay A.↗
NASA NTRS2015

Evaluating a New Homogeneous Total Ozone Climate Data Record from GOME/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A

The European Space Agency's Ozone Climate Change Initiative (O3-CCI) project aims at producing and validating a number of high-quality ozone data products generated from different satellite sensors. For total ozone, the O3-CCI approach consists of minimizing sources of bias and systematic uncertainties by applying a common retrieval algorithm to all level 1 data sets, in order to enhance the consistency between the level 2 data sets from individual sensors. Here we present the evaluation of the total ozone products from the European sensors Global Ozone Monitoring Experiment (GOME)/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A produced with the GOME-type Direct FITting (GODFIT) algorithm v3. Measurements from the three sensors span more than 16 years, from 1996 to 2012. In this work, we present the latest O3-CCI total ozone validation results using as reference ground-based measurements from Brewer and Dobson spectrophotometers archived at the World Ozone and UV Data Centre of the World Meteorological Organization as well as from UV-visible differential optical absorption spectroscopy (DOAS)/Système D′Analyse par Observations Zénithales (SAOZ) instruments from the Network for the Detection of Atmospheric Composition Change. In particular, we investigate possible dependencies in these new GODFIT v3 total ozone data sets with respect to latitude, season, solar zenith angle, and different cloud parameters, using the most adequate type of ground-based instrument. We show that these three O3-CCI total ozone data products behave very similarly and are less sensitive to instrumental degradation, mainly as a result of the new reflectance soft-calibration scheme. The mean bias to the ground-based observations is found to be within the 1 plus or minus 1 percent level for all three sensors while the near-zero decadal stability of the total ozone columns (TOCs) provided by the three European instruments falls well within the 1-3 percent requirement of the European Space Agency's Ozone Climate Change Initiative project.

Satellite sensors↗
NASA NTRS2015

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of VIIRS, OMPS, and CALIOP Observations

Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height as well as single scattering albedo (SSA) for biomass burning smoke aerosols. One of the advantages of this algorithm was that the aerosol layer height can be retrieved over broad areas, which had not been available from lidar observations only. The algorithm utilized aerosol properties from three different satellite sensors, i.e., aerosol optical depth (AOD) and Ångström exponent (AE) from Moderate Resolution Imaging Spectroradiometer (MODIS), UV aerosol index (UVAI) from Ozone Monitoring Instrument (OMI), and aerosol layer height from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Here, we extend the application of the algorithm to Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) data. We also now include dust layers as well as smoke. Other updates include improvements in retrieving the AOD of nonspherical dust from VIIRS, better determination of the aerosol layer height from CALIOP, and more realistic input aerosol profiles in the forward model for better accuracy.

aerosol↗
NASA NTRS2016

The Role of Cloud Contamination, Aerosol Layer Height and Aerosol Model in the Assessment of the OMI Near-UV Retrievals Over the Ocean

Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD less than 0.3, 30% for AOD greater than 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm approximately less than 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (less than 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

aerosols↗
NASA NTRS2021

OMPS LP Version 2.0 Multi-wavelength Aerosol Extinction Coefficient Retrieval Algorithm

The OMPS Limb Profiler (LP) instrument is de-signed to provide high-vertical-resolution ozone and aerosol profiles from measurements of the scattered solar radiation in the 290–1000 nm spectral range. It collected its first Earth limb measurement on 10 January 2012 and continues to provide daily global measurements of ozone and aerosol profiles from the cloud top up to 60 and 40 km, respectively. The relatively high vertical and spatial sampling allow detection and tracking of sporadic events when aerosol particles are injected into the stratosphere, such as volcanic eruptions or pyro cumulonimbus (PyroCb) events. In this paper we discuss the newly released Version 2.0 OMPS multi-wavelength aerosol extinction coefficient retrieval algorithm. The algorithm now produces aerosol extinction profiles at 510, 600, 674, 745, 869 and 997 nm wavelengths. The OMPS LP Version 2.0 data products are compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies. The comparison shows significant improvements in the OMPS LP retrieval performance in the Southern Hemisphere (SH) and at lower altitudes. These improvements arise from use of the longer wavelengths, in contrast with the V1.0 and V1.5 OMPS aerosol retrieval algorithms, which used radiances only at 675 nm and therefore had limited sensitivity in those regions. In particular, the extinction coefficients at 745, 869 and 997 nm are shown to be the most accurate, with relative accuracies and precisions close to 10% and 15%, respectively, while the 675 nm relative accuracy and precision are on the order of 20%. The 510 nm extinction coefficient is shown to have limited accuracy in the SH and is only recommended for use between 20–24 km and only in the Northern Hemisphere. The V2.0 retrieval algorithm has been applied to the complete set of OMPS LP measurements, and the new dataset is publicly available.

OMPS↗
NASA NTRS2016

Monitoring O3 and Aerosols with the NASA LaRC Mobile Ozone Lidar System

The NASA's Langley Mobile Ozone Lidar (LMOL) system routinely measures tropospheric ozone and aerosol profiles, and is part of the Tropospheric Lidar Network (TOLNet). Recent upgrades to the system include a new pump laser that has tripled the transmission output power extending measurements up to 8 km in altitude during the day. In addition, software and algorithm developments have improved data output quality and enabled a real-time ozone display capability. In 2016, a number of ozone features were captured by LMOL, including the dynamics of an early-season ozone exceedance that impacted the Hampton Roads region. In this presentation, we will review current LMOL capabilities, recent air quality events observed by the system, and show a comparison of aerosol retrieval through the UV channel and the green line channel.

Ganoe, Rene↗
NASA NTRS2014

Highlights from a Decade of OMI-TOMS Total Ozone Observations on EOS Aura

Total ozone measurements from OMI have been instrumental in meeting Aura science objectives. In the last decade, OMI has extended the length of the TOMS total ozone record to over 35 years to monitor stratospheric ozone recovery. OMI-TOMS total ozone measurements have also been combined synergistically with measurements from other Aura instruments and MLS in particular, which provides vertically resolved information that complements the total O3 mapping capability of OMI. With this combined approach, the EOS Aura platform has produced more accurate and detailed measurements of tropospheric ozone. This has led in turn to greater understanding of the sources and transport of tropospheric ozone as well as its radiative forcing effect. The combined use of OMI and MLS data was also vital to the analysis of the severe Arctic ozone depletion event of 2011. The quality of OMI-TOMS total O3 data used in these studies is the result of several factors: a mature and well-validated algorithm, the striking stability of the OMI instrument, and OMI's hyperspectral capabilities used to derive cloud pressures. The latter has changed how we think about the effects of clouds on total ozone retrievals. We will discuss the evolution of the operational V8.5 algorithm and provide an overview and motivation for V9. After reviewing results and developments of the past decade, we finally highlight how ozone observations from EOS Aura are playing an important role in new ozone mapping missions.

Ozone↗
NASA NTRS2017

Intercomparison of Snow Depth Retrievals over Arctic Sea Ice from Radar Data Acquired by Operation IceBridge

Since 2009, the ultra-wideband snow radar on Operation IceBridge (OIB; a NASA airborne mission to survey the polar ice covers) has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Progressive improvements in radar hardware and data processing methodologies have led to improved data quality for subsequent retrieval of snow depth. Existing retrieval algorithms differ in the way the air-snow (a-s) and snow-ice (s-i) interfaces are detected and localized in the radar returns and in how the system limitations are addressed (e.g., noise, resolution). In 2014, the Snow Thickness On Sea Ice Working Group (STOSIWG) was formed and tasked with investigating how radar data quality affects snow depth retrievals and how retrievals from the various algorithms differ. The goal is to understand the limitations of the estimates and to produce a well-documented, long-term record that can be used for understanding broader changes in the Arctic climate system. Here, we assess five retrieval algorithms by comparisons with field measurements from two groundbased campaigns, including the BRomine, Ozone, and Mercury EXperiment (BROMEX) at Barrow, Alaska; a field program by Environment and Climate Change Canada at Eureka, Nunavut; and available climatology and snowfall from ERA-Interim (ECMWF (European Centre for Medium-Range Weather Forecasts) Re-Analysis) reanalysis. The aim is to examine available algorithms and to use the assessment results to inform the development of future approaches. We present results from these assessments and highlight key considerations for the production of a long-term, calibrated geophysical record of springtime snow thickness over Arctic sea ice.

Operation IceBridge↗
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 NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global chemistry-climate models (CCMs) where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) CCM through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗
NASA NTRSDate not supplied

Improved Characterization of PSC Processes Derived from a Third-Generation CALIOP and MLS Detection and Composition Classification Algorithm

The new 3-year CloudSat and CALIPSO Science Team project described in this poster will use a unique combination of data from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on CALIPSO and the Microwave Limb Sounder (MLS) on Aura, in conjunction with supporting meteorological information and detailed modeling studies, to advance our understanding of polar stratospheric cloud (PSC) processes and their role in ozone depletion. We will develop a third-generation (Gen3) PSC detection and composition algorithm that incorporates a new, more robust two-dimensional, multi-channel CALIOP feature detection scheme (2D-McDA). We will also devise and implement an improved two-dimensional PSC composition classification scheme that utilizes multiple parameters (e.g., CALIOP 532-nm parallel and perpendicular scattering ratios, CALIOP 1064-nm total scattering ratio, MLS HNO3 and H2O, ambient temperature, and temperature histories) in a Bayesian approach to determine the most likely PSC composition and help constrain solid PSC particle number density and size/shape. The combined CALIOP/MLS analyses will allow us to study in detail the full life cycle of PSCs and their resulting impact on gas-phase HNO3 and H2O, which should lead to improved parameterizations of PSC microphysics in global CCMs where detailed particle information is not available. The Gen3 CALIOP PSC algorithm will be a natural stepping-stone toward the analysis of data collected during future spaceborne lidar missions, such as NASA’s Atmosphere Observation System (AtmOS) mission currently scheduled for launch late in this decade. We will also investigate possible trends in PSC occurrence and composition over the entire CALIOP data record and through further comparisons with the Stratospheric Aerosol Measurement (SAM) II solar occultation PSC record from 1979-1989. Finally, we will validate the mountain-wave parameterization and PSC schemes used in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol module) chemistry-climate model through detailed comparisons with earlier CALIOP PSC data products and those developed under this proposal.

CALIPSO↗
NASA NTRSDate not supplied

Assessment of the 10-year Ozone Profile Record Derived from Suomi NPP OMPS-LP

In this presentation we evaluate ozone profile retrievals from Ozone Mapping and Profiling Suite Limb Profiler (OMPS-LP) launched in October 2011 on Suomi NPP satellite. The data from OMPS-LP were re-processed with the new retrieval algorithm that combines measurements from UV and VIS parts of the spectra to retrieve a single ozone profile between 12.5 km (or cloud tops) and 57.5 km. To improve ozone retrievals in the Upper Troposphere Lower Stratosphere (UTLS) region, a new aerosol correction with a gamma-function particle size distribution was implemented. The OMPS-LP altitude registration was also adjusted in the new version to ensure the stability of the ozone record. The continuous ozone profile observations with Suomi NPP OMPS LP exceeds 10 years. We will compare OMPS-LP ozone profiles with coincident stratospheric ozone measurements from NASA Aura MLS, ISS SAGE III, and OMPS NP and with the observations in UTLS and middle stratosphere from a ground-based network of ozone sonde stations to evaluate accuracy and precision of OMPS-LP retrievals and overall stability of the record. We will also investigate the quality of stratospheric ozone columns obtained from OMPS-LP and estimate the contribution of various errors to integrated stratospheric columns from OMPS-LP.

stratospheric ozone↗