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NASA NTRS2007

Cloud Motion Vectors from MISR using Sub-pixel Enhancements

The operational retrieval of height-resolved cloud motion vectors by the Multiangle Imaging SpectroRadiometer on the Terra satellite has been significantly improved by using sub-pixel approaches to co-registration and disparity assessment, and by imposing stronger quality control based on the agreement between independent forward and aft triplet retrievals. Analysis of the fore-aft differences indicates that CMVs pass the basic operational quality control 67% of the time, with rms differences - in speed of 2.4 m/s, in direction of 17 deg, and in height assignment of 290 m. The use of enhanced quality control thresholds reduces these rms values to 1.5 m/s, 17 deg and 165 m, respectively, at the cost of reduced coverage to 45%. Use of the enhanced thresholds also eliminates a tendency for the rms differences to increase with height. Comparison of CMVs from an earlier operational version that had slightly weaker quality control, with 6-hour forecast winds from the Global Modeling and Assimilation Office yielded very low bias values and an rms vector difference that ranged from 5 m/s for low clouds to 10 m/s for high clouds.

Davies, Roger↗
NASA NTRS2007

A Global Perspective: NASA's Prediction of Worldwide Energy Resources (POWER) Project

The Prediction of the Worldwide Energy Resources (POWER) Project, initiated under the NASA Science Mission Directorate Applied Science Energy Management Program, synthesizes and analyzes data on a global scale that are invaluable to the renewable energy industries, especially to the solar and wind energy sectors. The POWER project derives its data primarily from NASA's World Climate Research Programme (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Version 2.9) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (Version 4). The latest development of the NASA POWER Project and its plans for the future are presented in this paper.

Zhang, Taiping↗
NASA NTRS2006

Implementation of Cloud Retrievals for Tropospheric Emission Spectrometer (TES) Atmospheric Retrievals: Part 1. Description and Characterization of Errors on Trace Gas Retrievals

We develop an approach to estimate and characterize trace gas retrievals in the presence of clouds in high spectral measurements of upwelling radiance in the infrared spectral region (650-2260/cm). The radiance contribution of clouds is parameterized in terms of a set of frequency-dependent nonscattering optical depths and a cloud height. These cloud parameters are retrieved jointly with surface temperature, emissivity, atmospheric temperature, and trace gases such as ozone from spectral data. We demonstrate the application of this approach using data from the Tropospheric Emission Spectrometer (TES) and test data simulated with a scattering radiative transfer model. We show the value of this approach in that it results in accurate estimates of errors for trace gas retrievals, and the retrieved values improve over the initial guess for a wide range of cloud conditions. Comparisons are made between TES retrievals of ozone, temperature, and water to model fields from the Global Modeling and Assimilation Office (GMAO), temperature retrievals from the Atmospheric Infrared Sounder (AIRS), tropospheric ozone columns from the Goddard Earth Observing System (GEOS) GEOS-Chem, and ozone retrievals from the Total Ozone Mapping Spectrometer (TOMS). In each of these cases, this cloud retrieval approach does not introduce observable biases into TES retrievals.

aerosols↗
NASA NTRS2008

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

There are some in the science community who believe that the response of the climate system to anthropogenic radiative forcing is unpredictable and we should therefore call off the quest . The key limitation in climate predictability is associated with cloud feedback. Narrowing the uncertainty in cloud feedback (and therefore climate sensitivity) requires optimal use of the best available observations to evaluate and improve climate model processes and constrain climate model simulations over longer time scales. The Clouds and the Earth s Radiant Energy System (CERES) is a satellite-based program that provides global cloud, aerosol and radiative flux observations for improving our understanding of cloud-aerosol-radiation feedbacks in the Earth s climate system. CERES is the successor to the Earth Radiation Budget Experiment (ERBE), which has widely been used to evaluate climate models both at short time scales (e.g., process studies) and at decadal time scales. A CERES instrument flew on the TRMM satellite and captured the dramatic 1998 El Nino, and four other CERES instruments are currently flying aboard the Terra and Aqua platforms. Plans are underway to fly the remaining copy of CERES on the upcoming NPP spacecraft (mid-2010 launch date). Every aspect of CERES represents a significant improvement over ERBE. While both CERES and ERBE measure broadband radiation, CERES calibration is a factor of 2 better than ERBE. In order to improve the characterization of clouds and aerosols within a CERES footprint, we use coincident higher-resolution imager observations (VIRS, MODIS or VIIRS) to provide a consistent cloud-aerosol-radiation dataset at climate accuracy. Improved radiative fluxes are obtained by using new CERES-derived Angular Distribution Models (ADMs) for converting measured radiances to fluxes. CERES radiative fluxes are a factor of 2 more accurate than ERBE overall, but the improvement by cloud type and at high latitudes can be as high as a factor of 5. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

Loeb, Norman G.↗
NASA NTRS2008

Improving Incremental Balance in the GSI 3DVAR Analysis System

The Gridpoint Statistical Interpolation (GSI) analysis system is a unified global/regional 3DVAR analysis code that has been under development for several years at the National Centers for Environmental Prediction (NCEP)/Environmental Modeling Center. It has recently been implemented into operations at NCEP in both the global and North American data assimilation systems (GDAS and NDAS). An important aspect of this development has been improving the balance of the analysis produced by GSI. The improved balance between variables has been achieved through the inclusion of a Tangent Linear Normal Mode Constraint (TLNMC). The TLNMC method has proven to be very robust and effective. The TLNMC as part of the global GSI system has resulted in substantial improvement in data assimilation both at NCEP and at the NASA Global Modeling and Assimilation Office (GMAO).

Errico, Ronald M.↗
NASA NTRS2008

Observations and Modeling of Composition of Upper Troposphere/Lower Stratosphere (UTILS): Isentropic Mixing Events and Morphology of HNO3 as Observed by HIRDLS and Comparison with Results from Global Modeling Initiative

isentropic exchange of air masses between the tropical upper troposphere and mid-latitude lowermost stratosphere (the so-called "middle world") is an important pathway for stratospheric-tropospheric exchange. A seasonal, global view of this process has been difficult to obtain, in part due to the lack of the vertical resolution in satellite observations needed to capture the laminar character of these events. Ozone observations at a resolution of about 1 km from the High Resolution Dynamic Limb Sounder (HIRDLS) on NASA's Aura satellite show instances of these intrusions. Such intrusions should also be observable in HN03 observations; however, the abundances of nitric acid could be additionally controlled by chemical processes or incorporation and removal into ice clouds. We present a systematic examination of the HIRDLS data on O3 and HNO3 to determine the seasonal and spatial characteristics of the distribution of isentropic intrusions. At the same time, we compare the observed distributions with those calculated by the Global Modeling Initiative combined tropospheric-stratospheric model, which has a vertical resolution of about I km. This Chemical Transport Model (CTM) is driven by meteorological fields obtained from the GEOS-4 system of NASA/Goddard Global Modeling and Assimilation Office (GMAO), for the Aura time period, at a vertical resolution of about 1 km. Such comparison brings out the successes and limitations of the model in representing isentropic stratospheric-tropospheric exchange, and the different processes controlling HNO3 in the UTAS.

Rodriquez, J. M.↗
NASA NTRS2007

Saharan Air and Atlantic Tropical Cyclone Suppression From a Global Modeling Perspective

During summer 2006, the NASA African Monsoon Multidisciplinary Analysis (NAMMA) organized a field campaign in Africa called Special Observation Period (SOP-3), in which scientists in the field were involved in a number of surface network and aircraft measurements. One of the scientific goals of the campaign was to understand the nature and causes for tropical cyclogenesis originating out of African Easterly Waves (AEWs, westward propagating atmospheric disturbances sometimes associated with precursors of hurricanes), and the role that the Saharan Air Layer (SAL, a hot and dry air layer advecting large amounts of dust) can play in the formation or suppression of tropical cyclones. During the NAMMA campaign a high-resolution global model, the NASA GEOS-5, was operationally run by the NASA Global Modeling and Assimilation Office (GMAO) in support to the mission. The daily GEOS-5 forecasts were found to be very useful by decision-making scientists in the field as an aid to discriminate between developing and non-developing AEWs and plan the flight tracks. In the post-event analyses which were performed mostly by the Goddard Laboratory for Atmospheres, two events were highlighted: a non-developing AEW which appeared to have been suppressed by Saharan air, compared to a developing AEW which was the precursor of hurricane Helene. Both events were successfully predicted by the GEOS-5 during the real-time forecasts provided in support to the mission. In this work it is found that very steep moisture gradients and a strong thermal dipole, with relatively warm air in the mid-troposphere and cool air below, are associated with SAL in both the GEOS-5 forecasts and the NCEP analyses, even at -great distance- from the Sahara. The presence of these unusual thermodynamic features over the Atlantic Ocean, at several thousands of kilometers from the African coastline, is suggestive that SAL mixing is very minimal and that the model's capability of retaining the different properties of air masses during transport are important to represent effectively the role of dry air intrusions in the tropical circulation.

Reale, O.↗
NASA NTRS2007

Simulations of Tropospheric NO2 by the Global Modeling Initiative (GMI) Model Utilizing Assimilated and Forecast Meteorological Fields: Comparison to Ozone Monitoring Instrument (OMI) Measurements

We present simulations of the tropospheric composition for the years 2004 and 2005, carried out by the GMI Combined Stratosphere-Troposphere (Combo) model, at a resolution of 2degx2.5deg. The model includes a new parameterization of lightning sources of NO(x) which is coupled to the cloud mass fluxes in the adopted meteorological fields. These simulations use two different sets of input meteorological fields: a)late-look assimilated fields from the Global Modeling and Assimilation Office (GMAO), GEOS-4 system and b) 12-hour forecast fields initialized with the assimilated data. Comparison of the forecast to the assimilated fields indicates that the forecast fields exhibit less vigorous convection, and yield tropical precipitation fields in better agreement with observations. Since these simulations include a complete representation of the stratosphere, they provide realistic stratosphere-tropospheric fluxes of O3 and NO(y). Furthermore, the stratospheric contribution to total columns of different troposheric species can be subtracted in a consistent fashion, and the lightning production of NO(y) will depend on the adopted meteorological field. We concentrate here on the simulated tropospheric columns of NO2, and compare them to observations by the OM1 instrument for the years 2004 and 2005. The comparison is used to address these questions: a) is there a significant difference in the agreement/disagreement between simulations for these two different meteorological fields, and if so, what causes these differences?; b) how do the simulations compare to OMI observations, and does this comparison indicate an improvement in simulations with the forecast fields? c) what are the implications of these simulations for our understanding of the NO2 emissions over continental polluted regions?

Rodriquez, J. M.↗
NASA NTRS2009

Developing a Model-based Capability to Analyze Requirements for the Climate Observing System

Models are foundational for estimating states of the earth's climate system, both as tools to extrapolate information in time and space, and as observation 'operators' used to relate what is analyzed and predicted to what is observed. Expanding the simulation approach further, observing system simulation experiments (OSSEs) are designed to mimic the complete process of analyzing the climate state by replacing real observations with entirely simulated ones determined from a model-based depiction of nature. OSSEs provide a framework to 'fly' simulated satellite instruments through a synthetic atmosphere and investigate the trade-spaces of measurements for various satellite configurations and sampling strategies, and assess their measurement impact on modeling and forecasting capabilities. Such a tool is a crucial but as yet unfulfilled need for future mission selection and design. The components of a state-of-the-art OSSE system are being assembled at the Global Modeling and Assimilation Office (GMAO, Code 610.1) at NASA/GSFC, leveraging on the GMAO's existing modeling and data assimilation infrastructure for numerical weather prediction (NWP). The OSSE framework is based on the GMAO's Goddard Earth Observing System atmospheric general circulation model, version 5 (GEOS-5) and the Gridpoint Statistical Interpolation (GSI) observational analysis scheme, combined with the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model developed by the Atmospheric Chemistry and Dynamics Branch (Code 613.3). This system is an evolving, key component of Goddard's planned development of an Integrated Earth System Analysis (IESA) capability, which will bring together into a single, fully interactive system Goddard's modeling and assimilation efforts in atmosphere, ocean and chemistry and aerosols to provide a comprehensive analysis and prediction system for weather and climate In addition to providing a state-of-the-art capability for assimilating current observation types, GEOS-5, and the future IESA, provide the capability to identify the need for, and assess the potential impact of, future observing systems under consideration for improving weather and climate prediction.

Gelaro, Ronald↗
NASA NTRS2009

The GMAO ADVAR System: Preliminary Results

The Goddard Earth Observing System (GEOS-S) Data Assimilation System is now configurable to run strong constraint 4DVAR. The system combines the 4DVAR-capable Grid-point Statistical Interpolation analysis with the GEOS-S general circulation model and an early version of the tangent linear and adjoint models of the finite-volume hydrodynamics with simplified physics. The GMAO 4DVAR uses a Lanczos-based conjugate gradient algorithm in a nested resolution inner-loop setting. A range of tests and experiments will have been carried out by the time of the Symposium. Results on balance-related issues, resolution configuration, and choice of assimilation time window will be shown. A comparison with the Global Modeling and Assimilation Office (GMAO) 3DVAR and a discussion of future directions of development will also be presented.

Todling, Ricardo↗
NASA NTRS2011

Results of the Simulation and Assimilation of Doppler Wind Lidar Observations in Preparation for European Space Agency's Aeolus Mission

With the launch of the European Space Agency's Aeolus Mission in 2013, direct spaceborne measurements of vertical wind profiles are imminent via Doppler wind lidar technology. Part of the preparedness for such missions is the development of the proper data assimilation methodology for handling such observations. Since no heritage measurements exist in space, the Joint Observing System Simulation Experiment (Joint OSSE) framework has been utilized to generate a realistic proxy dataset as a precursor to flight. These data are being used for the development of the Gridpoint Statistical Interpolation (GSI) data assimilation system utilized at a number of centers through the United States including the Global Modeling and Assimilation Office (GMAO) at NASA/Goddard Space Flight Center and at the National Centers for Environmental Prediction (NOAA/NWS/NCEP) as an activity through the Joint Center for Satellite Data Assimilation. An update of this ongoing effort will be presented, including the methodology of proxy data generation, the limitations of the proxy data, the handling of line-of-sight wind measurements within the GSI, and the impact on both analyses and forecasts with the addition of the new data type.

McCarty, Will↗
NASA NTRS2011

The Simulation and Assimilation of Doppler Wind Lidar Observations in Support of Future Instruments

With the launch of the European Space Agency's Atmospheric Dynamics Mission (ADM-Aeolus) in 2011 and the call for the 3D-Winds mission in National Research Council's decadal survey, direct spaceborne measurements of vertical wind profiles are imminent via Doppler wind lidar technology. Part of the preparedness for such missions is the development of the proper data assimilation methodology for handling such observations. Since no heritage measurements exist in space, the Joint Observing System Simulation Experiment (Joint OSSE) framework is being utilized to generate a realistic proxy dataset as a precursor to flight. These data are being used for the development of the Gridpoint Statistical Interpolation (GSI) data assimilation system utilized at a number of centers through the United States including the Global Modeling and Assimilation Office (GMAO) at NASA/Goddard Space Flight Center and at the National Centers for Environmental Prediction (NOAA/NWS/NCEP). This effort will be presented, including the methodology of proxy data generation, the handling of line-of-sight wind measurements within the GSI, and the impact on both analyses and forecasts with the addition of the new data type.

McCarty, Will↗
NASA NTRS2011

The NASA GEOS-5 Aerosol Forecasting System

The NASA Goddard Earth Observing System modeling and data assimilation environment (GEOS-5) is maintained by the Global Modeling and Assimilation Office (GMAO) at the NASA Goddard Space Flight Center. Near-realtime meteorological forecasts are produced to support NASA satellite and field missions. We have implemented in this environment an aerosol module based on the Goddard Chemistry, Aerosol, Radiation, and Transport (GOCART) model. This modeling system has previously been evaluated in the context of hindcasts based on assimilated meteorology. Here we focus on the development and evaluation of the near-realtime forecasting system. We present a description of recent efforts to implement near-realtime biomass burning emissions derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) fire radiative power products. We as well present a developing capability for improvement of aerosol forecasts by assimilation of aerosol information from MODIS.

Colarco, Peter↗
NASA NTRS2012

Towards the Handing of Cloud-Affected Infrared Radiances in the GSI

In the gridpoint statistical interpolation (GSI) data assimilation algorithm, only thermal infrared measurements determined to be uncontaminated by clouds are assimilated. Using this approach, typically only 19-29% of footprints are deemed to have no cloud affects through the measured spectra. This study will discuss the efforts underway at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center, in conjunction with the Joint Center for Satellite Data Assimilation (JCSDA), to actively assimilate these morecomplicated observations by using a graybody assumption. In the GSI, cloud top pressure and effective cloud amount are retrieved concurrently using a minimum residual method. This study will address the limitations and advantages of the technique and the modifications underway to the assimilation system to incorporate those two parameters into the radiative transfer forward operators and TL/AD calculations. Furthermore, it will explain the efforts underway to incorporate these parameters into the control vector so that they can be altered variationally as part of the minimization.

McCarty, William↗
NASA NTRS2012

Ground and Airborne Methane Measurements using Optical Parametric Amplifiers

We report on an initial airborne demonstration of atmospheric methane column measurements at 1.65 micrometers using a widely tunable, seeded optical parametric amplifier (OPA) lidar and a photon counting detector. Methane is an important greenhouse gas and accurate knowledge of its sources and sinks is needed for climate modeling. Our lidar system uses 20 pulses at increasing wavelengths and integrated path differential absorption (IPDA) to map a methane line at 1650.9 nanometers. The wavelengths are generated by using a Nd:YAG pump laser at 1064.5 nanometers and distributed feedback diode laser at 1650.9 nanometers and a periodically-poled lithium niobate (PPLN) crystal. The pulse width was 3 nanoseconds and the pulse repetition rate was 6.28 KHz. The outgoing energy was approximately 13 microJoules/pulse. A commercial 20 nanometer diameter fiber-coupled telescope with a photon counting detector operated in analog mode with a 0.8 nanometer bandpass filter was used as the lidar receiver. The lidar system was integrated on NASA's DC-8 flying laboratory, based at Dryden Airborne operations Facility (DAOF) in Palmdale CA. Three flights were performed in the central valley of California. Each flight lasted about 2.5 hours and it consisted of several flight segments at constant altitudes at approximately 3, 4.5, 6, 7.6, 9.1, 10.6 km (l0, 15, 20, 25, 30, 35 kft). An in-situ cavity ring down spectrometer made by Picarro Inc. was flown along with the lidar instrument provided us with the "truth" i.e. the local CH4, CO2 and H2O concentrations at the constant flight altitude segments. Using the aircraft's altitude, GPS, and meteorological data we calculated the theoretical differential optical depth of the methane absorption at increasing altitudes. Our results showed good agreement between the experimentally derived optical depth measurements from the lidar instrument and theoretical calculations as the flight altitude was increased from 3 to 10.6 kilometers, assuming a constant methane mixing ratio of 1.8 parts per million. The in-situ spectrometer did not show any significant deviations from the ambient concentrations. Further analysis using meteorological data from the Global Modeling and Assimilation Office (http://gmao.gsfc.nasa.gov/) to derive the theoretical optical depth also showed good agreement with the experimentally derived values. The OPA lidar system with slight modifications has also been used to measure CO2, water vapor, and CO in the near and mid-infrared spectral regions on the ground.

Riris, Haris↗
NASA NTRS2012

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Koster, Randal↗
NASA NTRS2012

Decadal Prediction Skill in the GEOS-5 Forecast System

A suite of decadal predictions has been conducted with the NASA Global Modeling and Assimilation Office?s GEOS-5 Atmosphere-Ocean General Circulation Model (AOGCM). The hindcasts are initialized every December from 1959 to 2010 following the CMIP5 experimental protocol for decadal predictions. The initial conditions are from a multi-variate ensemble optimal interpolation ocean and sea-ice reanalysis, and from the atmospheric reanalysis (MERRA, the Modern-Era Retrospective Analysis for Research and Applications) generated using the GEOS-5 atmospheric model. The forecast skill of a three-member-ensemble mean is compared to that of an experiment without initialization but forced with observed CO2. The results show that initialization acts to increase the forecast skill of Northern Atlantic SST compared to the uninitialized runs, with the increase in skill maintained for almost a decade over the subtropical and mid-latitude Atlantic. The annual-mean Atlantic Meridional Overturning Circulation (AMOC) index is predictable up to a 5-year lead time, consistent with the predictable signal in upper ocean heat content over the Northern Atlantic. While the skill measured by Mean Squared Skill Score (MSSS) shows 50% improvement up to 10-year lead forecast over the subtropical and mid-latitude Atlantic, however, prediction skill is relatively low in the subpolar gyre, due in part to the fact that the spatial pattern of the dominant simulated decadal mode in upper ocean heat content over this region appears to be unrealistic. An analysis of the large-scale temperature budget shows that this is the result of a model bias, implying that realistic simulation of the climatological fields is crucial for skillful decadal forecasts.

Ham, Yoo-Geun↗
NASA NTRS2012

Expected Performance of Ozone Climate Data Records from Ozone Mapping and Profiler Suite Limb Profiler

The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) was launched on board of the Soumi NPP space platform in late October 2011. It provides ozone-profiling capability with high-vertical resolution from 60 Ian to cloud top. In this study, an end-to-end Observing System Simulation Experiment (OSSE) of OMPS/LP ozone is discussed. The OSSE was developed at NASA's Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System (GEOS-5) data assimilation system. The "truth" for this OSSE is built by assimilating MLS profiles and OMI ozone columns, which is known to produce realistic three-dimensional ozone fields in the stratosphere and upper troposphere. OMPS/LP radiances were computed at tangent points computed by an appropriate orbital model. The OMPS/LP forward RT model, Instrument Models (IMs) and EDR retrieval model were introduced and pseudo-observations derived. The resultant synthetic OMPS/LP observations were evaluated against the "truth" and subsequently these observations were assimilated into GEOS-5. Comparison of this assimilated dataset with the "truth" enables comparisons of the likely uncertainties in 3-D analyses of OMPS/LP data. This study demonstrated the assimilation capabilities of OMPS/LP ozone in GEOS-5, with the monthly, zonal mean (O-A) smaller than 0.02ppmv at all levels, the nns(O-A) close to O.lppmv from 100hPa to 0.2hPa; and the mean(O-B) around the 0.02ppmv for all levels. The monthly zonal mean analysis generally agrees to within 2% of the truth, with larger differences of 2-4% (0.1-0.2ppmv) around 10hPa close to North Pole and in the tropical tropopause region, where the difference is above 20% due to the very low ozone concentrations. These OSSEs demonstrated that, within a single data assimilation system and the assumption that assimilated MLS observations provide a true rendition of the stratosphere, the OMPS/LP ozone data are likely to produce accurate analyses through much of the stratosphere. Additional studies are needed to evaluate the importance of the extremely high vertical resolution of the OMPS/LP ozone data

Xu, P. Q.↗