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NASA NTRS2005

Assimilation of MLS and OMI Ozone Data

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

Stajner, I.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-10726-DND

The principal component radiative transfer model PCRTM (Xu 2006) simulates spectral longwave radiance at a 0.5cm-1 resolution over the wavelengths (50-2760cm-1) using 280 principal components. The CERES product SSF containing CERES field-of-view (FOV) cloud properties based on MODIS pixel information are used as inputs. NASA GMAO(Global Modeling and Assimilation Office)Geos-4 temperature and humidity profiles, as well as SMOBA (Stratosphere Monitoring Ozone Blended Analysis) ozone profiles allow computations for five years (Jan 2001- Dec 2006) of FOV nadir spectral radiance. The approximately twice daily FOV PCRTM simulations along with CERES broadband measurements are time-space averaged to 10deg zonal monthly data. Analysis of monthly seasonal and deseasonalized interannual variability in terms of brightness temperature are presented. Comparison of interannual variability in the portions of the spectrum seen by the AIRS instrument are shown. Comparisons of spectral integrated PCRTM simulations to CERES broadband longwave radiance measurements are made. In order to study the sensitivity of the spatially and temporally averaged TOA spectrum to various atmospheric properties, we perturbed atmospheric and surface temperatures, humidity, cloud height, cloud fraction, and particle size. The sensitivity of the spectrum to these properties depends on region and seasons. Month to month variability of the longwave spectra to these perturbations is 10 to 20% of the global monthly mean perturbation response. In addition, it depends on time period and size of the area used for averaging spectra. In this poster, the magnitude of sensitivity variability and how the sensitivity changes depending on temporal and spatial scale of averaging will be discussed.

Fred G. Rose↗
NASA NTRS2022

Using OSSEs to Evaluate the Impacts of Geostationary Infrared Sounders

An observing system simulation experiment (OSSE) was performed to assess the impact of assimilating hyperspectral infrared (IR) radiances from geostationary orbit on numerical weather prediction, with a focus on the proposed sounder on board the Geostationary Extended Observations (GeoXO) program’s central satellite. Infrared sounders on a geostationary platform would fill several gaps left by IR sounders on polar-orbiting satellites, and the increased temporal resolution would allow the observation of weather phenomena evolution. The framework for this OSSE was the Global Modeling and Assimilation Office (GMAO) OSSE system, which includes a full suite of meteorological observations. The experiment additionally assimilated four identical IR sounders from geostationary orbit to create a “ring” of vertical profiling observations. Based on the experimentation, assimilation of the IR sounders provided a beneficial impact on the analyzed mass and wind fields, particularly in the tropics, and produced an error reduction in the initial 24–48 h of the subsequent forecasts. Specific attention was paid to the impact of the GeoXO Sounder (GXS) over the contiguous United States (CONUS) as this is a region that is well-observed and as such difficult to improve. The forecast sensitivity to observation impact (FSOI) metric, computed across all four synoptic times over the CONUS, reveals that the GXS had the largest impact on the 24-h forecast error of the assimilated hyperspectral infrared satellite radiances as measured using a moist energy error norm. Based on this analysis, the proposed GXS has the potential to improve numerical weather prediction globally and over the CONUS.

OSSE↗
NASA NTRS2006

Atmospheric Teleconnection over Eurasia Induced by Aerosol Radiative Forcing during Boreal Spring

The direct effects of aerosols on global and regional climate during boreal spring are investigated based on numerical simulations with the NASA Global Modeling and Assimilation Office finite-volume general circulation model (fvGCM) with Microphyics of Clouds with the Relaxed Arakawa Schubert Scheme (McRAS), using aerosol forcing functions derived from the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The authors find that anomalous atmospheric heat sources induced by absorbing aerosols (dust and black carbon) excite a planetary-scale teleconnection pattern in sea level pressure, temperature, and geopotential height spanning North Africa through Eurasia to the North Pacific. Surface cooling due to direct effects of aerosols is found in the vicinity and downstream of the aerosol source regions, that is, South Asia, East Asia, and northern and western Africa. Significant atmospheric heating is found in regions with large loading of dust (over northern Africa and the Middle East) and black carbon (over Southeast Asia). Paradoxically, the most pronounced feature in aerosol-induced surface temperature is an east west dipole anomaly with strong cooling over the Caspian Sea and warming over central and northeastern Asia, where aerosol concentrations are low. Analyses of circulation anomalies show that the dipole anomaly is a part of an atmospheric teleconnection pattern driven by atmospheric heating anomalies induced by absorbing aerosols in the source regions, but the influence was conveyed globally through barotropic energy dispersion and sustained by feedback processes associated with the regional circulations. The surface temperature signature associated with the aerosol-induced teleconnection bears striking resemblance to the spatial pattern of observed long-term trend in surface temperature over Eurasia. Additionally, the boreal spring wave train pattern is similar to that reported by Fukutomi et al. associated with the boreal summer precipitation seesaw between eastern and western Siberia. The results of this study raise the possibility that global aerosol forcing during boreal spring may play an important role in spawning atmospheric teleconnections that affect regional and global climates.

Kim, Maeng-Ki↗
NASA NTRS2019

Impact of GMI All-Sky Radiance Assimilation in the NASA GEOS Forecast System

The assimilation of cloud- and precipitation-affected ("all-sky") radiances has become an important focus of development at most numerical weather prediction centers. Efforts at the Global Modeling and Assimilation Office (GMAO) have focused on all-sky assimilation of GPM Microwave Imager (GMI) radiances, which became operational in the GEOS real-time production system in July 2018. Implementation of the all-sky capability required several upgrades to the GEOS hybrid 4D-EnVar assimilation infrastructure including the addition of control variables for cloud liquid, cloud ice, rain and snow, enhancements to the radiative transfer model, new hybrid background and observational error models, and modified quality control and bias correction procedures. This talk describes the impact of GMI all-sky radiance assimilation on GEOS analyses and forecasts as determined from examination of various metrics including statistics of background departures and analysis increments, forecast skill scores, and forecast sensitivity observation impact (FSOI) calculations. It is shown that in addition to the hydrometeors themselves, the initial wind, temperature and pressure fields all undergo significant dynamic adjustment in response to the analyzed cloud and precipitation features. Assimilation of GMI radiances leads to improved forecasts of lower tropospheric wind, temperature and humidity, especially in the tropics. The largest forecast improvements occur during the first 48 hours, with diminishing impact thereafter. However, combining GMI all-sky assimilation with improvements to the GEOS model physics as in the recent implementation of the real-time production system, extends these forecast improvements well in to the medium range. FSOI results based on a 24-hr moist global energy norm show that GMI radiances provide nearly uniform beneficial impact throughout the tropics, with more mixed impacts in the subtropics. While the overall impact of GMI is smaller than that of other, much more numerous microwave and hyperspectral infrared radiance types, its impact is among the largest of all radiance types on a per-observation basis.

Gelaro, Ron↗
NASA NTRSDate not supplied

Snow Depth from AMSR-2 Using Multispectral Satellite Data in an Artificial Neural Network

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu et al. (2022) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, an artificial neural network (ANN) algorithm, employing several channels from Advanced Microwave Scanning Radiometer 2 (AMSR-2) and the humidity vertical profiles from Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System for Instrument Teams (GEOS-IT) product, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained ANN snow-depth was applied to 2018 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. The validation data (different from the training set) of ANN snow depth from AMSR-2 showed a good agreement with time matched and co-located snow-depth values from ICESat-2. The bias was near zero, with mean absolute error (MAE) 0.05 cm and a root-mean-square-error (RMSE) 0.08 cm. Prior applying the trained ANN snow depth to AMSR-2 data, a cloud screening algorithm was developed with a similar approach. A separate ANN cloud mask was trained to determine an AMSR-2 pixel is clear or cloudy with time and geolocation matched 2015 CALIOP Vertical Feature Mask (VFM) over Arctic sea ice. The ANN cloud mask from AMSR-2 under-estimated cloud fraction by 3-6% compared to CALIOP . The additional research is needed to conclusively evaluate the ANN cloud mask accuracy. Finally, this paper will lay the foundation for a sustained long-term snowfall and snow-storm monitoring system. The future Cloud Aerosol LIdar for Global scale Observations of the ocean-Land Atmosphere system (CALIGOLA) mission will provide a means to calculate snow depth from the lidar backscattering pathlength distribution, benefiting from the UV, visible and infrared pulses. With the calculated snow depth as the truth one could develop a machine learning algorithm, as it was done in this paper, using a passive microwave instrument available at that time to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗
NASA NTRS2018

A Study of the Carbon Cycle Using NASA Observations and the GEOS Model

The Goddard Earth Observing System (GEOS) model has been developed in the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center. From its roots in chemical transport and as a General Circulation Model, the GEOS model has been extended to an Earth System Model based on a modular construction using the Earth System Modeling Framework (ESMF), combining elements developed in house in the GMAO with others that are imported through collaborative research. It is used extensively for research and for product generation, both as a free-running model and as the core of the GMAO's data assimilation system. In recent years, the GMAO's modeling and assimilation efforts have been strongly supported by Piers Sellers, building on both his earlier legacy as an observationally oriented model developer and his post-astronaut career as a dynamic leader into new territory. Piers' long-standing interest in the carbon cycle and the combination of models with observations motivates this presentation, which will focus on the representation of the carbon cycle in the GEOS Earth System Model. Examples will include: (i) the progression from specified land-atmosphere surface fluxes to computations with an interactive model component (Catchment-CN), along with constraints on vegetation distributions using satellite observations; (ii) the use of high-resolution satellite observations to constrain human-generated inputs to the atmosphere; (iii) studies of the consistency of the observed atmospheric carbon dioxide concentrations with those in the model simulations. The presentation will focus on year-to-year variations in elements of the carbon cycle, specifically on how the observations can inform the representation of mechanisms in the model and lead to integrity in global carbon dioxide simulations. Further, applications of the GEOS model to the planning of new carbon-climate observations will be addressed, as an example of the work that was strongly supported by Piers in the last months of his leadership of Earth Science at NASA Goddard.

Pawson, Steven↗
NASA NTRS2005

Atmospheric Teleconnection over Eurasia Induced by Aerosol Radiative Forcing During Boreal Spring

The direct effects of aerosols on global and regional climate during boreal spring are investigated based on simulations using the NASA Global Modeling and Assimilation Office (GMAO) finite-volume general circulation model (fvGCM) with Microphyics of clouds in Relaxed Arakawa Schubert Scheme (McRAS). The aerosol loading are prescribed from three-dimensional monthly distribution of tropospheric aerosols viz., sulfate, black carbon, organic carbon, soil dust, and sea salt from output of the Goddard Ozone Chemistry Aerosol Radiation and Transport model (GOCART). The aerosol extinction coefficient, single scattering albedo, and asymmetric factor are computed as wavelength-dependent radiative forcing in the radiative transfer scheme of the fvGCM, and as a function of the aerosol loading and ambient relative humidity. We find that anomalous atmospheric heat sources induced by absorbing aerosols (dust and black carbon) excites a planetary scale teleconnection pattern in sea level pressure, temperature and geopotential height spanning North Africa through Eurasia to the North Pacific. Surface cooling due to direct effects of aerosols is found in the vicinity and downstream of the aerosol source regions, i.e., South Asia, East Asia, and northern and western Africa. Additionally, atmospheric heating is found in regions with large loading of dust (over Northern Africa, and Middle East), and black carbon (over South-East Asia). Paradoxically, the most pronounced feature in aerosol-induced surface temperature is an east-west dipole anomaly with strong cooling over the Caspian Sea, and warming over central and northeastern Asia, where aerosol concentration are low. Analyses of circulation anomalies show that the dipole anomaly is a part of an atmospheric teleconnection driven by atmospheric heating anomalies induced by absorbing aerosols in the source regions, but the influence was conveyed globally through barotropic energy dispersion and sustained by feedback processes associated with the regional circulations.

Kim, Maeng-Ki↗
NASA NTRS2011

An Overview of the GEOS-5 Aerosol Reanalysis

GEOS-5 is the latest version of the NASA Global Modeling and Assimilation Office (GMAO) earth system model. GEOS-5 contains components for atmospheric circulation and composition (including data assimilation), ocean circulation and biogeochemistry, and land surface processes. In addition to traditional meteorological parameters, GEOS-5 includes modules representing the atmospheric composition, most notably aerosols and tropospheric/stratospheric chemical constituents, taking explicit account of the impact of these constituents on the radiative processes of the atmosphere. MERRA is a NASA meteorological reanalysis for the satellite era (1979-present) using GEOS-5. This project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales. As a first step towards an integrated Earth System Analysis (IESA), the GMAO is extending MERRA with reanalyses for other components of the earth system: land, ocean, bio-geochemistry and atmospheric constituents. In this talk we will present results from the MERRA-driven aerosol reanalysis covering the Aqua period (2003-present). The assimilation of Aerosol Optical Depth (AOD) in GEOS-5 involves very careful cloud screening and homogenization of the observing system by means of a Neural Net scheme that translates MODIS radiances into AERONET calibrated AOD. These measurements are further quality controlled using an adaptive buddy check scheme, and assimilated using the Local Displacement Ensemble (LDE) methodology. For this reanalysis, GEOS-5 runs at a nominal 50km horizontal resolution with 72 vertical layers (top at approx. 8Skm). GEOS-5 is driven by daily biomass burning emissions derived from MODIS fire radiative power retrievals. We will present a summary of our efforts to validate such dataset. The GEOS-5 assimilated aerosol fields are first validated by comparison to independent in-situ measurements (AERONET and PM2.5 surface concentrations). In order to asses aerosol absorption on a global scale, we perform a detailed radiative transfer calculation to simulate the UV aerosol index, comparing our results to OMI measurements. By simulating aerosol attenuated backscatter, we use CALIPSO measurements to evaluate the vertical structure of our aerosol estimates, in particular in regions where we have larger discrepancies with OMI. Finally, the consistency of our AOD estimates with estimates from MISR, MODIS/Deep Blue, OMI and PARASOL will be briefly discussed.

da Silva, Arlindo↗
NASA NTRS2021

Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0

The Goddard Earth Observing System composition forecast (GEOS-CF) system is a high-resolution (0.25 degree) global constituent prediction system from NASA’s Global Modeling and Assimilation Office (GMAO). GEOS-CF offers a new tool for atmospheric chemistry research, with the goal to supplement NASA’s broad range of space-based and in-situ observation sand to support flight campaign planning, support of satellite observations, and air quality research. GEOS-CF expands on the GEOS weather and aerosol modeling system by introducing the GEOS-Chem chemistry module to provide analyses and 5-day forecasts of atmospheric constituents including ozone (O3), carbon monoxide (CO), nitrogen dioxide (NO2), and fine particulate matter (PM2.5). The chemistry module integrated in GEOS-CF is identical to the offline GEOS-Chem model and readily benefits from the innovations provided by the GEOS-Chem community.Evaluation of GEOS-CF against satellite, ozone sonde and surface observations show realistic simulated concentrations of O3, NO2, and CO, with normalized mean biases of -0.1 to -0.3, normalized root mean square errors (NRMSE) between 0.1-0.4, and correlations between 0.3-0.8. Comparisons against surface observations highlight the successful representation of air pollutants under a variety of meteorological conditions, yet also highlight current limitations, such as an over prediction of summertime ozone over the Southeast United States. GEOS-CFv1.0 generally overestimates aerosols by 20-50% due to known issues in GEOS-Chem v12.0.1 that have been addressed in later versions.The 5-day hourly forecasts have skill scores comparable to the analysis. Model skills can be improved significantly by applying a bias-correction to the surface model output using a machine-learning approach.

GEOS-CF↗
DOE OSTI2022

Airborne Lidar Measurements of XCO 2 in Synoptically Active Environment and Associated Comparisons With Numerical Simulations

Frontal boundaries have been shown to cause large changes in CO 2 mole-fractions, but clouds and the complex vertical structure of fronts make these gradients difficult to observe. It remains unclear how the column average CO 2 dry air mole-fraction (XCO 2 ) changes spatially across fronts, and how well airborne lidar observations, data assimilation systems, and numerical models without assimilation capture XCO 2 frontal contrasts (ΔXCO 2 , i.e., warm minus cold sector average of XCO 2 ). We demonstrated the potential of airborne Multifunctional Fiber Laser Lidar (MFLL) measurements in heterogeneous weather conditions (i.e., frontal environment) to investigate the ΔXCO 2 during four seasonal field campaigns of the Atmospheric Carbon and Transport-America (ACT-America) mission. Most frontal cases in summer (winter) reveal higher (lower) XCO 2 in the warm (cold) sector than in the cold (warm) sector. During the transitional seasons (spring and fall), no clear signal in ΔXCO 2 was observed. Intercomparison among the MFLL, assimilated fields from NASA's Global Modeling and Assimilation Office (GMAO), and simulations from the Weather Research and Forecasting-—Chemistry (WRF-Chem) showed that (a) all products had a similar sign of ΔXCO 2 though with different levels of agreement in ΔXCO 2 magnitudes among seasons; (b) ΔXCO 2 in summer decreases with altitude; and (c) significant challenges remain in observing and simulating XCO 2 frontal contrasts. A linear regression analyses between ΔXCO 2 for MFLL versus GMAO, and MFLL versus WRF-Chem for summer-2016 cases yielded a correlation coefficient of 0.95 and 0.88, respectively. The reported ΔXCO 2 variability among four seasons provide guidance to the spatial structures of XCO 2 transport errors in models and satellite measurements of XCO 2 in synoptically-active weather systems.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Data Management as a Cluster Middleware Centerpiece

Through earth and space modeling and the ongoing launches of satellites to gather data, NASA has become one of the largest producers of data in the world. These large data sets necessitated the creation of a Data Management System (DMS) to assist both the users and the administrators of the data. Halcyon Systems Inc. was contracted by the NASA Center for Computational Sciences (NCCS) to produce a Data Management System. The prototype of the DMS was produced by Halcyon Systems Inc. (Halcyon) for the Global Modeling and Assimilation Office (GMAO). The system, which was implemented and deployed within a relatively short period of time, has proven to be highly reliable and deployable. Following the prototype deployment, Halcyon was contacted by the NCCS to produce a production DMS version for their user community. The system is composed of several existing open source or government-sponsored components such as the San Diego Supercomputer Center s (SDSC) Storage Resource Broker (SRB), the Distributed Oceanographic Data System (DODS), and other components. Since Data Management is one of the foremost problems in cluster computing, the final package not only extends its capabilities as a Data Management System, but also to a cluster management system. This Cluster/Data Management System (CDMS) can be envisioned as the integration of existing packages.

Zero, Jose↗
NASA NTRS2004

Antarctic Stratospheric Ozone from the Assimilation of Occultation Data

Ozone data from the solar occultation Polar Ozone and Aerosol Measurement (POAM) III instrument are included in the ozone assimilation system at NASA's Global Modeling and Assimilation Office, which uses Solar Backscatter UItraViolet/2 (SBUV/2) instrument data. Even though POAM data are available at only one latitude in the southern hemisphere on each day, their assimilation leads to more realistic ozone distribution throughout the Antarctic region, especially inside the polar vortex. Impacts of POAM data were evaluated by comparisons of assimilated ozone profiles with independent ozone sondes. Major improvements in ozone representation are seen in the Antarctic lower stratosphere during austral Winter and spring in 1998. Limitations of assimilation of sparse occultation data are illustrated by an example.

Stajner, Ivanka↗
NASA NTRS2005

Using Microwave and Infrared Radiances from Off-Nadir Pixels: Application of Radiative Transfer to Slanted Line-of-Sight and Comparisons with NASA EOS Aqua Data

The passive infrared and microwave nadir sounders such as (A)TOVS observe the atmosphere from a polar orbit by directing their scan pointed at the ground up to about 49 degrees from nadir. Except for the pixels located right on the satellite ground track, the radiance measurements collected by these instruments characterize hence atmospheric emission paths which are slanted with respect to the zenithal direction at the ground. At the outer swath edges, the deviations from nadir reach about 60 degrees in terms of Satellite Zenith Angle (SZA). The radiative transfer codes used in operational Numerical Weather Prediction applications make the appropriate corrections to account for the extra path induced by the non-zero SZA. However, no corrections are made to account for the fact that the atmospheric profiles along the slanted line-of-sight (LOS) are different from the vertical because of horizontal gradients in the atmosphere. Using NASA EOS Aqua satellite's orbits, zenith and azimuth angles, as well as three-dimensional fields of temperature, water vapor, and ozone produced by the NASA Global Modeling and Assimilation Office, we extracted slanted atmospheric profiles for actual soundings performed by the AIRS and AMSU-A instruments onboard EOS Aqua. We will present the results of our study comparing the calculated brightness temperatures along slanted LOS and vertical LOS with AIRS and AMSU-A observations.

Poli, Paul↗
NASA NTRS2005

AGCM Biases in Evaporation Regime: Impacts on Soil Moisture Memory and Land-Atmosphere Feedback

Because precipitation and net radiation in an atmospheric general circulation model (AGCM) are typically biased relative to observations, the simulated evaporative regime of a region may be biased, with consequent negative effects on the AGCM s ability to translate an initialized soil moisture anomaly into an improved seasonal prediction. These potential problems are investigated through extensive offline analyses with the Mosaic land surface model (LSM). We first forced the LSM globally with a 15-year observations-based dataset. We then repeated the simulation after imposing a representative set of GCM climate biases onto the forcings - the observational forcings were scaled so that their mean seasonal cycles matched those simulated by the NSIPP-1 (NASA Global Modeling and Assimilation Office) AGCM over the same period-The AGCM s climate biases do indeed lead to significant biases in evaporative regime in certain regions, with the expected impacts on soil moisture memory timescales. Furthermore, the offline simulations suggest that the biased forcing in the AGCM should contribute to overestimated feedback in certain parts of North America - parts already identified in previous studies as having excessive feedback. The present study thus supports the notion that the reduction of climate biases in the AGCM will lead to more appropriate translations of soil moisture initialization into seasonal prediction skill.

Mahanama, Sarith P. P.↗
NASA NTRS2005

Assimilation of ozone profiles from the Improved Limb Atmospheric Spectrometer: Study on Antarctic Ozone - 2

Ozone data from the Improved Limb Atmospheric Spectrometer-II (ILAS-II) were included in addition to other satellite observations in the ozone assimilation system at the Global Modeling and Assimilation Office (GMAO) of NASA/Goddard. The control run assimilated data from NOAA 16 Solar Backscatter Ultraviolet/2 (SBUV/2) and Polar Ozone and Aerosol Measurement III (POAM III) instruments. Persistent impacts over Antarctica and transient impacts over northern middle and high latitudes are seen from April to October 2003, when ILAS-II provided good coverage. The largest improvements with respect to independent ozone sonde data are seen over the South Pole station. Ozone analyses and forecasts from the assimilation of SBUV/2, POAM III and ILAS-II data b e used to investigate the transport of ozone to southern middle latitudes following the breakup of the Antarctic vortex. The quality of analyses and forecasts is evaluated by comparison with independent Stratospheric Aerosol and Gas Experiment III (SAGE III) ozone data near 46degs. Anomaly correlations between SAGE III data and forecasts'exceed 0.6 for up to five to seven days at 30,50, and 70 ma. The loss of skill with advancing forecast length is related to dynamical errors due to an excessively persistent vortex in longer forecasts, which hampers the transport of low ozone air into middle latitudes.

Stajner, Ivanka↗
NASA NTRS2006

Tropospheric and stratospheric ozone from assimilation of Aura data

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

Stajner, I.↗
NASA NTRS2006

The Ozone Budget in the Upper Troposphere from Global Modeling Initiative (GMI)Simulations

Ozone concentrations in the upper troposphere are influenced by in-situ production, long-range tropospheric transport, and influx of stratospheric ozone, as well as by photochemical removal. Since ozone is an important greenhouse gas in this region, it is particularly important to understand how it will respond to changes in anthropogenic emissions and changes in stratospheric ozone fluxes.. This response will be determined by the relative balance of the different production, loss and transport processes. Ozone concentrations calculated by models will differ depending on the adopted meteorological fields, their chemical scheme, anthropogenic emissions, and treatment of the stratospheric influx. We performed simulations using the chemical-transport model from the Global Modeling Initiative (GMI) with meteorological fields from (It)h e NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM), (2) the atmospheric GCM from NASA's Global Modeling and Assimilation Office(GMAO), and (3) assimilated winds from GMAO . These simulations adopt the same chemical mechanism and emissions, and adopt the Synthetic Ozone (SYNOZ) approach for treating the influx of stratospheric ozone -. In addition, we also performed simulations for a coupled troposphere-stratosphere model with a subset of the same winds. Simulations were done for both 4degx5deg and 2degx2.5deg resolution. Model results are being tested through comparison with a suite of atmospheric observations. In this presentation, we diagnose the ozone budget in the upper troposphere utilizing the suite of GMI simulations, to address the sensitivity of this budget to: a) the different meteorological fields used; b) the adoption of the SYNOZ boundary condition versus inclusion of a full stratosphere; c) model horizontal resolution. Model results are compared to observations to determine biases in particular simulations; by examining these comparisons in conjunction with the derived budgets, we may pinpoint deficiencies in the representation of chemical/dynamical processes.

Rodriquez, J.↗