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At least 649 records · Page 36
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NASA NTRS2005

Coronal Current Sheet Evolution in the Aftermath of a CME

We report on SOHO-UVCS observations of coronal restructuring following a Coronal Mass Ejection (CME) on November 26, 2002, at the time of a SOHO-Ulysses quadrature campaign. Starting about 3 hours after the CME, which was directed towards Ulysses, UVCS began taking spectra at 1.7 solar radii, covering emission from both cool and hot plasma. Observations continued, with occasional gaps, for more than 2 days. Emission in the 974.8 Angstrom line of [Fe XVIII], indicating temperatures above 6x10(6) K, was observed throughout the campaign in a spatially limited location. Comparison with EIT images shows the [Fe XVIII] emission to overlie a growing post-flare loop system formed in the aftermath of the CME. The emission most likely originates in a current sheet overlying the arcade. Analysis of the [Fe XVIII] emission allows us to infer the evolution of physical parameters in the current sheet over the entire span of our observations: in particular, we give the temperature vs. time in the current sheet and estimate the density. Ulysses was directly above the location of the CME and intercepted the ejecta. High ionization state Fe was detected by SWICS throughout the magnetic cloud associated with the CME, although the rapid temporal variation suggests bursty, rather than smooth, reconnection in the coronal current sheet. Both the remote and in situ observations are compared with predictions of theoretical CME models.

Bemporad, A.↗
NASA NTRS2006

Current Sheet Evolution In The Aftermath Of A CME Event

We report on SOHO UVCS observations of the coronal restructuring following a coronal mass ejection (CME) on 2002 November 26, at the time of a SOHO-Ulysses quadrature campaign. Starting about 1.5 hr after a CME in the northwest quadrant, UVCS began taking spectra at 1.7 R, covering emission from both cool and hot plasma. Observations continued, with occasional gaps, for more than 2 days. Emission in the 974.8 A line of [Fe XVIII], indicating temperatures above 6 x 10(exp 6) K, was observed throughout the campaign in a spatially limited location. Comparison with EIT images shows the [Fe XVIII] emission to overlie a growing post-flare loop system formed in the aftermath of the CME. The emission most likely originates in a current sheet overlying the arcade. Analysis of the [Fe XVIII] emission allows us to infer the evolution of physical parameters in the current sheet over the entire span of our observations: in particular, we give the temperature versus time in the current sheet and estimate its density. At the time of the quadrature, Ulysses was directly above the location of the CME and intercepted the ejecta. High ionization state Fe was detected by the Ulysses SWICS throughout the magnetic cloud associated with the CME, although its rapid temporal variation suggests bursty, rather than smooth, reconnection in the coronal current sheet. The SOHO-Ulysses data set provided us with the unique opportunity of analyzing a current sheet structure from its lowest coronal levels out to its in situ properties. Both the remote and in situ observations are compared with predictions of theoretical CME models.

Bemporad, A.↗
NASA NTRS2017

Dynamical Conditions of Ice Supersaturation and Ice Nucleation in Convective Systems: A Comparative Analysis Between in Situ Aircraft Observations and WRF Simulations

Occurrence frequency and dynamical conditions of ice supersaturation (ISS, where relative humidity with respect to ice (RHi) greater than 100%) are examined in the upper troposphere around convective activity. Comparisons are conducted between in situ airborne observations and the Weather Research and Forecasting model simulations using four double-moment microphysical schemes at temperatures less than or or equal to -40degdegC. All four schemes capture both clear-sky and in-cloud ISS conditions. However, the clear-sky (in-cloud) ISS conditions are completely (significantly) limited to the RHi thresholds of the Cooper parameterization. In all of the simulations, ISS occurrence frequencies are higher by approximately 3-4 orders of magnitude at higher updraft speeds (greater than 1 m s(exp -1) than those at the lower updraft speeds when ice water content (IWC) greater than 0.01 gm(exp -3), while observations show smaller differences up to approximately 1-2 orders of magnitude. The simulated ISS also occurs less frequently at weaker updrafts and downdrafts than observed. These results indicate that the simulations have a greater dependence on stronger updrafts to maintain/generate ISS at higher IWC. At lower IWC (less than or equal or 0.01 gm(exp -3), simulations unexpectedly show lower ISS frequencies at stronger updrafts. Overall, the Thompson aerosol-aware scheme has the closest magnitudes and frequencies of ISS greater than 20% to the observations, and the modified Morrison has the closest correlations between ISS frequencies and vertical velocity at higher IWC and number density. The Cooper parameterization often generates excessive ice crystals and therefore suppresses the frequency and magnitude of ISS, indicating that it should be initiated at higher ISS (e.g.,lees than or equal to 25%).

D’Alessandro, John J.↗
NASA NTRS2017

Predicting Electron Population Characteristics in 2-D Using Multispectral Ground-Based Imaging

Ground-based imaging and in situ sounding rocket data are compared to electron transport modeling for an active inverted-V type auroral event. The Ground-to-Rocket Electrodynamics-Electrons Correlative Experiment (GREECE) mission successfully launched from Poker Flat, Alaska, on 3 March 2014 at 11:09:50 UT and reached an apogee of approximately 335 km over the aurora. Multiple ground-based electron-multiplying charge-coupled device (EMCCD) imagers were positioned at Venetie, Alaska, and aimed toward magnetic zenith. The imagers observed the intensity of different auroral emission lines (427.8, 557.7, and 844.6 nm) at the magnetic foot point of the rocket payload. Emission line intensity data are correlated with electron characteristics measured by the GREECE onboard electron spectrometer. A modified version of the GLobal airglOW (GLOW) model is used to estimate precipitating electron characteristics based on optical emissions. GLOW predicted the electron population characteristics with 20% error given the observed spectral intensities within 10 deg of magnetic zenith. Predictions are within 30% of the actual values within 20 deg of magnetic zenith for inverted-V-type aurora. Therefore, it is argued that this technique can be used, at least in certain types of aurora, such as the inverted-V type presented here, to derive 2-D maps of electron characteristics. These can then be used to further derive 2-D maps of ionospheric parameters as a function of time, based solely on multispectral optical imaging data.

multispectral ground-based imaging↗
NASA NTRS2019

Verification of the SMAP Level-4 Soil Moisture Analysis Using Rainfall Observations in Australia

Global, 3-hourly, 9-km resolution soil moisture estimates are available with a mean latency of ~2.5 days from the NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product. These estimates are based on the assimilation of SMAP radiometer brightness temperature (Tb) observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. Routine monitoring of the L4_SM system's assimilation diagnostics revealed occasionally large observation-minus-forecast Tb differences across eastern central Australia that resulted in large analysis increments (or adjustments) of the model forecast soil moisture. Because this region lacks in situ soil moisture measurements, we developed an alternative approach to assess the veracity of the soil moisture analysis increments in the L4_SM system. Using regional gauge-based precipitation data, we demonstrate that the L4_SM soil moisture increments are correlated with errors in the L4_SM precipitation forcing, suggesting that the SMAP Tb observations contribute valuable information to the L4_SM soil moisture estimates.

Reichle, R.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-18322-DND

MetOp-A satellite was launched on 19 October 2006 and MetOp-B was launched on 17 September 2013. Two satellites fly in complementary orbits and in a sun synchronous morning orbit passing over the Equator at the same local time 9:30 am. MetOp-B phased 50 minutes apart from MetOp-A. Presented here are the global surface IR emissivity spectra retrieved from IASI measurements observed from both MetOp-A and MetOp-B satellites. Inter-comparison of the emissivities obtained from MetOp-A and MetOp-B is performed to ensure the continuity of emissivity monitoring and its trend analysis. Effort on emissivity validation continues with available ground in-situ measurements and retrieval consistency check through radiative transfer model simulations. The spatial resolution of emissivity climatology atlas is now increased from 0.5 to 0.25 degrees latitude-longitude, and available to the community.

Daniel K Zhou↗
NASA NTRS2021

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Ghada Y.H. El Serafy↗
NASA NTRS2023

Polar Firn Properties in Greenland and Antarctica and Related Effects on Microwave Brightness Temperatures

In studying the mass balance of polar ice sheets, fluctuations of firn density near the surface is a major uncertainty. In this paper, we explore these variations at locations in the Greenland Ice Sheet and at the Dome C location in Antarctica. Borehole in situ measurements, Snow Radar echoes, microwave brightness temperatures, and modelling results from the Community firn model (CFM) are used. It is shown that firn density profiles can be represented using 3 processes: “long” and “short” length scale density variations and “refrozen layers”. Consistency with this description is observed in the dynamic range of airborne 0.5-2 GHz brightness temperatures and Snow Radar echo peaks in measurements performed in Greenland in 2017. Based on these insights, a new analytical partially coherent model is implemented to explain the microwave brightness temperatures using the three scale description of the firn. Short and long scale firn processes are modelled as a 3D continuous random medium with finite vertical and horizontal correlation lengths as opposed to past 1D random layered medium descriptions. Refrozen layers are described as deterministic sheets with planar interfaces, with the number of refrozen layer interfaces determined by radar observations. Firn density and correlation length parameters used in forward modelling to match measured 0.5-2 GHz brightness temperatures in Greenland show consistency with similar parameters in CFM predictions. Model predictions also are in good agreement with multi-angle 1.4 GHz vertically and horizontally polarized brightness temperature measured by the SMOS satellite at DOME C, Antarctica. This work shows that co-located active and passive microwave measurements can be used to infer polar firn properties that can be compared with predictions of the CFM. In particular, 0.5-2 GHz brightness temperature measurements are shown to be sensitive to long scale firn density fluctuations with density standard deviations in the range 0.01-0.06 g/cm^3 and vertical correlation lengths of 6-20 cm.

Haokui Xu↗
NASA NTRSDate not supplied

Evaluation of Aerosol Data Assimilation and Forecasts in the NASA GEOS Model during the ASIA-AQ Campaign

Fine particulate matter (PM2.5) poses significant risks to human health and the environment by penetrating the lungs and causing respiratory and cardiovascular diseases, making it crucial to understand its sources and behavior for effective air quality management. The Goddard Earth Observing System (GEOS) Forward Processing (FP) system model, operated by the Global Modeling and Assimilation Office (GMAO) at NASA's Goddard Space Flight Center, provides real-time weather and aerosol analyses and forecasts. In addition to meteorological data assimilation, the GEOS-FP system also assimilates aerosol using Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) and Aerosol Robotic Network (AERONET) AOD data. In this study, the aerosol data assimilation and forecasts performance of the GEOS-FP model were evaluated for predicting PM2.5 in Korea using observations from the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign. The ASIA-AQ campaign, an international collaborative field study initiative, aims to enhance understanding of local air quality issues and address common challenges in interpreting satellite data and air quality modeling. Conducted in South Korea from February 15 to March 13, 2024, during the high PM2.5 concentration winter season, this campaign provided extensive airborne and ground observations for intensive analysis of PM2.5 model simulations. We demonstrate how the assimilation runs and the forecasting performance of PM2.5 at 24-hour and 48-hour intervals vary. Additionally, we analyzed the differences and characteristics of PM2.5 composition in cases of long-range transport and local emissions. Using ASIA-AQ airborne data, we also examined the vertical profile of fine particulate matter. Through the intensive observations of this campaign, the GEOS model was assessed over South Korea using both in situ and airborne measurements to establish a baseline and identify priorities for future development.

Seunghee Lee↗
NASA NTRS2007

Implementation of In-Situ Impedance Techniques on a Full Scale Aero-Engine System

Determination of acoustic liner impedance for jet engine applications remains a challenge for the designer. Although suitable models have been developed that take account of source amplitude and the local flow environment experienced by the liner, experimental validation of these models has been difficult. This is primarily due to the inability of researchers to faithfully mimic the environment in jet engine nacelles in the laboratory. An in-situ measurement technique, one that can be implemented in an actual engine, is desirable so an accurate impedance can be determined for future modeling and quality control. This paper documents the implementation of such a local acoustic impedance measurement technique that is used under controlled laboratory conditions as well as on full scale turbine engine liner test article. The objective for these series of in-situ measurements is to substantiate treatment design, provide understanding of flow effects on installed liner performance, and provide modeling input for fan noise propagation computations. A series of acoustic liner evaluation tests are performed that includes normal incidence tube, grazing incidence tube, and finally testing on a full scale engine on a static test stand. Lab tests were intended to provide insight and guidance for accurately measuring the impedance of the liner housed in the inlet of a Honeywell Tech7000 turbofan. Results have shown that one can acquire very reasonable liner impedance data for a full scale engine under realistic test conditions. Furthermore, higher fidelity results can be obtained by using a three-microphone coherence technique that can enhance signal-to-noise ratio at high engine power settings. This research has also confirmed the limitations of this particular type of in-situ measurement. This is most evident in the installation of instrumentation and its effect on what is being measured.

Gaeta, R. J.↗
NASA NTRSDate not supplied

Validation of Remotely Sensed and Modeled Soil Moisture at Forested and Unforested Sites

Soil moisture is an important driver for forest ecosystems, influencing fire occurrence and extent, insect and pathogen impacts, and tree growth, which creates a need for regular, globally extensive soil moisture information that only satellite-based sensors or models can achieve. However, the reliability of soil moisture measurements in forests is not well understood due to a lack of suitable validation sites (especially relative to unforested ecosystems) and interference caused by high vegetation water content on remotely sensed measurements; although recent studies have started to address this gap [1], [2], [3], [4]. Here we validate the performance of multiyear remotely sensed (SMAP/Sentinel), remotely sensed data assimilation modelled (SMAP-L4), and modelled (NLDAS) surface and root zone (0-1 m) soil moisture datasets with data from in-situ sensors at 39 National Ecological Observatory Network (NEON) sites throughout the contiguous US. Due to differences in spatial resolution, NEON soil moisture (~0.2 km measurement zone) correlations were expected to be stronger with the SMAP/Sentinel product (3 km resolution) than with coarser resolution SMAP-L4 (9 km resolution) or NLDAS products (13 km resolution). However, given the sensitivity of satellite measurements to vegetation water content we expected a deterioration in the correlations based on remotely sensed measurements (SMAP/Sentinel and SMAP-L4) as aboveground biomass increased, whereas the model-based data (NLDAS) was expected to be largely insensitive to vegetation type. We recognize that the SMAP/Sentinel product was developed for unforested regions, therefore our application is outside its primary use case. Soil moisture is measured at up to 8 depths in five soil plots spaced up to 40 m apart at each NEON terrestrial site. Correlation parameters were calculated for the three remotely sensed and modelled data products relative to in-situ measurement following Entekhabi et al. [5]. The datasets comprised 94 (SMAP-L4), 28 (SMAP/Sentinel), and 106 (NLDAS) sites-years for surface soils and 13 (SMAP-L4) and 14 (NLDAS) site-years for the root zone. At unforested sites, the performance of the three remotely sensed and modelled data products was similar for surface soils (Table 1). For example, unbiased RMSD (ubRMSD), which SMAP uses as its primary performance metric [6], ranged from 0.05 to 0.06 m3 m-3 (Table 1), indicating the ability of all three products to track changes in soil moisture over time. The performance of the three products deteriorated at forested sites, however, while the difference in performance was modest for SMAP-L4 and NLDAS, the deterioration in SMAP/Sentinel performance was substantial. For instance, SMAP/Sentinel ubRMSD increased from 0.06 to 0.11 m3 m-3 and absolute mean difference (Abs MD; which includes measurement bias and spatial representativeness errors) increased from 0.06 to 0.16 m3 m-3, indicating both a reduction in ability to track temporal changes and absolute amounts of soil moisture in forest ecosystems. SMAP-L4 and NLDAS had lower unbiased RMSD for root zone (0-1 m) than surface soils at both forested and unforested sites (Tables 1 and 2; SMAP/Sentinel does not produce a root zone measurement). However, in most cases the correlation coefficient (r) was lower for the root zone than surface soils, suggesting the lower unbiased RMSD may be attributed to greater temporal stability of soil moisture in the root zone rather than improved data product performance. Mean difference and absolute mean difference, which encompass measurement bias and spatial representativeness errors, were greater for root zone than surface soils at unforested sites for both data products, but the opposite was generally true at forested sites. As with surface soils, there was relatively little change in the performance of SMAP-L4 and NLDAS between the unforested and forested sites. In summary, all three data products were able to adequately represent soil moisture at unforested sites, at least when aggregating across sites. However, while the performance of all three products deteriorated at forested sites, SMAP-L4 and NLDAS maintained sufficient performance to remain suitable for some use cases (ubRMSD <0.06 m3 m-3 and RMSD <0.13 m3 m-3). In contrast, the relatively poorer performance of the SMAP/Sentinel product at forested sites seems insufficient for most use cases (ubRMSD >0.1 m3 m-3 and RMSD >0.2 m3 m-3). We attribute the large reduction in the performance of the SMAP/Sentinel product in forests to its use of C-band wavelengths, which are particularly sensitive to vegetation interference, and apparently outweighed any gains provided by its higher spatial resolution. A combined SMAP/NISAR soil moisture product may provide improved performance relative to SMAP/Sentinel due to NISAR’s use of L-band wavelengths, which are less sensitive to vegetation (NISAR is scheduled for launch in early 2024).

Edward Ayres↗
NASA NTRS1994

Empirical convection models for northward IMF

It is clear that polar cap convection during times of northward Interplanetary Magnetic Field (IMF) is more structured and of lower mean speed than at times of southward IMF. This, coupled with the fact that the polar cap is smaller, means that empirical models are more difficult to construct with certainty. It is also clear that sunward flow deep in the polar cap is often observed, but its connection with the rest of the flow pattern is controversial. At present, empirical models are of three types: 'statistical' models wherein data from different days but with similar IMF conditions are averaged together; 'pattern recognition' models, which are built up by examining individually hundreds of passes to derive a 'typical' pattern which embodies features frequently observed; and 'assimilative' models, which use data of different types and from as many locations as possible, but all taken at the same time, in order to derive a snapshot (or series of snapshots) of the entire pattern. Each type of model has its own difficulties. Statistical models, by their very nature, smooth out flow features (e.g. the convection reversal, and the locus of sunward flow deep in the polar cap) which are not found at precisely the same invariant latitudes and magnetic local times on different days. Pattern recognition models are better at reproducing small-scale features, but the large-scale pattern can be a matter of interpretation. Assimilative models (such as AMIE) hold out the best hope for creating instantaneous, global convection patterns; however, the analysis technique tends to be most irregular (and least reliable) in the regions which are not well covered by in situ data. It appears that, at least at times, a four cell model with sunward flow at the highest and lowest latitudes, and antisunward flow in between, is consistent with the observations. At other times, the observations may be consistent with a two-cell convection pattern, but which includes significant meanders within the polar cap.

Moses, Julie J.↗
NASA NTRS2004

EOS Aqua AMSR-E Arctic Sea Ice Validation Program: Intercomparison Between Modeled and Measured Sea Ice Brightness Temperatures

During March 2003, an extensive field campaign was conducted near Barrow, Alaska to validate AQUA Advanced Microwave Scanning Radiometer (AMSR) sea ice products. Field, airborne and satellite data were collected over three different types of sea ice: 1) first year ice with little deformation, 2) first year ice with various amounts of deformation and 3) mixed first year ice and multi-year ice with various degrees of deformation. The validation plan relies primarily on comparisons between satellite, aircraft flights and ground-based measurements. Although these efforts are important, key aspects such as the effects of atmospheric conditions, snow properties, surface roughness, melt processes, etc on the sea ice algorithms are not sufficiently well understood or documented. To improve our understanding of these effects, we combined the detailed, in-situ data collection from the 2003 field campaign with radiance modeling using a radiative transfer model to simulate the top of the atmosphere AMSR brightness temperatures. This study reports on the results of the simulations for a variety of snow and ice types and compares the results with the National Oceanographic and Atmospheric Administration Environmental Technology Laboratory Polarimetric Scanning Radiometer (NOAA) (ETL) (PSR) microwave radiometer that was flown on the NASA P-3.

Stroeve, J.↗
NASA NTRS2021

Probabilistic Machine Learning Estimation of Ocean Mixed Layer Depth from Dense Satellite and Sparse In-Situ Observations

The ocean mixed layer plays an important role in the coupling between the upper ocean and atmosphere across a wide range of time scales. Estimation of the variability of the ocean mixed layer is therefore important for atmosphere-ocean prediction and analysis. The increasing coverage of in situ Argo profile data allows for an increasingly accurate analysis of the mixed layer depth (MLD) variability associated with deviations from the seasonal climatology. However, sampling rates are not sufficient to fully resolve subseasonal (<90 day) MLD variability. Yet, many multivariate observations-based analyses include implicit modeled subseasonal MLD variability. One analysis method is optimal interpolation of in situ data, but the interior analysis can be improved by leveraging surface data with regression or variational approaches. Here, we demonstrate how machine learning methods and satellite sea surface temperature, salinity, and height facilitate MLD estimation in a pilot study of two regions: the mid-latitude southern Indian and the eastern equatorial Pacific Oceans. We construct multiple machine learning architectures to produce weekly 1/2° gridded MLD anomaly fields (relative to a monthly climatology) with uncertainty estimates. We test multiple traditional and probabilistic machine learning techniques to compare both accuracy and probabilistic calibration. We validate our methodology by applying it to ocean model simulations. We find that incorporating sea surface data through a machine learning model improves the performance of spatiotemporal MLD variability estimation compared to optimal interpolation of Argo observations alone. These preliminary results are a promising first step for the application of machine learning to MLD prediction.

Machine Learning↗
NASA NTRS1980

Physical studies of the planetary rings

In this review paper, the physical properties of the Saturnian and Uranian rings as derived from ground-based observations are first discussed. Focus is then shifted to the study of the orbital dynamics of the ring particles. Numerical simulations of the evolutionary history of a system of colliding particles in differential rotation together with theoretical modeling of the inelastic collision processes are surveyed. In anticipation of the information returned from in situ measurements by space probes, interactions of the planetary rings with the interplanetary meteoroids and planetary magnetospheres are briefly considered. Finally, models of planetary ring origin are examined. In this connection, some recent work on the satellite resonant perturbation effects on the ring structure are also touched upon.

Ip, W.-H.↗
NASA NTRS1989

The Southern Hemisphere lower stratosphere during August and September 1987 - Analyses based on the United Kingdom Meteorological Office Global Model

This paper presents a series of meteorological analyses used to aid the interpretation of the in situ Airborne Antarctic Ozone Experiment (AAOE) observations obtained aboard the ER-2 and DC-8 aircraft and examines the basis and accuracy of the analytical procedure. Maps and sections of meteorological variables derived from the UK Meteorological Office Global Model are presented for ER-2 and DC-8 flight days. It is found that analyzed temperatures and winds are generally in good agreement with AAOE observations at all levels; minor discrepancies were evident only at DC-8 altitudes. Maps of potential vorticity presented on the 428-K potential temperature surface show that the vortex is essentially circumpolar, although there are periods when major distortions are apparent.

Mckenna, D. S.↗
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.↗
NASA NTRS2007

Using High Frequency Passive Microwave, A-train, and TRMM Data to Evaluate Hydrometer Structure in the NASA GEOS-5 Data Assimilation System

Validating water vapor and prognostic condensate in global models remains a challenging research task. Model parameterizations are still subject to a large number of tunable parameters; furthermore, accurate and representative in situ observations are very sparse, and satellite observations historically have significant quantitative uncertainties. Progress on improving cloud / hydrometeor fields in models stands to benefit greatly from the growing inventory ofA-Train data sets. ill the present study we are using a variety of complementary satellite retrievals of hydrometeors to examine condensate produced by the emerging NASA Modem Era Retrospective Analysis for Research and Applications, MERRA, and its associated atmospheric general circulation model GEOS5. Cloud and precipitation are generated by both grid-scale prognostic equations and by the Relaxed Arakawa-Schubert (RAS) diagnostic convective parameterization. The high frequency channels (89 to 183.3 GHz) from AMSU-B and MRS on NOAA polar orbiting satellites are being used to evaluate the climatology and variability of precipitating ice from tropical convective anvils. Vertical hydrometeor structure from the Tropical Rainfall Measuring Mission (TRMM) and CloudSat radars are used to develop statistics on vertical hydrometeor structure in order to better interpret the extensive high frequency passive microwave climatology. Cloud liquid and ice water path data retrieved from the Moderate Resolution Imaging Spectroradiometer, MODIS, are used to investigate relationships between upper level cloudiness and tropical deep convective anvils. Together these data are used to evaluate cloud / ice water path, gross aspects of vertical hydrometeor structure, and the relationship between cloud extent and surface precipitation that the MERRA reanalysis must capture.

Robertson, Franklin↗