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NASA NTRS2006

Observations over Hurricanes from the Ozone Monitoring Instrument

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

Joiner, J.↗
NASA NTRS2006

Chemical Observations of a Polar Vortex Intrusion

An intrusion of vortex edge air in D the interior of the Arctic polar vortex was observed on the January 31,2005 flight of the NASA DC-8 aircraft. This intrusion was identified as anomalously high values of ozone by the AROTAL and DIAL lidars. Our analysis shows that this intrusion formed when a blocking feature near Iceland collapsed, allowing edge air to sweep into the vortex interior. along the DC-8 flight track also shows the intrusion in both ozone and HNO3. Polar Stratospheric Clouds (PSCs) were observed by the DIAL lidar on the DC-8. The spatial variability of the PSCs can be explained using MLS HNO3 and H2O observations and meteorological analysis temperatures. We also estimate vortex denitrification using the relationship between N2O and HNO3. Reverse domain fill back trajectory calculations are used to focus on the features in the MLS data. The trajectory results improve the agreement between lidar measured ozone and MLS ozone and also improve the agreement between the HNO3 measurements PSC locations. The back trajectory calculations allow us to compute the local denitrification rate and reduction of HCl within the filament. We estimate a denitrification rate of about lO%/day after exposure to below PSC formation temperature. Analysis of Aura MLS observations made

Schoeberl, M. R.↗
NASA NTRS2006

Constellation Operations: Lessons Learned For Future Exploration

The Earth science community has long advocated placing numerous instruments in space to study the Earth and its environment. Space agencies from many countries have responded to this call with a wide range of orbiting satellites. Scientists also envisioned placing some satellites in constellations, to enable diverse remote sensing instruments to observe the same part of the Earth (or its atmosphere) at about the same time, thereby increasing the opportunities for coincident science observations. The Earth Science Afternoon Constellation is answering this call, but there have been unique challenges on the way to its deployment. Currently, the Afternoon Constellation is to comprise six satellites. Three are currently on orbit: NASA's Earth Observing System (EOS)-Aqua (2002) and EOS-Aura (2004), and CNES's Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) (2004). Two more satellites, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Cloudsat, are to be jointly launched in late 2005, followed by the Orbiting Carbon Observatory (OCO) in 2008. The Afternoon Constellation is unlike most satellite constellations in that: 1) It is not a homogenous mix of identical satellites; rather it comprises several satellites with complementary observational capabilities; 2) The satellites are not spaced around the Earth to provide instantaneous, global coverage (as for a communications satellite constellation); rather they orbit in close proximity so observations occur at about the same time over approximately the same region; and 3) Lastly, the satellites are not managed and controlled by one organization; rather the list of organizations is diverse: CNES in France, NASA Centers at Goddard, Langley, and the Jet Propulsion Laboratory, and the US Air Force facility in New Mexico. The PARASOL launch and early orbit (L&EO) phase proved to be a learning experience for constellation members (including Constellation management). Prior to launch, all members signed an operations coordination document that spelled out basic requirements for keeping the constellation safe and resolving non-nominal events. Once PARASOL reached orbit and the mission teams gained experience using the newly-developed constellation monitoring tools, it became clear that some of the guidelines in the signed agreements had to be adjusted. This paper presents the L&EO lessons learned and how they were used to prepare for the next phase - the period following the CloudSat/CALIPSO launch.

Kelly, Angelita C.↗
NASA NTRS2006

Future NASA Earth Science Missions

Following on the successful launch of Aura in July 2004, NASA will continue to add to the A-train with the spring 2006 launch of the CALIPSO and Cloudsat missions, followed by the fall 2008 launch of the Orbiting Carbon Observatory (OCO). The CALIPSO mission has three nadir-viewing instruments: a cloud-aerosol lidar for measuring aerosol and cloud height and properties, a 3-channel thermal infrared imaging radiometer, and a wide field cloud camera. The Cloudsat mission has a 94 GHz cloud profiling radar, returning cloud structure vs. height profiles. Orbiting Carbon Observatory (OCO) is a mission focused on precision measurements of total column CO2 using reflected sunlight. These missions and how they relate to the other parts of the A-train will be presented. A brief report from a NASA workshop on future atmospheric science missions will also be presented.

Gleason, James↗
NASA NTRS2005

Denitrification in the Arctic mid-winter 2004/2005 observed by airborne submillimeter radiometry

We present measurements of unusually low mixing ratios of HNO3 in the exceptionally cold Arctic vortex of late-January and early-February 2005. The measurements were obtained by the airborne submillimeter radiometer ASUR during the polar aura validation experiment (PAVE). The distribution of HNO3 inside the vortex reaches minima below 4 ppbv around 22 km altitude and maxima above 13 ppbv around 16 km altitude, with a considerable spatial variability.

measurements↗
NASA NTRS2006

Realistic Covariance Prediction For the Earth Science Constellations

Routine satellite operations for the Earth Science Constellations (ESC) include collision risk assessment between members of the constellations and other orbiting space objects. One component of the risk assessment process is computing the collision probability between two space objects. The collision probability is computed via Monte Carlo techniques as well as numerically integrating relative probability density functions. Each algorithm takes as inputs state vector and state vector uncertainty information for both objects. The state vector uncertainty information is expressed in terms of a covariance matrix. The collision probability computation is only as good as the inputs. Therefore, to obtain a collision calculation that is a useful decision-making metric, realistic covariance matrices must be used as inputs to the calculation. This paper describes the process used by NASA Goddard's Earth Science Mission Operations Project to generate realistic covariance predictions for three of the ESC satellites: Aqua, Aura, and Terra

Duncan, Matthew↗
NASA NTRS2006

Interannual and Seasonal Variability of the Tropopause Layer over the Tropical Americas

This study explores the thermodynamic and convective characteristics of the Tropical Tropopause Layer (TTL) over the Tropical Americas using multi-platform measurements collected during the last five years. This region is chosen for the following reasons: (i) it becomes the second most dominant source of air to the TTL, (ii) it exhibits the largest seasonal increase in percent contribution to stratospheric moisture, (iii) it has the warmest tropical tropopause temperatures, and (iv) it can be influenced by midlatitude and subtropical air masses that are transported equatorward by the upper-level circulation associated with the North American Monsoon. We examine the interannual and seasonal variability of water vapor, ozone, and temperature using aircraft data collected aboard the WB-57, satellite data from the Aura-MLS and Aqua-AIRS instruments, and GPS radio occultation measurements from the CHAMP satellite. We also examine the vertical extent and frequency of convection in the region using data from TRMM. In addition, we perform seasonal trajectory calculations to elucidate the origin and fate of air masses found in our region of interest.

Pittman, Jasna V.↗
NASA NTRS2006

A-Train Data Depot: Integrating and Visualizing Atmospheric Measurements Along the A-Train Tracks

The succession of US and international satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000) The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot, to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The A-Train Data Depot (ATDD) will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth s Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archwing for fast data access, and Cooperative Institute for Research in the Atmosphere (CRA) data co-registration tools. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be followed by associated measurements from MLS, OMI, HIRDLS, and TES. Given the independent nature of instrument/platform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be discussed. The project s resulting visualizations and analysis illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗
NASA NTRS2006

Establishment and Implementation of a Close Approach Evaluation and Avoidance Process for Earth Observing System Missions

In the fall of 2004, the Earth Science Mission Operations Project tasked the Goddard Space Flight Center (GSPC) Flight Dynamics Analysis Branch with establishment of a process to protect the high-value Earth Observing System (EOS) missions (Terra, Aqua, and Aura) from close approaches with space debris and other orbiting objects. An agreement between GSFC and the United States Strategic Command was put in place so that close approach predictions would be routinely generated. This paper describes the ESMO conjunction assessment process for the EOS satellites. Process details, including tools and algorithms developed, are discussed. Particular details for a predicted close approach between Terra and a piece of space debris that resulted in the execution of a debris avoidance maneuver are included. This close approach example is described in detail fiom the first screening identification through execution of the mitigation maneuver to illustrate both the process and lessons learned fiom its implementation.

Newman, Lauri↗
NASA NTRS2006

Development of a Nonlinear Probability of Collision Tool for the Earth Observing System

The Earth Observing System (EOS) spacecraft Terra, Aqua, and Aura fly in constellation with several other spacecraft in 705-kilometer mean altitude sun-synchronous orbits. All three spacecraft are operated by the Earth Science Mission Operations (ESMO) Project at Goddard Space Flight Center (GSFC). In 2004, the ESMO project began assessing the probability of collision of the EOS spacecraft with other space objects. In addition to conjunctions with high relative velocities, the collision assessment method for the EOS spacecraft must address conjunctions with low relative velocities during potential collisions between constellation members. Probability of Collision algorithms that are based on assumptions of high relative velocities and linear relative trajectories are not suitable for these situations; therefore an algorithm for handling the nonlinear relative trajectories was developed. This paper describes this algorithm and presents results from its validation for operational use. The probability of collision is typically calculated by integrating a Gaussian probability distribution over the volume swept out by a sphere representing the size of the space objects involved in the conjunction. This sphere is defined as the Hard Body Radius. With the assumption of linear relative trajectories, this volume is a cylinder, which translates into simple limits of integration for the probability calculation. For the case of nonlinear relative trajectories, the volume becomes a complex geometry. However, with an appropriate choice of coordinate systems, the new algorithm breaks down the complex geometry into a series of simple cylinders that have simple limits of integration. This nonlinear algorithm will be discussed in detail in the paper. The nonlinear Probability of Collision algorithm was first verified by showing that, when used in high relative velocity cases, it yields similar answers to existing high relative velocity linear relative trajectory algorithms. The comparison with the existing high velocity/linear theory will also be used to determine at what relative velocity the analysis should use the new nonlinear theory in place of the existing linear theory. The nonlinear algorithm was also compared to a known exact solution for the probability of collision between two objects when the relative motion is strictly circular and the error covariance is spherically symmetric. Figure I shows preliminary results from this comparison by plotting the probabilities calculated from the new algorithm and those from the exact solution versus the Hard Body Radius to Covariance ratio. These results show about 5% error when the Hard Body Radius is equal to one half the spherical covariance magnitude. The algorithm was then combined with a high fidelity orbit state and error covariance propagator into a useful tool for analyzing low relative velocity nonlinear relative trajectories. The high fidelity propagator is capable of using atmospheric drag, central body gravitational, solar radiation, and third body forces to provide accurate prediction of the relative trajectories and covariance evolution. The covariance propagator also includes a process noise model to ensure realistic evolutions of the error covariance. This paper will describe the integration of the nonlinear probability algorithm and the propagators into a useful collision assessment tool. Finally, a hypothetical case study involving a low relative velocity conjunction between members of the Earth Observation System constellation will be presented.

McKinley, David P.↗
NASA NTRS2006

Realistic Covariance Prediction for the Earth Science Constellation

Routine satellite operations for the Earth Science Constellation (ESC) include collision risk assessment between members of the constellation and other orbiting space objects. One component of the risk assessment process is computing the collision probability between two space objects. The collision probability is computed using Monte Carlo techniques as well as by numerically integrating relative state probability density functions. Each algorithm takes as inputs state vector and state vector uncertainty information for both objects. The state vector uncertainty information is expressed in terms of a covariance matrix. The collision probability computation is only as good as the inputs. Therefore, to obtain a collision calculation that is a useful decision-making metric, realistic covariance matrices must be used as inputs to the calculation. This paper describes the process used by the NASA/Goddard Space Flight Center's Earth Science Mission Operations Project to generate realistic covariance predictions for three of the Earth Science Constellation satellites: Aqua, Aura and Terra.

Duncan, Matthew↗
NASA NTRS2007

Effects of the 2004 El Nino on Tropospheric Ozone and Water Vapor

The global effects of the 2004 El Nino on tropospheric ozone and H2O based on Aura OM1 and MLS measurements are analyzed. Although it was a weak El Nino from a historical perspective, it produced significant changes in these parameters in tropical latitudes. Tropospheric ozone increased by 10-20% over most of the western Pacific region and decreased by about the same amount over the eastern Pacific region. H2O in the upper troposphere showed similar changes but with opposite sign. These zonal changes in tropospheric ozone and H2O are caused by the eastward shift in the Walker circulation in the tropical pacific region during El Nino. For the 2004 El Nino, biomass burning did not have a significant effect on the ozone budget in the troposphere unlike the 1997 El Nino. Zonally averaged tropospheric column ozone did not change significantly either globally or over the tropical and subtropical latitudes.

Chandra, S.↗
NASA NTRS2006

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000). The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be foilowed by associated measurements from TVILS, =MI, HIRDLS, sad TES. Given the independent nature of instrumentlplatform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗
NASA NTRS2007

Three Way Comparison between Two OMI/Aura and One POLDER/PARASOL Cloud Pressure Products

The cloud pressures determined by three different algorithms, operating on reflectances measured by two space-borne instruments in the "A" train, are compared with each other. The retrieval algorithms are based on absorption in the oxygen A-band near 760 nm, absorption by a collision induced absorption in oxygen near 477nm, and the filling in of Fraunhofer lines by rotational Raman scattering. The first algorithm operates on data collected by the POLDER instrument on board PARASOL, while the latter two operate on data from the OMI instrument on board Aura. The satellites sample the same air mass within about 15 minutes. Using one month of data, the cloud pressures from the three algorithms are found to show a similar behavior, with correlation coefficients larger than 0.85 between the data sets for thick clouds. The average differences in the cloud pressure are also small, between 2 and 45 hPa, for the whole data set. For optically thin to medium thick clouds, the cloud pressure the distribution found by POLDER is very similar to that found by OMI using the O2 - O2 absorption. Somewhat larger differences are found for very thick clouds, and we hypothesise that the strong absorption in the oxygen A-band causes the POLDER instrument to retrieve lower pressures for those scenes.

Sneep, M.↗
NASA NTRS2006

Algorithm for NO2 Vertical Column Retrieval from the Ozone Monitoring Instrument

We describe the operational algorithm for the retrieval of stratospheric, tropospheric, and total column densities of nitrogen dioxide NO2 from earthshine radiances measured by the Ozone Monitoring Instrument (OMI), aboard the EOS-Aura satellite. The algorithm uses the DOAS method for the retrieval of slant column NO densities. Air mass factors (AMFs) calculated from a stratospheric NO2 profile are used to make initial estimates of the vertical column density. Using data collected over a 24-h period, a smooth estimate of the global stratospheric field is constructed. Where the initial vertical column densities exceed the estimated stratospheric field, we infer the presence of tropospheric NO2, and recalculate the vertical column density (VCD) using an AMF calculated from an assumed tropospheric NO2 profile. The parameters that control the operational algorithm were selected with the aid of a set of data assembled from stratospheric and tropospheric chemical transport models. We apply the optimized algorithm to OMI data and present global maps of NO2 VCDs for the first time.

Bucsela, Eric J.↗
NASA NTRS2006

First Results from the OMI Rotational Raman Scattering Cloud Pressure Algorithm

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

Joiner, Joanna↗