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NASA NTRS2016

Calibration Improvements in the Detector-to-Detector Differences for the MODIS Ocean Color Bands

The Moderate Resolution Imaging Spectroradiometer (MODIS), a major instrument within NASAs Earth Observation System missions, has operated for over 16 and 14 years onboard the Terra and Aqua satellites, respectively. Its reflective solar bands (RSB) covering a spectral range from 0.4 to 2.1 micrometers are primarily calibrated using the on-board solar diffuser(SD), with its on-orbit degradation monitored using the Solar Diffuser Stability Monitor. RSB calibrations are supplemented by near-monthly lunar measurements acquired from the instruments space-view port. Nine bands (bands 8-16) in the visible to near infrared spectral range from 0.412 to 0.866 micrometers are primarily used for ocean color observations.During a recent reprocessing of ocean color products, performed by the NASA Ocean Biology Processing Group, detector-to-detector differences of up to 1.5% were observed in bands 13-16 of Terra MODIS. This paper provides an overview of the current approach to characterize the MODIS detector-to-detector differences. An alternative methodology was developed to mitigate the observed impacts for bands 13-16. The results indicated an improvement in the detector residuals and in turn are expected to improve the MODIS ocean color products. This paper also discusses the limitations,subsequent enhancements, and the improvements planned for future MODIS calibration collections.

Li, Yonghong↗

NASA NTRS2016

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

soil moisture↗

NASA NTRS2015

Improving AIRS Radiance Spectra in High Contrast Scenes Using MODIS

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in 2378 channels ranging in wavelength from 3.7-15.4 microns with spectral resolution of better than 1200, and spatial resolution of 13.5 km with global daily coverage. The AIRS is designed to measure temperature and water vapor profiles for improvement in weather forecast accuracy and improved understanding of climate processes. As with most instruments, the AIRS Point Spread Functions (PSFs) are not the same for all detectors. When viewing a non-uniform scene, this causes a significant radiometric error in some channels that is scene dependent and cannot be removed without knowledge of the underlying scene. The magnitude of the error depends on the combination of non-uniformity of the AIRS spatial response for a given channel and the non-uniformity of the scene, but is typically only noticeable in about 1% of the scenes and about 10% of the channels. The current solution is to avoid those channels when performing geophysical retrievals. In this effort we use data from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument to provide information on the scene uniformity that is used to correct the AIRS data. For the vast majority of channels and footprints the technique works extremely well when compared to a Principal Component (PC) reconstruction of the AIRS channels. In some cases where the scene has high inhomogeneity in an irregular pattern, and in some channels, the method can actually degrade the spectrum. Most of the degraded channels appear to be slightly affected by random noise introduced in the process, but those with larger degradation may be affected by alignment errors in the AIRS relative to MODIS or uncertainties in the PSF. Despite these errors, the methodology shows the ability to correct AIRS radiances in non-uniform scenes under some of the worst case conditions and improves the ability to match AIRS and MODIS radiances in non-uniform scenes.

spatial↗

NASA NTRS2017

Improving X-Ray Optics via Differential Deposition

Differential deposition, a post-fabrication figure correction technique, has the potential to significantly improve the imaging quality of grazing-incidence X-ray optics. DC magnetron sputtering is used to selectively coat the mirror in order to minimize the figure deviations. Custom vacuum chambers have been developed at NASA MSFC that will enable the implementation of the deposition on X-ray optics. A factor of two improvement has been achieved in the angular resolution of the full-shell X-ray optics with first stage correction of differential deposition. Current efforts are focused on achieving higher improvements through efficient implementation of differential deposition.

differential deposition grazing↗

NASA NTRS2017

Improvement of Reynolds-Stress and Triple-Product Lag Models

The Reynolds-stress and triple product Lag models were created with a normal stress distribution which was defined by the accepted 4:3:2 distribution of streamwise, spanwise and wall normal stresses, and a ratio of τ(sub w) = 0.3k in the log layer region of high Reynolds number flat plate flow, which implies R11(+) = 4/(9/2)∗.3 ≈ 2.96. More recent measurements show a more complex picture of the log layer region at high Reynolds numbers. The first cut at improving these models along with the direction for future refinements is described. Comparison with recent high Reynolds number data shows areas where further work is needed, but also shows inclusion of the modeled turbulent transport terms improve the prediction where they influence the solution. Additional work is needed to develop a model that better matches experiments, but there is significant improvement in many of the details of the log layer behavior.

Fluid dynamics↗

NASA NTRS2017

Exposing the Strategies that Can Reduce the Obstacles: Improving the Science User Experience

It is now well established that pursuing generic solutions to what seem are common problems in Earth science data access and use can often lead to disappointing results for both system developers and the intended users. This presentation focuses on real-world experience of managing a large and complex data system, NASAs Earth Science Data and Information Science System (EOSDIS), whose mission is to serve both broad user communities and those in smaller niche applications of Earth science data and services. In the talk, we focus on our experiences with known data user obstacles characterizing EOSDIS approaches, including various technological techniques, for engaging and bolstering, where possible, user experiences with EOSDIS. For improving how existing and prospective users discover and access NASA data from EOSDIS we introduce our cross-archive tool: Earthdata Search. This new search and order tool further empowers users to quickly access data sets using clever and intuitive features. The Worldview data visualization tool is also discussed highlighting how many users are now performing extensive data exploration without necessarily downloading data. Also, we explore our EOSDIS data discovery and access webinars, data recipes and short tutorials, targeted technical and data publications, user profiles and social media as additional tools and methods used for improving our outreach and communications to a diverse user community. These efforts have paid substantial dividends for our user communities by allowing us to target discipline specific community needs. The desired take-away from this presentation will be an improved understanding of how EOSDIS has approached, and in several instances achieved, removing or lowering the barriers to data access and use. As we look ahead to more complex Earth science missions, EOSDIS will continue to focus on our user communities, both broad and specialized, so that our overall data system can continue to serve the needs of science and applications users.

communications↗

NASA NTRS2018

Orion Heat Shield Manufacturing Producibility Improvements for the EM-1 Flight Test Program

This paper describes how the ORION program is incorporating improvements in the heat shield design and manufacturing processes reducing programmatic risk and ensuring crew safety in support of NASA's Exploration missions. The approach for the EFT-1 heat shield utilized a low risk Apollo heritage design and manufacturing process using an Avcoat TPS ablator with a honeycomb substrate to provide a one piece heat shield to meet the mission re-entry heating environments. The EM-1 mission will have additional flight systems installed to fly to the moon and return to Earth. Heat shield design and producibility improvements have been incorporated in the EM-1 vehicle to meet deep space mission requirements. The design continues to use the Avcoat material, but in a block configuration to enable improvements in consistant and repeatable application processes using tile bonding experience developed on the Space Shuttle Transportation System Program.

Producibility↗

NASA NTRS2018

The SMAP Level-4 ECO Project: Improving Terrestrial Flux Estimates Through Coupled Hydrology-Vegetation Data Assimilation

Simulations of hydrologic and vegetation states as well as water, energy and carbon fluxes from the land surface to the atmosphere are crucial for a wide range of applications, including agricultural advisories, forecasts of (short-term) atmospheric behavior and seasonal weather predictions including forecasts of extreme events, such as heatwaves or droughts. The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Eco-Hydrology (L4-ECO) project aims to improve modeled estimates of the terrestrial water, energy and carbon fluxes and states by developing a fully-coupled hydrology-vegetation data assimilation system. This system is developed around the NASA Goddard Earth Observing System (GEOS) Catchment-CN land surface model, which combines land hydrology and energy balance components of the GEOS Catchment model with dynamic vegetation components of the Community Land Model version 4. Catchment-CN fully couples the terrestrial water, energy and carbon cycles, allowing feedbacks from the land hydrology to the biosphere and vice versa.Here, we implement a calibration of the Catchment-CN vegetation parameterization against observations of the fraction of absorbed photosynthetically active radiation (FPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve the model's standalone skill. Later, the DA algorithm used to produce the SMAP L4 soil moisture product will be adapted to Catchment-CN to assimilate SMAP brightness temperatures and inform the model's land hydrology component. Finally, the DA system will be further extended to assimilate MODIS FPAR observations in order to constrain the model's dynamic vegetation component.In this presentation, we demonstrate that the Catchment-CN parameter calibration leads to more realistic vegetation simulations and reduces the root mean squared error between modeled and observed vegetation states across the model's various plant functional types. We also show that the assimilation of SMAP observations is able to improve the average correlation, bias and unbiased RMSE between the modeled surface and root zone soil moisture estimates, and ground observations from the SMAP core validation sites.

Kolassa, Jana↗

NASA NTRS2018

Improving AIRS NRT Imagery for the Enhancement of Visualization Services in LANCE

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of processing, archiving, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002. AIRS provides data enabling global observations of the atmospheric state. The GES DISC provides service to both AIRS standard products and Near Real-time (NRT) products. The AIRS NRT product is one important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). The LANCE processing of the AIRS NRT product and the generation of the imagery are performed at the GES DISC. The AIRS NRT imagery are generated by mosaicking and mapping the available AIRS 6-minute retrieval granules to a global cylindrical projection. The images are constantly refreshed when new granules are produced. The AIRS NRT Viewer and LANCE Worldview provide visualization services to online users for AIRS NRT imagery. The imagery include atmospheric temperature, humidity, precipitation, Dust Score, CO, and SO2. The AIRS Applications Development Team at NASA JPL developed a new orbit-based algorithm and software to improve the AIRS NRT imagery. The GES DISC is collaborating with the AIRS Applications Development Team for the implementation of the new algorithm and software. The improvements include image quality, new color palettes, and variable changes. In this presentation, we will detail the improvements and demonstrate visualization of the new imagery.

Ding, Feng↗

NASA NTRS2018

An Improved UAV-Based Fog Collector for Local-Scale Aerobiological Sampling

The use of unmanned air vehicles (UAVs) to passively collect fog for microbiological analysis is being investigated at NASA Ames, contributing to our understanding of the dynamics and limits of the biosphere. Current improvements to a preliminary payload design include physically modifying the mesh of the passive impactor collection unit (PICU) to increase fog-capture efficiency and a quick- mounting system to improve sample turnaround and contamination control. Increasing the water-capture efficiency of the PICU involved changing the surface roughness of the polypropylene mesh by abrasive sanding. Four scale models of the PICU were created, with three of those models sanded with 80-, 150-, and 240-grit sand paper for a minimum of thirty seconds on each side. Each mesh was individually tested in a fog-simulation chamber to measure collection efficiency. Tests showed that sanding the mesh will increase the water-capture efficiency by at least 3-fold for the 150- and 240-grit. Next steps are to determine the scaling laws and minimum amount of exposure time as a function of the fog density, to acquire enough microorganisms for analysis; a light-weight ground module for the PICU has been developed to allow rapid, easy field testing. Developing a mounting system that will ensure sterile deployment, as well as prompt changes of PICUs, for collection of fog water, utilized computational fluid dynamics (CFD) for the UAV to ensure that the location of the impactors will not be contaminated by particulates in the UAV downwash. The original design allowed the impactors to remain within sterile packaging until mounted on the UAV but did not address the concerns of contamination from aerodynamic ground effects and particulate lofting during takeoff. Design for a raised launch pad would allow for the sterile PICU to be attached to UAV and launched from outside the region of projected particulate lofting. California coastal sites have been scouted for appropriate testing locations. The improvements to the PICU design and operations will allow for multiple sampling points within a single fog event. The returned fog samples will undergo ion chromatography, qPCR, ATP quantification, and other tests to characterize microbial species and relevant biochemistry.

Wong, Amber↗

NASA NTRS2018

The SMAP Level-4 ECO Product - Phase 1: Improving Vegetation Simulations Through Observation-Driven Parameter Estimation

Simulations of hydrological fields as well as water, energy and carbon fluxes from the land surface to the atmosphere are crucial for a wide range of applications, including agricultural advisories, forecasts of (short-term) atmospheric behavior and seasonal weather predictions including forecasts of extreme events, such as heatwaves or droughts. The NASA Soil Moisture Active Passive (SMAP) mission Level-4 (L4) Eco-Hydrology (ECO) project aims to improve modeled estimates of the terrestrial water, energy and carbon fluxes and states by developing a fully-coupled hydrology-vegetation data assimilation (DA) algorithm. The DA system is developed for the NASA Goddard Earth Observing System version 5 (GEOS-5) Catchment-CN land surface model, which combines land hydrology components of the GEOS-5 Catchment model with dynamic vegetation components of the Community Land Model version 4. Catchment-CN fully couples the terrestrial water, energy and carbon cycles, allowing feedbacks from the land hydrology to the biosphere and vice versa. For SMAP L4 ECO a calibration of the Catchment-CN vegetation parameterization against observations of the fraction of absorbed photosynthetically active radiation (FPAR) from the Moderate Resolution Imaging Spectroradiometer (MODIS) is implemented to improve the model's standalone skill. Next, the DA algorithm used to produce the SMAP L4 soil moisture product is adapted to Catchment-CN to assimilate SMAP brightness temperatures and inform the model's land hydrology component. The DA system is further extended to assimilate MODIS FPAR observations in order to constrain the model's dynamic vegetation component. In this presentation, we demonstrate that the Catchment-CN parameter calibration leads to more realistic vegetation simulations and reduces the root mean squared error between modeled and observed vegetation states across the model's various plant functional types. We also show that the assimilation of SMAP observations is able to improve the average correlation, bias and unbiased RMSE between the modeled surface and root zone soil moisture estimates, and ground observations from the SMAP core validation sites.

Kolassa, J.↗

NASA NTRS2019

Potential Improvements to the Nuclear Safety and Launch Approval Process for Nuclear Reactors Utilized for Space Power and Propulsion Applications

This study examines potential improvements that could be made to the nuclear safety and launch approval process for fission reactors to reduce the associated uncertainties in cost and schedule while continuing to ensure public safety and environmental protection. It concentrates on the launch approval and mission safety of fission power and propulsion applications of nuclear energy. Improvements to the launch approval process for radioisotope power systems (RPSs) are being considered elsewhere but are acknowledged throughout the report. The study considered technical, process, and organizational improvements to the launch approval processes. The study exclusively evaluated reactors that would not be started up prior to achieving a “sufficiently high orbit,” per United Nations (UN) Resolution 47/68.Potential criticality accidents were considered that could occur during a launch failure or abort or during reentry. Numerous scenarios were examined that might involve one or more Earth flybys as well as potential transportation missions that could intentionally return an active, or previously active fission reactor to Earth orbit. The Study Group was guided in its deliberations according to a number of fundamental principles. These included the paramount importance of adequate and appropriate levels of public safety and environmental protection as well as the importance of the inclusion of independent scientific, engineering, and safety reviews of the applications and proposals as a critical part of the process. Also considered was the need for the development of launch approval processes that might be different, depending upon the source of the application for launch approval, whether it be derived as a governmental launch, a commercial launch, or a hybrid/combination of the two. It is clear that all launches of nuclear reactors into space should have similar safety requirements; however, the safety review effort and the details of the analysis that are required should be commensurate with the potential hazards and the actual risk, which may differ based on the reactor design and its intended purpose. Finally, the study aimed at ensuring that whatever processes and procedures are developed should maximize the sufficiency, simplicity, and transparency of the processes. The Study Group reached five Conclusions and makes thirteen Recommendations. The Conclusions and Recommendations presented here are extensions of those presented previously in other studies. This report attempts to add specificity to the actions that need to be taken in order to move forward with successful space fission reactor programs. Without action to address the perceived and real problems in the launch approval process, designers and mission managers will be reluctant to commit the resources necessary to make space fission reactors a reality.

Camp, Allen↗

NASA NTRS2018

TRMM Version 8 Reprocessing Improvements and Incorporation into the GPM Data Suite

The National Aeronautics and Space Administration (NASA) has always included data reprocessing as a major component of every science mission. A final reprocessing is typically a part of mission closeout (known as phase F).The Tropical Rainfall Measuring Mission (TRMM) is currently in phase F, and NASA is preparing for the last reprocessing of all the TRMM precipitation data as part of the closeout. This reprocessing includes improvements in calibration of both the TRMM Microwave Imager (TMI) and the TRMM Precipitation Radar (PR). An initial step in the version 8 reprocessing is the improvement of geolocation. The PR calibration is being updated by the Japan Aerospace Exploration Agency (JAXA) using data collected as part of the calibration of the Dual-Frequency Precipitation Radar (DPR) on the Global Precipitation Measurement (GPM) Core Observatory. JAXA undertook a major effort to ensure TRMM PR and GPM Ku-band calibration is consistent. A major component of the TRMM version 8 reprocessing is to create consistent retrievals with the GPM version 05 (V05) retrievals. To this end, the TRMM version 8 reprocessing uses retrieval algorithms based on the GPM V05 algorithms. This approach ensures consistent retrievals from December 1997 (the beginning of TRMM) through the current ongoing GPM retrievals. An outcome of this reprocessing is the incorporation of TRMM data products into the GPM data suite. Incorporation also means that GPM file naming conventions and reprocessed TRMM data carry the V05 data product version. This paper describes the TRMM version 8 reprocessing, focusing on the improvements in TMI level 1 products.

Stocker, E. F.↗

NASA NTRS2019

Assimilation of Satellite Soil Moisture for Improved Atmospheric Reanalyses

A newly developed, weakly coupled land and atmosphere data assimilation system for NASA’s Global Earth Observing System model is presented, and used to demonstrate the benefit of assimilating satellite soil moisture into an atmospheric reanalysis. Specifically, Advanced Scatterometer and Soil Moisture Ocean Salinity soil moisture retrievals are assimilated into a system that uses the same model, atmospheric assimilation system, and atmospheric observations as the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The atmosphere is sensitive to soil moisture only under certain conditions. Hence, while the globally averaged model improvements were small, regionally, the soil moisture assimilation induced some substantial improvements. For example, in a large region spanning from western Europe across southern Russia, the soil moisture assimilation decreased the RMSE against independent station observations of daily maximum 2-m temperature (T(sup 2m, sub max)) by up to 0.4 K, and of 2-m specific humidity (q(exp 2m)) by up to 0.5 g/kg. Over all available stations, the mean T(sup 2m, sub max) RMSE was reduced from 2.82 to 2.79 K, while the mean q(exp 2m) RMSE was reduced from 1.25 to 1.20 g/kg. The soil moisture assimilation also reduced the mean RMSE across 29 flux tower sites from 34.2 to 32.6 Wm(exp −2) for latent heating, and from 37.7 to 36.5 Wm(exp −2) for sensible heating. For all variables evaluated, the soil moisture assimilation improved the model at monthly to seasonal, rather than daily, time scales. Based on the above experiments, it is recommended that satellite soil moisture be assimilated into future reanalyses, including the follow-on to MERRA-2.

Clara Draper↗

NASA NTRS2019

Improvements to an Explicit Algebraic Stress Model for Turbulent Jet Mixing Predictions

Modifications to key coefficients in a k − E based explicit algebraic stress model (EASM) are examined with the objective of improving the prediction of turbulent jet flows. The pressure strain coefficient, C2 and the turbulent diffusion coefficients, σk and σE were investigated. For a series of benchmark subsonic jets at heated and unheated conditions, lowering C2 from the default value of 0.36 to 0.10 resulted in a significant improvement in the jet mixing, when compared to experimental data. Changing σk and σE from default values of 1.00 and 1.4489, respectively, to 0.50 and 0.7244, respectively, improved the initial mixing rate, while reducing the farfield mixing rate and the peak turbulent kinetic energy along the centerline. A high-speed mixing layer was also investigated for performance of baseline and modified EASM coefficients, with similar results as for the jet cases. A flat plate boundary layer was briefly examined to determine the effects of changing the coefficients on the turbulent skin friction coefficient. The change to the pressure strain coefficient, C2 = 0.10 is recommended for future EASM calculation of jets flow; however, it is also recommended that the diffusion coefficients remain at their default values.

Turbulent Mixing↗

NASA NTRS2019

Potential Improvements in Global Carbon Flux Estimates from a Network of Laser Heterodyne Radiometer Measurements of Column Carbon Dioxide

We present observing system simulation experiments (OSSEs) to evaluate the impact of a proposed network of ground-based miniaturized laser heterodyne radiometer (mini-LHR) instruments that measure atmospheric column-averaged carbon dioxide (XCO2) with a 1 ppm precision. A particular strength of this passive measurement approach is its insensitivity to clouds and aerosols due to its direct sun pointing and narrow field of view (0.2°). Developed at the NASA Goddard Space Flight Center (GSFC), these portable, low-cost mini-LHR instruments were designed to operate in tandem with the sun photometers used by the AErosol RObotic NETwork (AERONET). This partnership allows us to leverage the existing framework of AERONET's global ground network of more than 500 sites as well as providing simultaneous measurements of aerosols that are known to be a major source of error in retrievals of XCO2 from passive nadir-viewing satellite observations. We show, using the global 3-D GEOS-Chem chemistry transport model, that a deployment of 50 mini-LHRs at strategic (but not optimized) AERONET sites significantly improves our knowledge of global and regional land-based CO2 fluxes. This improvement varies seasonally and ranges 58%–81% over southern lands, 47%–76% over tropical lands, 71%–92% over northern lands, and 64%–91% globally. We also show significant added value from combining mini-LHR instruments with the existing ground-based NOAA flask network. Collectively, these data result in improved a posteriori CO2 flux estimates on spatial scales of ∼10 km2, especially over North America and Europe, where the ground-based networks are densest. Our studies suggest that the mini-LHR network could also play a substantive role in reducing carbon flux uncertainty in Arctic and tropical systems by filling in geographical gaps in measurements left by ground-based networks and space-based observations. A realized network would also provide necessary data for the quinquennial global stock takes that form part of the Paris Agreement.

Palmer, Paul I.↗

NASA NTRS2019

Investigating the Utility of Hyperspectral Sounders in the 9.6 μm Band to Improve Ozone Analyses

Currently, hyperspectral sounder brightness temperatures assimilated in the Goddard Earth Observing System - Atmospheric Data Assimilation System (GEOS-ADAS) are limited to assimilating temperature and moisture. The ozone sensitive 9.6 micron region is sensed by several hyperspectral sounders including AIRS (Atmospheric InfraRed Sounder), IASI (Infrared Atmospheric Sounding Interferometer), and CrIS (Cross-track Infrared Sounder). Direct assimilation of brightness temperatures in the 9.6 micron region have been used previously to improve ozone analyses. This has recently been achieved by ECMWF (European Centre for Medium-Range Weather Forecast) (Dragani and McNally, 2013; Eresmaa et al., 2017), and while every system presents its challenges, it should be possible to take advantage of this spectral region using the GEOS-ADAS. For this study, channels were selected from available operational subsets evaluating information content, and minimizing inter-channel correlation. Additionally, information such as channel selections made by other studies, and vertical sensitivities of ozone and temperature were considered in developing the study. The analyses produced show improvements verified against ozonesondes taken from SHADOZ (Southern Hemisphere Additional Ozonesondes), and WOUDC (World Ozone and Ultraviolet Data Center). The addition of ozone channels does degrade forecast skill in the Tropics, on the border of statistical significance. Overall, the addition of these channels in some form could improve ozone analyses in the GEOS-ADAS.

Karpowicz, Bryan M.↗

NASA NTRS2017

Improvement of Reynolds-Stress and Triple-Product Lag Models

Turbulence↗