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The Multi-angle Imaging SpectroRadiometer (MISR) instrument, scheduled to fly on board the first Earth Observing System (EOS) spacecraft, will have a data stream that produces over 100 GB of data per day, once in full operation, of information about the Earth's atmosphere, clouds, and surface.
Planetary probes have long been a tool used by scientists to gain early clues on environments and systems of new planetary targets. This not only fueled the scientific process but also helped prepare for future missions, such as landers, and helped ensure their success. Venus, Earth's sister planet, has been the target of more probes and landers than any other body in our solar system except for Earth and yet many fundamental questions are unanswered. Challenge for Venus Surface Science: This lack of knowledge is a result of the challenging Venus environments. Remote sensing of the surface and portions of the atmosphere is difficult at best due to the thick layers of sulfuric acid clouds and the high pressure supercritical CO2 atmosphere below those clouds. This has hampered the ability of orbiting missions to provide us insight into surface features and processes and thus hides potential clues on interior process from our view. Surface probes and landers face an even more daunting challenge, which is the extreme temperature, pressure and unfriendly chemical composition of the near surface atmosphere. Over 10 assets have landed on the surface yet the longest surviving asset Venera-13 lasted only 127 minutes before succumbing to the extreme temperature. While this and other landers provided valuable new data, the short life impacted ability to understand any temporal processes, for example meteorology, seismic active, and therefore very little is known about the interior and surface atmosphere interactions. New Capability Offering Potential Solutions: Re-cent developments by NASA are offering hope of overcoming the technical challenges of surface operations and life with the use of high temperature electronics and systems. Wide band gap, SiC based electronics have been demonstrated to function successfully for extended periods of time both at 500C, Venus surface temperatures as well as when temperature is combined with the reactive chemistry of the surface atmosphere and the high pressures (over 90 bar pressure at the surface). In addition to electronics a number of other subsystems are in development including power in the form of high temperature batteries and power management devices, communications including antennas, transmitters and other components, materials, and structures and mechanisms. These are all activities under NASA's Long Lived In situ Solar System Exploration (LLISSE) project. Other activities are also funded under NASA's HOTTech program.
Abstract We explore the decoupling physics of a stratocumulus-topped boundary layer (STBL) moving over cooler water, a situation mimicking warm-air advection (WADV). We simulate an initially well-mixed STBL over a doubly periodic domain with the sea surface temperature decreasing linearly over time using the System for Atmospheric Modeling large-eddy model. Due to the surface cooling, the STBL becomes increasingly stably stratified, manifested as a near-surface temperature inversion topped by a well-mixed cloud-containing layer. Unlike the stably stratified STBL in cold-air advection (CADV) that is characterized by cumulus coupling, the stratocumulus deck in the WADV is unambiguously decoupled from the sea surface, manifested as weakly negative buoyancy flux throughout the subcloud layer. Without the influxes of buoyancy from the surface, the convective circulation in the well-mixed cloud-containing layer is driven by cloud-top radiative cooling. In such a regime, the downdrafts propel the circulation, in contrast to that in CADV regime for which the cumulus updrafts play a more determinant role. Such a contrast in convection regime explains the difference in many aspects of the STBLs including the entrainment rate, cloud homogeneity, vertical exchanges of heat and moisture, and lifetime of the stratocumulus deck, with the last being subject to a more thorough investigation in Part II. Finally, we investigate under what conditions a secondary stratus near the surface (or fog) can form in the WADV. We found that weaker subsidence favors the formation of fog whereas a more rapid surface cooling rate does not. Significant Statement The low-lying blanketlike clouds, called stratocumulus (Sc), reflect much incoming sunlight, substantially modulating Earth’s temperature. While much is known about how the Sc evolves when it moves over warmer water, few studies examine the opposite situation of Sc moving over colder water. We used a high-resolution numerical model to simulate such a case. When moving over cold water, the Sc becomes unambiguously decoupled from the water surface, distinctive from its warm counterpart in which the Sc interacts with the water surface via intermittent cauliflower-like clouds called cumulus clouds. Such decoupling influences many aspects of the Sc–sea surface system, which combine to alter the ability of the Sc to reflect sunlight, thereby influencing the climate. This work laid the foundation for future work that quantifies the contribution of such a decoupled Sc regime to Earth’s radiative budget and climate change.
Since the beginning of space remote sensing of the earth, there has been a natural progression widening the range of electromagnetic radiation used to sense the earth, and slowly, steadily increasing the spatial, spectral, and radiometric resolution of the measurements. There has also been a somewhat slower trend toward active measurements across the electromagnetic spectrum, motivated in part by increased resolution, but also by the ability to make new measurements. Active microwave instruments have been used to measure ocean topography, to study the land surface. and to study rainfall from space. Future NASA active microwave missions may add detail to the topographical studies, sense soil moisture, and better characterize the cryosphere. Only recently have active optical instruments been flown in space by NASA; however, there are currently several missions in development which will sense the earth with lasers and many more conceptual active optical missions which address the priorities of NASA's earth science program. Missions are under development to investigate the structure of the terrestrial vegetation canopy, to characterize the earth's ice caps, and to study clouds and aerosols. Future NASA missions may measure tropospheric vector winds and make vastly improved measurements of the chemical components of the earth's atmosphere.
The assignment is to make precise (better than 1 %) measurements of isotope ratios and accurate (5-10%) measurements of abundances of noble gas and to obtain vertical profiles of trace chemically active gases from above the clouds all the way down to the surface. Science measurement objectives are as follows: 1) Determine the composition of Venus atmosphere, including trace gas species and light stable isotopes; 2) Accurately measure noble-gas isotopic abundance in the atmosphere; 3) Provide descent, surface, and ascent meteorological data; 4) Measure zonal cloud-level winds over several Earth days; 5) Obtain near-IR descent images of the surface from 10-km altitude to the surface; 6) Accurately measure elemental abundances & mineralogy of a core from the surface; and 7) Evaluate the texture of surface materials to constrain weathering environment.
The Multi-angle Imaging SpectroRadiometer (MISR) has been in Earth orbit since December 1999 on NASA's Terra spacecraft. This instrument provides new ways of looking at the Earth's atmosphere, clouds, and surface for the purpose of understanding the Earth's ecology, environment, and climate. To facilitate the potential future continuation of MISR's multi-angle observations, a study was undertaken in 1999 and 2000 under the Instrument Incubator Program (IIP) of NASA Code Y's Earth Science Technology Office (ESTO) to investigate and demonstrate the feasibility of a successor to MISR that will have greatly reduced size and mass. The kernel of the program was the design, construction, and testing of a highly miniaturized camera, one of the nine that would probably be used on a future space borne MISR-like instrument. This demonstrated that the size and mass reduction of the optical system and camera electronics are possible and that filters can be assembled to meet the miniaturized packaging requirements. An innovative, reflective optics design was used, enabling the wavelength range to be extended into the shortwave infrared. This was the smallest all-reflective camera ever produced by the contractor. A study was undertaken to determine the feasibility of implementing nine (multi-angle) cameras within a single structure. This resulted in several possible configurations. It would also be possible to incorporate one of the cameras into an airborne instrument.
The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-09-16] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].
The 2019-2020 season has been one of the worst fire seasons on record. Australia has seen unprecedented heat waves, with temperatures reaching 120 F (49.1 C) in January across central and eastern Australia. NASA's satellites not only tracked the event in real time, using resources such as the Global Actives Fires and Hotspots Dashboard you see below, but also collected large volumes of rich data that scientists and researchers can use to study the event and the regional and global effects of the disaster. In this Esri StoryMap, we will guide you through the factors leading up to the 2019-2020 Australian bushfires disaster, the effect this event has had on air quality and global atmospheric composition, and the science behind researching the tie between disasters and public health. This story map will use data from ASDC-supported NASA missions such as the Measurements Of Pollution In The Troposphere (MOPITT), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), Clouds and the Earth’s Radiant Energy System (CERES), Stratospheric Aerosol and Gas Experiment (SAGE III) on the International Space Station (ISS), and Multi-angle Imaging SpectroRadiometer (MISR).
Soil Moisture Measurement - Remote Sensing. - Microwave (MW) Remote Sensing: Physically based and quantitative in nature; Based on difference in dielectric constant; Coarse spatial resolution 25-40 km; Shallow SM estimation depth 0-5 cm (approx.); All weather capabilities (e.g. Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Soil Moisture and Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP) etc.) - Thermal Infrared (TIR) Remote Sensing: Indirect SM retrieval through energy flux estimations; Relatively better spatial resolution 1-10 km; Root-zone moisture retrieval capability; Can not penetrate through clouds, hence data gaps (e.g. Surface Energy Balance Algorithm for Land (SEBAL), Atmospheric Land Exchange Inverse (ALEXI) etc.)
Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events, and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, enable detection of atmospheric features during daytime operations with a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.
Clouds and aerosols play a significant role in determining the overall atmospheric radiation budget, yet remain a key uncertainty in understanding and predicting the future climate system. In addition to their impact on the Earth’s climate system, aerosols from volcanic eruptions, wildfires, man-made pollution events and dust storms are hazardous to aviation safety and human health. Space-based lidar systems provide critical information about the vertical distributions of clouds and aerosols that greatly improve our understanding of the climate system. However, daytime data from backscatter lidars, such as the Cloud-Aerosol Transport System (CATS) on the International Space Station (ISS), must be averaged during science processing at the expense of spatial resolution to obtain sufficient signal-to-noise ratio (SNR) for accurately detecting atmospheric features. For example, 50% of all atmospheric features reported in daytime operational CATS data products require averaging to 60 km for detection. Furthermore, the single-wavelength nature of the CATS primary operation mode makes accurately typing these features challenging in complex scenes. This paper presents machine learning (ML) techniques that, when applied to CATS data, (1) increased the 1064 nm SNR by 75%, (2) increased the number of layers detected (any resolution) by 30%, and (3) enabled detection of 40% more atmospheric features during daytime operations at a horizontal resolution of 5 km compared to the 60 km horizontal resolution often required for daytime CATS operational data products. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime.
The Atmospheric Infrared Sounder (AIRS) mission is entering its 13th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing long-wave radiation, cloud properties, and trace gases. Thus AIRS data have been widely used, among other things, for short-term climate research and observational component for model evaluation. One instance is the fifth phase of the Coupled Model Intercomparison Project (CMIP5) which uses AIRS version 5 data in the climate model evaluation. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the AIRS mission. The GES DISC, in collaboration with the AIRS Project, released data from the version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. The ongoing Earth System Grid for next generation climate model research project, a collaborative effort of GES DISC and NASA JPL, will bring temperature and humidity profiles from AIRS version 6. The AIRS version 6 product adds a new "TqJoint" data group, which contains data for a common set of observations across water vapor and temperature at all atmospheric levels and is suitable for climate process studies. How different may the monthly temperature and humidity profiles in "TqJoint" group be from the "Standard" group where temperature and water vapor are not always valid at the same time? This study aims to answer the question by comprehensively comparing the temperature and humidity profiles from the "TqJoint" group and the "Standard" group. The comparison includes mean differences at different levels globally and over land and ocean. We are also working on examining the sampling differences between the "TqJoint" and "Standard" group using MERRA data.
The Level-1 and Atmosphere Archive Distribution System (LAADS) Distributed Active Archive Center (DAAC) primarily archives and distributes data on clouds and aerosols in Earth’s atmosphere in addition to providing Level 0 and 1 Moderate Imaging Radiometer Suite (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and airborne data as well as data from the European Space Agency’s Sea and Land Surface Temperature Radiometer (SLSTR) and the Ocean and Land Colour Instrument (OLCI). Secondarily, LAADS DAAC serves as a backup source for MODIS and VIIRS land products. As one of twelve DAACS supported by NASA’s Earth Science Data and Information System (ESDIS), LAADS DAAC provides a gateway to data through multiple tools. The newest, View Data, allows users to preview data sets before downloading or applying any post-processing transformations. Learn about how to access LAADS DAAC data, get up-to-date information about LAADS DAAC's migration to hosting data in the cloud, and discover how to use the View Data tool.
High above the world-class observatories that dot Hawaii's dormant Mauna Kea volcano, floating farther yet over the hostile and nearly inaccessible peaks of Mt. Everest, lies a summit waiting to be conquered. Here above the clouds and city lights and over 99.7% of the atmosphere is a platform on the edge of space, home to a broad range of astronomy and physics experiments. Today, balloons are lifting experiments longer, higher and more inexpensively than ever before, and returning them safely to Earth for reuse. Week-long flights at altitudes of approximately 35 kilometers carrying payloads in excess of several tons are the norm. NASA now plans to extend this platform and create a new generation of balloons capable of staying afloat with such cargo for 100 days and ultimately 1,000 days. What do some scientists hope to accomplish with 100 or even 1,000 days at the edge of space? To name but a few proposals on the table: Jupiter-size planet searches, large-aperture solar astronomy, large-aperture infrared astronomy, cosmic-ray investigations, long-duration Earth science missions, and hard x-ray imaging experiments. Olympus defines a new era in scientific ballooning. Advances in material science and trajectory control are enabling revolutionary capabilities. Very large scientific payloads can now be reliably launched and retrieved for reflight at a range of altitudes. Balloon flight still remains a fraction of the cost of a rocket launch. The ultra long duration balloon, with its 100-day maiden flight planned for 2001, provides a long-term facility in a near-space environment for many types of science. This is a stratospheric mountaintop well worth the climb.
SEDSAT-1 is designed to be a low cost scientific satellite which is to be used to perform a minimum of five tasks which include: (1) the acquisition of a number of important parameters associated with the tethering processes from the payloads perspective (such as accelerations incurred and imaging data of the tether during deployment), (2) to act as a remote sensing platform for making measurements of the Earth's Atmosphere (allowing research to be performed in such areas as vertical lightning observation, visible light spectrography, and cloud cover studies, (3) to act as a general purpose amateur radio communication satellite relaying information back to earth, (4) to demonstrate the feasibility of the deployment in low earth orbit of advanced technology such as the Gallium Arsenide Solar Cells, Nickel Metal Hydride batteries, and multi-chip module technology and, (5) to support student's active participation in applying the disciplines of engineering and science to space-based hardware platforms. The project includes the Three-axis Accelerometer System, TAS, Experiment which is designed to report the accelerations that the satellite undergoes during the tethering operations and during the second phase of the mission when the free floating satellite comes in contact with orbit debris. The SEASIS (SEDS Earth, Atmosphere, and Space Imaging System) is another SEDSAT experiment designed to provide images of the tether during its deployment and the earth during the second phase of the mission. To control these experiments and virtually all other satellite operations the Command Data System, CDS is employed. This system utilizes a moderate complexity micro-controller controlled by tasks operating under a real-time operating system to dynamically monitor and control the satellite. The scope of this researchers efforts has been in the general area of coordinating and assisting the student researchers with the development of the CDS and ground station interfaces. This included the low level CDS hardware design and the formulization of a general software plan and schedule for both the CDS and ground station portions of the project.
A summary of selected atmospheric conditions observed near the Space Shuttle Columbia (STS-40) launch time on 5 Jun. 1991, at KSC is presented. Values of ambient pressure, temperature, moisture, ground winds, visual observation (cloud), and winds aloft are included. The sequence of prelaunch Jimsphere-measured vertical wind profiles is given. The final atmospheric tape, which consists of wind and thermodynamic parameters versus altitude, for STS-40 vehicle ascent was constructed. The STS-40 ascent atmospheric data tape was constructed by MSFC's Earth Science and Applications Division to provide an internally consistent data set for use in postflight performance assessments and represents the best estimate of the launch environment to the 400,000-ft altitude that was traversed by the STS-40 vehicle.
The Suomi National Polar-orbiting Partnership (SNPP) satellite was successfully launched into a polar orbit on October 28, 2011 carrying 5 remote sensing instruments designed to provide data to improve weather forecasts and to increase understanding of long-term climate change. SNPP provides operational continuity of satellite-based observations for NOAA's Polar-orbiting Operational Environmental Satellites (POES) and continues the long-term record of climate quality observations established by NASA's Earth Observing System (EOS) satellites. In the 2003 to 2011 pre-launch timeframe, NASA's SNPP Science Team assessed the adequacy of the operational Raw Data Records (RDRs), Sensor Data Records (SDRs), and Environmental Data Records (EDRs) from the SNPP instruments for use in NASA Earth Science research, examined the operational algorithms used to produce those data records, and proposed a path forward for the production of climate quality products from SNPP. In order to perform these tasks, a distributed data system, the NASA Science Data Segment (SDS), ingested RDRs, SDRs, and EDRs from the NOAA Archive and Distribution and Interface Data Processing Segments, ADS and IDPS, respectively. The SDS also obtained operational algorithms for evaluation purposes from the NOAA Government Resource for Algorithm Verification, Independent Testing and Evaluation (GRAVITE). Within the NASA SDS, five Product Evaluation and Test Elements (PEATEs) received, ingested, and stored data and performed NASA's data processing, evaluation, and analysis activities. The distributed nature of this data distribution system was established by physically housing each PEATE within one of five Climate Analysis Research Systems (CARS) located at either at a NASA or a university institution. The CARS were organized around 5 key EDRs directly in support of the following NASA Earth Science focus areas: atmospheric sounding, ocean, land, ozone, and atmospheric composition products. The PEATES provided the system level interface with members of the NASA SNPP Science Team and other science investigators within each CARS. A sixth Earth Radiation Budget CARS was established at NASA Langley Research Center (NASA LaRC) to support instrument performance, data evaluation, and analysis for the SNPP Clouds and the Earth's Radiant Budget Energy System (CERES) instrument. Following the 2011 launch of SNPP, spacecraft commissioning, and instrument activation, the NASA SNPP Science Team evaluated the operational RDRs, SDRs, and EDRs produced by the NOAA ADS and IDPS. A key part in that evaluation was the NASA Science Team's independent processing of operational RDRs and SDRs to EDRs using the latest NASA science algorithms. The NASA science evaluation was completed in the December 2012 to April 2014 timeframe with the release of a series of NASA Science Team Discipline Reports. In summary, these reports indicated that the RDRs produced by the SNPP instruments were of sufficiently high quality to be used to create data products suitable for NASA Earth System science and applications. However, the quality of the SDRs and EDRs were found to vary greatly when considering suitability for NASA science. The need for improvements in operational algorithms, adoption of different algorithmic approaches, greater monitoring of on-orbit instrument calibration, greater attention to data product validation, and data reprocessing were prominent findings in the reports. In response to these findings, NASA, in late 2013, directed the NASA SNPP Science Team to use SNPP instrument data to develop data products of sufficiently high quality to enable the continuation of EOS time series data records and to develop innovative, practical applications of SNPP data. This direction necessitated a transition of the SDS data system from its pre-launch assessment mode to one of full data processing and production. To do this, the PEATES, which served as NASA's data product testing environment during the prelaunch and early on-orbit periods, were transitioned to Science Investigator-led Processing Systems (SIPS). The distributed data architecture was maintained in this new system by locating the SIPS at the same institutions at which the CARS and PEATES were located. The SIPS acquire raw SNPP instrument Level 0 (i.e. RDR) data over the full SNPP mission from the NOAA ADS and IDPS through the NASA SDS Data Distribution and Depository Element (SD3E). The SIPS process those data into NASA Level 1, Level 2, and global, gridded Level 3 standard products using peer-reviewed algorithms provided by members of the NASA Science Team. The SIPS work with the NASA SNPP Science Team in obtaining enhanced, refined, or alternate real-time algorithms to support the capabilities of the Direct Readout Laboratory (DRL). All data products, algorithm source codes, coefficients, and auxiliary data used in product generation are archived in an assigned NASA Distributed Active Archive Center (DAAC).
The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of processing, archiving, and distribution services for the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002 for global observations of the atmospheric state. Giovanni, a Web-based application developed by the GES DISC, provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Most important AIRS variables, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases, are available in Giovanni. AIRS is an instrument suite comprised of a hyperspectral infrared instrument (AIRS) and two multichannel microwave instruments, the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB). As HSB ceased operation in the very early stages of the AIRS mission, the AIRS project operates two parallel retrieval algorithms: one using both IR and MW measurements (AIRS+AMSU) and the other using only IR measurements (AIRS-only), which covers most of the mission duration. The AIRS+AMSU product is better quality, and the variables in Giovanni are from this product. However, generation of the AIRS+AMSU product has been suspended since the AMSU instrument anomaly occurred in late September 2016. To continue exploring up-to-date AIRS observations, the same set of variables from the AIRS-only product have been added to Giovanni by the GES DSIC. This will also support comparison of AIRS-only with AIRS+AMSU retrievals. In this presentation, we demonstrate the visualization of the AIRS-only product and plots/statistics of comparison with AIRS+AMSU product using Giovanni.