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At least 109 records · Page 6

Cooperative Robotics and the Search for Extraterrestrial Life

If we think tenuous abodes of life may be hiding in remote extraterrestrial environmental niches, and if we want to assess the biological status of a given locale or entire planet before sending humans (perhaps because of contamination concerns or other motivations) then we face the challenge of robotically exploring a large space efficiently and in enough detail to have confidence in our assessment of the biological status of the environment in question. On our present schedule of perhaps two or so missions per opportunity, we will likely need a different exploratory approach than singular stationary landers or singular rover missions or sample return, because there appear to be fundamental limitations in these mission profiles to obtain the many samples we will likely need if we want to have confidence in assessing the biological status of an environment in which life could be hiding in remote environmental niches. Singular rover missions can potentially accommodate sampling over a fairly large area, but are still limited by range and can be a single point of failure. More importantly, such mission profiles have limited payload capabilities which are unlikely to meet the demanding requirements of life-detection. Sample return has the advantage of allowing sophisticated analysis of the sample, but also has the severe limitations associated with only being able to bring back a few samples. This presentation will suggest two cooperative robotic approaches for exploration that have the potential to overcome these difficulties and facilitate efficient and thorough life-detecting exploration of a large space. Given the two premises stated above, it appears at least two fundamental challenges have to be met simultaneously: (1) coverage of a large space and (2) bringing to bear a sophisticated suite of detection and experimental payloads on any specific location in order to address a major challenge in looking for extraterrestrial life: namely, executing a wide variety of detection scenarios and in situ experiments in order to gather the required data for a confident assessment that life has been detected and to, more generally, cover a wide range of extraterrestrial life possibilities. Cooperative robotics lends itself to this kind of problem because cooperation among the combined capabilities of a variety of simple single function agents can give rise to fairly complex task execution such as the search for and detection of extraterrestrial life.

Lupisella, M. L.↗

Full-Coverage High-Resolution Daily PM(sub 2.5) Estimation using MAIAC AOD in the Yangtze River Delta of China

Satellite aerosol optical depth (AOD) has been used to assess population exposure to fine particulate matter (PM (sub 2.5)). The emerging high-resolution satellite aerosol product, Multi-Angle Implementation of Atmospheric Correction(MAIAC), provides a valuable opportunity to characterize local-scale PM(sub 2.5) at 1-km resolution. However, non-random missing AOD due to cloud snow cover or high surface reflectance makes this task challenging. Previous studies filled the data gap by spatially interpolating neighboring PM(sub 2.5) measurements or predictions. This strategy ignored the effect of cloud cover on aerosol loadings and has been shown to exhibit poor performance when monitoring stations are sparse or when there is seasonal large-scale missngness. Using the Yangtze River Delta of China as an example, we present a Multiple Imputation (MI) method that combines the MAIAC high-resolution satellite retrievals with chemical transport model (CTM) simulations to fill missing AOD. A two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM(sub 2.5) concentrations in 2013 and 2014 at 1 km resolution with complete coverage in space and time. The daily MI models have an average R(exp 2) of 0.77, with an inter-quartile range of 0.71 to 0.82 across days. The overall Ml model 10-fold cross-validation R(exp 2) (root mean square error) were 0.81 (25 gm(exp 3)) and 0.73 (18 gm(exp 3)) for year 2013 and 2014, respectively. Predictions with only observational AOD or only imputed AOD showed similar accuracy.Comparing with previous gap-filling methods, our MI method presented in this study performed bette rwith higher coverage, higher accuracy, and the ability to fill missing PM(sub 2.5) predictions without ground PM(sub 2.5) measurements. This method can provide reliable PM(sub 2.5)predictions with complete coverage that can reduce biasin exposure assessment in air pollution and health studies.

PM2.5↗

A Perfect View of Vesta: Creating Pointing Observations for the Dawn Spacecraft on Asteroid 4 Vesta

The Dawn spacecraft has a timely and clever assignment in store. It will take a close look at two intact survivors from the dawn of the solar system (asteroids 4 Vesta and 1 Ceres) to understand more about solar system origin and evolution. To optimize science return, Dawn must make carefully designed observations on approach and in survey orbit, high altitude mapping orbit, and low altitude mapping orbit at each body. In this report, observations outlined in the science plan are modeled using the science opportunity analyzer program for the Vesta encounter. Specifically, I encoded Dawn's flight rules into the program, modeled pointing profiles of the optical instruments (framing camera, visible infrared spectrometer) and mapped their fields of view onto Vesta's surface. Visualization of coverage will provide the science team with information necessary to assess feasibility of alternative observation plans. Dawn launches in summer 2006 and ends its journey in 2016. Instrument observations on Vesta in 2011 will supply detailed information about Vesta's surface and internal structure. These data will be used to analyze the formation and history of the protoplanet and, therefore, complete an important step in understanding the development of our solar system.

Hay, Katrina M.↗

Flood warnings, flood disaster assessments, and flood hazard reduction : the roles of orbital remote sensing

Orbital remote sensing is now poised to make three fundamental contributions towards reducing the detrimental effects of extreme floods. Effective Flood warning requires frequent (near-daily) radar observation of the Earth's surface through cloud cover. In contrast, both optical and radar wavelengths will increasingly be used for disaster assessment and hazard reduction. These latter tasks are accomplished, in part, by accurate mapping of flooded lands and commonly over periods of several days or more. We use radar scatterometer data from QuikSCAT to detect changes in surface water area and with a full global coverage every 2.5 days. Also, MODIS, RADARSAT, and other higher spatial resolution data are used for flood mapping and other flood measurements. These records are preserved in a global flood hazard atlas at http://www.dartmouth.edu/-floods/Atlas.html.

Shabaneh, Tamer B.↗

Tropospheric Ozone Assessment Report: Tropospheric Ozone From 1877 to 2016, Observed Levels, Trends and Uncertainties

From the earliest observations of ozone in the lower atmosphere in the 19th century, both measurement methods and the portion of the globe observed have evolved and changed. These methods have different uncertainties and biases, and the data records differ with respect to coverage (space and time), information content, and representativeness. In this study, various ozone measurement methods and ozone datasets are reviewed and selected for inclusion in the historical record of background ozone levels, based on relationship of the measurement technique to the modern UV absorption standard, absence of interfering pollutants, representativeness of the well-mixed boundary layer and expert judgement of their credibility. There are significant uncertainties with the 19th and early 20th-century measurements related to interference of other gases. Spectroscopic methods applied before 1960 have likely underestimated ozone by as much as 11% at the surface and by about 24% in the free troposphere, due to the use of differing ozone absorption coefficients. There is no unambiguous evidence in the measurement record back to 1896 that typical mid-latitude background surface ozone values were below about 20 nmol mol–1, but there is robust evidence for increases in the temperate and polar regions of the northern hemisphere of 30–70%, with large uncertainty, between the period of historic observations, 1896–1975, and the modern period (1990–2014). Independent historical observations from balloons and aircraft indicate similar changes in the free troposphere. Changes in the southern hemisphere are much less. Regional representativeness of the available observations remains a potential source of large errors, which are difficult to quantify. The great majority of validation and intercomparison studies of free tropospheric ozone measurement methods use ECC ozonesondes as reference. Compared to UV-absorption measurements they show a modest (~1–5% ±5%) high bias in the troposphere, but no evidence of a change with time. Umkehr, lidar, and FTIR methods all show modest low biases relative to ECCs, and so, using ECC sondes as a transfer standard, all appear to agree to within one standard deviation with the modern UV-absorption standard. Other sonde types show an increase of 5–20% in sensitivity to tropospheric ozone from 1970–1995. Biases and standard deviations of satellite retrieval comparisons are often 2–3 times larger than those of other free tropospheric measurements. The lack of information on temporal changes of bias for satellite measurements of tropospheric ozone is an area of concern for long-term trend studies.

UV absorption standard↗

Satellite Monitoring for Air Quality and Health

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016–2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 μm in diameter (PM(sub 2.5)) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Satellites↗

Application of Suomi-NPP Green Vegetation Fraction and NUCAPS for Improving Regional Numerical Weather Prediction

The NASA SPoRT Center is working to incorporate Suomi‐NPP products into its research and transition activities to improve regional numerical weather prediction (NWP). Specifically, SPoRT seeks to utilize two data products from NOAA/NESDIS: (1) daily global VIIRS green vegetation fraction (GVF), and (2) NOAA Unique CrIS and ATMS Processing System (NUCAPS) temperature and moisture retrieved profiles. The goal of (1) is to improve the representation of vegetation in the Noah land surface model (LSM) over existing climatological GVF datasets in order to improve the land‐atmosphere energy exchanges in NWP models and produce better temperature, moisture, and precipitation forecasts. The goal of (2) is to assimilate NUCAPS retrieved profiles into the Gridpoint Statistical Interpolation (GSI) data assimilation system to assess the impact on a summer pre‐frontal convection case. Most regional NWP applications make use of a monthly GVF climatology for use in the Noah LSM within the Weather Research and Forecasting (WRF) model. The GVF partitions incoming energy into direct surface heating/evaporation over bare soil versus evapotranspiration processes over vegetated surfaces. Misrepresentations of the fractional coverage of vegetation during anomalous weather/climate regimes (e.g., early/late bloom or freeze; drought) can lead to poor NWP model results when land‐atmosphere feedback is important. SPoRT has been producing a daily MODIS GVF product based on the University of Wisconsin Direct Broadcast swaths of Normalized Difference Vegetation Index (NDVI). While positive impacts have been demonstrated in the WRF model for some cases, the reflectances composing these NDVI do not correct for atmospheric aerosols nor satellite view angle, resulting in temporal noisiness at certain locations (especially heavy vegetation). The method behind the NESDIS VIIRS GVF is expected to alleviate the issues seen in the MODIS GVF real‐time product, thereby offering a higher‐quality dataset for modeling applications. SPoRT is evaluating the VIIRS GVF data against the MODIS real‐time and climatology GVF in both WRF and the NASA Land Information System. SPoRT has a history of assimilating hyperspectral infrared retrieved profiles

Numerical Weather Prediction↗

Temperature Fluctuations and Boundary Layer Turbulence as seen by Mars Exploration Rovers Miniature Thermal Emission Spectrometer

The Mini-TES spectrometer carried by Spirit and Opportunity is a unique instrument that enabled vertical temperature profiles to be retrieved at high frequency (every 2 s, or “ICK”). Observations obtained from this instrument provide information on boundary layer activity. As an extension of previous work, we have retrieved ICK-by-ICK vertical temperature profiles to characterize turbulent behavior at each rover site for up to two Mars Years. We have also retrieved ICK-by-ICK near-surface (1.1 m) atmospheric temperatures and surface temperatures from dedicated atmospheric observations as well as geologic observations that extend the coverage of near-surface observations. The extension and increased frequency of retrievals as well as the additional observations provide a more complete view of the vertical and temporal variation of temperature fluctuations within the PBL. Temperature fluctuations are assessed using detrended temperature time-series data. The results show fluctuations can be as large as 10 K at the surface and 8 K aloft with timescales on the order of minutes. We have calculated the peak-to-peak amplitudes of temperature fluctuations and the corresponding timescales over which they occur. Spirit and Opportunity temperature fluctuation amplitudes decrease in magnitude vertically, where higher atmospheric levels show smaller fluctuations in amplitudes than at the surface. The magnitude of temperature fluctuations changes with the difference in surface and air temperature. This difference varies little as a function of season at both rover sites. Fluctuations are observed to quickly decrease in the late afternoon reaching a minimum near 17:00 LTST followed by moderately increased activity near sunset caused by forced convection. There is no significant change in the observed convective activity as a function of dust optical depth during regional dust storms. The few large temperature fluctuations that are concurrent with dust events are likely the result of large-scale systems.

Mars, atmosphere↗

Ozone Profiles in the High-latitude Stratosphere and Lower Mesosphere Measured by the Improved Limb Atmospheric Spectrometer (ILAS)-II: Comparison with other Satellite Sensors and Ozonesondes

A solar occultation sensor, the Improved Limb Atmospheric Spectrometer (ILAS)-II, measured 5890 vertical profiles of ozone concentrations in the stratosphere and lower mesosphere and of other species from January to October 2003. The measurement latitude coverage was 54-71degN and 64-88degS, which is similar to the coverage of ILAS (November 1996 to June 1997). One purpose of the ILAS-II measurements was to continue such high-latitude measurements of ozone and its related chemical species in order to help accurately determine their trends. The present paper assesses the quality of ozone data in the version 1.4 retrieval algorithm, through comparisons with results obtained from comprehensive ozonesonde measurements and four satellite-borne solar occultation sensors. In the Northern Hemisphere (NH), the ILAS-II ozone data agree with the other data within +/-10% (in terms of the absolute difference divided by its mean value) at altitudes between 11 and 40 km, with the median coincident ILAS-II profiles being systematically up to 10% higher below 20 km and up to 10% lower between 21 and 40 km after screening possible suspicious retrievals. Above 41 km, the negative bias between the NH ILAS-II ozone data and the other data increases with increasing altitude and reaches 30% at 61-65 km. In the Southern Hemisphere, the ILAS-II ozone data agree with the other data within 10% in the altitude range of 11-60 km, with the median coincident profiles being on average up to 10% higher below 20 km and up to 10% lower above 20 km.

Sugita, T.↗

First Assessments of ICESat-2 Performance Using Aircraft Data

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) Is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in early 2016, ICESat-2 will use a high repetition rate (approximately 10 kHz), small footprint (10m diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise ranges to the earth's surface. Operating in the green (approximately 532nm), the six beams of ICESat-2 will provide improved spatial coverage compared with ICESat while the differences in transmit energy among the beams provide a large dynamic range. In order to evaluate models of predicted ICESat-2 performance, and provide ICESat-2-like data for algorithm development an airborne ICESat-2 simulator was developed and first flown in 2010, this simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) has now had three deployments in the western US, and will be deployed to the polar regions in spring of 2012. MABEL uses a similar measurement strategy to what will be used on ICESat-2. MABEL collects more spatially-dense data than ICESat-2 (approximately 2-cm along track) with a smaller 2m diameter footprint in 16 green channels and an additional 8 channels in the infrared. The comparison between frequencies allows for analysis of possible penetration of green energy into water or snow. We present MABEL data collected over deserts, forests, ocean water, lakes. snow covered mountains, and saft flats, provide examples of how these data are being used to develop algorithms that derive geophysical products from ICESat 2 and assess expected performances.

Neumann, Tom↗

Assessing the Sampleability of Bennu’s Surface for the OSIRIS-REx Asteroid Sample Return Mission

NASA’s first asteroid sample return mission, OSIRIS-REx, collected a sample from the surface of near-Earth asteroid Bennu in October 2020 and will deliver it to Earth in September 2023. Selecting a sample collection site on Bennu’s surface was challenging due to the surprising lack of large ponded deposits of regolith particles exclusively fine enough (≤ 2 cm diameter) to be ingested by the spacecraft’s Touch-and-Go Sample Acquisition Mechanism (TAGSAM). Here we describe the Sampleability Map of Bennu, which was constructed to aid in the selection of candidate sampling sites and to estimate the probability of collecting sufficient sample. “Sampleability” is a numeric score that expresses the compatibility of a given area’s surface properties with the sampling mechanism. The algorithm that determines sampleability is a best fit functional form to an extensive suite of laboratory testing outcomes tracking the TAGSAM performance as a function of four observable properties of the target asteroid. The algorithm and testing were designed to measure and subsequently predict TAGSAM collection amounts as a function of the minimum particle size, maximum particle size, particle size frequency distribution, and the tilt of the TAGSAM head off the surface. The sampleability algorithm operated at two general scales, consistent with the resolution and coverage of data collected during the mission. The first scale was global and evaluated nearly the full surface. Due to Bennu’s unexpected boulder coverage and lack of ponded regolith deposits, the global sampleability efforts relied heavily on additional strategies to find and characterize regions of interest based on quantifying and avoiding areas heavily covered by material too large to be collected. The second scale was site-specific and used higher-resolution data to predict collected mass at a given contact location. The rigorous sampleability assessments gave the mission confidence to select the best possible sample collection site and directly enabled successful collection of hundreds of grams of material.

Asteroid exploration↗

Using remotely sensed information to support landslide hazard and exposure assessment throughout the disaster lifecycle

The global coverage and temporal frequency that satellites provide offers a unique opportunity to estimate landslide hazard and exposure throughout the disaster lifecycle, from pre-event planning and forecasting to post-event mapping and impact assessment, and finally to recovery and mitigation. The relevance of satellite-derived data and model products is largely contingent on the spatiotemporal sampling, the hazard characteristics, and the needs from the research or applications community. This work presents an advanced Landslide Hazard Assessment for Situational Awareness (LHASA) framework that brings together satellite and model products with new machine learning techniques and global inventory data to better model landslide hazard and exposure. We present several new ways to map, model, and assess landslide hazard using a range of satellite data. Two new thrusts of this work are to better account for the exacerbating impacts of fires and to provide a multi-day forecast of potential hazard. Together, these additional components blend information from a suite of satellite and model sources to improve early warning of potentially hazardous areas, identify landslide occurrence and impacts in near real-time, and better characterize the spatiotemporal patterns of landslide hazard and exposure more broadly for future awareness and planning. This suite of tools and products is open to the public and provides information to better assess the potential occurrence and impacts of landslides within different regions of the world. This presentation explores both the architecture behind this framework and examples of how the model components and products have been used by different stakeholders around the world.

Thomas Stanley↗

The Global Water Monitor: Lake, Wetland, and River Reach Monitoring for Resource Management and Hazard Observation

The Global Water Monitor is a monitoring program offering surface water-related products for lakes, reservoirs, river reaches, and wetlands, https://blueice.gsfc.nasa.gov/gwm. These products are derived from multiple satellite-based altimetry and multispectral imaging platforms. The primary measurements are water level, slope, and extent, derived from a series of NASA and other agency instruments (Sentinel-3,-6, ICESat-2, SWOT, MODIS). The system serves stakeholders, the US Department of Agriculture Foreign Agricultural Service and the US Geological Survey, as well as various international, national, state, and intelligence agencies, engineers, ecologists, and hydrological researchers. Considering the sensitivity of ground-based data and the remote accessibility of many basins, the satellites offer global coverage, accuracy, and continuity of measurements. Observation of storage fluctuations in lakes and reservoirs provides users with knowledge of short and long-term drought conditions that can affect both water and energy resources. Emphasis is on changing climatic conditions, water sharing between nations, and regional stability. Measurements across a wetland complex can assist with efforts to assess hydrological dynamics with a focus on conservation efforts that aid both natural ecology and the sharing of precious water resources – the latter potentially being required in a basin across the municipal, crop irrigation, aquaculture, livestock, and power station spectrum. Observations of river reaches assists in the collection of basic hydraulic information, particularly in gauge-poor regions, for modelling efforts and the estimation of discharge, and at high-latitudes satellite-based river observations serve projects that warn of spring melts and flood hazards. We look at how recent improvements in instrument technology and mission operations are assisting with acquiring true global coverage and cross-validation efforts, and how stakeholders interact with the project in terms of setting requirements, product format, and accessibility methods. Examples show the application of the products across a range of programs, and in addition to meeting operational requirements, how the multi-decadal surface water levels are creating a high-quality timeline of Earth Data Records.

Lakes↗

Highest Resolution Topography of 433 Eros and Implications for MUSES-C

The highest resolution observations of surface morphology and topography at asteroid 433 Eros were obtained by the Near Earth Asteroid Rendezvous (NEAR) Shoemaker spacecraft on 12 February 2001, as it landed within a ponded deposit on Eros. Coordinated observations were obtained by the imager and the laser rangefinder, at best image resolution of 1 cm/pixel and best topographic resolution of 0.4 m. The NEAR landing datasets provide unique information on rock size and height distributions and regolith processes. Rocks and soil can be distinguished photometrically, suggesting that bare rock is indeed exposed. The NEAR landing data are the only data at sufficient resolution to be relevant to hazard assessment on future landed missions to asteroids, such as the MUSES-C mission which will land on asteroid 25143 (1998 SF36) in order to obtain samples. In a typical region just outside the pond where NEAR landed, the areal coverage by resolved positive topographic features is 18%. At least one topographic feature in the vicinity of the NEAR landing site would have been hazardous for a spacecraft.

Cheng, A. F.↗

Monitoring Global Freshwater Resources with GRACE

Freshwater resources include surface waters, groundwater, and seasonal snowpack. Given adequate ground based measurements, all of these can be monitored effectively, however, outside of the developed world such measurements often are not systematic and the data not centralized, and as a result reports of freshwater availability may be largely anecdotal. Even in the developed world it can be difficult to quantify changes in groundwater storage over large scales. Owing to its global coverage, satellite remote sensing has become a valuable tool for freshwater resources assessment. In particular, the Gravity Recovery and Climate Experiment (GRACE) has demonstrated an unequaled ability to monitor total terrestrial water storage including groundwater at regional to continental scales. In this presentation we will identify apparent trends in terrestrial water storage observed by GRACE over the past nine years and attempt to explain their origins and predict whether they are likely to continue. Trends in certain regions where groundwater extraction has significantly depleted aquifers, including northern India and California, will be discussed in detail.

Rodell, Matt↗

Comparing Eyewitness-Derived Trajectories of Bright Meteors to Ground Truth Data

The NASA Meteoroid Environment Office (MEO) is the only US government agency tasked with analyzing meteors of public interest. When queried about a meteor observed over the United States, the MEO must respond with a characterization of the trajectory, orbit, and size within a few hours. Using observations from meteor networks like the NASA All Sky Fireball Network or the Southern Ontario Meteor Network, such a characterization is often easy. If found, casual recordings from the public and stationary web cameras can be used to roughly analyze a meteor if the camera's location can be identified and its imagery calibrated. This technique was used with great success in the analysis of the Chelyabinsk meteorite fall. But if the event is outside meteor network coverage, if an insufficient number of videos are found, or if the imagery cannot be geolocated or calibrated, a timely assessment can be difficult if not impossible. In this situation, visual reports made by eyewitnesses may be the only resource available. This has led to the development of a tool to quickly calculate crude meteor trajectories from eyewitness reports made to the American Meteor Society. The output is illustrated in Figure 1. A description of the tool, example case studies, and a comparison to ground truth data observed by the NASA All Sky Fireball Network will be presented.

Moser, D. E.↗

Bridging the Last Mile with Open-Source Advancements: Empowering Communities through Fusion of Aerosol Optical Depth (AOD) Products from Multi-Satellite Sensors

Aerosol Optical Depth (AOD) is a crucial parameter for understanding atmospheric aerosol distribution and their impact on climate and air quality. With the growing number of Earth observation satellites, there is an abundance of AOD products derived from various sensors onboard both geostationary and low-orbit satellites. The availability of multiple datasets provides an opportunity to harness the strengths of each sensor and create comprehensive and accurate AOD datasets for climate and air quality studies at different temporal and spatial scales. Our NASA aerosol MEaSURES project has made significant strides in recent years by undertaking the ambitious task of developing an open-source package tailored for fusing AOD products from different sources. The package is based on OOP (Object-Oriented Programming) design and is implemented in Python modules. Generic interfaces enable easy inclusion of large and heterogeneous data. The package may be utilized to produce harmonized AOD datasets with enhanced spatial and temporal coverage. The latest version of the package is able to process and integrate the dark-target AOD data from six different sensors: AHI Himawari-8, ABI GOES-West, ABI GOES-East, MODIS AQUA, MODIS TERRA, and VIIRS SNPP. Rigorous validation and intercomparison studies have been performed to assess the accuracy and reliability of the fused AOD product against ground-based measurements and reference datasets. The open-source nature of the developed package ensures transparency, reproducibility, and community engagement. The research community and stakeholders can access, contribute to, and further improve the fusion methodology, making it adaptable to other studies, or expanding it to include new satellite data as they become available. In this poster presentation, we will introduce the accomplishments and challenges faced during the development of the open-source package for AOD data fusion, and demonstrate the advantages of combining AOD products from the six aforementioned satellite sensors. The presentation aims to foster discussions, collaborations, and future directions in integrating Earth observation and remote sensing data, which may contribute to a better understanding of atmospheric aerosols and their impacts on our environment.

Zhaohui Zhang↗

VIIRS Reflective Solar Band Radiometric and Stability Evaluation Using Deep Convective Clouds

This work takes advantage of the stable distribution of deep convective cloud (DCC) reflectance measurements to assess the calibration stability and detector difference in Visible Infrared Imaging Radiometer Suite (VIIRS) reflective bands. VIIRS Sensor Data Records (SDRs) from February 2012 to June 2015 are utilized to analyze the long-term trending, detector difference, and half angle mirror (HAM) side difference. VIIRS has two thermal emissive bands with coverage crossing 11 microns for DCC pixel identification. The comparison of the results of these two processing bands is one of the indicators of analysis reliability. The long-term stability analysis shows downward trends (up to approximately 0.4 per year) for the visible and near-infrared bands and upward trends (up to 0.5per year) for the short- and mid-wave infrared bands. The detector difference for each band is calculated as the difference relative to the average reflectance overall detectors. Except for the slightly greater than 1 difference in the two bands at 1610 nm, the detector difference is less than1 for other solar reflective bands. The detector differences show increasing trends for some short-wave bands with center wavelengths from 400 to 600 nm and remain unchanged for the bands with longer center wavelengths. The HAM side difference is insignificant and stable. Those short-wave bands from 400 to 600 nm also have relatively larger HAM side difference, up to 0.25.Comparing the striped images from SDR and the smooth images after the correction validates the analyses of detector difference and HAM side difference. These analyses are very helpful for VIIRS calibration improvement and thus enhance product quality

VIIRS↗