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NASA NTRS2014

Observations of Environmental Quenching in Groups in the 11 GYR Since z = 2.5: Different Quenching For Central and Satellite Galaxies

We present direct observational evidence for star formation quenching in galaxy groups in the redshift range 0 less than z less than 2.5. We utilize a large sample of nearly 6000 groups, selected by fixed cumulative number density from three photometric catalogs, to follow the evolving quiescent fractions of central and satellite galaxies over roughly 11 Gyr. At z approximately 0, central galaxies in our sample range in stellar mass from Milky Way/M31 analogs (M=6.5x10(exp 10) M/solar mass) to nearby massive ellipticals (M=1.5x10(exp 11) M/solar mass). Satellite galaxies in the same groups reach masses as low as twice that of the Large Magellanic Cloud (M=6.5x10(exp 9) M/solar mass). Using statistical background subtraction, we measure the average rest-frame colors of galaxies in our groups and calculate the evolving quiescent fractions of centrals and satellites over seven redshift bins. Our analysis shows clear evidence for star formation quenching in group halos, with a different quenching onset for centrals and their satellite galaxies. Using halo mass estimates for our central galaxies, we find that star formation shuts off in centrals when typical halo masses reach between 10(exp 12) and 10(exp 13) M/solar mass, consistent with predictions from the halo quenching model. In contrast, satellite galaxies in the same groups most likely undergo quenching by environmental processes, whose onset is delayed with respect to their central galaxy. Although star formation is suppressed in all galaxies over time, the processes that govern quenching are different for centrals and satellites. While mass plays an important role in determining the star formation activity of central galaxies, quenching in satellite galaxies is dominated by the environment in which they reside.

Environmental↗
NASA NTRS2014

Infrared Spectral Radiance Intercomparisons With Satellite and Aircraft Sensors

Measurement system validation is critical for advanced satellite sounders to reach their full potential of improving observations of the Earth's atmosphere, clouds, and surface for enabling enhancements in weather prediction, climate monitoring capability, and environmental change detection. Experimental field campaigns, focusing on satellite under-flights with well-calibrated FTS sensors aboard high-altitude aircraft, are an essential part of the validation task. Airborne FTS systems can enable an independent, SI-traceable measurement system validation by directly measuring the same level-1 parameters spatially and temporally coincident with the satellite sensor of interest. Continuation of aircraft under-flights for multiple satellites during multiple field campaigns enables long-term monitoring of system performance and inter-satellite cross-validation. The NASA / NPOESS Airborne Sounder Testbed - Interferometer (NAST-I) has been a significant contributor in this area by providing coincident high spectral/spatial resolution observations of infrared spectral radiances along with independently-retrieved geophysical products for comparison with like products from satellite sensors being validated. This presentation gives an overview of benefits achieved using airborne sensors such as NAST-I utilizing examples from recent field campaigns. The methodology implemented is not only beneficial to new sensors such as the Cross-track Infrared Sounder (CrIS) flying aboard the Suomi NPP and future JPSS satellites but also of significant benefit to sensors of longer flight heritage such as the Atmospheric InfraRed Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI) on the AQUA and METOP-A platforms, respectively, to ensure data quality continuity important for climate and other applications. Infrared spectral radiance inter-comparisons are discussed with a particular focus on usage of NAST-I data for enabling inter-platform cross-validation.

Larar, Allen M.↗
NASA NTRS2014

Extreme Thunderstorms as Seen by Satellite

Extreme events by their nature fall outside the bounds of routine experience. With imperfect or ambiguous measuring systems, it is appropriate to question whether an unusual measurement represents an extreme event or is the result of instrument errors or other sources of noise. About three weeks after the Tropical Rainfall Measuring Mission (TRMM) satellite began collecting data in Dec 1997, a thunderstorm was observed over northern Argentina with 85 GHz brightness temperatures below 50 K and 37 GHz brightness temperatures below 70 K (Zipser et al. 2006). These values are well below what had previously been observed from satellite sensors with lower resolution. The 37 GHz brightness temperatures are also well below those measured by TRMM for any other storm in the subsequent 16 years. Without corroborating evidence, it would be natural to suspect a problem with the instrument, or perhaps an irregularity with the platform during the first weeks of the satellite mission. But the TRMM satellite also carries a radar and a lightning sensor, both confirming the presence of an intense thunderstorm. The radar recorded 40+ dBZ (decibels relative to Z) reflectivity up to about 19 km altitude. More than 200 lightning flashes per minute were recorded. That same storm's 19 GHz brightness temperatures below 150 K would normally be interpreted as the result of a low-emissivity water surface (e.g., a lake, or flood waters) if not for the simultaneous measurements of such intense convection. This paper will examine records from TRMM and related satellite sensors including SSMI and AMSR-E to find the strongest signatures resulting from thunderstorms, and distinguishing those from sources of noise. The lowest brightness temperatures resulting from thunderstorms as seen by TRMM have been in Argentina in November and December. For SSMI sensors carried on five DMSP satellites examined so far, the lowest thunderstorm-related brightness temperatures have been from Argentina in November - December and from Minnesota in June-July. The Minnesota cases were associated with spotter reports of large hail, significant severe wind, and tornadoes. Those locations have the record holders for each satellite. This paper will show examples of cases with the lowest brightness temperatures, and map the locations of these and other storms with brightness temperatures nearly as low. Higher resolution data from the field program MC3E and possibly from IPHEX will be considered for context.

Cecil, Daniel J.↗
NASA NTRS2015

Parameter Impact on Sharing Studies Between UAS CNPC Satellite Transmitters and Terrestrial Systems

In order to provide a control and non-payload communication (CNPC) link for civil-use unmanned aircraft systems (UAS) when operating in beyond-line-of-sight (BLOS) conditions, satellite communication links are generally required. The International Civil Aviation Organization (ICAO) has determined that the CNPC link must operate over protected aviation safety spectrum allocations. Although a suitable allocation exists in the 5030-5091 MHz band, no satellites provide operations in this band and none are currently planned. In order to avoid a very lengthy delay in the deployment of UAS in BLOS conditions, it has been proposed to use existing satellites operating in the Fixed Satellite Service (FSS), of which many operate in several spectrum bands. Regulatory actions by the International Telecommunications Union (ITU) are needed to enable such a use on an international basis, and indeed Agenda Item (AI) 1.5 for the 2015 World Radiocommunication Conference (WRC) was established to decide on the enactment of possible regulatory provisions. As part of the preparation for AI 1.5, studies on the sharing FSS bands between existing services and CNPC for UAS are being contributed by NASA and others. These studies evaluate the potential impact of satellite CNPC transmitters operating from UAS on other in-band services, and on the potential impact of other in-band services on satellite CNPC receivers operating on UAS platforms. Such studies are made more complex by the inclusion of what are essentially moving FSS earth stations, compared to typical sharing studies between fixed elements. Hence, the process of determining the appropriate technical parameters for the studies meets with difficulty. In order to enable a sharing study to be completed in a less-than-infinite amount of time, the number of parameters exercised must be greatly limited. Therefore, understanding the impact of various parameter choices is accomplished through selectivity analyses. In the case of sharing studies for AI 1.5, identification of worst-case parameters allows the studies to be focused on worst-case scenarios with assurance that other parameter combinations will yield comparatively better results and therefore do not need to be fully analyzed. In this paper, the results of such sensitivity analyses are presented for the case of sharing between UAS CNPC satellite transmitters and terrestrial receivers using the Fixed Service (FS) operating in the same bands, and the implications of these analyses on sharing study results.

air traffic control↗
NASA NTRS2016

Tethered Space Satellite-1 (TSS-1): Technical Roundabouts

In the early 1990's US and Italian scientists collaborated to study the electrodynamics of dragging a satellite on a tether through the electrically charged portion of Earth's atmosphere called the ionosphere. An electrical current induced in the long wire could be used for power and thrust generation for a satellite. Other tether uses include momentum exchange, artificial gravity, deployment of sensors or antennas, and gravity-gradient stabilization for satellites. Before the Tethered Space Satellite (TSS-1), no long tether had ever been flown, so many questions existed on how it would actually behave. The TSS consisted of a satellite with science experiments attached to a 12.5 mile long, very thin (0.10 inch diameter) copper wire assembly wound around a spool in the deployer reel mechanism. With the Space Shuttle at an altitude of 160 nautical miles above earth, the satellite was to be deployed by raising it from the Shuttle bay on a boom facing away from Earth. Once cleared of the bay, the deployer mechanism was to slowly feed out the 12-plus miles of tether. Scientific data would be collected throughout the operation, after which the satellite would be reeled back in. Pre-flight testing system level tests involved setting up a tether receiver to catch the 12.5 mile tether onto another reel as it was being unwound by the deployer reel mechanism. Testing only the reel mechanism is straightforward. This test becomes more complicated when the TSS is mounted on the flight pallet at Kennedy Space Center (KSC). The system level tests must be passed before the pallet can be installed into the Space Shuttle cargo bay. A few months before flight, the TSS payload had been integrated onto the Spacelab pallet and system level tests, including unreeling and reeling the tether, had been successfully completed. Some of this testing equipment was then shipped back to the contractor Martin Marietta. Systems-level load analyses, which cannot be run until all information about each payload is finalized, was run in parallel with the physical integration of the hardware into the Shuttle payload bay. The coupled loads analysis, as it is called, incorporates any updates to the model due to system level tests, and any changes that were found during integration. The coupled loads analysis revealed that a single bolt attaching the deployer reel mechanism to the support structure had a "negative margin" - which is an indication that it might fail during operation. Hardware certification rules do not allow for hardware to fly with negative margins, so this issue had to be resolved before the flight. Since there is conservatism in engineering analysis, there is an option to "waive" the margin requirement, and fly the experiment as is. On the other hand, a structural failure of one payload could have serious or catastrophic consequences to other payloads and possibly the mission. Minor design changes or fixes might be feasible within the payload bay prior to launch. Any major design changes that required the spooling test to validate the hardware, or for the pallet to be removed, would cause TSS not to be ready for the Shuttle launch.

O'Connor, Brian↗
NASA NTRS2017

Advanced Deployable Shell-Based Composite Booms for Small Satellite Structural Applications Including Solar Sails

State of the art deployable structures are mainly being designed for medium to large size satellites. The lack of reliable deployable structural systems for low cost, small volume, rideshare-class spacecraft severely constrains the potential for using small satellite platforms for affordable deep space science and exploration precursor missions that could be realized with solar sails. There is thus a need for reliable, lightweight, high packaging efficiency deployable booms that can serve as the supporting structure for a wide range of small satellite systems including solar sails for propulsion. The National Air and Space Administration (NASA) is currently investing in the development of a new class of advanced deployable shell-based composite booms to support future deep space small satellite missions using solar sails. The concepts are being designed to: meet the unique requirements of small satellites, maximize ground testability, permit the use of low-cost manufacturing processes that will benefit scalability, be scalable for use as elements of hierarchical structures (e.g. trusses), allow long duration storage, have high deployment reliability, and have controlled deployment behavior and predictable deployed dynamics. This paper will present the various rollable boom concepts that are being developed for 5-20 m class size deployable structures that include solar sails with the so-called High Strain Composites (HSC) materials. The deployable composite booms to be presented are being developed to expand the portfolio of available rollable booms for small satellites and maximize their length for a given packaged volume. Given that solar sails are a great example of volume and mass optimization, the booms were designed to comply with nominal solar sail system requirements for 6U CubeSats, which are a good compromise between those of smaller form factors (1U, 2U and 3U CubeSats) and larger ones (12 U and 27 U future CubeSats, and ESPA-class microsatellites). Solar sail missions for such composite boom systems are already under consideration and development at NASA, as well as mission studies that will benefit from planned scaled-up versions of the composite boom technologies to be introduced. The paper presents ongoing research and development of thin-shell rollable composite booms designed under the particular stringent and challenging system requirements of relatively large solar sails housed on small satellites. These requirements will be derived and listed. Several new boom concepts are proposed and other existing ones are improved upon using thin-ply composite materials to yield unprecedented compact deployable structures. Some of these booms are shown in Fig. 1. For every boom to be introduced the scalable fabrication process developed to keep the overall boom system cost down will be shown. Finally, the initial results of purposely designed boom structural characterization test methods with gravity off-loading will be presented to compare their structural performance under expected and general load cases.

Fernandez, Juan M.↗
NASA NTRS2016

New Methods for Retrieval of Chlorophyll Red Fluorescence from Hyperspectral Satellite Instruments: Simulations and Application to GOME-2 and SCIAMACHY

Global satellite measurements of solar-induced fluorescence (SIF) from chlorophyll over land and ocean have proven useful for a number of different applications related to physiology, phenology, and productivity of plants and phytoplankton. Terrestrial chlorophyll fluorescence is emitted throughout the red and far-red spectrum, producing two broad peaks near 683 and 736nm. From ocean surfaces, phytoplankton fluorescence emissions are entirely from the red region (683nm peak). Studies using satellite-derived SIF over land have focused almost exclusively on measurements in the far red (wavelengths greater than 712nm), since those are the most easily obtained with existing instrumentation. Here, we examine new ways to use existing hyperspectral satellite data sets to retrieve red SIF (wavelengths less than 712nm) over both land and ocean. Red SIF is thought to provide complementary information to that from the far red for terrestrial vegetation. The satellite instruments that we use were designed to make atmospheric trace-gas measurements and are therefore not optimal for observing SIF; they have coarse spatial resolution and only moderate spectral resolution (0.5nm). Nevertheless, these instruments, the Global Ozone Monitoring Instrument 2 (GOME-2) and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), offer a unique opportunity to compare red and far-red terrestrial SIF at regional spatial scales. Terrestrial SIF has been estimated with ground-, aircraft-, or satellite-based instruments by measuring the filling-in of atmospheric andor solar absorption spectral features by SIF. Our approach makes use of the oxygen (O2) gamma band that is not affected by SIF. The SIF-free O2 gamma band helps to estimate absorption within the spectrally variable O2 B band, which is filled in by red SIF. SIF also fills in the spectrally stable solar Fraunhofer lines (SFLs) at wavelengths both inside and just outside the O2 B band, which further helps to estimate red SIF emission. Our approach is then an extension of previous approaches applied to satellite data that utilized only the filling-in of SFLs by red SIF. We conducted retrievals of red SIF using an extensive database of simulated radiances covering a wide range of conditions. Our new algorithm produces good agreement between the simulated truth and retrievals and shows the potential of the O2 bands for noise reduction in red SIF retrievals as compared with approaches that rely solely on SFL filling. Biases seen with existing satellite data, most likely due to instrumental artifacts that vary in time, space, and with instrument, must be addressed in order to obtain reasonable results. Our 8-year record of red SIF observations over land with the GOME-2 allows for the first time reliable global mapping of monthly anomalies. These anomalies are shown to have similar spatiotemporal structure as those in the far red, particularly for drought-prone regions. There is a somewhat larger percentage response in the red as compared with the far red for these areas that are drought sensitive. We also demonstrate that good-quality ocean fluorescence line height retrievals can be achieved with GOME-2, SCIAMACHY, and similar instruments by utilizing the full complement of radiance measurements that span the red SIF emission feature.

spatiotemporal structure↗
NASA NTRS2016

Satellite Communications for Unmanned Aircraft C2 Links: C-Band, Ku-Band and Ka-Band

Unmanned aircraft (UA) that require access to controlled (or non-segregated) airspace require a highly reliable and robust command and control (C2) link, operating over protected aviation spectrum. While operating within radio line-of-sight (LOS) UA can make use of air-to-ground C2 links to terrestrial stations. When operating beyond LOS (BLOS) where a group of networked terrestrial stations does not exist to provide effective BLOS coverage, a satellite communications link is required. Protected aviation spectrum for satellite C2 links has only recently been allocated in bands where operational satellites exist. A previously existing C-Band allocation covers a bands where there are currently no operational satellites. The new allocations, within the Fixed Satellite Service bands at Ku and Ka-Bands will not be finalized until 2023 due to the need for the development of standards and technical decisions on the operation of UA satellite C2 links within these bands. This paper provides an overview of BLOS satellite C2 links, some of the conditions which will need to be met for the operation of such links, and a look at some aspects of spectrum sharing which may constrain these operations.

radiofrequency spectrum↗
NASA NTRS2017

Transforming Satellite Data into Weather Forecasts

A NASA project spans the gap between research and operations, introducing new composites of satellite imagery to weather forecasters to prepare for the next generation of satellites. Satellite imagery has been an immense benefit to weather forecasters. With it, they can assess aviation hazards such as low clouds, monitor thunderstorms, and track the evolution of dust plumes. Satellite sensors are continually evolving to provide ever greater imaging capabilities, and researchers continue to develop advanced techniques to identify hazards in satellite imagery. However, barriers can prevent experimental products from reaching forecasters in the operational environment. A NASA project has developed an interactive process whereby weather forecasters learn to interpret the latest satellite imagery and apply it to their operations. Forecasters then provide feedback to the researchers who are developing algorithms and products to further improve future products. This effort has taken on greater importance with the anticipated launch of a new series of satellites that will provide substantially greater amounts of data than are currently available.

Emily Berndt↗
NASA NTRS2014

Nodes - Network & Operation Demonstration Satellite

Nodes is a technology demonstration mission that will launch from the International Space Station (ISS) in early 2015 and will demonstrate new network capabilities critical to the operation of swarms of multiple spacecraft. Nodes continues the legacy of the PhoneSat series of small satellites that first introduced and successfully implemented the use of Android Smartphone technology to perform many of the spacecraft functions previously accomplished through custom technology development efforts. The Nodes mission consists of two 1.5-unit (1.5U) nanosatellites each weighing approximately 2 kilograms (4 pounds) and measuring 10 centimeters by 10 centimeters by 15 centimeters. The Nodes spacecraft are derived from the hardware and software developed for the EDSN (Edison Demonstration of Smallsat Networks) mission (a swarm of eight spacecraft). Each Node utilizes the Android operating system with EDSN-specific software programmed to perform command and data handling tasks that allow the satellites to 1) relay ground commands through one satellite to the second satellite, 2) collect and relay science data from each satellite to the ground station, and 3) autonomously determine which of the two satellites is best suited to control the space network and relay data to the ground (“Captain”) and notify the ground system and second satellite (“Lieutenant”) of the result.

Network and Operations↗
NASA NTRS2019

Trends in Global Tropospheric Ozone Inferred from a Composite Record of TOMS/OMI/MLS/OMPS Satellite Measurements and the MERRA-2 GMI Simulation

Past studies have suggested that ozone in the troposphere has increased globally throughout much of the 20th century due to increases in anthropogenic emissions and transport. We show, by combining satellite measurements with a chemical transport model, that during the last four decades tropospheric ozone does indeed indicate increases that are global in nature, yet still highly regional. Satellite ozone measurements from Nimbus-7 and Earth Probe Total Ozone Mapping Spectrometer (TOMS) are merged with ozone measurements from the Aura Ozone Monitoring Instrument/Microwave Limb Sounder (OMI/MLS) to determine trends in tropospheric ozone for 1979–2016. Both TOMS (1979–2005) and OMI/MLS (2005–2016) depict large increases in tropospheric ozone from the Near East to India and East Asia and further eastward over the Pacific Ocean. The 38-year merged satellite record shows total net change over this region of about +6 to +7 Dobson units (DU) (i.e., ∼15 %–20 % of average background ozone), with the largest increase (∼4 DU) occurring during the 2005–2016 Aura period. The Global Modeling Initiative (GMI) chemical transport model with time-varying emissions is used to aid in the interpretation of tropospheric ozone trends for 1980–2016. The GMI simulation for the combined record also depicts the greatest increases of +6 to +7 DU over India and East Asia, very similar to the satellite measurements. In regions of significant increases in tropospheric column ozone (TCO) the trends are a factor of 2–2.5 larger for the Aura record when compared to the earlier TOMS record; for India and East Asia the trends in TCO for both GMI and satellite measurements are ∼+3 DU decade(exp −1) or greater during 2005–2016 compared to about +1.2 to +1.4 DU decade(exp −1) for 1979–2005. The GMI simulation and satellite data also reveal a tropospheric ozone increases in ∼+4 to +5 DU for the 38-year record over central Africa and the tropical Atlantic Ocean. Both the GMI simulation and satellite-measured tropospheric ozone during the latter Aura time period show increases of ∼+3 DU decade−1 over the N Atlantic and NE Pacific.

Ziemke, Jerald R.↗
NASA NTRS2019

Assessment of Satellite Sea Surface Salinity Products Using a Coupled ENSO Prediction Model

Much work has gone into revising and updating algorithms for converting satellite-measured radiances to useful ocean variables like sea surface salinity (e.g. SMOS - Boutin et al., 2017, SMAP - Fore et al., 2016 and Aquarius - Meissner et al., 2018). As part of our Ocean Salinity Science Team work, we utilize an intermediate-complexity air/sea coupled model as a transfer function to test if more mature satellite SSS model algorithms actually improve ENSO forecast skill. For initialization of the coupled forecast, we demonstrate that the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. In addition, salting near the ITCZ leads to a deepening of the mixed layer and thermocline near 8N. These patterns together provide the background state to amplify equatorial Kelvin waves and improve ENSO hindcasts (Hackert et al., 2019). Here we extend this work to compare the impact of various pairs of original and improved satellite SSS algorithms. For instance we compare SMAP V4.1 with the latest, SMAP V4.2, to see what impact algorithm improvements may have on ENSO forecasts. SSS observations are tested on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts by initializing twelve-month forecasts for each month of available data. All experiments assimilate satellite sea level (SL), sea surface temperature (SST), and in situ subsurface temperature and salinity observations (Tz, Sz). Additionally various satellite, blended, and in-situ SSS products are assimilated. We find that including satellite SSS significantly improves Niño3.4 sea surface temperature anomaly validation, more mature SSS model algorithms are generally improving ENSO forecasts over time, and more satellite SSS data coverage helps to extend useful forecasts.

Ocean↗
NASA NTRS2019

A New Discrete Wavelength BUV Algorithm for Consistent Volcanic SO2 Retrievals from Multiple Satellite Missions

This paper describes a new discrete wavelength algorithm developed for retrieving volcanic sulfur dioxide (SO2) vertical column density (VCD) from UV observing satellites. The Multi-Satellite SO2 algorithm (MS_SO2) simultaneously retrieves column densities of sulfur dioxide, ozone, and Lambertian effective reflectivity (LER) and its spectral dependence. It is used operationally to process measurements from the heritage Total Ozone Mapping Spectrometer (TOMS) onboard NASA's Nimbus-7 satellite (N7/TOMS: 1978-1993) and from the current Earth Polychromatic Imaging Camera (EPIC) onboard Deep Space Climate Observatory (DSCOVR: 2015-) from the Earth-Sun Lagrange (L1) orbit. Results from MS_SO2 algorithm for several volcanic cases were assessed using the more sensitive principal component analysis (PCA) algorithm. The PCA is an operational algorithm used by NASA to retrieve SO2 from hyperspectral UV spectrometers, such as the Ozone Monitoring Instrument (OMI) onboard NASA's Earth Observing System Aura satellite and Ozone Mapping and Profiling Suite (OMPS) onboard NASA-NOAA Suomi National Polar Partnership (SNPP) satellite. For this comparative study, the PCA algorithm was modified to use the discrete wavelengths of the Nimbus-7/TOMS instrument, described in Sect. S1 of the Supplement. Our results demonstrate good agreement between the two retrievals for the largest volcanic eruptions of the satellite era, such as the 1991 Pinatubo eruption. To estimate SO2 retrieval systematic uncertainties, we use radiative transfer simulations explicitly accounting for volcanic sulfate and ash aerosols. Our results suggest that the discrete-wavelength MS_SO2 algorithm, although less sensitive than hyperspectral PCA algorithm, can be adapted to retrieve volcanic SO2 VCDs from contemporary hyperspectral UV instruments, such as OMI and OMPS, to create consistent, multi-satellite, long-term volcanic SO2 climate data records.

Bradford L Fisher↗
NASA NTRSDate not supplied

The Satellite Flythrough and Reconstruction Softwares at CCMC

The next-generation of model data visualization to be offered at the Community Coordinated Modeling Center (CCMC) will be based on Kamodo, an open source python package. To increase the usefulness of our services, we are also developing new capabilities based on this software, called the satellite flythrough and the reconstruction tools, to be offered both as packages for offline analysis and through an online interface (coming soon). The satellite flythrough software ‘flies’ a satellite trajectory, whether real or imaginary, through either model data hosted at CCMC or on a personal machine. This service greatly simplifies the complexity of users’ access to model data, abstracting away the time-consuming details of model data formats and interpolation. We demonstrate execution times of a few seconds to a few minutes for several example flythroughs of a trajectory stretching over a few days, depending on the parameters chosen. We also demonstrate a reconstruction tool built on top of the satellite flythrough software, for use with mission planning and model-data comparisons. This tool, based on reconstructions provided for the GDC Science and Technology Definition Team, converts multiple, simultaneous satellite flythroughs into two-dimensional reconstructions. The reconstruction tool provides a software capability for satellite constellations to determine how many satellites are needed and in what configuration to resolve the desired features in the model data. Both tools are currently available through GitHub for a selection of CCMC-hosted ITM models. Finally, we present initial results from work in progress and plans for future work, including an expansion of the reconstruction tool to provide 3D reconstruction capabilities and a line-of-sight calculation tool.

software, python↗
NASA NTRS2021

The Salinity Pilot-Mission Exploitation Platform (Pi-MEP): A Hub for Validation and Exploitation of Satellite Sea Surface Salinity Data

The Pilot-Mission Exploitation Platform (Pi-MEP) for salinity is an ESA initiative originally meant to support and widen the uptake of Soil Moisture and Ocean Salinity (SMOS) mission data over the ocean. Starting in 2017, the project aims at setting up a computational web-based platform focusing on satellite sea surface salinity data, supporting studies on enhanced validation and scientific process over the ocean. It has been designed in close collaboration with a dedicated science advisory group in order to achieve three main objectives: gathering all the data required to exploit satellite sea surface salinity data, systematically producing a wide range of metrics for comparing and monitoring sea surface salinity products’ quality, and providing user-friendly tools to explore, visualize and exploit both the collected products and the results of the automated analyses. The Salinity Pi-MEP is becoming a reference hub for the validation of satellite sea surface salinity missions by providing valuable information on satellite products (SMOS, Aquarius, SMAP), an extensive in situ database (e.g., Argo, thermosalinographs, moorings, drifters) and additional thematic datasets (precipitation, evaporation, currents, sea level anomalies, sea surface temperature, etc.). Co-localized databases between satellite products and in situ datasets are systematically generated together with validation analysis reports for 30 predefined regions. The data and reports are made fully accessible through the web interface of the platform. The datasets, validation metrics and tools (automatic, user-driven) of the platform are described in detail in this paper. Several dedicated scientific case studies involving satellite SSS data are also systematically monitored by the platform, including major river plumes, mesoscale signatures in boundary currents, high latitudes, semi-enclosed seas, and the high-precipitation region of the eastern tropical Pacific. Since 2019, a partnership in the Salinity Pi-MEP project has been agreed between ESA and NASA to enlarge focus to encompass the entire set of satellite salinity sensors. The two agencies are now working together to widen the platform features on several technical aspects, such as triple-collocation software implementation, additional match-up collocation criteria and sustained exploitation of data from the SPURS campaigns

ocean↗
NASA NTRS2022

Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters using a Deep Neural Network

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) series, have been observing severe convection at 15–60-minute intervals for over 40 years. When properly assessed, such a data record can be valuable in efforts of estimating severe storm risk throughout the diurnal cycle based on automated detection of patterns consistently found atop severe storms. Furthermore, environmental conditions favorable for severe weather are well-known and are thought to be represented well by modern reanalysis products. Promoting resilience against such hazards on local and global scales is a chief goal the NASA Disasters program, which seeks to encourage use of satellite observations to mitigate risk. For instance, hail is the costliest severe weather hazard across the globe in terms of insured loss, but reporting inconsistencies for hail events globally make it difficult to develop models that can quantify the risk. Satellite observation and model reanalysis taken together have the potential to, with reasonable skill and specificity, characterize environmental conditions that are favorable for hazardous weather, and thereby enable creation of hazard climatologie. Such climatologies are particularly useful over regions without extensive radar networks or storm reporting. By mapping the multivariate combination of observed cloud features and reanalysis environmental parameters/indices to United States Next Generation Weather Radar (NEXRAD) radar-estimated Maximum Expected Size of Hail (MESH) by way of a deep neural network (DNN), estimates of likelihood for potentially severe hail can be produced. Such estimates are of greater complexity and efficiency than could be performed with previous multivariate or logistic regression analyses for observed points within convective systems. Statistical distributions of convective parameters from satellite and reanalysis are shown to highlight non-severe/severe class separation for well-known hailstorm predictors, e.g., overshooting cloud top characteristics, deep-layer wind shear, mid-level stability, helicity, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN, which can efficiently produce a quantitative hail risk metric with better than 70% detection rate and under 30% false alarms. These hail classifications can then be aggregated across the satellite record to yield a hazard climatology for hail frequency and severity – knowledge of which is of particular interest to those who manage risk (e.g., insurers) and are seeking opportunities to identify hail-prone regions, particularly in developing nations. This NASA study uses satellite observations and model parameters in a DNN to perform climatological hailstorm analysis in support of catastrophe model development, with the hope of promoting risk resilience particularly in regions without adequate weather radar coverage.

Passive Remote Sensing↗
NASA NTRS2021

Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions

Wetland methane (CH4) emissions comprise about one-third of the global CH4 source. The latitudinal distribution and climate sensitivity of wetland CH4 fluxes are the key determinants of the global CH4-climate feedback. However, large differences exist between bottom-up estimates, informed by ground-based flux measurements, and top-down estimates derived from spaceborne total column CH4. Despite the extensive coverage of satellite CH4 concentration observations, challenges remain with using top-down estimates to test bottom-up models, mainly because of the uncertainties in the satellite retrievals, the model representation errors, the variable prior emissions, and the confounding role of the posterior error covariance structures. Here, we use satellite-based top-down CH4 flux estimates (2010–2012) to test and refine 42 bottom-up estimates of wetland emissions that use a range of hypothesized wetland extents and process controls. Our comparison between bottom-up models and satellite-based fluxes innovatively accounts for cross-correlations and spatial uncertainties typically found in top-down inverse estimates, such that only the information from satellite observations and the atmospheric transport model is kept as a constraint. We present a satellite-constrained wetland CH4 ensemble product derived from assembling the highest-performance bottom-up models, which estimates global wetland CH4 emissions of 148 (117–189, 5th–95th percentile) Tg CH4 yr−1. We find that tropical wetland emissions contribute 72% (63%–85%) to the global wetland total. We also find that a lower-than-expected temperature sensitivity agrees better with atmospheric CH4 measurements. Overall, our approach demonstrates the potential for using satellites to quantitatively refine bottom-up wetland CH4 emission estimates, their latitudinal distributions, and their sensitivity to climate.

wetland ch4↗
NASA NTRSDate not supplied

Open Source Application of Fusing Aerosol Products from GEO and LEO Satellites

Retrieving aerosol optical depths (AODs) from sun-synchronous polar orbiting (aka low earth orbit, LEO) satellites, such as MODISs, and VIIRSs, OMI, TROPOMI, etc, has become well-established as a tool for extracting information on particulate matter (PM) and related processes in the atmosphere. However, with recently launched geostationary satellites (GEO), such as GOES-16/17/18, and Himawari-8/9, and Meteosat Third Generation (MTG) they provide a much higher temporal resolution (order of 10 minutes), typically an image once or more per hour during daylight compared to LEO once per day. By combining these observations, we may be able to characterize the diurnal cycle of global AOD at the local, regional and global scale. While the science community is still exploring the new data from GEO observations, we have been thinking about how to properly combine/merge/fuse those data considering differences in their spatial and temporal resolutions. However, this poses a “Big Data” challenge. The big data challenge is not just about data storage, but also about data discoverability, and accessibility, and even more, about data migration/mirroring in the cloud-computing environment. This paper is merely showing some of the efforts and approaches we have attempted in fusing six satellites’ Level 2 aerosol data (three are from GEO (GOES-16/17 and Himawari-8), and the other three are from LEO (TERRA/MODIS, AQUA/MODIS, SNPP-VIIRS) from Dark Target (DT) aerosol retrieval algorithm. Having the on-demand capability of fusing remote sensing products onto the desired temporal and spatial domain enables researchers and application practitioners to better manipulate and work with satellite and sensor data. It is our hopeWe hope that by making such an open-source package, and the accompanying functionality, the scientific community will be granted easier access to aerosol data processing resources. The MEaSUREs Program (Making Earth System Data Records for Use in Research Environments) expands our understanding of the Earth's current system through atmospheric and surface measurements. In an effort to aid the scientific research component and improve open source methods, this project developed Python code for fusing six satellite Level 2 aerosol data (three are from geostationary satellites (GEO), and the other three are from low earth orbital satellites (LEO)) from Dark Target Aerosol Retrieval Algorithm.

Jennifer Wei↗