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NASA NTRS2011

The GOES-R GeoStationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms (environmental data records), cal/val performance monitoring tools, and new applications using GLM alone, in combination with the ABI, merged with ground-based sensors, and decision aids augmented by numerical weather prediction model forecasts. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. An international field campaign planned for 2011-2012 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Goodman, Steven J.↗

NASA NTRS2011

The Goes-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved storm diagnostic capability with the Advanced Baseline Imager. The GLM will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. In this paper we will report on new Nowcasting and storm warning applications being developed and evaluated at various NOAA Testbeds.

Goodman, Steven J.↗

NASA NTRS2011

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. A major advancement over the current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM). The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Science Team and Algorithm Working Group Lightning Applications Team have begun to develop cal/val performance monitoring tools and new applications using the GLM alone, in conjunction with other instruments, and merged or blended integrated observing system products combining satellite, radar, in-situ and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms.

Goodman, Steven↗

NASA NTRS2011

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

Goodman, Steven J.↗

NASA NTRS2012

Safety Risk Knowledge Elicitation in Support of Aeronautical R and D Portfolio Management: A Case Study

Aviation is a problem domain characterized by a high level of system complexity and uncertainty. Safety risk analysis in such a domain is especially challenging given the multitude of operations and diverse stakeholders. The Federal Aviation Administration (FAA) projects that by 2025 air traffic will increase by more than 50 percent with 1.1 billion passengers a year and more than 85,000 flights every 24 hours contributing to further delays and congestion in the sky (Circelli, 2011). This increased system complexity necessitates the application of structured safety risk analysis methods to understand and eliminate where possible, reduce, and/or mitigate risk factors. The use of expert judgments for probabilistic safety analysis in such a complex domain is necessary especially when evaluating the projected impact of future technologies, capabilities, and procedures for which current operational data may be scarce. Management of an R&D product portfolio in such a dynamic domain needs a systematic process to elicit these expert judgments, process modeling results, perform sensitivity analyses, and efficiently communicate the modeling results to decision makers. In this paper a case study focusing on the application of an R&D portfolio of aeronautical products intended to mitigate aircraft Loss of Control (LOC) accidents is presented. In particular, the knowledge elicitation process with three subject matter experts who contributed to the safety risk model is emphasized. The application and refinement of a verbal-numerical scale for conditional probability elicitation in a Bayesian Belief Network (BBN) is discussed. The preliminary findings from this initial step of a three-part elicitation are important to project management practitioners as they illustrate the vital contribution of systematic knowledge elicitation in complex domains.

Shih, Ann T.↗

NASA NTRS2013

SPoRT Participation in the GOES-R and JPSS Proving Grounds

For the last several years, the NASA Short-term Prediction Research and Transition (SPoRT) project at has been working with the various algorithm working groups and science teams to demonstrate the utility of future operational sensors for GOES-R and the suite of instruments for the JPSS observing platforms. For GOES-R, imagery and products have been developed from polar-orbiting sensors such as MODIS and geostationary observations from SEVIRI, simulated imagery, enhanced products derived from existing GOES satellites, and data from ground-based observing systems to generate pseudo or proxy products for the ABI and GLM instruments. The suite of products include GOES-POES basic and RGB hybrid imagery, total lightning flash products, quantitative precipitation estimates, and convective initiation products. SPoRT is using imagery and products from VIIRS, CrIS, ATMS, and OMPS to show the utility of data and products from their operational counterparts on JPSS. The products include VIIRS imagery in swath form, the GOES-POES hybrid, a suite of RGB products including the air mass RGB using water vapor and ozone channels from CrIS, and several DNB products. Over a dozen SPoRT collaborative WFOs and several National Centers are involved in an intensive evaluation of the operational utility of these products.

Jedlovec, Gary↗

NASA NTRS2014

EVA Suit R and D for Performance Optimization

Designing a planetary suit is very complex and often requires difficult trade‐offs between performance, cost, mass, and system complexity. To verify that new suit designs meet requirements, full prototypes must be built and tested with human subjects. However, numerous design iterations will occur before the hardware meets those requirements. Traditional draw‐prototype‐test paradigms for R&D are prohibitively expensive with today's shrinking Government budgets. Personnel at NASA are developing modern simulation techniques which focus on human‐centric designs by creating virtual prototype simulations and fully adjustable physical prototypes of suit hardware. During the R&D design phase, these easily modifiable representations of an EVA suit's hard components will allow designers to think creatively and exhaust design possibilities before they build and test working prototypes with human subjects. It allows scientists to comprehensively benchmark current suit capabilities and limitations for existing suit sizes and sizes that do not exist. This is extremely advantageous and enables comprehensive design down‐selections to be made early in the design process, enables the use of human performance as design criteria, and enables designs to target specific populations

Cowley, Matthew S.↗

NASA NTRS2014

Ar-40/Ar-39 Age of Hornblende-bearing R Chondrite LAP 04840

Chondrites have a complex chronology due to several variables affecting and operating on chondritic parent bodies such as radiogenic heating, pressure and temperature variation with depth, aqueous alteration, and shock or impact heating [1]. Unbrecciated chondrites can record ages from 4.56 to 4.4 Ga that represent cooling in small parent bodies. Some brecciated chondrites exhibit younger ages (<<4 to 4.4 Ga) that may reflect the age of brecciation, disturbance, or shock and impact events (<< 4 Ga). A unique R chondrite was recently found in the LaPaz Icefield of Antarctica - LAP 04840 [2]. This chondrite contains approx.15% hornblende and trace amounts of biotite, making it the first of its kind. Studies have revealed an equigranular texture, mineral equilibria yielding equilibration near 650-700 C and 250-500 bars, hornblende that is dominantly OH-bearing (very little Cl or F), and high D/H ratios [8,9,10]. To help gain a better understanding of the origin of this unique sample, we have measured the Ar-40/Ar-39 age. Age of 4.290 +/- 0.030 Ga is younger than one would expect for a sample that has cooled within a small body [4], and one might instead attribute the age to a younger shock event, On the other hand, there is no evidence for extensive shock in this meteorite (shock stage S2; [3]), so this sample may have been reannealed after the shock event. This age is similar to Ar-Ar ages determined for some other R chondrites

Righter, K.↗

NASA NTRS2014

Colorado Lightning Mapping Array Collaborations through the GOES-R Visiting Scientist Program

For the past two years, the GOES‐R Proving Ground has solicited proposals for its Visiting Scientist Program. NASA's Short‐term Prediction Research and Transition (SPoRT) Center has used this opportunity to support the GOES‐R Proving Ground by expanding SPoRT's total lightning collaborations. In 2012, this expanded the evaluation of SPoRT's pseudo‐geostationary lightning mapper product to the Aviation Weather Center and Storm Prediction Center. This year, SPoRT has collaborated with the Colorado Lightning Mapping Array (COLMA) and potential end users. In particular, SPoRT is collaborating with the Cooperative Institute for Research in the Atmosphere (CIRA) and Colorado State University (CSU) to obtain these data in real‐time. From there, SPoRT is supporting the transition of these data to the local forecast offices in Boulder, Colorado and Cheyenne, Wyoming as well as to Proving Ground projects (e.g., the Hazardous Weather Testbed's Spring Program and Aviation Weather Center's Summer Experiment). This presentation will focus on the results of this particular Visiting Scientist Program trip. In particular, the COLMA data are being provided to both forecast offices for initial familiarization. Additionally, several forecast issues have been highlighted as important uses for COLMA data in the operational environment. These include the utility of these data for fire weather situations, situational awareness for both severe weather and lightning safety, and formal evaluations to take place in the spring of 2014.

Stano, Geoffrey T.↗

NASA NTRS2013

Simulations of the Mid-Pliocene Warm Period Using Two Versions of the NASA-GISS ModelE2-R Coupled Model

The mid-Pliocene Warm Period (mPWP) bears many similarities to aspects of future global warming as projected by the Intergovernmental Panel on Climate Change (IPCC, 2007). Both marine and terrestrial data point to high-latitude temperature amplification, including large decreases in sea ice and land ice, as well as expansion of warmer climate biomes into higher latitudes. Here we present our most recent simulations of the mid-Pliocene climate using the CMIP5 version of the NASAGISS Earth System Model (ModelE2-R). We describe the substantial impact associated with a recent correction made in the implementation of the Gent-McWilliams ocean mixing scheme (GM), which has a large effect on the simulation of ocean surface temperatures, particularly in the North Atlantic Ocean. The effect of this correction on the Pliocene climate results would not have been easily determined from examining its impact on the preindustrial runs alone, a useful demonstration of how the consequences of code improvements as seen in modern climate control runs do not necessarily portend the impacts in extreme climates.Both the GM-corrected and GM-uncorrected simulations were contributed to the Pliocene Model Intercomparison Project (PlioMIP) Experiment 2. Many findings presented here corroborate results from other PlioMIP multi-model ensemble papers, but we also emphasize features in the ModelE2-R simulations that are unlike the ensemble means. The corrected version yields results that more closely resemble the ocean core data as well as the PRISM3D reconstructions of the mid-Pliocene, especially the dramatic warming in the North Atlantic and Greenland-Iceland-Norwegian Sea, which in the new simulation appears to be far more realistic than previously found with older versions of the GISS model. Our belief is that continued development of key physical routines in the atmospheric model, along with higher resolution and recent corrections to mixing parameterisations in the ocean model, have led to an Earth System Model that will produce more accurate projections of future climate.

climate change↗

NASA NTRS2016

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation↗

NASA NTRS2016

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Registration↗

NASA NTRS2016

Correcting GOES-R Magnetometer Data for Stray Fields

Time-varying spacecraft magnetic fields, i.e. stray fields, are a problem for magnetometer systems. While constant fields can be removed by calibration, stray fields are difficult to distinguish from ambient field variations. Putting two magnetometers on a long boom and solving for both the ambient and stray fields can help, but this gradiometer solution is more sensitive to noise than a single magnetometer. As shown here for the R-series Geostationary Operational Environmental Satellites (GOES-R), unless the stray fields are larger than the noise, simply averaging the two magnetometer readings gives a more accurate solution. If averaging is used, it may be worthwhile to estimate and remove stray fields explicitly. Models and estimation algorithms to do so are provided for solar array, arcjet and reaction wheel fields.

Magnetometer↗

NASA NTRS2019

Rotary-motion-extended Array Synthesis (R-MXAS)

R-MXAS is a revolutionary aerospace architecture for realizing a synthetic aperture imaging radiometer (SAIR) with dramatically lower SWaP than existing state-of-the-art (SOTA) methods. The space-based component of the RMXAS system (Figure 1) is a single platform comprising a 1-D sparse / decimated antenna array on a rigid tether (deployed parallel to the horizon) and one or more additional tethered antennas that rotate in a plane orthogonal to the 1-D array.The processing that correlates the data from these two antenna systems and performs image reconstruction has both space-based and ground-based components. The processing exploits the interferometric baselines formed between the rotating tethered antenna at radius R and each of the antennas of the 1-D array on the rigid tether.

Radiometer↗

NASA NTRS2019

Observations from the GOES-R Solar UltraViolet Imager Extended Coronal Imaging Campaign

Solar corona in 17.1nm and 19.5nmwavelengths up to three solar radii from Sun center was observed by the Solar UltraViolet Imager (SUVI) on the Geostationary Operational Environmental Satellite (GOES) –16 and GOES-17. The nominally Sun-pointed SUVI was off-pointed to the left and to the right of the Sun center at a regular cadence and a composite Extended Coronal Imaging (ECI) frame was created. The imaging area in the composite is about three times the nominal image area in the East-West direction (about 5*R(sub Sun) versus 1.6*R(sub Sun) for nominal images). The campaign was conducted in February (4 hours), June (72 hours), and August-September of 2018 (5 weeks). Limited solar CME activity during the 5-week campaign was observed in both the SUVI and LASCO C2 imagers. Some of the observations during this campaign include structures up to a few solar radii off the solar limb, and interesting coronal activity –both on and off the solar disk. They are presented here.

Tadikonda, Sivakumar K.↗

NASA NTRS2018

Solar Irradiance Variability, Influenced by r Modes

A spectrum of the four-decade solar irradiance record has a prominent cluster of power for periodicities near 1 yr. Correlating irradiance with a bandpass filter showed that periodicity values were not constant, but varied sinusoidally with each cycle lasting 14 ± 1 yr. The large modulation amplitude makes solar frequencies ≥1 yr(exp −1) hard to detect at the solar surface. After removing the modulation, a Lomb–Scargle spectrum exposed two true periodicities: 1.006 and 0.920 yr. They are interpreted as the synodic rotation periods of r modes of lowest angular degree (ℓ = 1). The first propagates in the stable interior and the second in the convective envelope perturbed by its several flow fields. The rotational beat period of the two modes is about 10.9 yr. This is close to the average length of a solar cycle and possibly controls this average. The 1.006 yr periodicity dominates most of the filtered irradiance record but an abrupt change to about 0.8 yr occurs in mid-2010. Also found was evidence for higher-degree r modes (ℓ = 2 to 8) and a curious sawtooth modulation with a recurrence period of 2.6 yr.

Wolff, Charles L.↗

NASA NTRS2019

Surface Emissivity Impacts on GOES-R Series Multi-Spectral Imagery Applications

Value-added imagery products from the GOES-R series Advanced Baseline Imager are used to identify features of interest for operational forecasters, including: blowing dust, smoke, volcanic ash, cloud cover, atmospheric moisture, biomass fires and snow cover. These features each have a specific spectral signal that algorithms are designed to detect, but those signals are not always unique to just a single feature. Sometimes, the surface can mimic the spectral signal associated with an atmospheric feature of interest, creating a false alarm in a value-added product which negatively impacts interpretation of that product. This case study focuses on one such situation where areas of desert in the southwestern United States mimic the positive value associated with low clouds in the Brightness Temperature Difference (BTD) between the 10.35 μm and 3.9 μm channels, producing a false alarm. In order to characterize these “false alarm” areas, this study uses the cloud-cleared background product from the Cooperative Institute for Research in the Atmosphere (CIRA) to create a dataset of the cloud-free surface. Previous results have shown that cloud-cleared backgrounds of the 10.35 μm-3.9 μm BTD have successfully identified areas of positive BTDs in the cloud-free environment, proving that it is a property of the surface emissivity and a true “false alarm”. This study builds on that previous research to further characterize the seasonality of the “false-alarm” regions and to catalogue how they impact interpretation of multi-spectral imagery products from the GOES-R series ABI, especially the Nighttime Microphysics RGB created by NASA Short-term Prediction Research and Transition (SPoRT) Center.

Burke, Angela↗

NASA NTRS2018

Development of a Guidebook in Support of the NASA R&M Standard

This paper describes a guidebook currently in development to support the application of the NASA R&M Standard [1]. NASA-STD-8729.1A identifies the objectives and strategies for how to develop a system or design that is reliable and maintainable. Rather than requiring a checklist of mandatory tasks, such as specific design or Reliability & Maintainability (R&M) analyses, the standard explains objectives that need to be accomplished, and how to accomplish the objectives in the form of strategies. Currently, the standard presents the hierarchy without defining or explaining elements, or how to use the hierarchy efficiently. This is where this accompanying guideline comes into play; the guideline helps clarify through discussion and examples the standard in more detail, and how to apply it in real world situations that engineers face every day.

DiVenti, Anthony↗