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NASA NTRS1986

Vertical structure of the wind field during the Special Observing Period I of the Global Weather Experiment

The vertical structure of the global atmosphere is analyzed for selected periods of the Special Observing Period I (SOP-I) for the Global Weather Experiment (GWE). The analysis consists of projection of the stream-function and velocity potential at 200 and 850 mb on spherical harmonics and of the wind and height fields on the normal modes of a linearized form of the primitive equations for a basic state at rest. The kinematic vertical structure is discussed in terms of correlation coefficients of the 200 mb and 850 mb winds and analysis of the internal and external normal modes of the primitive equations. The reliability of the results is checked by applying the same analysis methods to data sets obtained from three different institutions: Geophysical Fluid Dynamics Laboratory (GFDL), European Center for Medium Range Weather Forecasting (ECMWF), and Goddard Laboratory for the Atmospheres (GLA). It is found that, on a global basis, vertically reversing circulations are as important as the equivalent barotropic structures. For the verticaly reversing components, the gravity and mixed Rossby-gravity modes have contributions of the same order of magnitude as those of the Rossby modes in tropical latitudes.

Paegle, J. N.↗

NASA NTRS2019

Towards the Development of Real-Time Normalized Burn Ratio (NBR) and Delta NBR Imagery from GOES-16/17 and S-NPP

Burned landscapes present difficult hydrologic forecasting challenges for National Weather Service Offices. Burned soils and landscapes can be conducive to the development of flash flooding and landslides from heavy precipitation events. The severity of the burn scar can be directly related to the risk for debris flows and flash flooding. Burned Area Reflectance Classification (BARC) map is generated to indicate the degree of burn severity, which is generated initially by high-resolution satellite imagery from sources such as Landsat, and later by labor-intensive efforts conducted at the burn scar by Burned Area Emergency Response (BAER) teams. The challenge for operational meteorologists is that these sources of information are not readily available in near real-time. Landsat imagery, for example, may only be available about once every eight days, and cloudy conditions can obstruct the observation of the burn scar during a single pass. BAER teams cannot conduct assessments until the wildfire has been at least 40 percent contained (up to 80 percent in some regions), and the process itself can take further days to weeks to complete depending on a number of factors. To help remedy this lapse in knowledge, NASA SPoRT has developed the generation of NBR imagery in the Advanced Weather Interactive Processing System (AWIPS) using data from the operational GOES 16 and 17 satellites and S-NPP. This presentation will discuss the development of the GOES- and SNPP-derived NBR and dNBR imagery and their initial evaluation by real-time decision makers.

Berndt, Emily↗

DOE OSTI2023

Multi-scenario Extreme Weather Simulator application to heat waves: Ko’olauloa community resilience hub

Heat waves are increasing in severity, duration, and frequency. The Multi-Scenario Extreme Weather Simulator (MEWS) models this using historical data, climate model outputs, and heat wave multipliers. In this study, MEWS is applied for planning of a community resilience hub in Hau'ula, Hawaii. The hub will have normal operations and resilience operations modes. Both these modes were modeled using EnergyPlus. The resilience operations mode includes cutting off air conditioning for many spaces to decrease power requirements during emergencies. Results were simulated for 300 future weather files generated by MEWS for 2020, 2040, 2060, and 2080. Shared socioeconomic pathways 2-4.5, 3-7.0 and 5-8.5 were used. The resilience operations mode results show two to six times increase of hours of exceedance beyond 32.2 °C from present conditions, depending on climate scenario and future year. The resulting decrease in thermal resilience enables an average decrease of energy use intensity of 26% with little sensitivity to climate change. The decreased thermal resilience predicted in the future is undesirable, but was not severe enough to require a more energy-intensive resilience mode. Instead, planning is needed to assure vulnerable individuals are given prioritized access to air-conditioned parts of the hub if worst-case heat waves occur.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2012

P69 Using the NASA-Unified WRF to Assess the Impacts of Real-Time Vegetation on Simulations of Severe Weather

Since June 2010, the NASA Short-term Prediction Research and Transition (SPoRT; Goodman et al. 2004; Darden et al. 2010; Stano et al. 2012; Fuell et al. 2012) Center has been generating a real-time Normalized Difference Vegetation Index (NDVI) and corresponding Green Vegetation Fraction (GVF) composite based on reflectances from NASA s Moderate Resolution Imaging Spectroradiometer (MODIS) instrument. This dataset is generated at 0.01 resolution across the Continental United States (CONUS), and updated daily. The goal of producing such a vegetation dataset is to improve over the default climatological GVF dataset in land surface and numerical weather prediction models, in order to have better simulations of heat and moisture exchange between the land surface and the planetary boundary layer. Details on the SPoRT/MODIS vegetation composite algorithm are presented in Case et al. (2011). Vegetation indices such as GVF and Leaf Area Index (LAI) are used by land surface models (LSMs) to represent the horizontal and vertical density of plant vegetation (Gutman and Ignatov 1998), in order to calculate transpiration, interception and radiative shading. Both of these indices are related to the NDVI; however, there is an inherent ambiguity in determining GVF and LAI simultaneously from NDVI, as described in Gutman and Ignatov (1998). One practice is to specify the LAI while allowing the GVF to vary both spatially and temporally, as is done in the Noah LSM (Chen and Dudhia 2001; Ek et al. 2003). Operational versions of Noah within several of the National Centers for Environmental Prediction (NCEP) global and regional modeling systems hold the LAI fixed, while the GVF varies according to a global monthly climatology. This GVF climatology was derived from NDVI data on the NOAA Advanced Very High Resolution Radiometer (AVHRR) polar orbiting satellite, using information from 1985 to 1991 (Gutman and Ignatov 1998; Jiang et al. 2010). Representing data at the mid-point of every month, the climatological dataset is on a grid with 0.144 (~16 km) spatial resolution and is distributed with the community WRF model (Ek et al. 2003; Jiang et al. 2010; Skamarock et al. 2008).

Case, Jonathan L.↗

NASA NTRS1981

Development and evaluation of automatic landing control laws for power lift STOL aircraft

A series of investigations were conducted to generate and verify through ground bases simulation and flight research a data base to aid in the design and certification of advanced propulsive lift short takeoff and landing aircraft. Problems impacting the design of powered lift short haul aircraft that are to be landed automatically on STOL runways in adverse weather were examined. An understanding of the problems was gained by a limited coverage of important elements that are normally included in the certification process of a CAT 3 automatic landing system.

Feinreich, B.↗

NASA NTRS1999

The 1997-98 El Nino Event and Related Wintertime Lightning Variations in the Southeastern United States

The El Nino Southern Oscillation (ENSO) is a climate anomaly responsible for world-wide weather impacts ranging from droughts to floods. In the United States, warm episode years are known to produce above normal rainfall along the Southeast US Gulf Coast and into the Gulf of Mexico, with the greatest response observed in the October-March period of the latest warm-episode year. The 1997-98 warm episode, notable for being the strongest event since 1982-83, presents our first opportunity to examine the response to a major ENSO event and determine the variation of wintertime thunderstorm activity in this part of the world. Due to the recent launch of a lightning sensor on NASA's Tropical Rainfall Measuring Mission (TRMM) in November 1997 and the expanded coverage of the National Lightning Detection Network (NLDN), we are able to examine such year-to-year changes in lightning activity with far greater detail than ever before.

Goodman, S. J.↗

NASA NTRS1999

The 1997-98 El-Nino Event and Related Lightning Variations in the Southeastern United States

The El Nino Southern Oscillation (ENSO) is a climate anomaly responsible for world-wide weather impacts ranging from droughts to floods. In the United States, warm episode years are known to produce above normal rainfall along the Southeast US Gulf Coast and into the Gulf of Mexico, with the greatest response observed in the October-March period of the current warm-episode year. The 1997-98 warm episode, notable for being the strongest event since 1982-83, presents our first opportunity to examine the response to a major ENSO event and determine the variation of wintertime thunderstorm activity in this part of the world. Due to the recent launch of a lightning sensor on NASA's Tropical Rainfall Measuring Mission (TRMM) in November 1997 and the expanded coverage of the National Lightning Detection Network (NLDN), we are able to examine such year-to-year changes in lightning activity with far greater detail than ever before.

Buechler, D. E.↗

NASA NTRS1999

The 1997-98 El Nino Event and Related Wintertime Lightning Variations in the Southeastern United States

The El Nino Southern Oscillation (ENSO) is a climate anomaly responsible for world-wide weather impacts ranging from droughts to floods. In the United States, warm episode years are known to produce above normal rainfall along the Southeast US Gulf Coast and into the Gulf of Mexico, with the greatest response observed in the October-March period of the latest warm-episode year. The 1997-98 warm episode is notable for being the strongest event since 1982-83. With the recent launch of a lightning sensor on NASA's Tropical Rainfall Measuring Mission (TRMM) in November 1997 and the expanded coverage of the National Lightning Detection Network (NLDN), such year-to-year changes in lightning activity can be examined with far greater detail than ever before. For the recent ENSO event the greatest year-to-year changes in lightning frequency occur within a broad swath across the northern Gulf of Mexico basin where there is nearly a 200% increase in lightning days year-to-year (35 days in 1997-98 vs. 13 days in 1996-97) and a 200% increase in lightning hours (150 hours vs. 50). These changes occur in association with a 100% increase in the number of synoptic scale cyclones and an anomalously strong jet stream encompassing much of the Gulf basin.

Goodman, S. J.↗

NASA NTRS2000

The 1997-98 El Nino Event and Related Wintertime Lightning Variations in the Southeastern United States

The El Nino Southern Oscillation (ENSO) is a climate anomaly responsible for worldwide weather impacts ranging from droughts to floods. In the United States, warm episode years are known to produce above normal rainfall along the Southeast U.S. Gulf Coast and into the Gulf of Mexico, with the greatest response observed in the October-March period of the warm episode year. The 1997-98 warm episode is notable for being the strongest event since 198283. With the recent launch of a lightning sensor on NASA's Tropical Rainfall Measuring Mission (TRMM) in November 1997 and the detailed coverage of the U.S. National Lightning Detection Network (NLDN), such interannual changes in lightning activity can be examined with far greater detail than ever before. For the 1997-98 ENSO event the most significant year-to-year changes in lightning frequency worldwide occurred along the Gulf Coast and within the Gulf of Mexico basin during the Northern Hemisphere winter. Within a broad swath across the northern Gulf of Mexico basin there is a 100-150% increase in lightning days year-to-year (a peak of 33 days in the winter of 1997-98 vs. only 15 days or fewer in both the 1996-97 and 1998-99 winter). In addition, there is a nearly 200% increase in lightning hours (a peak of 138 hours in 1996-97 vs. 50 hours in both 1996-97 and 1998-99). The increase in lightning activity during ENSO occurs in association with a 100% increase in the number of synoptic scale cyclones that developed within or moved through the Gulf basin. The primary variables controlling these enhancements in thunderstorm activity are the position and strength of the jet stream.

Goodman, S. J.↗

NASA NTRS1937

A Study of Transparent Plastics for use on Aircraft, Special Report

Various transparent organic plastics, including both commercially available and experimental materials, have been examined to determine their suitability for use as flexible windshields on aircraft, The properties which have been studied include light transmission, haziness, distortion, resistance to weathering, scratch and indentation hardness, impact strength, dimensional stability, resistance to water and various cleaning fluids, bursting strength at normal and low temperatures, and flammability.

Axilrod, Benjamin M.↗

DOE OSTI2024

A Novel Concentrating Solar Weathering Apparatus for Experimental Validation of Multi-Modal Degradation Models

High-performance coatings for Concentrating Solar Power (CSP) receivers are subjected to remarkable environmental stressors during normal operations. Applied to the receiver tubes, these coatings serve to maximize the solar absorptivity of the receiver, transferring as much heat as possible from the solar collectors into the heat-transfer fluid (HTF). The lifecycle of these coatings is not well-defined, and the harsh operational conditions make them difficult to test. NREL has designed, built, and tested an apparatus to expose these samples to design levels of environmental stress and well beyond, into accelerated and destructive conditions. The chamber is actively cooled, monitored, and has the capability to supply humidification for cycling tests, allowing us to test multi-modal degradation and failure conditions at high temperature, high flux, and high humidity conditions. These conditions can catalyze high-temperature oxidation, mechanical degradation, and other modes of absorptivity loss seen in selective solar receiver coatings. The experimental data can feed lifecycle models for expensive and necessarily resilient materials, offering insights to aid maintenance schedules, technoeconomic analysis, and material industry performance benchmarks. This presentation will demonstrate the apparatus design and performance, as well as initial results for aging on a selective receiver coating.

14 SOLAR ENERGY↗

NASA NTRS1986

Ragland - An LL3.4 chondrite find from New Mexico

The Ragland, New Mexico, chondrite was found in 1978. It consists of a single stone of 12.16 kg that broke into three pieces. The stone is moderately weathered and has a pronounced chondritic texture. Bulk composition favors an LL classification, and modal analysis and oxygen isotopic composition are consistent with this. The thermoluminescence sensitivity of 0.056 + or - 0.020 normalized to Dhajala, compositional variability of olivine (mean Fa 18.3, sigma = 10.1) and low-Ca pyroxene (mean Fs 14.6, sigma = 6.7), and Ca concentrations in olivine indicate metamorphic subtype 3.4 + or - 0.1. The isotopically heavy oxygen composition, which is characteristic of subtypes 3.0-3.1, may be a primary characteristic and not a result of weathering. Low concentrations of radiogenic Ar-40 and planetary Ar-36 suggest noble gas loss.

Recca, S. I.↗

DOE OSTI2021

Design of the New DARHT X-ray and Neutron Shielding and Measured Results

The DARHT Weather Enclosure (WE) project provided an excellent opportunity to redesign and rebuild some of DARHT systems without introducing interruptions to normal operations. Multiple improvements were made to the facility to improve data quality and operational reliability.

43 PARTICLE ACCELERATORS↗

NASA NTRS1989

Adaptive clutter rejection filters for airborne Doppler weather radar applied to the detection of low altitude windshear

An optimum adaptive clutter rejection filter for use with airborne Doppler weather radar is presented. The radar system is being designed to operate at low-altitudes for the detection of windshear in an airport terminal area where ground clutter returns may mask the weather return. The coefficients of the adaptive clutter rejection filter are obtained using a complex form of a square root normalized recursive least squares lattice estimation algorithm which models the clutter return data as an autoregressive process. The normalized lattice structure implementation of the adaptive modeling process for determining the filter coefficients assures that the resulting coefficients will yield a stable filter and offers possible fixed point implementation. A 10th order FIR clutter rejection filter indexed by geographical location is designed through autoregressive modeling of simulated clutter data. Filtered data, containing simulated dry microburst and clutter return, are analyzed using pulse-pair estimation techniques. To measure the ability of the clutter rejection filters to remove the clutter, results are compared to pulse-pair estimates of windspeed within a simulated dry microburst without clutter. In the filter evaluation process, post-filtered pulse-pair width estimates and power levels are also used to measure the effectiveness of the filters. The results support the use of an adaptive clutter rejection filter for reducing the clutter induced bias in pulse-pair estimates of windspeed.

Keel, Byron M.↗

NASA NTRS2005

Development and Application of Non-Linear Image Enhancement and Multi-Sensor Fusion Techniques for Hazy and Dark Imaging

The purpose of this research was to develop enhancement and multi-sensor fusion algorithms and techniques to make it safer for the pilot to fly in what would normally be considered Instrument Flight Rules (IFR) conditions, where pilot visibility is severely restricted due to fog, haze or other weather phenomenon. We proposed to use the non-linear Multiscale Retinex (MSR) as the basic driver for developing an integrated enhancement and fusion engine. When we started this research, the MSR was being applied primarily to grayscale imagery such as medical images, or to three-band color imagery, such as that produced in consumer photography: it was not, however, being applied to other imagery such as that produced by infrared image sources. However, we felt that it was possible by using the MSR algorithm in conjunction with multiple imaging modalities such as long-wave infrared (LWIR), short-wave infrared (SWIR), and visible spectrum (VIS), we could substantially improve over the then state-of-the-art enhancement algorithms, especially in poor visibility conditions. We proposed the following tasks: 1) Investigate the effects of applying the MSR to LWIR and SWIR images. This consisted of optimizing the algorithm in terms of surround scales, and weights for these spectral bands; 2) Fusing the LWIR and SWIR images with the VIS images using the MSR framework to determine the best possible representation of the desired features; 3) Evaluating different mixes of LWIR, SWIR and VIS bands for maximum fog and haze reduction, and low light level compensation; 4) Modifying the existing algorithms to work with video sequences. Over the course of the 3 year research period, we were able to accomplish these tasks and report on them at various internal presentations at NASA Langley Research Center, and in presentations and publications elsewhere. A description of the work performed under the tasks is provided in Section 2. The complete list of relevant publications during the research periods is provided in Section 5. This research also resulted in the generation of intellectual property.

Rahman, Zia-ur↗

NASA NTRS2018

Investigations of Hail Damage Swaths Using Various Satellite Remote Sensing Platforms

Severe thunderstorms that bring damaging winds and large hail can cause significant damage to agricultural crops. Severe thunderstorms can cause upwards of several hundreds of millions of dollars in damage to agricultural areas. Formal ground surveys are not conducted on these areas of damage, like they are for suspected tornado damaged areas. IF ground surveys were conducted, they would likely be time and resources consuming due to their large spatial extent. Satellite remote sensing has been frequently used in identification and analysis of these hail damage swaths. Previous analysis have looked at the simple change in damaged vegetation to looking at the damage areas in satellite imagery with varying spatial resolutions. One study has even looked at the impacts that these damage swaths can have on the land surface, associated fluxes and how they affect numerical weather prediction. Previous studies have focused on using optical remote (VIS, NIR, SWIR) sensing instruments and derived indices, such as Normalized Difference Vegetation Index (NDVI) for analysis. NDVI is used to monitor the health (greenness) of the vegetation. Optical sensors however are limited by sky conditions over the areas they are imaging and certain bands are further limited by the diurnal cycle. These limitations can lead to sometimes upwards of 7 to 10 day gaps of the surface not being imaged, especially during the height of summer convection. One way to obtain more views of the surface, regardless of the sky conditions or time of day is through the use of synthetic aperture radar (SAR). SAR sensors are active instruments that transmit in the microwave portion of the EM spectrum. The surface and its characteristics will determine the amount of energy scattered back to the sensor. The SAR sensors then measure amplitude and phase of wavelength coming back from surface.

Bell, Jordan R.↗

NASA NTRS2016

Improved Calibration of Reflectance Data from the LRO Lunar Orbiter Laser Altimeter (LOLA) and Implications for Space Weathering

The Lunar Orbiter Laser Altimeter (LOLA) experiment on Lunar Reconnaissance Orbiter (LRO) is a laser altimeter that also measures the strength of the return pulse from the lunar surface. These data have been used to estimate the reflectance of the lunar surface, including regions lacking direct solar illumination. A new calibration of these data is presented that features lower uncertainties overall and more consistent results in the polar regions. We use these data, along with newly available maps of the distribution of lunar maria, also derived from LRO instrument data, to investigate a newly discovered dependence of the albedo of the lunar maria on latitude (Hemingway et al., [2015]). We confirm that there is an increase in albedo with latitude in the lunar maria, and confirm that this variation is not an artifact arising from the distribution of compositions within the lunar maria, using data from the Lunar Prospector Neutron Spectrometer. Radiative transfer modeling of the albedo dependence within the lunar maria is consistent with the very weak to absent dependence of albedo on latitude in the lunar highlands; the lower abundance of the iron source for space weathering products in the lunar highlands weakens the latitude dependence to the extent that it is only weakly detectable in current data. In addition, photometric mod- els and normalization may take into account the fact that the lunar albedo is latitude dependent, but this dependence can cause errors in normalized reflectance of at most 2% for the majority of near-nadir geometries. We also investigate whether the latitude dependent albedo may have obscured detection of small mare deposits at high latitudes. We find that small regions at high latitudes with low roughness similar to the lunar maria are not mare deposits that may have been misclassified owing to high albedos imposed by the latitude dependence. Finally, we suggest that the only modest correlations among space weathering indicators defined for the lunar samples may be due to mixing of soils from distinct latitudes.

Lemelin, M.↗

DOE OSTI2024

Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach

The escalating energy demand and the adverse environmental impacts of fossil-fuel use necessitate a shift towards cleaner and renewable alternatives. Concentrated Solar Power (CSP) technology emerges as a promising solution, offering a carbon-free alternative for power generation. The efficiency and profitability of CSP depend on the Direct Normal Irradiance (DNI) component of solar radiation; hence, accurate DNI forecasting can help optimize CSP plants’ operations and performance. The unpredictable nature of weather phenomena, particularly cloud cover, introduces uncertainty into DNI projections. Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. This research addresses the challenge by presenting a novel approach that formulates DNI prediction as a multi-class classification problem, departing from conventional regression-based methods. The primary objective of this classification framework is to identify optimal periods aligning with specific operational thresholds for CSP plants, contributing to enhanced dispatch optimization strategies. We model the DNI classification problem using four advanced deep neural networks – rectified linear unit (ReLU) networks, 1D residual networks (ResNets), bidirectional long short-term memory (BiLSTM) networks, and transformers – achieving accuracies up to 93.5% without requiring meteorological parameters.

14 SOLAR ENERGY↗