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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Intercomparison of Dynamically and Statistically Downscaled Climate Change Projections over the Midwest and Great Lakes Region

Downscaling of global climate model (GCMs) simulations is a key element of regional-to-local-scale climate change projections that can inform impact assessments, long-term planning, and resource management in different sectors. Here, we conduct an intercomparison between statistically and dynamically downscaled GCMs simulations using the hybrid delta (HD) and the Weather Research and Forecast (WRF) Model, respectively, over the Midwest and Great Lakes region to 1) validate their performance in reproducing extreme daily precipitation (P) and daily maximum temperature (T max ) for summer and winter and 2) evaluate projections of extremes in the future. Our results show the HD statistical downscaling approach, which includes large-scale bias correction of GCM inputs, can reproduce observed extreme P and T max reasonably well for both summer and winter. However, raw historical WRF simulations show significant bias in both extreme P and T max for both seasons. Interestingly, the convection-permitting WRF simulation at 4-km grid spacing does not produce better results for seasonal extremes than the WRF simulation at 12 km using a parameterized convection scheme. Despite a broad similarity for winter extreme P projections, the projected changes in the future summer storms are quite different between downscaling methods; WRF simulations show substantial increases in summer extreme precipitation, while the changes projected by the HD approach exhibit moderate decreases overall. The WRF simulations at 4 km also show a pronounced decoupling effect between seasonal totals and extreme daily P for summer, which suggests that there could be more intense summer extremes at two different time scales, with more severe individual convective storms combined with longer summer droughts at the end of the twenty-first century.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

The Extreme 2016 Wheat Failure in France

France suffered in 2016 the most extreme wheat yield decline in recent history, with some districts losing 55% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information and yield physiology. The 2016 yield was composed of up to 40% fewer grains that were up to 30% lighter than expected across eight research stations in France. The flowering stage was affected by prolonged cloud cover and heavy rainfall when 31% of the loss in grain yield was incurred from reduced solar radiation and 19% from floret damage. Grain filling was also affected as 26% of grain yield loss was caused by soil anoxia, 11% by fungal foliar diseases and 10% by ear blight. Compounding climate effects caused the extreme yield decline. The likelihood of these compound factors recurring under future climate change is estimated to change with a higher frequency of extremely low wheat yields.

Extreme weather↗
NASA NTRSDate not supplied

Assessing the Viability of Using GEOS-Forecast Product for Landslides Forecasting: A Step Toward Early Warning System

Landslides across the globe are mostly triggered by extreme rainfall events affecting infrastructure, transportation and livelihoods. The risks are rarely quantified due to lack of data, analytical skills and limited modeling techniques. Knowledge of local to global scale landslide risks provides communities and national agencies the ability to adapt disaster management practices to mitigate and recover from these hazards. In order to minimize the risks and improve characterization of community resilience to landslides, it is vital to have reliable information about the factors triggering landslides such as rainfall, well ahead in time. Forecasting potential landslide activity and impacts can be achieved through reliable precipitation forecast models. However, it is challenging because of the temporal and spatial variability of precipitation, an important factor in triggering landslides. Evaluation of the precipitation field, associated errors, and sampling uncertainties is integral for development of efficient and reliable landslide forecasting and early warning system. This study develops a methodology to assess the viability of using a precipitation field provided by a global model and its potential integration in the landslide forecasting system. The study focuses on the comparison between the IMERG (Integrated Multi-satellitE Retrievals for Global Precipitation Mission) and GEOS (NASA Goddard Earth Observing System)-Forecast product over contiguous United States (CONUS). GEOS model assimilates new observations every 6 hours, at 00, 06, 12, and 18 UTC. The framework is tested on the GEOS-Forecast Model initialized at 00 UTC using daily IMERG early product as reference using both categorical and continuous statistics. The categorical statistics includes the probability of detection (POD), success ratio (SR), critical success index (CSI), and the hit bias. Continuous statistics such as correlation, normalized standard deviation, and root-mean-square error are also evaluated. Overall, GEOS-Forecast precipitation field over the analysis period (~1 year) show underestimation with respect to IMERG early for the daily accumulated rainfall. However, the probability distribution function and cumulative distribution function of both show similar patterns. In terms of correlations, POD, SR, CSI, hit bias, the performance varies with respect to the rainfall threshold used.

Sana Khan↗
NASA NTRS1998

Evolution of the 1997-98 El Nino and La Nina: the Role of Altimetry in ENSO Studies and Prediction

El Nino and the Southern Oscillation (ENSO) are known to be a quasi-periodic coupled ocean-atmosphere phenomenon occurring roughly every 3-7 years. Its largest oceanic manifestations are found in the equatorial Pacific, but it is of global climatic significance. During the flight of the TOPEX]Poseidon altimeter, the equatorial Pacific was in the midst of an unusual period of prolonged ENSO warming in the mid-1990's. In 1997, the tropical Pacific witnessed the development of a major El Nino event, rivaling in strength the 1982-83 El Nino. The intensity of this El Nino, and its rapid intensification early in the calendar year, caught the scientific community by surprise. None of the forecast models, statistical or dynamical, captured these features of the 1997 El Nino, although those models that assimilated in situ ocean observations did better than most in predicting that the event would occur in 1997. The onset of the El Nino coincided with the occurrence of several westerly wind events in the western Pacific rather than to delayed oscillator physics. However, western Pacific sea levels were anomalously elevated a year and a half prior to the onset, which may have helped precondition the system to a particularly strong ENSO episode. The coming of La Nina was foreshadowed by large-scale drops in sea level in the western tropical Pacific and cyclonic wind stress curl anomalies far beyond the +\- 8 degrees latitude bounds of the TAO mooring array. In past El Nino events, the evolution of the coupled system could only be studied from the perspective of in situ observations. The 1997-1998 El Nino event will be the first time a major El Nino event will have been observed from start to finish via remotely-sensed measurements of sea surface topography, sea surface temperature, sea surface winds, ocean color, and precipitation. These observations have considerable potential for advancing coupled climate forecasts on time scales from seasons to decades. This presentation will address questions along the lines of: (1) What are the scientific problems in ENSO that can benefit most from altimetry data? (2) Are there any precursors in the global ocean-atmosphere system for the 1997-98 extreme event? (3) Is there a unique role of altimetry in detecting potential precursors?(4) Has Topex/Poseidon data been adequately used to improve ENSO forecasts? Is there any firm evidence? (6) What is the status of the transition of El Nino into a La Nina?

Busalacchi, Antonio J.↗
NASA NTRS1964

Unmanned Spacecraft of the United States

In 1957 the first earth satellite ushered in the age of space flight. Since that historic event, space exploration has become a major national objective of both the United States and the Soviet Union. These two nations have attempted a total of well over 200 space flight missions. Other nations are also participating in various degrees in what will continue to grow as a cooperative world effort. In the years since 1957, man has successfully flown in earth orbit. He has initiated programs to land on the moon and return. He has made dramatic applications of earth satellites in meteorology, communications, navigation, and geodesy. A host of scientific satellites.continue to advance understanding of the earth's environment, the sun, and the stars. Automated spacecraft are being flown to the moon, deep into interplanetary space, and to the near planets, Mars and Venus. One of the most exciting technological aspects of space exploration has been the development of automated spacecraft. Most of the scientific exploration of space and the useful applications of space flight thus far have been made possible by automated spacecraft. Development of these spacecraft and their many complex subsystems is setting the pace today for many branches of science and technology. Guidance, computer, attitude control, power, telecommunication, instrumentation, and structural subsystems are being subjected to new standards of light weight, high efficiency, extreme accuracy, and unsurpassed reliability and quality. This publication reviews the automated spacecraft which have been developed and flown, or which are under active development in the United States by the National Aeronautics and Space Administration. From the facts and statistics contained herein, certain observations can be made and certain conclusions drawn.

Cortright, Edgar M.↗
NASA NTRSDate not supplied

Shoulder Postures in EVA Training in Reduced Gravity Analogues

Shoulder Postures in EVA Training in Reduced Gravity Analogues K. Guhl1, L. Vu2, H. Kim3, S. Rajulu4 1KBR Inc., Houston, TX, 2Aegis Aerospace Inc., Houston, TX, 3Leidos Innovations, Houston, TX, 4NASA Johnson Space Center, Houston, TX. During extravehicular activities (EVAs) and EVA training in both the Neutral Buoyancy Laboratory (NBL) and at the Active Response Gravity Offload System (ARGOS), crewmembers perform a variety of hand-intensive tasks with frequent arm/shoulder repositioning while wearing a pressurized spacesuit. As a result, crewmembers may experience ergonomic stressors such as awkward shoulder postures. The ergonomic shoulder risk is also compounded by limited or restricted shoulder mobility of the spacesuit, extreme work positions such as overhead tasks, and tasks with heavy tools and repetitive motions. Prolonged or frequent shoulder elevation and overhead work, in particular, can lead to excessive stresses and musculoskeletal injuries of the shoulder joints. Future EVA missions, specifically lunar surface EVAs, will also be longer in duration and thus increase the exposure to awkward shoulder postures. In this study, we aimed to assess the ergonomic risk of awkward shoulder postures in simulated lunar surface EVAs by quantifying when and how long the arms are raised above the chest level. We assessed video recordings of pilot lunar EVA simulations (3 lunar trials each in the NBL and at ARGOS and 2 microgravity EVA trials in the NBL). These runs consisted of both training and engineering test objectives. Actual demands for shoulder use varied for different EVA types and analogues, but many EVA runs have common tasks and require similar motion components. A video observation and event logging software was used to document the duration and occurrence of the subject’s arms being raised throughout the video recordings of each EVA run. An arm raised instance was classified as the arm being at 90 degrees or above with relation to gravity for lunar EVA training events and with relation to the body for microgravity EVA training events. Such events included EVA hardware maintenance or heavy geology sampling tool operations. Events where the arm load was partially supported by external objects, like climbing a ladder or leaning against a surface were separately identified and excluded. Statistical analysis was performed to summarize the timing, frequency, and durations of the arm raise events and compared across the different EVA tasks and analogue types. Preliminary observations indicated that the total duration and number of arm raised instances were surprisingly smaller for lunar surface EVA training as compared to microgravity EVA training. The observed difference may be attributed to differing task demands and unique environmental characteristics found in lunar EVAs in comparison to microgravity EVAs. A detailed statistical analysis will be performed between lunar surface EVA training events and microgravity EVA training events in the final submission. Overall, this analysis is expected to provide insight into how ergonomic recommendations can be refined for lunar EVA training with pressurized suits. It may also inform task design and influence suit padding design to better protect crewmembers during future lunar training.

Kaitlyn Lea Guhl↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
DOE OSTI2020

The Argonne SuperGel for CBRN Decontamination - 20160

The Argonne SuperGel was developed between 2003 and 2015 to fill a gap in our nation's capability to quickly decontaminate important structures following a radiological or nuclear release event. Specifically, the decontamination technology was developed to minimize damage to monuments, high valued structures, and critical infrastructure while reducing environmental and health impacts. An important criterion during its development, common reagents were employed that could be easily acquired in order to minimize the timeline for its deployment. Its current formulation uses off-the-shelf super-absorbing hydrogels common to the food and agricultural industry and common salts. Over the years, two formulations of the Argonne SuperGel have been developed to specifically target radioactive cesium contaminations and then, more generically, actinide and fission product contaminations. A biodegradable derivative of phosphoric acid is used in small amounts to promote the removal of insoluble actinide species. The original order of unit operations for the SuperGel technology was 1) applying the wash solution to promote mobility of the contaminants on the surface, 2) applying the hydrogel to absorb the wash solution and contaminants, and 3) removing the hydrogel for disposal. During the course of our studies, we tested a new formulation of the gel technology that eliminated the need for a separate step to apply the wash solution without a compromise in decontamination factors. Greater than 70% and >95% of Cs-137 were removed from concrete and tile coupons, respectively, after two decontaminations, with the best results using wash solutions of 1.0 M KCl and 1.0 M NH{sub 4}Cl formulations. We found no statistical difference between results at 30 deg. C and 40 deg. C or at 70% and 90% relative humidity. We tested the gel under strong UV irradiation to simulate extreme environments. While a tropical noontime UV flux did not adversely affect the gel system decontamination of Cs-137 from concrete or tile coupons, the noontime flux resulted in significant dehydration of the gel after two hours of constant exposure. The rehydration of the gel by the humid air (at 90% humidity and 40 deg. C) was slow and may not be sufficient to offset dehydration by the sun. Americium decontamination from concrete was 70% after optimizing the phosphoric acid derivative and carbonate salt concentration in the wash solution. Since its development, we have had the opportunity to test the SuperGel in the removal of legacy contaminations in hot cell facilities and former glovebox facilities at Argonne. This has provided a unique opportunity to evaluate the SuperGel on a range of contaminants outside the original specifications for its use. We will report on the origin of the gel formulation, some highlighted experimental data including independent testing by the US EPA which has never been reported, and its efficacy for removing legacy alpha contaminations and its potential use for removal of chemical and biological hazardous agents. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2006

Remote Sensing Time Series Product Tool

The TSPT (Time Series Product Tool) software was custom-designed for NASA to rapidly create and display single-band and band-combination time series, such as NDVI (Normalized Difference Vegetation Index) images, for wide-area crop surveillance and for other time-critical applications. The TSPT, developed in MATLAB, allows users to create and display various MODIS (Moderate Resolution Imaging Spectroradiometer) or simulated VIIRS (Visible/Infrared Imager Radiometer Suite) products as single images, as time series plots at a selected location, or as temporally processed image videos. Manually creating these types of products is extremely labor intensive; however, the TSPT development tool makes the process simplified and efficient. MODIS is ideal for monitoring large crop areas because of its wide swath (2330 km), its relatively small ground sample distance (250 m), and its high temporal revisit time (twice daily). Furthermore, because MODIS imagery is acquired daily, rapid changes in vegetative health can potentially be detected. The new TSPT technology provides users with the ability to temporally process high-revisit-rate satellite imagery, such as that acquired from MODIS and from its successor, the VIIRS. The TSPT features the important capability of fusing data from both MODIS instruments onboard the Terra and Aqua satellites, which drastically improves cloud statistics. With the TSPT, MODIS metadata is used to find and optionally remove bad and suspect data. Noise removal and temporal processing techniques allow users to create low-noise time series plots and image videos and to select settings and thresholds that tailor particular output products. The TSPT GUI (graphical user interface) provides an interactive environment for crafting what-if scenarios by enabling a user to repeat product generation using different settings and thresholds. The TSPT Application Programming Interface provides more fine-tuned control of product generation, allowing experienced programmers to bypass the GUI and to create more user-specific output products, such as comparison time plots or images. This type of time series analysis tool for remotely sensed imagery could be the basis of a large-area vegetation surveillance system. The TSPT has been used to generate NDVI time series over growing seasons in California and Argentina and for hurricane events, such as Hurricane Katrina.

Predos, Don↗
NASA NTRSDate not supplied

Insights into Long-Term Global Precipitation from IMERG and GPCP

Multiple satellite-based datasets provide estimates of the long-term record of global precipitation. Each necessarily includes both the real atmospheric behavior and a collection of artifacts driven by the input data sources and design choices in the retrievals and dataset construction. For this presentation, the Integrated Multi-satellitE Retrievals for GPM (IMERG) products from the Global Precipitation Measurement (GPM) mission’s U.S. Science Team are designed as a modern High-Resolution Precipitation Product (HRPP), while the Global Precipitation Climatology Project’s (GPCP) products are designed as a modern Climate Data Record (CDR). Although they share some common input data sources, the computational process for each is rather different. Comparing the precipitation estimates from each algorithm gives us insights into likely artifacts and the natural variations that are common to both. The goal of an HRPP is to give the best estimate of precipitation at each time step in the dataset, generally meaning that “all possible available” data are used. In contrast, the CDR is intended to provide a precipitation record that has relatively homogeneous statistics, necessary for climate analysis. Each analysis strives for both goals, of course, but this means that the HRPP uses the disparate collection of satellites whose statistics don’t quite match the ideal record, while the CDR is computed from fewer satellites that provide a relatively homogeneous set of precipitation statistics. This presentation employs the current versions of the IMERG and GPCP products, V07B and V3.2, respectively. A variety of analyses have demonstrated that IMERG has more artifacts, as expected, which tend to result from changes in the source of intercalibration for the various input satellites, namely the Combined Radar-Radiometer Algorithm using TMI and PR during the TRMM era and using GMI and DPR-Ku during the GPM era. As well, a shift occurs when the altitudes of the TRMM and GPM satellites change as a result of orbit boosts. For the most part the mean precipitation shows good continuity across these boundaries, but there are noticeable changes in the respective histograms. The latter has taken on more importance in recent years due to increased scrutiny on extremes which implicitly focus on the upper end of the precipitation histograms. The GPCP product is more homogeneous, with only one major change in calibrator, transitioning from the SSMI series of satellites to the SSMIS series of satellites in 2009. The GPCP analysis does a good job of minimizing artifacts in the means at this boundary, while the histograms show a smaller, but still noticeable shift in the histograms, a result that is similar to data boundaries in IMERG. The GPCP Daily, which is a month-by-month rescaling of the daily accumulated IMERG Final product, shows more consistency than the equivalent daily IMERG, but inherits the histogram shifts from IMERG. Given this overlay of artifacts, there is enough consistency between the products to illustrate some important long-term variations, including interannual variations, not all of which are easily attributable to ENSO events, and trends that are large regionally, but comparatively small when averaged across the globe.

precipitation↗
NASA NTRS2011

Northern Hemisphere Atmospheric Influence of the Solar Proton Events and Ground Level Enhancement in January 2005

Solar eruptions in early 2005 led substantial barrage of charged particles on the Earth's atmosphere during the January 16-21 period. Proton fluxes were greatly increased during these several days and led to the production ofHO(x)(H, OH, BO2)and NO(x)(N, NO, NO2), which then caused the destruction of ozone. We focus on the Northern polar region, where satellite measurements and simulations with the Whole Atmosphere Community Climate Model (WACCM3) showed large enhancements in mesospheric HO(x) and NO(x) constituents, and associated ozone reductions, due 10 these solar proton events (SPEs). The WACCM3 simulations show enhanced short-lived OH throughout the mesosphere in the 60-82.5degN latitude band due to the SPEs for most days in the Jan.16-2l,2005 period, in reasonable agreement with the Aura Microwave Limb Sounder (MLS) measurements. Mesospheric HO2 is also predicted to be increased by the SPEs, however, the modeled HO2 results are somewhat larger than the MLS measurements. These HO(x) enhancements led to huge predicted and MLS-measured ozone decreases of greater than 40% throughout most of the Northern polar mesosphere during the SPE period. Envisat Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) measurements of hydrogen peroxide (H2O2) show increases throughout the stratosphere with highest enhancements of about 60 ppt y in the lowermost mesosphere over the Jan. 16-18, 2005 period due to the solar protons. WACCM3 predictions indicate H2O2 enhancements over the same time period of more than twice that amount. Measurements of nitric acid (HNO3) by both MLS and MIPAS show an increase of about 1 ppbv above background levels in the upper stratosphere during January 16-29, 2005. WACCM3 simulations show only minuscule HNO3 changes in the upper stratosphere during this time period. However due to the small loss rates during winter, polar mesospheric enhancements of NO(x) are computed to be greater than 50 ppbv during the SPE period. Computed NO(x)increases, which were statistically significant at the 95% level, lasted about a month past the SPEs. The SCISAT-I Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) NO(x) measurements and MIPAS NO, measurements for the polar Northern Hemisphere are in reasonable agreement with these predictions. An extremely large ground level enhancement (GLE) occurred during the SPE period on January 20, 2005. We find that protons of energies 300 to 20,000 MeV, not normally included in our computations, led to enhanced lower stratospheric odd nitrogen concentrations of less than 0.1% as a result of this GLE.

Jackman, C. H.↗
NASA NTRS2001

Dealing with the Asteroid Impact Hazard

The small fraction of the asteroids with Earth-crossing or Earth-approaching orbits is of special interest to us because many will eventually impact our planet. The time-averaged impact flux as a function of projectile energy can be derived from lunar cratering statistics, although we have little information on the possible variability of this flux over time. The effects of impacts of various energies can be modeled, using data from historic impacts (such as the KT impactor 65 million years ago), nuclear explosive testing, and the observed 1994 bombardment of Jupiter by fragments of comet Shoemaker-Levy 9. It is of particular interest to find from such models that the terrestrial environment is highly vulnerable to perturbation from impacts, so that even such a small event as the KT impact (by a projectile roughly 15 km in diameter) can lead to a mass extinction. Combining the impact flux with estimates of environmental and ecological effects reveals that the greatest contemporary hazard is associated with impactors near one million megatons energy. The current impact hazard is significant relative to other natural hazards, and arguments can be developed to illuminate a variety of public policy issues. These include the relative risk of different impact scenarios and the associated costs and probability of success of countermeasures. It is generally agreed that the first step is to survey and catalogue the thousand-or-so Near Earth Asteroids (NEAs), and we review the status of the Spaceguard NEA Survey. We compare the efficiency of various ground and space-based approaches and consider the challenges of international coordination and the problems and opportunities associated with communicating the results with the press and the public. It is also important to reflect on how the impact hazard might be dealt with by both national governments and international decision-making bodies, and to anticipate ways of mitigating the danger if a NEA were located on an apparent Earth-impact trajectory. As the most extreme known example of a natural hazard with low probability but severe global consequences. the NEA impact hazard calls for the most careful consideration and planning.

Morrison, David↗
NASA NTRSDate not supplied

Comprehensive Analysis of Thirty Years of Land Change in Georgia: Forest Degradation, Land-Use Patterns, and Drivers

In this talk, we present results from a study, funded by the NASA Land-Cover and Land-Use Change program, of thirty years of environmental change in the country of Georgia. The country, a former Soviet Union Republic, has experienced more political, economic and social change in the last 30 years than most countries. But the environmental implications of these extreme events remain largely unknown – the region is understudied, no national forest inventory has been completed in 20 years, and previous research in the area conducted by the authors were not successful. The latter statement is because of forest degradation. After the collapse of the Soviet Union, much of the forestry infrastructure broke down and people resorted to chopping down individual trees. The result was in many parts of the country a reduction in forest biomass but not to the point of a change in land cover. This type of forest degradation, which was either gradual over decades or abrupt, could not be readily identified using the methods and data at our disposal at the time. In the recent study, we had full access to the Landsat archive in combination with computing power. By using monitoring methods that are based on time series analysis, we were able to capture and identify the gradual processes driven by small scale activities that are so characteristic of the post-Soviet Georgian landscape. We developed an approach (“CCDC-SMA”) that combines time series analysis and spectral mixture analysis running on Google Earth Engine for monitoring abrupt and gradual forest degradation. By using this approach, we found that forest degradation was significantly larger than the area estimate of deforestation; 3,541 ± 556 km2 (11% of the forest area in 1987) compared to 158 ± 98 km2 from 1987 to 2020. The prevailing narrative is that legal and illegal cutting of trees for fuelwood is primarily responsible for this process. Yet, since independence from the Soviet Union in 1991, the country has undergone rapid socioeconomic and institutional changes which have not been explored as drivers of forest change. To further our understanding of the underlying causes, we combined forest disturbance estimates, Georgian statistical data, and historical institutional change data to examine socioeconomic drivers of forest degradation. We found that higher winter temperature and drought were associated with higher degradation at the regional scale, while major institutional changes and drought were associated with higher forest degradation at the national level. Access to natural gas, the major energy alternative to fuelwood, had no significant association with degradation. Our results challenge the narrative that poverty and a lack of alternative energy infrastructure drive forest degradation and suggest that government policies banning household fuelwood cutting, including the new Forest Code of 2020, may not reduce forest degradation. Given these results, improved data on wood harvesting and more research on the commercial drivers of degradation and their links to economic and political reforms is needed to better inform forest policy in the region, especially given ongoing risks from climate change.

Pontus Olofsson↗
DOE OSTI2025

Time-interval distributions in a digital gamma multi-channel analyzer at extreme input rates

Here, this study explores the relationship between experimentally observed inter-event time-interval distributions (TIDs) and measured dead times for pulses generated by a HPGe gamma detector and processed by a digital spectrometer. The system utilizes a fast and slow channel, pile-up rejector, trapezoid filtering, and flash analog-to-digital converter. The experimentally derived TIDs were compared with theory for validation. The results demonstrate that the theoretical model reliably describes measured TIDs up to 40% dead time. However, significant distortion effects become increasingly pronounced at higher input rates. It appears that the deviation between the measured and calculated time-interval distributions take the shape of higher-order convolutions of the TID, which represent the time difference between counts for more than two successive events. In this work, theoretical functions for the TID are expanded to reproduce measurements up to 90%. This refinement in the interpretation and treatment of the measured TIDs provides improved accuracy and precision in the prediction of the true event rate and measured dead time in the counter. Even though it reflects occasional count loss that is specific to the set-up, it is expected that a similar adjustment may be applicable to other detection systems as well.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Performance of New Near-Real-Time PERSIANN Product (PDIR-Now) for Atmospheric River Events over the Russian River Basin, California

Most heavy precipitation events and extreme flooding over the U.S. Pacific coast can be linked to prevalent atmospheric river (AR) conditions. Thus, reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for water management and early warning systems of flooding and landslides over these regions. At the same time, high-quality near-real-time measurements of AR precipitation remain challenging due to the complex topographic features of land surface and meteorological conditions of the region: specifically, orographic features occlude radar measurements while infrared-based algorithms face challenges, differentiating between both cold brightband (BB) precipitation and the warmer nonbrightband (NBB) precipitation. It should be noted that the latter precipitation is characterized by greater orographic enhancement. In this study, we evaluate the performance of a recently developed near-real-time satellite precipitation algorithm: Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) Dynamic Infrared–Rain Rate-Now (PDIR-Now). This model is primarily dependent on infrared information from geostationary satellites as input; consequently, PDIR-Now has the advantage of short data latency, 15–60-min delay between observation to precipitation product delivery. The performance of PDIR-Now is analyzed with a focus on AR-related events for cases dominated by NBB and BB precipitation over the Russian River basin. In our investigations, we utilize S-band (3-GHz) precipitation profilers with Joss/Parsivel disdrometer measurements at the Middletown and Santa Rosa stations to classify BB and NBB precipitation events. In general, our analysis shows that PDIR-Now is more skillful in retrieving precipitation rates over both BB and NBB events across the topologically complex study area as compared to PERSIANN-Cloud Classification System (CCS). Also, we discuss the performance of well-known operational near-real-time precipitation products from 2017 to 2019. Conventional categorical and volumetric categorical indices, as well as continuous statistical metrics, are used to show the differences between various high-resolution precipitation products such as Multi-Radar Multi-Sensor (MRMS).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Multi-Mechanism Flood Hazard Assessment: Critical Review of Current Practice and Approaches

This report documents the initial findings from the Nuclear Regulatory commission (NRC)-sponsored research project Methods for Estimating Joint Probabilities of Coincident and Correlated Flooding Mechanisms for Nuclear Power Plant Flood Hazard Assessments.1 This research project is a part of NRC’s Probabilistic Flood Hazard Assessment (PFHA) Research Program and will aid the development of guidance on the use of PFHA methods to evaluate infrastructure safety for existing and proposed US nuclear power plants (NPPs). More specifically, this project intends to provide technical background for the development of flood hazard curves for multi-mechanism floods (MMFs). MMFs are flood events caused by more than one flooding mechanism (e.g., flood events due to the simultaneous occurrence of precipitation-induced river flooding and storm surge). Project activities include three main tasks: Task 1—Survey of current concepts and methods in assessing MMF hazards; Task 2—Critical assessment of selected methods and approaches for quantifying probabilistic MMF hazard risk; Task 3—Development of example case studies to illustrate best practices for quantifying probabilistic MMF hazard risk The initial findings from Tasks 1 and 2 are documented in this report. Task 1 comprised a survey of approaches and methods that have been applied to understand and assess flood hazards due to MMFs. Task 2 involved a critical review of the selected approaches and methods. To that end, the scope of this report includes documentation of (1) a reconnaissance-level survey of the current state of concepts and practice for MMF hazard assessment; (2) a generalized MMF assessment framework to address the distinctions among various types of flood-forcing phenomena, flood mechanisms (grouped into three mechanism types), and flood severity metrics; (3) a wide-ranging survey of approaches and methods that have been applied to various flooding phenomena and settings; and (4) a critical assessment of MMF hazard assessment methods. Studies were identified involving MMFs related to coastal flooding mechanisms, fluvial (rivers/streams) flooding mechanisms, and associated combinations of coastal and fluvial flooding mechanisms. Studies were also identified that address MMFs involving coastal and fluvial flooding mechanisms as well as coastal flooding mechanisms along with extreme precipitation (without specific attribution to fluvial or pluvial mechanisms). The studies identified for review in this report included assessments at varying spatial scales (from local to global) with differing geographic regions of focus using both observed and synthetic data. The majority of studies identified and reviewed were site-specific assessments focusing on relatively short return periods. Studies considered a range of flood severity metrics, made differing assumptions regarding the occurrence of extrema, and used multiple statistical techniques; the use of copulas for the development of joint distributions was a particularly popular analysis technique. The literature review highlighted the differences among existing studies relative to terminology used, means of presenting results, framework and techniques employed, and level of sophistication regarding the number and types of variables considered. Despite the significant diversity in existing studies, the review identified several promising techniques that will be considered in future work under this project, including the development of joint distributions for MMFs using copula and Bayesian-motivated approaches.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Probing Strangeness Hadronization with Event-by-Event Production of Multistrange Hadrons

This Letter presents the first measurement of event-by-event fluctuations of the net number (difference between the particle and antiparticle multiplicities) of multistrange hadrons Ξ − and $\overline{Ξ}$ + and its correlation with the net-kaon number using the data collected by the ALICE Collaboration in pp, p-Pb, and Pb-Pb collisions at a center-of-mass energy per nucleon pair $\sqrt{s_{NN}}$ = 5.02 TeV. The statistical hadronization model with a correlation over three units of rapidity between hadrons having the same and opposite strangeness content successfully describes the results. On the other hand, string-fragmentation models that mainly correlate strange hadrons with opposite strange quark content over a small rapidity range fail to describe the data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2012

EPE The Extreme Physics Explorer

The Extreme Physics Explorer (EPE) is a mission concept that will address fundamental and timely questions in astrophysics which are primary science objectives of IXO. The reach of EPE to the areas outlined in NASA RFI NNH11ZDA018L is shown as a table. The dark green indicates areas in which EPE can do the basic IXO science, and the light green areas where EPE can contribute but will not reach the full IXO capability. To address these science questions, EPE will trace orbits close to the event horizon of black holes, measure black hole spin in active galactic nuclei (AGN), use spectroscopy to characterize outflows and the environment of AGN, map bulk motions and turbulence in galaxy clusters, and observe the process of cosmic feedback where black holes inject energy on galactic and intergalactic scales. EPE gives up the high resolution imaging of IXO in return for lightweight, high TRL foil mirrors which will provide >20 times the effective area of ASTRO-H and similar spatial resolution, with a beam sufficient to study point sources and nearby galaxies and clusters. Advances in micro-calorimeters allow improved performance at high rates with twice the energy resolution of ASTRO-H. A lower TRL option would provide 200 times the area of ASTRO-H using a micro-channel plate optic (MCPO) and a deployable optical bench. Both options are in the middle range of RFI missions at between $600M and $1000M. The EPE foil optic has direct heritage to ASTRO-H, allowing robust cost estimates. The spacecraft is entirely off the shelf and introduces no difficult requirements. The mission could be started and launched in this decade to an L2 orbit, with a three-year lifetime and consumables for 5 years. While ASTRO-H will give us the first taste of high-resolution, non-dispersive X-ray spectroscopy, it will be limited to small numbers of objects in many categories. EPE will give us the first statistically significant samples in each of these categories.

Garcia, Michael↗