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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Exploring Climate-Disease Connections in Geopolitical Versus Ecological Regions: The Case of West Nile Virus in the United States

Many infectious disease forecasting models in the United States (US) are built with data partitioned into geopolitical regions centered on human activity as opposed to regions defined by natural ecosystems; although useful for data collection and intervention, this has the potential to mask biological relationships between the environment and disease. We explored this concept by analyzing the correlations between climate and West Nile virus (WNV) case data aggregated to geopolitical and ecological regions. We compared correlations between minimum, maximum, and mean annual temperature; precipitation; and annual WNV neuroinvasive disease (WNND) case data from 2005 to 2019 when partitioned into (a) climate regions defined by the National Oceanic and Atmospheric Administration (NOAA) and (b) Level I ecoregions defined by the Environmental Protection Agency (EPA). We found that correlations between climate and WNND in NOAA climate regions and EPA ecoregions were often contradictory in both direction and magnitude, with EPA ecoregions more often supporting previously established biological hypotheses and environmental dynamics underlying vector-borne disease transmission. Using ecological regions to examine the relationships between climate and disease cases can enhance the predictive power of forecasts at various scales, motivating a conceptual shift in large-scale analyses from geopolitical frameworks to more ecologically meaningful regions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2011

Value of Probabilistic Weather Forecasts: Assessment by Real-Time Optimization of Irrigation Scheduling

This paper presents a modeling framework for real-time decision support for irrigation scheduling using the National Oceanic and Atmospheric Administration's (NOAA's) probabilistic rainfall forecasts. The forecasts and their probability distributions are incorporated into a simulation-optimization modeling framework. In this study, modeling irrigation is determined by a stochastic optimization program based on the simulated soil moisture and crop water-stress status and the forecasted rainfall for the next 1-7 days. The modeling framework is applied to irrigated corn in Mason County, Illinois. It is found that there is ample potential to improve current farmers practices by simply using the proposed simulation-optimization framework, which uses the present soil moisture and crop evapotranspiration information even without any forecasts. It is found that the values of the forecasts vary across dry, normal, and wet years. More significant economic gains are found in normal and wet years than in dry years under the various forecast horizons. To mitigate drought effect on crop yield through irrigation, medium- or long-term climate predictions likely play a more important role than short-term forecasts. NOAA's imperfect 1-week forecast is still valuable in terms of both profit gain and water saving. Compared with the no-rain forecast case, the short-term imperfect forecasts could lead to additional 2.4-8.5% gain in profit and 11.0-26.9% water saving. However, the performance of the imperfect forecast is only slightly better than the ensemble weather forecast based on historical data and slightly inferior to the perfect forecast. It seems that the 1-week forecast horizon is too limited to evaluate the role of the various forecast scenarios for irrigation scheduling, which is actually a seasonal decision issue. For irrigation scheduling, both the forecast quality and the length of forecast time horizon matter. Thus, longer forecasts might be necessary to evaluate the role of forecasts for irrigation scheduling in a more effective way.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

EVOLUTION OF HARD X-RAY SOURCES AND ULTRAVIOLET SOLAR FLARE RIBBONS FOR A CONFINED ERUPTION OF A MAGNETIC FLUX ROPE

We study the magnetic field structures of hard X-ray (HXR) sources and flare ribbons of the M1.1 flare in active region NOAA 10767 on 2005 May 27. We have found in a nonlinear force-free field extrapolation over the same polarity inversion line, a small pre-eruptive magnetic flux rope located next to sheared magnetic arcades. RHESSI and the Transition Region and Coronal Explorer (TRACE) observed this confined flare in the X-ray bands and ultraviolet (UV) 1600 A bands, respectively. In this event magnetic reconnection occurred at several locations. It first started at the location of the pre-eruptive flux rope. Then, the observations indicate that magnetic reconnection occurred between the pre-eruptive magnetic flux rope and the sheared magnetic arcades more than 10 minutes before the flare peak. This implies the formation of the larger flux rope, as observed with TRACE. Next, HXR sources appeared at the footpoints of this larger flux rope at the peak of the flare. The associated high-energy particles may have been accelerated below the flux rope in or around a reconnection region. Still, the close spatial association between the HXR sources and the flux rope footpoints favors an acceleration within the flux rope. Finally, a topological analysis of a large solar region, including active regions NOAA 10766 and 10767, shows the existence of large-scale Quasi-Separatrix Layers (QSLs) before the eruption of the flux rope. No enhanced emission was found at these QSLs during the flare, but the UV flare ribbons stopped at the border of the closest large-scale QSL.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

PHENOMENOLOGICAL STUDY OF INTERACTION BETWEEN SOLAR ACOUSTIC WAVES AND SUNSPOTS FROM MEASURED SCATTERED WAVEFUNCTIONS

The solar acoustic waves around a sunspot are modified because of the interaction with the sunspot. The interaction can be viewed as that the sunspot, excited by the incident wave, generates the scattered wave, and the scattered wave is added to the incident wave to form the total wave around the sunspot. We define an interaction parameter, which could be complex, describing the interaction between the acoustic waves and the sunspot. The scattered wavefunction on the surface can be expressed as a two-dimensional integral of the product of the Green's function, the wavefunction, and the two-dimensional interaction parameter over the sunspot area for the Born approximation of different orders. We assume a simple model for the two-dimensional interaction parameter distribution: its absolute value is axisymmetric with a Gaussian distribution and its phase is a constant. The measured scattered wavefunctions of various modes for NOAAs 11084 and 11092 are fitted to the theoretical scattered wavefunctions to determine the three model parameters, magnitude, Gaussian radius, and phase, for the Born approximation of different orders. The three model parameters converge to some values at high-order Born approximations. The result of the first-order Born approximation is significantly different from the convergent value in some cases. The rate of convergence depends on the sunspot size and wavelength. It converges more rapidly for the smaller sunspot and longer wavelength. The magnitude increases with mode frequency and degree for each radial order. The Gaussian radius is insensitive to frequency and degree. The spatial range of the interaction parameter is greater than that of the continuum intensity deficit, but smaller than that of the acoustic power deficit of the sunspot. The phase versus phase speed falls into a small range. This suggests that the phase could be a function phase speed. NOAAs 11084 and 11092 have a similar magnitude and phase, although the ratio of their sizes is 0.75.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

ON THE INJECTION OF HELICITY BY THE SHEARING MOTION OF FLUXES IN RELATION TO FLARES AND CORONAL MASS EJECTIONS

An investigation of helicity injection by photospheric shear motions is carried out for two active regions (ARs), NOAA 11158 and 11166, using line-of-sight magnetic field observations obtained from the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. We derived the horizontal velocities in the ARs from the differential affine velocity estimator (DAVE) technique. Persistent strong shear motions at maximum velocities in the range of 0.6-0.9 km s{sup -1} along the magnetic polarity inversion line and outward flows from the peripheral regions of the sunspots were observed in the two ARs. The helicities injected in NOAA 11158 and 11166 during their six-day evolution period were estimated as 14.16 Multiplication-Sign 10{sup 42} Mx{sup 2} and 9.5 Multiplication-Sign 10{sup 42} Mx{sup 2}, respectively. The estimated injection rates decreased up to 13% by increasing the time interval between the magnetograms from 12 minutes to 36 minutes, and increased up to 9% by decreasing the DAVE window size from 21 Multiplication-Sign 18 to 9 Multiplication-Sign 6 pixel{sup 2}, resulting in 10% variation in the accumulated helicity. In both ARs, the flare-prone regions (R2) had inhomogeneous helicity flux distribution with mixed helicities of both signs and coronal mass ejection (CME) prone regions had almost homogeneous distribution of helicity flux dominated by a single sign. The temporal profiles of helicity injection showed impulsive variations during some flares/CMEs due to negative helicity injection into the dominant region of positive helicity flux. A quantitative analysis reveals a marginally significant association of helicity flux with CMEs but not flares in AR 11158, while for the AR 11166, we find a marginally significant association of helicity flux with flares but not CMEs, providing evidence of the role of helicity injection at localized sites of the events. These short-term variations of helicity flux are further discussed in view of possible flare-related effects. This study suggests that flux motions and spatial distribution of helicity injection are important to understanding the complex nature of the magnetic flux system of the AR, and how it can lead to conditions favorable for eruptive events.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Study on the triggering process of solar flares based on Hinode/SOT observations

We investigated four major solar flare events that occurred in active regions NOAA 10930 (2006 December 13 and 14) and NOAA 11158 (2011 February 13 and 15) by using data observed by the Solar Optical Telescope on board the Hinode satellite. To reveal the trigger mechanism of solar flares, we analyzed the spatio-temporal correlation between the detailed magnetic field structure and the emission image of the Ca II H line at the central part of flaring regions for several hours prior to the onset of the flares. In all the flare events, we observed that the magnetic shear angle in the flaring regions exceeded 70°, as well as that characteristic magnetic disturbances developed at the centers of flaring regions in the pre-flare phase. These magnetic disturbances can be classified into two groups depending on the structure of their magnetic polarity inversion lines; the so-called opposite-polarity and reversed-shear magnetic field recently proposed by our group, although the magnetic disturbance in one event of the four samples is too subtle to clearly recognize the detailed structure. The result suggests that some major solar flares are triggered by rather small magnetic disturbances. We also show that the critical size of the flare-trigger field varies among flare events and briefly discuss how the flare-trigger process depends on the evolution of active regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Evolution of the magnetic helicity flux during the formation and eruption of flux ropes

We describe the evolution and the magnetic helicity flux for two active regions (ARs) since their appearance on the solar disk: NOAA 11318 and NOAA 11675. Both ARs hosted the formation and destabilization of magnetic flux ropes. In the former AR, the formation of the flux rope culminated in a flare of C2.3 GOES class and a coronal mass ejection (CME) observed by Large Angle and Spectrometric Coronagraph Experiment. In the latter AR, the region hosting the flux rope was involved in several flares, but only a partial eruption with signatures of a minor plasma outflow was observed. We found a different behavior in the accumulation of the magnetic helicity flux in the corona, depending on the magnetic configuration and on the location of the flux ropes in the ARs. Our results suggest that the complexity and strength of the photospheric magnetic field is only a partial indicator of the real likelihood of an AR producing the eruption of a flux rope and a subsequent CME.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

ESTIMATE OF SOLAR MAXIMUM USING THE 1-8 Å GEOSTATIONARY OPERATIONAL ENVIRONMENTAL SATELLITES X-RAY MEASUREMENTS

We present an alternate method of determining the progression of the solar cycle through an analysis of the solar X-ray background. Our results are based on the NOAA Geostationary Operational Environmental Satellites (GOES) X-ray data in the 1-8 Å band from 1986 to the present, covering solar cycles 22, 23, and 24. The X-ray background level tracks the progression of the solar cycle through its maximum and minimum. Using the X-ray data, we can therefore make estimates of the solar cycle progression and the date of solar maximum. Based upon our analysis, we conclude that the Sun reached its hemisphere-averaged maximum in solar cycle 24 in late 2013. This is within six months of the NOAA prediction of a maximum in spring 2013.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Machine Learning-Based Investigation of the Associations between Residential Power Consumption and Weather Conditions

Machine learning feature selection analyses were conducted to understand the impact of various weather attributes on power electricity demand and its components in the northwest United States. Load profiles data were obtained from the Northwest Energy Efficiency Alliance (NEEA) and processed to yield hourly load profiles with the same temporal resolution as the weather conditions data obtained from the National Oceanic and Atmospheric Administration (NOAA) for representative weather stations. The data were divided into five seasons; for each season, for each load component, the influences of weather factors were evaluated and quantified using cross-correlation, principal component analysis, and mutual information evaluation; then predictive models were developed based on the ranked/screened factors using the regression tree (RT) approach. After multi-fold cross-validation, the optimal complexity/depth of the regress tree models is found to vary for different load components, and the prediction accuracy using RT and weather data can be higher than 80% for heating and refrigeration, or lower than 30% for vent and cooking. The study provides guidance on improvement of load profile generation, or even serves as a standalone predictive tool for approximating load profiles in balance authorities or climate zones where load profile data is absent.

load composite, load profiling, NEEA, mutual infor↗
DOE OSTI2023

Evaluation of the Near-Surface Variables in the HRRR Weather Model Using Observations from the ARM SGP Site

Abstract The performance of version 4 of the NOAA High-Resolution Rapid Refresh (HRRR) numerical weather prediction model for near-surface variables, including wind, humidity, temperature, surface latent and sensible fluxes, and longwave and shortwave radiative fluxes, is examined over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) region. The study evaluated the model’s bias and bias-corrected mean absolute error relative to the observations on different time scales. Forecasts of near-surface geophysical variables at five SGP sites (HRRR at 3-km scale) were found to agree well with observations, but some consistent observation–forecast differences also occurred. Sensible and latent heat fluxes are the most challenging variables to be reproduced. The diurnal cycle is the main temporal scale affecting observation–forecast differences of the near-surface variables, and almost all of the variables showed different biases throughout the diurnal cycle. Results show that the overestimation of downward shortwave and the underestimation of downward longwave radiative flux are the two major biases found in this study. The timing and magnitude of downward longwave flux, wind speed, and sensible and latent heat fluxes are also different with contributions from model representations, data assimilation limitations, and differences in scales between HRRR and SGP sites. The positive bias in downward shortwave and negative bias in longwave radiation suggests that the model is underestimating cloud fraction in the study domain. The study concludes by showing a brief comparison with version 3 of the HRRR and shows that version 4 has better performance in almost all near-surface variables. Significance Statement A correct representation of the near-surface variables is important for numerical weather prediction models. This study investigates the capability of the latest NOAA High-Resolution Rapid Refresh (HRRRv4) model in simulating the near-surface variables by comparing against the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) in situ observations. Among others, we find that the surface heat fluxes, such as sensible and latent heat fluxes, are the most difficult variables to be reproduced. This study also shows that the diurnal cycle has the dominant impact on the model’s performance, which means the majority of the outputted near-surface variables have the strong diurnal cycle in their bias errors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Subseasonal Earth System Prediction with CESM2

Abstract Prediction systems to enable Earth system predictability research on the subseasonal time scale have been developed with the Community Earth System Model, version 2 (CESM2) using two configurations that differ in their atmospheric components. One system uses the Community Atmosphere Model, version 6 (CAM6) with its top near 40 km, referred to as CESM2(CAM6). The other employs the Whole Atmosphere Community Climate Model, version 6 (WACCM6) whose top extends to ∼140 km, and it includes fully interactive tropospheric and stratospheric chemistry [CESM2(WACCM6)]. Both systems are utilized to carry out subseasonal reforecasts for the 1999–2020 period following the Subseasonal Experiment’s (SubX) protocol. Subseasonal prediction skill from both systems is compared to those of the National Oceanic and Atmospheric Administration CFSv2 and European Centre for Medium-Range Weather Forecasts (ECMWF) operational models. CESM2(CAM6) and CESM2(WACCM6) show very similar subseasonal prediction skill of 2-m temperature, precipitation, the Madden–Julian oscillation, and North Atlantic Oscillation to its previous version and to the NOAA CFSv2 model. Overall, skill of CESM2(CAM6) and CESM2(WACCM6) is a little lower than that of the ECMWF system. In addition to typical output provided by subseasonal prediction systems, CESM2 reforecasts provide comprehensive datasets for predictability research of multiple Earth system components, including three-dimensional output for many variables, and output specific to the mesosphere and lower-thermosphere (MLT) region from CESM2(WACCM6). It is shown that sudden stratosphere warming events, and the associated variability in the MLT, can be predicted ∼10 days in advance. Weekly real-time forecasts and reforecasts with CESM2(CAM6) and CESM2(WACCM6) are freely available. Significance Statement We describe here the design and prediction skill of two subseasonal prediction systems based on two configurations of the Community Earth System Model, version 2 (CESM2): CESM2 with the Community Atmosphere Model, version 6 [CESM2(CAM6)] and CESM 2 with Whole Atmosphere Community Climate Model, version 6 [CESM2(WACCM6)] as its atmospheric component. These two systems provide a foundation for community-model based subseasonal prediction research. The CESM2(WACCM6) system provides a novel capability to explore the predictability of the stratosphere, mesosphere, and lower thermosphere. Both CESM2(CAM6) and CESM2(WACCM6) demonstrate subseasonal surface prediction skill comparable to that of the NOAA CFSv2 model, and a little lower than that of the ECMWF forecasting system. CESM2 reforecasts provide a comprehensive dataset for predictability research of multiple aspects of the Earth system, including the whole atmosphere up to 140 km, land, and sea ice. Weekly real-time forecasts, reforecasts, and models are publicly available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Nowcasting Approach for Low-Earth-Orbiting Hyperspectral Infrared Soundings within the Convective Environment

Low-Earth-orbiting (LEO) hyperspectral infrared (IR) sounders have significant yet untapped potential for characterizing thermodynamic environments of convective initiation and ongoing convection. While LEO soundings are of value to weather forecasters, the temporal resolution needed to resolve the rapidly evolving thermodynamics of the convective environment is limited. Here, we have developed a novel nowcasting methodology to extend snapshots of LEO soundings forward in time up to 6 h to create a product available within National Weather Service systems for user assessment. Our methodology is based on parcel forward-trajectory calculations from the satellite-observing time to generate future soundings of temperature (T) and specific humidity (q) at regularly gridded intervals in space and time. The soundings are based on NOAA-Unique Combined Atmospheric Processing System (NUCAPS) retrievals from the Suomi National Polar-Orbiting Partnership (Suomi NPP) and NOAA-20 satellite platforms. The tendencies of derived convective available potential energy (CAPE) and convective inhibition (CIN) are evaluated against gridded, hourly accumulated rainfall obtained from the Multi-Radar Multi-Sensor (MRMS) observations for 24 hand-selected cases over the contiguous United States. Areas with forecast increases in CAPE (reduced CIN) are shown to be associated with areas of precipitation. The increases in CAPE and decreases in CIN are largest for areas that have the heaviest precipitation and are statistically significant compared to areas without precipitation. These results imply that adiabatic parcel advection of LEO satellite sounding snapshots forward in time are capable of identifying convective initiation over an expanded temporal scale compared to soundings used only during the LEO satellite overpass time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Lower Columbia River and Estuary Habitat Monitoring Study, 2011 - Final Report

The Ecosystem Monitoring Program is a collaborative effort between the Lower Columbia River Estuary Partnership (LCREP), University of Washington, Wetland Ecosystem Team (UW), US Geological Survey, Water Science Center (USGS), National Oceanic and Atmospheric Administration, National Marine Fisheries Service (NOAA-Fisheries, hereafter NOAA), and Pacific Northwest National Laboratory, Marine Sciences Laboratory (PNNL). The goal of the program is to conduct emergent wetland monitoring aimed at characterizing salmonid habitats in the lower Columbia River and estuary (LCRE) from the mouth of the estuary to Bonneville Dam (Figure 1). This is an ecosystem based monitoring program focused on evaluating status and trends in habitat and reducing uncertainties regarding these ecosystems to ultimately improve the survival of juvenile salmonids through the LCRE. This project comprehensively assesses habitat, fish, food web, and abiotic conditions in the lower river, focusing on shallow water and vegetated habitats used by juvenile salmonids for feeding, rearing and refugia. The information is intended to be used to guide management actions associated with species recovery, particularly that of threatened and endangered salmonids. PNNL’s role in this multi-year study is to monitor the habitat structure (e.g., vegetation, topography, channel morphology, and sediment type) as well as hydrologic patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Installation and Initial Operation of DOE's 449-MHz Wind Profiling Radars on the U.S. West Coast

The U.S. Department of Energy (DOE), in collaboration with the National Oceanic and Atmospheric Administration (NOAA), has recently completed the installation of three new wind profiling radars on the Washington and Oregon coasts. These systems operate at a frequency of 449 MHz and provide mean wind profiles to a height of roughly 8 km, with the maximum measurement height depending on time-varying atmospheric conditions. This is roughly half the depth of the troposphere at these latitudes. Each system is also equipped with a radio acoustic sounding system (RASS), which provides a measure of the temperature profile to heights of approximately 2 km. Other equipment deployed alongside the radar includes a surface meteorological station and GPS for column water vapor. This project began in fiscal year 2014, starting with equipment procurements and site selection. In addition, environmental reviews, equipment assembly and testing, site access agreements, and infrastructure preparations have been performed. Finally, with equipment deployment with data collection and dissemination, the primary tasks of this project have been completed. The three new wind profiling radars have been deployed at airports near Coos Bay, OR, and Astoria, OR, and at an industrial park near Forks, WA. Data are available through the NOAA Earth Systems Research Laboratory Data Display website, and will soon be made available through the DOE Atmosphere to Electrons data archive and portal as well.

17 WIND ENERGY↗
DOE OSTI2016

DOE's 449 MHz Wind Profiling Radars on the U.S. West Coast: Annual Report for Fiscal Year 2016

The three coastal wind profilers and associated meteorological instruments located in Forks, WA, Astoria, OR, and North Bend, OR, provide important observations at high temporal and vertical spatial resolution to characterize the meteorological inflow to the western region of the United States. These instruments have been operating for a year or more, and furnish boundary conditions for the modeling efforts of the WFIP2 project. The data have been delivered to archives at both NOAA and the DOE A2e DAP at a data recovery rate in excess of 98%. Site maintenance activities have been relatively minor, with a few component replacements and repairs to RASS foam. Bird mortality surveys have found no bird nests or carcasses, and the U.S. Fish and Wildlife Service has regularly been provided survey reports. This project represents a successful collaboration between PNNL and NOAA to procure, test, deploy, maintain, and operate three 449 MHz radar wind profilers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

The Verification and Validation Strategy Within the Second Wind Forecast Improvement Project (WFIP 2)

The Wind Forecast Improvement Project 2 (WFIP2), in the complex terrain of the Columbia Gorge, focuses on a set of weather phenomena that poses particular challenges for wind and wind power forecasting. It further aims to understand and improve the skill of weather forecast models, particularly the National Oceanic and Atmospheric Administration's (NOAA's) High Resolution Rapid Refresh (HRRR), in complex terrain. The project also includes an extensive field campaign in the Columbia River Gorge, during which data from many different instruments were collected. WFIP2 is funded by the U.S. Department of Energy (DOE). Scientists from four U.S. national laboratories, NOAA, Vaisala, and universities contribute to the project with wide and varied interests and skill sets. Therefore, coordinated verification & validation (V&V) efforts across these members allows for the development of a clear picture of model improvements and scientific findings within WFIP2. The WFIP2 V&V team is tasked with providing tools, methods, and guidance to enable repeatable, metrics-based assessment of the Weather Research and Forecasting (WRF) model and associated modeling suites for analysis and forecasting of mesoscale weather phenomena that are important for wind energy in the Columbia River Gorge and other parts of the continental United States. This report summarizes what has been worked on and accomplished within the duration of the WFIP2 project, 4 years, by the V&V team.

17 WIND ENERGY↗
DOE OSTI2021

Application of Point Precipitation Frequency Estimates to Watersheds

This report documents work sponsored by the U.S. Nuclear Regulatory Commission (NRC) at the Oak Ridge National Laboratory (ORNL) as part of the RES project, “Application of Point Precipitation Frequency Estimates to Watersheds.” This project was implemented as part of the Probabilistic Flood Hazard Assessment (PFHA) Research Program. The objective of the PFHA Research Program is to develop tools and guidance on the use of PFHA methods to risk-inform NRC’s licensing of new facilities as well as licensing and oversight of currently operating facilities as they relate to flooding hazards. Many nuclear power plants (NPPs) are located on or near rivers so riverine flooding hazards need to be considered in their design and operation. Probabilistic riverine flood models are important tools for realistic assessment of flooding risks. However, these models require areal estimates of the depth, duration, and frequency of rainfall distributed over the watershed, which are not often available. Point precipitation frequency estimates are more widely available. For example, the National Oceanic and Atmospheric Administration (NOAA) has published NOAA Atlas 14, which provides point precipitation frequency estimates for 5-minute through 60-day durations at average recurrence intervals of 1-year through 1,000-year. The research documented in this report addresses areal reduction factors (ARFs), which can be used to convert the widely available point precipitation frequency estimates, to estimates of areal precipitation frequency over a watershed. The most widely used ARF source is Technical Paper 29 (TP-29) published by the then U.S. Weather Bureau in 1958. However, both the methods and the underlying precipitation data used to produce TP-29 are seriously out of date. For example, due to the small gauge network available at the time of TP-29’s compilation, ARF estimates developed are only for watersheds smaller than about 400 square miles. Due to the relatively short record lengths of precipitation data available, frequency considerations could not be accurately determined. Other factors such as regional climate and seasonality were not addressed. Several newer methods have been published since TP-29 was developed and both the type and quantity of precipitation data have increased significantly, along with computational resources and analytical tools such as geographic information systems. This report reviewed and assessed the available precipitation products and methods for conducting ARF analysis. The work applied up-to-date precipitation data products and analysis methods with a novel watershed-based approach to investigate how ARF estimates vary across different methods, data sources, geographical locations, return periods, and seasons. The overall findings reported here regarding basic ARF trends are in line with other recent studies showing that ARFs decrease with increasing area, increase with increasing duration, and decrease with increasing return period. This study found significant differences among the available ARF methods. This work also found a strong geographical variability across different US hydrologic regions, suggesting that the ARF are specific to regional climate patterns and geographical characteristics and should not be applied arbitrarily to other locations. The results also reveal the importance of data record length, especially for high return level ARFs. The work reported in NUREG/CR-7271 will assist NRC staff in assessing different classes of ARF methods in conjunction with available rainfall data sets. It will also support the development of guidance for application of point precipitation data in PFHAs. It should be noted that the ARF values presented in this report for any location or region were developed for the purposes of comparing methods and investigating the factors that influence ARFs. They should not be considered official and should not be used in leu of a site-specific analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The Multi-scenario Extreme Weather Simulator: Energy Resilience for Mission Assurance

The Multi-scenario extreme weather simulator (MEWS) is a stochastic weather generation tool. The MEWS algorithm uses 50 or more years of National Oceanic and Atmospheric Association (NOAA) daily summaries [1] for maximum and minimum temperature and NOAA climate norms [2] to calculate historical heat wave and cold snap statistics. The algorithm takes these statistics and shifts them according to multiplication factors provided in the Intergovernmental Panel on Climate Change (IPCC) physical basis technical summary [3] for heat waves.

54 ENVIRONMENTAL SCIENCES↗