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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Projecting exposure to extreme climate impact events across six event categories and three spatial scales

The extent and impact of climate‐related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter‐Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events considered: river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves. Global warming of 2°C relative to preindustrial conditions is projected to lead to a more than five‐fold increase in cross‐category aggregate exposure globally. Changes in exposure are unevenly distributed, with tropical and subtropical regions facing larger increases than higher latitudes. The largest increases in overall exposure are projected for the population of South Asia.

climate‐related extreme events↗
DOE OSTI2024

Sensitivity of Fine‐Resolution Urban Heat Island Simulations to Soil Moisture Parameterization

ABSTRACT Urban areas experience the impact of natural disasters, such as heatwaves and flash floods, disparately in different neighbourhoods across a city. The demand for precise urban hydrometeorological and hydroclimatological modelling to examine this disparity, and the interacting challenges posed by climate change and urbanisation, has thus surged. The Weather Research and Forecasting (WRF) model has served such operational and research purposes for decades. Recent advancements in WRF, including enhanced numerical schemes and sophisticated urban atmospheric‐hydrological parameterizations, have empowered the simulation of urban geophysical processes at high resolution (~1 km), but even this resolution misses significant urban microclimate variability. This study applies the large‐eddy simulations (LES) mode within WRF, coupled with single‐layer urban canopy models (SLUCM), to enable even finer‐scale modelling (150 m) of the Urban Heat Island (UHI) effect in the Baltimore metropolitan area. We run nine scenarios to evaluate various methods of initializing soil moisture and various spinup lead times, and to assess the impact of WRF's Mosaic approach in depicting subgrid‐scale processes. We evaluate the scenarios by comparing the WRF simulated land surface temperature (LST) against Landsat LST and the WRF simulated hourly 2‐m air temperatures (AT) with observations from eight weather stations across the domain. Results underscore the paramount influence of the lead spinup time on the spatiotemporal distribution of simulated soil moisture, consequently shaping WRF's efficacy in predicting the UHI. Furthermore, interpolating soil moisture‐related parameters from the parent for child domain initialization yields a notable reduction in mean and root‐mean‐squared errors. This improvement was particularly evident in simulations with the longest spinup time, affirming the importance of carefully designing the initialization of soil moisture for improved urban temperature predictions.

Talebpour, Mahdad↗
NASA NTRS2015

Using Dynamically Downscaled Climate Model Outputs to Inform Projections of Extreme Precipitation Events

Many of the storms that generate damaging floods are caused by locally intense, sub-daily precipitation, yet the spatial and temporal resolution of the most widely available climate model outputs are both too coarse to simulate these events. Thus there is often a disconnect between the nature of the events that cause damaging floods and the models used to project how climate change might influence their magnitude. This could be a particular problem when developing scenarios to inform future storm water management options under future climate scenarios. In this study we sought to close this gap, using sub-daily outputs from the Weather Research and Forecasting model (WRF) from each of the nine climate regions in the United States. Specifically, we asked 1) whether WRF outputs projected consistent patterns of change for sub-daily and daily precipitation extremes; and 2) whether this dynamically downscaled model projected different magnitudes of change for 3-hourly vs 24-hourly extreme events. We extracted annual maximum values for 3-hour through 24-hour precipitation totals from an 11-year time series of hindcast (1995-2005) and mid-century (2045-2055) climate, and calculated the direction and magnitude of change for 3-hour and 24-hour extreme events over this timeframe. The model results project that the magnitude of both 3-hour and 24-hour events will increase over most regions of the United States, but there was no clear or consistent difference in the relative magnitudes of change for sub-daily vs daily events.

Climate models↗
NASA NTRS1977

Flood-plain delineation using multispectral data analysis

The paper explores the application of a remote sensing technique that may permit the determination of flood-plain areas without the extensive work associated with existing techniques. Multispectral scanner data were simulated by utilizing the density differences in a color-infrared transparency for a section of the Navasota River, Texas. The transparency was taken from a low-flying aircraft and covered an area approximating a square mile. The simulated data were processed by an automatic classification technique previously developed in the remote sensing field. The technique used involves the application of the maximum likelihood rule in order to categorize the data being processed. An attempt was made to distinguish between areas known to be in the flood plain and those outside. A reasonabke correlation was found between boundaries based on computer-processed multispectral data and those produced by techniques currently in use.

Harker, G. R.↗
NASA NTRS2021

Daily Precipitation Frequency Distributions Impacts on Land-Surface Simulations of CONUS

Many precipitation-driven data products from land data assimilation systems support assessments of droughts, floods, and other societally-relevant land-surface processes.The accumulated precipitation used as input to these products has a significant impacton water budgets; however, the effects of daily distribution of precipitation on theseproducts are not well known. A comparison of the Integrated Multi-satellite Retrievalsfor GPM (IMERG) and Climate Hazards Group InfraRed Precipitation with Stationsversion 2 (CHIRPS2) rainfall products over the continentalUnited States (CONUS) wasperformed to quantify the impacts of the daily distributionof precipitation on biases anderrors in soil moisture, runoff, and evapotranspiration (ET). Since the total accumulatedprecipitation between the IMERG and CHIRPS product differed, a third precipitationproduct, CHIRPS-to-IMERG (CHtoIM), was produced that usedCHIRPS2 accumulatedprecipitation totals and the daily precipitation frequency distribution of IMERG. Thisnew product supported a controlled analysis of the impact ofprecipitation frequencydistribution on simulated hydrological fields. The CHtoIM had higher occurrences ofprecipitation in the 0–5 mm day−1range, with a lower occurrence of dry days, whichdecreased soil moisture and surface runoff in the land-surface model. The surface soillayer had a tendency to reach saturation more often in the CHIRPS2 simulations, wherethe number of moderate to heavy precipitation days (>5mm day−1) was increased. Usingthe blended CHtoIM product as input reduced errors in surface soil moisture by 5–15%when compared to Soil Moisture Active/Passive (SMAP) data.Similarly, ET errors werealso slightly decreased (∼2%) when compared to SSEBop data. Moderate changes indaily precipitation distributions had a quantifiable impact on soil moisture, runoff, andET. These changes usually improved the model when compared to other modeled andobservational datasets, but the magnitude of the improvements varied by region andtime of year.

Daniel P Sarmiento↗
NASA NTRS1999

Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

Fox-Rabinovitz, Michael S.↗
NASA NTRS1985

Ohio River main stem study - The role of geographic information systems and remote sensing in flood damage assessments

The Pittsburgh District, Corps of Engineers, has conducted feasibility analyses of various procedures for performing flood damage assessments along the main stem of the Ohio River. Procedures using traditional, although highly automated, techniques and those based on geographic information systems have been evaluated at a test site, the City of New Martinsville, Wetzel County, WV. The flood damage assessments of the test site developed from an automated, conventional structure-by-structure appraisal served as the ground truth data set. A geographic information system was developed for the test site which includes data on hydraulic reach, ground and reference flood elevations, and land use/cover. Damage assessments were made using land use mapping developed from an exhaustive field inspection of each tax parcel. This ground truth condition was considered to provide the best comparison of flood damages to the conventional approach. Also, four land use/cover data sets were developed from Thematic Mapper Simulator (TMS) and Landsat-4 Thematic Mapper (TM) data. One of these was also used to develop a damage assessment of the test site. This paper presents the comparative absolute and relative accuracies of land use/cover mapping and flood damage assessments, and the recommended role of geographic information systems aided by remote sensing for conducting flood damage assessments and updates along the main stem of the Ohio River.

Edwardo, H. A.↗
DOE OSTI2024

Risk Considerations of Transitioning CO2-EOR Field to CO2 storage Field: Case Study

In the United States (U.S.), carbon dioxide (CO2) injection wells at EOR sites are currently regulated as Class II wells under the U.S. Environmental Protection Agency’s (EPA) Underground Injection Control (UIC) program while dedicated geological CO2 storage (GCS) wells are considered Class VI wells. A CO2-EOR facility considering a transitioning from tertiary oil recovery to injecting CO2 for the primary purpose of long-term storage is required to obtain a Class VI permit where this transition poses an increased risk to underground sources of drinking water. This study considers how transitioning operations from CO2-EOR to storage can impact reservoir plume and pressure transient in the storage envelope, and how these changes could impact area of review and potential unwanted fluid migration. We developed a case study to assess subsurface response and leakage risks associated with a representative, hypothetical operation in a carbonate reservoir. This reservoir transitions from tertiary hydrocarbon recovery to dedicated GCS. Reservoir simulations were run for a set of credible CO2-EOR scenarios to estimate distributions of fluids phases and pressures throughout the model domain after CO2 flooding as well as forecasting the behavior of the reservoir after the transition to a dedicated storage phase. The evolutions from all simulated scenarios were used as the basis for leakage risk quantification using the National Risk Assessment Partnership’s Open-Source Integrated Assessment Model (NRAP-Open-IAM) with a novel reduced-order model to estimate time-dependent leakage of CO2, brine, and hydrocarbon fluids through potentially leaky wells. Results include a description of reservoir response, an estimate of the areal extent that could potentially be impacted by leakage to underground sources of drinking water, and estimates of the magnitude of potential leakage. Considerations for dedicated storage injection well selection, injectivity, and injection scheme performance and potential leakage risk are presented, with implications for risk assessment of well transition discussed. This study presents a risk-based workflow for the Class II to Class VI well transition. Integrating credible numerical simulation of viable CO2-EOR to dedicated CO2 storage with quantitative risk assessment tools, such as the NRAP-Open-IAM, will provide a valuable means to devise operational scenarios and inform decision-making related to storage benefit, leakage risk, and liability. Presented at the SPE/AAPG/SEG Carbon Capture Utilization and Storage Conference in Houston, TX, March 11-13, 2024.

Liu, Guoxiang↗
NASA NTRS1995

Remote sensing of flooding in the U.S. upper Midwest during the summer of 1993

The U.S. upper Midwest was subjected to severe flooding during the summer of 1993. Heavy rainfall in the Mississippi River basin from April through July caused flooding on many Midwest rivers, including the Mississippi, Illinois, Missouri, and Kansas Rivers. The flood crest of 15.1 m at St. Louis, Missouri, on 1 August 1993 was the highest ever measured, surpassing the previous record of 13.2 m set on 28 April 1973. Damage estimates include at least 47 flood-related deaths and a total damage cost of $12 billion. Remotely sensed imagery of severe flooding in the U.S. Midwest was obtained under cloud-free skies on 29 July 1993 by the MODIS (Moderate Resolution Imaging Spectroradiometer) Airborne Simulator (MAS). The MAS is a newly developed scanning spectrometer with 50 spectral bands in the wavelength range 0.55-14.3 micrometers. Estimation of the total flooded area in the MAS scene acquired near St. Louis was accomplished by comparing the MAS scene to a Landsat-5 thematic mapper (TM) scene of the same area acquired on 14 April 1984 in nonflood conditions. For comparison, the MAS band centered at 0.94 micrometers and the TM band centered at 1.65 micrometers were selected because of the high contrast seen in these bands between land and water-covered surfaces. An estimate of the area covered by water in the MAS and TM scenes was obtained by developing land/water brightness thresholds from histograms of the MAS and TM digital image data. Afetr applying the thresholds, the difference between the area covered by water in the MAS and TM scenes, and hence the flooded area in the MAS scene, was found to be about 396 sq km, or about 153 square miles.

Gumley, Liam E.↗
NASA NTRS2003

Comparisons and Contrasts Between Mediterranean Flood-Producing Orographic Storms and Tropical Cyclones Modified by Complex Orography

Often, late-year, flood-producing storms in the Mediterranean Alps region arise from baroclinic disturbances developing on westerly longwaves, with the incipient storm circulations appearing well west of the flood zone. Regardless of the genesis locations and before the storms begin their flow interactions with the orography of the Mediterranean Alps, a process which can produce intense long-lived rainfall over the mountainous terrain of Italy and France, most of their moisture is drawn from warm Mediterranean waters while important elements of their thermodynamic structure are derived from airmass properties originating in north Africa and the Mediterranean basin itself. In fact, because of strong thermodynamic contrasts between the baroclinic zone producing the incipient disturbance and high potential temperature air from the south advecting into and wrapping around the storm center, a Mediterranean storm whose origins are from an evolving shortwave baroclinic perturbation, can become a quasi-warm core hybrid in term of its energetics composition, a process somewhat akin to the development of polar lows. This process begs the question of whether there are similarities between the autumn-winter season flood producing storms of the Mediterranean Alps and warm core tropical cyclones which become altered dynamically and thermodynamically by landfall over steep orographic terrain. This study investigates, from a comparison and contrast perspective, how the similarities and differences between the two types of storms manifest themselves over their respective life cycles. Before the orographically-induced precipitation-release stage in which both types of storm have evolved to the same hydrometeorlogical conclusion, the two storm categories are transforming from entirely distinctive origins, i.e., the classic eastward traveling, baroclinic mid-latitude cyclone forming in western Europe, and the classic eastward-traveling, warm core tropical cyclone developing in the western Pacific. The analyses use high resolution, nonhydrostatic model simulations, satellite data, and various types of ground data to conduct the study. The flood events of Piemonte- 2000 in northern Italy and Typhoon Rusa-2002 in South Korea are selected to focus the analysis on well documented meteorological events.

Smith, Eric A.↗
NASA NTRS1972

A digital simulation of message traffic for natural disaster warning communications satellite

Various types of weather communications are required to alert industries and the general public about the impending occurrence of tornados, hurricanes, snowstorms, floods, etc. A natural disaster warning satellite system has been proposed for meeting the communications requirements of the National Oceanic and Atmospheric Administration. Message traffic for a communications satellite was simulated with a digital computer in order to determine the number of communications channels to meet system requirements. Poisson inputs are used for arrivals and an exponential distribution is used for service.

Hein, G. F.↗
DOE OSTI2021

A HPC Theory-Guided Machine Learning Cyberinfrastructure for Communicating Hydrometeorological Data Across Scales

High-resolution predictions of hydrometeorological variables are critical for supporting hydropower generation decisions and flood control at hydroelectric power plants. Traditional climate and hydrologic models rely on the numerical simulation of detailed physical processes. Therefore, running these simulations is time-, labor-, and computation-intensive. Improving the spatial and temporal resolution in these modeling outputs could lead to cubic increases in both the simulation time and computational demands, rendering high-resolution hydrometeorological predictions expensive and impractical. Many past studies apply the super resolution (SR) technique to downscale climate models using deep learners. However, deep learners are deemed “black-boxes,” as their derivation processes from low-resolution outputs to high-resolution outputs are often hidden. Their results are difficult for domain scientists to interpret and validate. Thus, there is a need for an exploratory machine learning approach that can partially integrate domain-specific theory and knowledge into the data-driven mapping process between simulation outputs of different spatial scales. The domain-specific theory and knowledge can be incorporated into the data model through an inductive approach in which process-related environmental variables are used and analyzed as key drivers (i.e., environmental surrogates) to reflect the complex physical processes. Many of these variables, such as land use land cover, soil types, topography, digital elevation, air temperature, and various watershed characteristics, can be directly measured through sensors or remote sensing techniques. Additionally, SR applications that can downscale hydrological and hydrodynamics models to efficiently produce high-resolution (1 m) flood depth grids are still rare. Since the flood depth grid can be used to support critical decisions for flood control operation at hydroelectric power plants, it is crucial to enable an SR-based capability for interpolating high-resolution flood inundation maps.

13 HYDRO ENERGY↗
NASA NTRS1978

Communications technology satellite: United States experiments and disaster communications applications

Ground antennas from 0.6 to 5.0 meters in diameter were used as remote earth terminals by the United States for both wideband (television) and narrowband (voice, data) communication in conjunction with the Canadian Hermes satellite's high power transmitter. Experiments summarized cover teleconferencing and duplex videoconferencing for medical, educational, and civic purposes, as well as the remote interpretation of multilingual broadcasts from the United Nations. The capabilities of the system during real and simulated disasters at airports are assessed. Particular attention is given to miniexperiments for flood control in the Mississippi River basin and in Johnstown, Pennsylvania during the 1977 flood.

Donoughe, P.↗
NASA NTRS1991

Spatial Analysis and Modeling Systems (SAMS)

The objective is to develop a uniform environmental data gathering and distribution system to support (1) emergency management for environmental disasters, and (2) the calibration and validation of remotely sensed data. Initial activities will be to select a data test site and to demonstrate multi-discipline applications using simulated or satellite data in a non real-time mode. Rainfall and flooding are chosen as the testbeds for the SAMS concept because of the abundance of data and the availability of models. The capability to display and process GOES data and analyze GOES generated rain-rate maps will be integrated into SAMS.

Vermillion, Charles↗
NASA NTRS1999

Precipitation Recycling in the NASA GEOS Data Assimilation System

Analysis of precipitation recycling can improve the understanding of regional hydrologic anomalies, especially their evolution and maintenance. Diagnostic models of the recycling of precipitation and are applied to 15 years of the NASA Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). Recycled precipitation is defined as the fraction of precipitation within a given region that originated as surface evaporation from the same region. The focus of the present work is on the interannual variability of the central United States hydrologic cycle and precipitation recycling. The extreme years of 1988 (drought) and 1993 (flood) are compared with the 15 year base period mean annual cycle. The results indicate that recycling ratio (the amount of precipitation with a local source relative to the total precipitation) is greater in 1988 than both the base period mean and the 1993 season (with 1993 recycling ratio less than the mean). On the other hand, both the summers of 1988 and 1993 show less total recycled precipitation than the mean. The results also show that precipitation recycling may have been more important in the spring of 1993, when the region was primed for flooding, than the summer, when the sever flooding occurred. The diagnostic approaches to precipitation recycling suffer from some weaknesses. Numerical simulations and assimilation using passive tracers have the potential to provide more accurate calculations of precipitation recycling and the remote sources of water. This ability is being incorporated into the latest GEOS data assimilation system, and some preliminary results will be presented.

Bosilovich, Michael G.↗
DOE OSTI2025

An efficient hybrid downscaling framework to estimate high-resolution river hydrodynamics

Flow depth and velocity are the most important hydrodynamic variables that govern various river functions, including water resources, navigation, sediment transport, and biogeochemical cycling. Existing high-resolution flow depth simulations rely on either computationally expensive river hydrodynamic models (RHMs) or data-driven models with formidable training costs, whereas data-driven modeling of flow velocity has rarely been explored. Here, using the hybrid Low-fidelity, Spatial analysis, and Gaussian process learning (LSG) model, we developed a downscaling approach to construct high-resolution flow depth and velocity from a two-dimensional (2-D) RHM simulation at coarse resolution. The LSG models were trained and tested in an urban watershed in Houston using two different hurricane-driven flood events. The high-resolution (as fine as 30 m resolution) and low-resolution (mostly 1000 m resolution) meshes include 664 724 and 14 536 grid cells, respectively. The results showed that through downscaling, the simulation errors were reduced to less than one-fourth and one-third of the errors of the low-resolution 2-D RHM for flow depth and velocity, respectively. Our analysis further revealed that the dominant uncertainty sources of the downscaled hydrodynamics are different, with flow velocity dominated by the dimensionality reduction error, which we reduced by using a regionalized training procedure. The downscaling approach achieves an 84-fold acceleration in computational time compared to the high-resolution 2-D RHM, making high-fidelity ensemble flood modeling feasible. More importantly, the developed method provides an opportunity to couple large-scale hydrodynamical processes with local physical, chemical, and biological processes in river models.

Tan, Zeli [Pacific Northwest National Laboratory (↗
DOE OSTI2021

Insights into storm direction effect on flood response

In this study, we investigate the directional influence of storm movement on catchment flood peak response using the synthetic circular basin. Due to the complexity in defining storm movements that require meteorological modeling, we adopt a novel approach of combining the basin rotation method (BRM) with a circular basin construct. A systematic basin rotation approach provides a proxy for the storm direction relative to the river network topology to study its hydrologic response. Using Stage-IV rainfall with 4-km by 1-hour resolution for 16 years period from 2003 to 2018 in Iowa, U.S., we systematically analyze consequent flood peak response due to storm directions (basin rotations) using a distributed hydrologic model called the Hillslope-Link Model (HLM). HLM has demonstrated the ability to reproduce observed streamflow for real river basins studied in Iowa. The hydrologic simulation results show that the BRM can quantify the relationship between the rainstorm direction and catchment hydrologic response. Also, the maximum flood peak response is strongly dependent on the interaction of the peak of the rainstorm with the peak of the width function. The results indicate significant differences in runoff volume and runoff peak and their interannual variability due to rainstorm direction. The study has important implications for flood frequency predictions and developing flood resilience and watershed management strategies, particularly due to changing storm tracks under a warming climate.

42 ENGINEERING↗