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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Steelhead Overshoot and Fallback Rates in the Columbia–Snake River Basin and the Influence of Hatchery and Hydrosystem Operations

Abstract Tributary overshoot occurs when adult salmonids homing to natal sites continue upstream past the mouth of their natal stream. Although overshooting is a common behavior by steelhead Oncorhynchus mykiss in the Columbia River basin, it has not been adequately quantified or explained. Using multistate release–recapture models, we examined the prevalence of overshooting and fallback to natal tributaries by 37,806 PIT-tagged steelhead from 14 tributaries of the Columbia River basin during 2005–2015. Eight populations had overshooting rates exceeding 50% in at least 1 year. Source of hatchery stock, rearing location, and release practices were found to have appreciable effects on overshoot rates. Overshooting was elevated in hatchery stocks reared upstream of release sites, but this effect may be lessened by utilizing endemic broodstocks and acclimating juveniles within the release basin. For one population of hatchery steelhead, acclimation within the release basin was found to decrease overshooting from 81% to 40%. Across both hatchery and wild populations, successful homing was found to decline 4 percentage points for every 5-percentage-point increase in overshoot rate. Average annual fallback probabilities ranged from 0.18 for Walla Walla River hatchery steelhead to 0.75 for Umatilla River wild steelhead. Fish stocks with the greatest fallback probabilities also had the greatest interannual variability in fallback rates. For John Day River wild steelhead and Tucannon River hatchery steelhead, the interannual range in fallback probabilities exceeded 0.50. We found evidence that spill at dams during March may enhance the fallback of overshooting steelhead and contribute to increased homing to natal tributaries. Therefore, additional attention should be paid to facilitating downstream dam passage of adult salmon.

Richins, Shelby M.↗
NASA NTRS1989

Constraints on the deep structure and dynamic processes beneath the Alps and adjacent regions from an analysis of gravity anomalies

Gravity anomalies over the Alps and the Molasse Basin are examined, focusing on the relationship between the anomalies and the tectonic processes beneath the region. Bouguer gravity anomalies measured in France, Germany, Italy, and Switzerland are analyzed. No large isostatic anomalies are observed over the Alps and an elastic model is unable to account for gravity anomalies over the Molasse Basin. These results suggest that the dynamic processes that flexed the European plate down, forming the Molasse Basin and building the Alpine chain, have waned. It is proposed that the late Cenozoic uplift of the region may be due to a diminution or termination of downwelling of mantle material.

Lyon-Caen, Helene↗
NASA NTRS2021

Powder River Basin Water Resources: Mapping Russian Olive in the Powder River Basin to Inform Invasive Species Management

Since its introduction in the late 1800s, Elaeagnus augustifolia (Russian olive) has become a widespread invasive shrub that poses a threat to native riparian species in the United States by competing with native riparian plants for space and resources. To date, limited information on the distribution of Russian olive in the Powder River Basin of Montana and Wyoming have hampered management efforts and decision making. Here, we detect and model the distribution of Russian Olive using field surveys, ocular sampling, and variables from Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and Shuttle Radar Topography Mission (SRTM) using the Random Forest algorithm. We derived topographic, spectral, and hydrological variables from Landsat 8 OLI, Sentinel-2 MSI, and SRTM to utilize as model inputs. The team was able to successfully create a spectral Russian olive detection map for the Powder River Basin (RMSE =15.44%, R2 = 0.6482). The team also examined change in stream channel geomorphology from 1984-2020 in a time-series analysis using Landsat visible imagery and the RivMap MATLAB package and found little change. Our results will help our partners at the Powder River County Weed Board, Gay Ranch, United States Geological Survey, and University of Northern Colorado to locate and prioritize areas for riparian habitat restoration and to understand the region’s hydrology and geomorphology.

Catherine Buczek↗
NASA NTRS2018

The Little Ice Age and Human-Environmental Interactions in the Central Balkans: Insights from a New Serbian Paleorecord

This paper presents a 600-year well-dated, high-resolution Central Balkan paleo-record including the Little Ice Age (LIA; 1450-850 CE). Utilizing pollen-based REVEALS modelling estimates, geochemical indicators, rarefaction analyses and the AMS 14C-based Bacon age model, this first-hand record from the Sava Basin reveals the transformation of the Central Balkan landscape involving linkages between changing climatic and socio-political regimes. The pre-LIA interval (1370-1418 CE) in the Sava Region reveals a wooded steppe and increased cultivation under warmer/stable climatic and socio-political conditions. In contrast, the LIA interval in the region is expressed through continuous transitions between forest and grassland, extensive land erosion and stressed agriculture, potentially as a collective artifact of the climatic variability and human impact associated with socio- political stressors of the time. The post-LIA/Industrial Era interval (1850-2012 CE) in the Sava Region shows an overall increase in woodland as well as agriculture following the exit of the Ottomans. However, increased population pressures and the subsequent onset of the Industrial Revolution as well as increased trade led to intense deforestation throughout the 20th Century, which continued during the Socialist period.

Societal impacts of climate change↗
DOE OSTI2014

Modeling the effect of glacier recession on streamflow response using a coupled glacio-hydrological model

Here, we describe an integrated spatially distributed hydrologic and glacier dynamic model, and use it to investigate the effect of glacier recession on streamflow variations for the Upper Bow River basin, a tributary of the South Saskatchewan River. Several recent studies have suggested that observed decreases in summer flows in the South Saskatchewan River are partly due to the retreat of glaciers in the river's headwaters. Modeling the effect of glacier changes on streamflow response in river basins such as the South Saskatchewan is complicated due to the inability of most existing physically-based distributed hydrologic models to represent glacier dynamics. We compare predicted variations in glacier extent, snow water equivalent and streamflow discharge made with the integrated model with satellite estimates of glacier area and terminus position, observed streamflow and snow water equivalent measurements over the period of 1980 2007. Simulations with the coupled hydrology-glacier model reduce the uncertainty in streamflow predictions. Our results suggested that on average, the glacier melt contribution to the Bow River flow upstream of Lake Louise is about 30% in summer. For warm and dry years, however, the glacier melt contribution can be as large as 50% in August, whereas for cold years, it can be as small as 20% and the timing of glacier melt signature can be delayed by a month.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Abstract Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

Air Pollution Over the Ganges Basin and Northwest Bay of Bengal in the Early Postmonsoon Season Based on NASA MERRAero Data

The MERRA Aerosol Reanalysis (MERRAero) has been recently developed at NASA's Global Modeling Assimilation Office. This reanalysis is based on a version of the Goddard Earth Observing System-5 (GEOS-5) model radiatively coupled with Goddard Chemistry, Aerosol, Radiation, and Transport aerosols, and it includes assimilation of bias-corrected aerosol optical thickness (AOT) from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on both Terra and Aqua satellites. In October over the period 2002-2009, MERRAero showed that AOT was lower over the east of the Ganges basin than over the northwest of the Ganges basin: this was despite the fact that the east of the Ganges basin should have produced higher anthropogenic aerosol emissions because of higher population density, increased industrial output, and transportation. This is evidence that higher aerosol emissions do not always correspond to higher AOT over the areas where the effects of meteorological factors on AOT dominate those of aerosol emissions. MODIS AOT assimilation was essential for correcting modeled AOT mainly over the northwest of the Ganges basin, where AOT increments were maximal. Over the east of the Ganges basin and northwest Bay of Bengal (BoB), AOT increments were low and MODIS AOT assimilation did not contribute significantly to modeled AOT. Our analysis showed that increasing AOT trends over northwest BoB (exceeding those over the east of the Ganges basin) were reproduced by GEOS-5, not because of MODIS AOT assimilation butmainly because of the model capability of reproducing meteorological factors contributing to AOT trends. Moreover, vertically integrated aerosol mass flux was sensitive to wind convergence causing aerosol accumulation over northwest BoB.

AOT↗
DOE OSTI2019

Using a coupled agent-based modeling approach to analyze the role of risk perception in water management decisions

Abstract. Managing water resources in a complex adaptive natural–human system is a challenge due to the difficulty of modeling human behavior under uncertain risk perception. The interaction between human-engineered systems and natural processes needs to be modeled explicitly with an approach that can quantify the influence of incomplete/ambiguous information on decision-making processes. In this study, we two-way coupled an agent-based model (ABM) with a river-routing and reservoir management model (RiverWare) to address this challenge. The human decision-making processes is described in the ABM using Bayesian inference (BI) mapping joined with a cost–loss (CL) model (BC-ABM). Incorporating BI mapping into an ABM allows an agent's psychological thinking process to be specified by a cognitive map between decisions and relevant preceding factors that could affect decision-making. A risk perception parameter is used in the BI mapping to represent an agent's belief on the preceding factors. Integration of the CL model addresses an agent's behavior caused by changing socioeconomic conditions. We use the San Juan River basin in New Mexico, USA, to demonstrate the utility of this method. The calibrated BC-ABM–RiverWare model is shown to capture the dynamics of historical irrigated area and streamflow changes. The results suggest that the proposed BC-ABM framework provides an improved representation of human decision-making processes compared to conventional rule-based ABMs that do not take risk perception into account. Future studies will focus on modifying the BI mapping to consider direct agents' interactions, up-front cost of agent's decision, and upscaling the watershed ABM to the regional scale.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Analyzing historical snow trends in interior Alaska

Study region The Chena River watershed in Interior Alaska, USA Study focus This study examines 40 years (water years 1982–2021) of snowpack characteristics to consider its hydrological implications in the 5350 km² Chena River basin. Using observations and a fine-scale physics model, we analyzed trends of snow water equivalent (SWE), snow onset and disappearance, and snow cover duration (SCD). New hydrological insights for the region Results indicate a decline in SWE across the modeled domain, averaging a decrease of 3 mm per decade, with larger decreases (up to 10 mm per decade) at lower elevations. While domain-averaged SWE trends were not statistically significant, observed SCD showed statistically significant decreases: −5.2, −5.0, and −4.4 days per decade at Teuchet Creek, Fairbanks F.O., and Little Chena Ridge, respectively. Notably, observations at SNOTEL stations and modeling revealed no statistically significant change in domain-averaged Rain-on-Snow (ROS) events over the 40-year period, contrasting some regional future estimates of increased ROS frequency. Peak streamflow did not consistently correlate with peak SWE levels, suggesting that other environmental factors such as ROS events and rapid temperature increases (e.g., a 10°C spike observed in 1992) are key drivers of hydrological outcomes. These findings improve understanding of complex subarctic hydrological processes impacting permafrost and highlight the need for adaptive water resource management to mitigate multi-factor risks like flooding and wildfire, requiring proactive planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Geomechanical Framework for Secure CO 2 Storage in Fractured Reservoirs and Caprocks for Sedimentary Basins in theMidwest United States

This report presents final technical results for the project Geomechanical Framework for Secure CO 2 Storage in Fractured Reservoirs and Caprocks for Sedimentary Basins in the Midwest United States (DE-FE0023330). The project was a three-year effort consisting of seven technical tasks focused on defining geomechanical factors for CO 2 storage applications in deep saline rock formations in Ohio and the Midwest United States, because geomechancial issues have been identified as a significant risk factor for large-scale CO 2 storage applications. A basin-scale stress-strain analysis was completed to describe the geomechanical setting for rock formations of Ordovician-Cambrian age in Ohio and adjacent areas of the Midwest United States in relation to geologic CO 2 storage applications. The tectonic setting, stress orientation-magnitude, and geomechanical and petrophysical parameters for CO 2 storage zones and caprocks in the region were cataloged. Ten geophysical image logs were analyzed for natural fractures, borehole breakouts, and drilling-induced fractures. The logs indicated mostly less than 10 fractures per 100 vertical feet in the borehole, with mostly N65E principal stress orientation through the section. Geophysical image logs and other logs were obtained for three wells located near the sites where specific models were developed for geomechanical simulations: Arches site in Boone County, Kentucky; Northern Appalachian Basin site in Chautauqua County, New York; and E-Central Appalachian Basin site in Tuscarawas County, Ohio. For these three wells, 9,700 feet of image logs were processed and interpreted to provide a systematic review of the distribution within each well of natural fractures, wellbore breakouts, faults, and drilling induced fractures. There were many borehole breakouts and drilling-induced tensile fractures but few natural fractures. Concentrated fractures were present at the Rome-basal sandstone and basal sandstone-Precambrian contacts at the Arches and East-Central Appalachian Basin sites. Geophysical logs were utilized to develop local-scale geologic models by determining geomechanical and petrophysical parameters within the geologic formations. These data were ported to coupled fluid-flow and reservoir geomechanics multi-phase CO 2 injection simulations. The models were developed to emphasize the geomechanical layers within the CO 2 storage zones and caprocks. A series of simulations were completed for each site to evaluate whether commercial-scale CO 2 could be safely injected into each site, given site-specific geologic and geomechanical controls. This involved analyzing the simulation results for the integrity of the caprock, intermediate, and reservoir zones, as well quantifying the areal uplift at the surface. Simulation results were also examined to ensure that the stress-stress perturbations were isolated within the subsurface, and that there was only limited upward migration of the CO 2 . Simulations showed capacity to inject more than 10 million metric tons of CO 2 in a single well at the Arches and East Central Appalachian Basin sites without excessive geomechanical risks. Low-permeability rock layers at the Northern Appalachian Basin study area well resulted in very low CO 2 injection capacity. Fracture models developed for the sites suggests that the sites have sparse fracture network in the deeper Cambrian rocks. However, there were indicators in image logs of a moderate fracture matrix in the Rose Run Sandstone at the Northern Appalachian Basin site. Dual permeability fracture matrix simulations suggest the much higher injection rates may be feasible in the fractured interval. Guidance was developed for geomechanical site characterization in the areas of geophysical logging, rock core testing, well testing, and site monitoring. The guidance demonstrates that there is a suitable array of options for addressing geomechanical issues at CO 2 storage sites. Finally, a review of Marcellus and Utica-Point Pleasant shale gas wells and CO 2 storage intervals indicates that these items are vertically separated, except for the Oriskany sandstone and Marcellus wells in southwest Pennsylvania and northern West Virginia. Together, project results present a more realistic portrayal of geomechanical risk factors related to CO 2 storage for existing and future coal-fired power plants in Ohio.

58 GEOSCIENCES↗
DOE OSTI2018

A hydrological emulator for global applications – HE v1.0.0

Abstract. While global hydrological models (GHMs) are very useful in exploring water resources and interactions between the Earth and human systems, their use often requires numerous model inputs, complex model calibration, and high computation costs. To overcome these challenges, we construct an efficient open-source and ready-to-use hydrological emulator (HE) that can mimic complex GHMs at a range of spatial scales (e.g., basin, region, globe). More specifically, we construct both a lumped and a distributed scheme of the HE based on the monthly abcd model to explore the tradeoff between computational cost and model fidelity. Model predictability and computational efficiency are evaluated in simulating global runoff from 1971 to 2010 with both the lumped and distributed schemes. The results are compared against the runoff product from the widely used Variable Infiltration Capacity (VIC) model. Our evaluation indicates that the lumped and distributed schemes present comparable results regarding annual total quantity, spatial pattern, and temporal variation of the major water fluxes (e.g., total runoff, evapotranspiration) across the global 235 basins (e.g., correlation coefficient r between the annual total runoff from either of these two schemes and the VIC is >0.96), except for several cold (e.g., Arctic, interior Tibet), dry (e.g., North Africa) and mountainous (e.g., Argentina) regions. Compared against the monthly total runoff product from the VIC (aggregated from daily runoff), the global mean Kling–Gupta efficiencies are 0.75 and 0.79 for the lumped and distributed schemes, respectively, with the distributed scheme better capturing spatial heterogeneity. Notably, the computation efficiency of the lumped scheme is 2 orders of magnitude higher than the distributed one and 7 orders more efficient than the VIC model. A case study of uncertainty analysis for the world's 16 basins with top annual streamflow is conducted using 100 000 model simulations, and it demonstrates the lumped scheme's extraordinary advantage in computational efficiency. Our results suggest that the revised lumped abcd model can serve as an efficient and reasonable HE for complex GHMs and is suitable for broad practical use, and the distributed scheme is also an efficient alternative if spatial heterogeneity is of more interest.

Liu, Yaling↗
DOE OSTI2018

Regional Geologic Evaluations for Disposal of HLW and SNF: Alluvial Basins of the Basin and Range Province

The DOE Spent Fuel and Waste Technology (SFWT) R&D Campaign supports research on crystalline rock, shale (argillite) and salt as potential host rocks for disposal of HLW and SNF in a mined geologic repository. Modeling involving these host rocks for the generic GDSA reference cases has assumed saturated conditions at repository depths. In order to test two-phase flow capabilities of the GDSA flow and transport models, the SFWT Campaign is developing an unsaturated zone reference case. Alluvial basin-fill deposits within the Basin and Range province have unsaturated zones that can be as thick as 600 meters, although the thickness is typically much less. Basin-fill alluvium has been considered as a potential medium for HLW disposal in the US since the 1950s (NAS,1957; Smyth et al., 1979; Winograd, 1981). Attributes considered favorable for HLW disposal in alluvium in the Basin and Range province include an arid environment, low water flux , high sorption capacity (from clay s and zeolites), and ease of construction and stability of repository openings (Hardin et al., 2012). Hardin et al. (2012) also address the thermal issues inherent in the design of a HLW repository in alluvium with low thermal conductivity, which are not discussed in this report.

58 GEOSCIENCES↗
NASA NTRS2016

Snow Process Estimation Over the Extratropical Andes Using a Data Assimilation Framework Integrating MERRA Data and Landsat Imagery

A data assimilation framework was implemented with the objective of obtaining high resolution retrospective snow water equivalent (SWE) estimates over several Andean study basins. The framework integrates Landsat fractional snow covered area (fSCA) images, a land surface and snow depletion model, and the Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis as a forcing data set. The outputs are SWE and fSCA fields (1985-2015) at a resolution of 90 m that are consistent with the observed depletion record. Verification using in-situ snow surveys showed significant improvements in the accuracy of the SWE estimates relative to forward model estimates, with increases in correlation (0.49-0.87) and reductions in root mean square error (0.316 m to 0.129 m) and mean error (-0.221 m to 0.009 m). A sensitivity analysis showed that the framework is robust to variations in physiography, fSCA data availability and a priori precipitation biases. Results from the application to the headwater basin of the Aconcagua River showed how the forward model versus the fSCA-conditioned estimate resulted in different quantifications of the relationship between runoff and SWE, and different correlation patterns between pixel-wise SWE and ENSO. The illustrative results confirm the influence that ENSO has on snow accumulation for Andean basins draining into the Pacific, with ENSO explaining approximately 25% of the variability in near-peak (1 September) SWE values. Our results show how the assimilation of fSCA data results in a significant improvement upon MERRA-forced modeled SWE estimates, further increasing the utility of the MERRA data for high-resolution snow modeling applications.

SWE↗
DOE OSTI2022

Investigating coastal backwater effects and flooding in the coastal zone using a global river transport model on an unstructured mesh

Abstract. Coastal backwater effects are caused by the downstream water level increase as a result of elevated sea level, high river discharge and their compounding influence. Such effects have crucial impacts on floods in densely populated regions but have not been well represented in large-scale river models used in Earth system models (ESMs), partly due to model mesh deficiency and oversimplifications of river hydrodynamics. Using two mid-Atlantic river basins as a testbed, we perform the first attempt to simulate the backwater effects comprehensively over a coastal region using the MOSART river transport model under an ESM framework, i.e., Energy Exascale Earth System Model (E3SM) configured on a regionally refined unstructured mesh, with a focus on understanding the backwater drivers and their long-term variations. By including sea level variations at the river downstream boundary, the model performance in capturing backwaters is greatly improved. We also propose a new flood event selection scheme to facilitate the decomposition of backwater drivers into different components. Our results show that while storm surge is a key driver, the influence of extreme discharge cannot be neglected, particularly when the river drains to a narrow river-like estuary. Compound flooding, while not necessarily increasing the flood peaks, exacerbates the flood risk by extending the duration of multiple coastal and fluvial processes. Furthermore, our simulations and analysis highlight the increasing strength of backwater effects due to sea level rise and more frequent storm surge during 1990–2019. Thus, backwaters need to be properly represented in ESMs to improve the predictive understanding of coastal flooding.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Age Dependent 3-D Magnetic Modeling of the North Pacific and North Atlantic Oceanic Crust at Intermediate Wavelengths

Three-dimensional magnetic modeling of the North Atlantic and Northeast pacific is performed at intermediate wavelengths using three models for the acquisition of a natural remanent magnetization. It is shown that a remanent magnetization which is dependent on the rustal age is the dominant source for the intermediate wavelength pattern in both basins.

magnetic modeling tectonics plate tectonics oceani↗
NASA NTRS2011

Changes in the Carbon Cycle of Amazon Ecosystems During the 2010 Drought

Satellite remote sensing was combined with the NASA-CASA carbon cycle simulation model to evaluate the impact of the 2010 drought (July through September) throughout tropical South America. Results indicated that net primary production (NPP) in Amazon forest areas declined by an average of 7% in 2010 compared to 2008. This represented a loss of vegetation CO2 uptake and potential Amazon rainforest growth of nearly 0.5 Pg C in 2010. The largest overall decline in ecosystem carbon gains by land cover type was predicted for closed broadleaf forest areas of the Amazon River basin, including a large fraction of regularly flooded forest areas. Model results support the hypothesis that soil and dead wood carbon decomposition fluxes of CO2 to the atmosphere were elevated during the drought period of 2010 in periodically flooded forest areas, compared to forests outside the main river floodplains.

Potter, Christophera↗
DOE OSTI2023

Stream Temperature Prediction in a Shifting Environment: Explaining the Influence of Deep Learning Architecture

Stream temperature is a fundamental control on ecosystem health. Recent efforts incorporating process guidance into deep learning models for predicting stream temperature have been shown to outperform existing statistical and physical models. This performance is in part because deep learning architectures can actively learn spatiotemporal relationships that govern how water and energy propagate through a river network. However, exploration of how spatiotemporal awareness and process guidance influence a model's generalizability under shifting environmental conditions such as climate change is limited. Here, we use Explainable Artificial Intelligence (XAI) to interrogate how differing deep learning architectures affect a model's learned spatial and temporal dependencies, and how those learned dependencies affect a model's ability to maintain high accuracy when applied to unseen environmental conditions. Using the Delaware River Basin in the northeastern United States as a test case, we compare two spatiotemporally aware process–guided deep learning models for predicting stream temperature (a recurrent graph convolution network—RGCN, and a temporal convolution graph model—Graph WaveNet). Both models achieve equally high predictive performance when testing data are well represented in the training data (test root mean squared errors of 1.64°C and 1.65°C); however, Graph WaveNet significantly outperforms RGCN in 4 out of 5 experiments where test partitions represent different types of unseen environmental conditions. XAI results show that the architecture of Graph WaveNet leads to learned spatial relationships with greater fidelity to physical processes, and that this fidelity improves the generalizability of the model when applied to shifting and/or unseen environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Reconstruction of the 1997/1998 El Nino from TOPEX/POSEIDON and TOGA/TAO Data Using a Massively Parallel Pacific-Ocean Model and Ensemble Kalman Filter

Two massively parallel data assimilation systems in which the model forecast-error covariances are estimated from the distribution of an ensemble of model integrations are applied to the assimilation of 97-98 TOPEX/POSEIDON altimetry and TOGA/TAO temperature data into a Pacific basin version the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. in the first system, ensemble of model runs forced by an ensemble of atmospheric model simulations is used to calculate asymptotic error statistics. The data assimilation then occurs in the reduced phase space spanned by the corresponding leading empirical orthogonal functions. The second system is an ensemble Kalman filter in which new error statistics are computed during each assimilation cycle from the time-dependent ensemble distribution. The data assimilation experiments are conducted on NSIPP's 512-processor CRAY T3E. The two data assimilation systems are validated by withholding part of the data and quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The pros and cons of each system are discussed.

Keppenne, C. L.↗