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At least 1,765 records · Page 98

ReEDS Performance Improvement

The Regional Energy Deployment System (ReEDS) is an open-source, spatially explicit, long-term capacity expansion model for the bulk electric power system of the contiguous United States, encompassing multiple scenarios with technological and political assumptions (see https://github.com/NREL/ReEDS-2.0). With the increased needs for capabilities, higher temporal and spatial resolutions to model the evolution of the power system with modern technologies and low-carbon pathways, ReEDS' model solution times have increased significantly from 4-6 hours in 2018 to 18-48+ hours in 2023 . Also, the model size for commonly-run ReEDS scenarios reached 22 and 28 million equations and variables, respectively. These runtimes can be especially challenging under certain scenario settings (e.g., very high temporal or spatial resolution) or with limited computational power. In this presentation, we will discuss several methods we used to improve model runtime, including data preparation, model modification, and solver tuning. The implementation of these methods shrank the model size to 7.2 and 7.3 million equations and variables, respectively. Furthermore, this led to a 77% reduction in the model's run time for commonly-run ReEDS scenarios. We will discuss the process of identifying areas for solve time improvements and how the specific enhancements for the ReEDS model might be applied to other similar large-scale models.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗

HST/ACS Observations of RR Lyrae Stars in Six Ultra-Deep Fields of M31

We present HST/ACS observations of RR Lyrae variable stars in six ultra deep fields of the Andromeda galaxy (M31), including parts of the halo, disk, and giant stellar stream. Past work on the RR Lyrae stars in M31 has focused on various aspects of the stellar populations that make up the galaxy s halo, including their distances and metallicities. This study builds upon this previous work by increasing the spatial coverage (something that has been lacking in previous studies) and by searching for these variable stars in constituents of the galaxy not yet explored. Besides the 55 RR Lyrae stars we found in our initial field located 11kpc from the galactic nucleus, we find additional RR Lyrae stars in four of the remaining five ultra deep fields as follows: 21 in the disk, 24 in the giant stellar stream, 3 in the halo field 21kpc from the galactic nucleus, and 5 in one of the halo fields at 35kpc. No RR Lyrae were found in the second halo field at 35kpc. The RR Lyrae populations of these fields appear to mostly be of Oosterhoff I type, although the 11kpc field appears to be intermediate or mixed. We will discuss the properties of these stars including period and reddening distributions. We calculate metallicities and distances for the stars in each of these fields using different methods and compare the results, to an extent that has not yet been done. We compare these methods not just on RR Lyrae in our M31 fields, but also on a data set of Milky Way field RR Lyrae stars.

Jeffery, E. J.↗

A Discontinuous Galerkin Method for Parabolic Problems with Modified hp-Finite Element Approximation Technique

A recent paper is generalized to a case where the spatial region is taken in R(sup 3). The region is assumed to be a thin body, such as a panel on the wing or fuselage of an aerospace vehicle. The traditional h- as well as hp-finite element methods are applied to the surface defined in the x - y variables, while, through the thickness, the technique of the p-element is employed. Time and spatial discretization scheme based upon an assumption of certain weak singularity of double vertical line u(sub t) double vertical line 2, is used to derive an optimal a priori error estimate for the current method.

Kaneko, Hideaki↗

Development of partitioning as an aid to spectral signature extension

Lists of spectrally similar LACIE sample segments may be constructed with the use of three basic information types: static, seasonal, and pass-specific variables. All are related directly or indirectly to spectral signature behavior and can be used to define spatial domains over which crop-specific signatures should be extendable. Topics covered include: (1) static spectral stratification; (2) evaluation of static partitions relative to variance control objectives; (3) evaluation of the relative importance of static versus seasonal and pass-specific partitioning variables in spectral variability; and (4) a current perspective on partitioning.

Thomas, R. W.↗

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗

Millimeter and hard x ray/gamma ray observations of solar flares during the June 1991 GRO campaign

We have carried out high-spatial-resolution millimeter observations of solar flares using the Berkeley-Illinois-Maryland Array (BIMA). At the present time, BIMA consists of only three elements, which is not adequate for mapping highly variable solar phenomena, but is excellent for studies of the temporal structure of flares at millimeter wavelengths at several different spatial scales. We present BIMA observations made during the Gamma Ray Observatories (GRO)/Solar Max 1991 campaign in Jun. 1991 when solar activity was unusually high. Our observations covered the period 8-9 Jun. 1991; this period overlapped the period 4-15 Jun. when the Compton Telescope made the Sun a target of opportunity because of the high level of solar activity.

Kundu, M. R.↗

Uncertainty in Atlantic Multidecadal Oscillation derived from different observed datasets and their possible causes

As a leading mode of sea surface temperature (SST) variability over the North Atlantic in both observations and model simulations, the Atlantic Multidecadal Oscillation (AMO) can have a substantial influence on regional and global climate. By using Low-Frequency Component Analysis, we explore the uncertainties of the resulting AMO indices and the corresponding spatial patterns derived from three observational SST datasets. We found that the known coherent spatial pattern of the AMO at the basin scale over the North Atlantic appears in two out of the three datasets. Further analysis indicates that both the warming trend and the different techniques used to construct these observed gridded SSTs contribute to the AMO’s spatial coherence over the North Atlantic, especially during periods of sparse data sampling. The SST in the Extended Reconstructed SST dataset version 5 (ERSSTv5), changes from being systematically below the other datasets during the dense sampling periods on either side of the Second World War (WWII), to systematically above the other datasets during WWII, thereby introducing an artificial 10–20-year variability that affects the AMO’s spatial coherence. This coherence in the AMO’s spatial pattern is also affected by bias adjustment in ERSSTv5 at relative cool (i.e., non-summer) seasons, and by the heterogeneous North Atlantic warming pattern. The different AMO patterns can induce the different effects of wind, surface heat fluxes, and then drive ocean circulation and its heat transport convergence, especially for some seasons. For AMO indices, both the different detrending methods and different observational data result in uncertainty for the period 1935–1950. Such SST uncertainty is important to detect the relative role of the atmosphere and ocean in shaping the AMO.

54 ENVIRONMENTAL SCIENCES↗

Nitrogen Fertilization Restructured Spatial Patterns of Soil Organic Carbon and Total Nitrogen in Switchgrass and Gamagrass Croplands in Tennessee USA

Nitrogen (N) fertilizers can potentially alter spatial distribution of soil organic carbon (SOC) and total nitrogen (TN) concentrations in croplands such as switchgrass (SG: Panicum virgatum L.) and gamagrass (GG: Tripsacum dactyloides L.), but it remains unclear whether these effects are the same between crops and under different rates of fertilization. 13 C and 15 N are two important proxy measures of soil biogeochemistry, but they were rarely examined as to their spatial distributions in soil. Based on a three-year long fertilization experiment in Middle Tennessee, USA, the top mineral horizon soils (0–15 cm) were collected using a spatially explicit design within two 15-m 2 plots under three fertilization treatments in SG and GG croplands. A total of 288 samples were collected based on 12 plots and 24 samples in each plot. The fertilization treatments were no N input (NN), low N input (LN: 84 kg N ha -1 in urea) and high N input (HN: 168 kg N ha -1 in urea). The SOC, TN, SOC/TN (C: N), δ 13 C and δ 15 N were quantified and their within-plot variations and spatial distributions were achieved via descriptive and geostatistical methods. Results showed that SG generally displayed 10~120% higher plot-level variations in all variables than GG, and the plot-level variations were 20~77% higher in NN plots than LN and HN plots in SG but they were comparable in unfertilized and fertilized plots in GG. Relative to NN, LN and HN showed more significant surface trends and spatial structures in SOC and TN in both croplands, and the fertilization effect appeared more pronounced in SG. Spatial patterns in C: N, δ 13 C and δ 15 N were comparable among different fertilization treatments in both croplands. The descending within-plot variations were also identified among variables (SOC > TN > δ 15 N > C: N > δ 13 C). This study demonstrated that N fertilizations generally reduced the plot-level variance and simultaneously re-established spatial structures of SOC and TN in bioenergy croplands, which little varied with fertilization rate but was more responsive in switchgrass cropland.

59 BASIC BIOLOGICAL SCIENCES↗

Fabricated ecosystem workshop: bridging laboratory to field science. Workshop report.

Lawrence Berkeley National Laboratory (Berkeley Lab) scientists held a workshop at the DOE BER Genomic Sciences PI meeting on the use of Fabricated Ecosystems in Washington D.C. on February 25th, 2020. Ecosystem fabrication is an approach to creating controlled microbial, soil and plant ecologies within a laboratory setting that enable discovery and dissection of environmental variables, activities, and interactions. At Berkeley Lab, we are developing two systems which span spatial and temporal scales — the EcoFAB and the EcoPOD. The participants of the workshop discussed the potential applications and challenges of using fabricated ecosystems as tools to tackle BER-relevant scientific questions. Specifically, they identified (1) research challenges that would benefit from ready access to this infrastructure (2) identified and prioritized technical challenges that currently limit these systems and (3) discussed how to use them to bridge the gap between lab and field research. To ensure that the fabricated ecosystems , in particular the larger-scale EcoPODs, are of use to as much of the BER community as possible, the workshop participants made the following recommendations: 1. Produce publicly available datasets for a set of control variables. Use for benchmarking, and assessing reproducibility between systems. 2. Implement data standards. 3. Develop/leverage nano/micro sensors and in situ root imaging. 4. Encourage the development of interdisciplinary teams to develop EcoPOD experiments. 5. Develop fabricated ecosystems with size and complexity that sits between the EcoFAB and EcoPOD to accelerate use and access.

42 ENGINEERING↗

Fast and accurate learned multiresolution dynamical downscaling for precipitation

Abstract. This study develops a neural-network-based approach for emulating high-resolution modeled precipitation data with comparable statistical properties but at greatly reduced computational cost. The key idea is to use combination of low- and high-resolution simulations (that differ not only in spatial resolution but also in geospatial patterns) to train a neural network to map from the former to the latter. Specifically, we define two types of CNNs, one that stacks variables directly and one that encodes each variable before stacking, and we train each CNN type both with a conventional loss function, such as mean square error (MSE), and with a conditional generative adversarial network (CGAN), for a total of four CNN variants. We compare the four new CNN-derived high-resolution precipitation results with precipitation generated from original high-resolution simulations, a bilinear interpolater and the state-of-the-art CNN-based super-resolution (SR) technique. Results show that the SR technique produces results similar to those of the bilinear interpolator with smoother spatial and temporal distributions and smaller data variabilities and extremes than the original high-resolution simulations. While the new CNNs trained by MSE generate better results over some regions than the interpolator and SR technique do, their predictions are still biased from the original high-resolution simulations. The CNNs trained by CGAN generate more realistic and physically reasonable results, better capturing not only data variability in time and space but also extremes such as intense and long-lasting storms. The new proposed CNN-based downscaling approach can downscale precipitation from 50 to 12 km in 14 min for 30 years once the network is trained (training takes 4 h using 1 GPU), while the conventional dynamical downscaling would take 1 month using 600 CPU cores to generate simulations at the resolution of 12 km over the contiguous United States.

54 ENVIRONMENTAL SCIENCES↗

Regional specialization in prefrontal cortex manifests in the reliability of task progression codes

The brain has the remarkable ability to guide the performance of complex tasks. Distinct prefrontal cortical areas make specific contributions to this ability, with the orbitofrontal cortex (OFC) critical for processing information related to trial outcomes and the dorsomedial prefrontal cortex (dmPFC) critical for sustained effort and selecting the right action at the right time. Yet, in both areas, neural activity represents both outcome- and action-related quantities. How similar neural representations support different functions remains unclear. Here, we compared OFC and dmPFC activity in rats performing a spatial alternation task. We show that, in contrast to other task-related variables, task progression is represented in both areas, but with distinct patterns of across-trial reliability that match each area’s previously documented functional specialization. Our results indicate that the engagement of reliable, task-phase-specific activity patterns differs across prefrontal regions in a manner well suited to engage different computations at different times.

Biological and medical sciences↗

Aircraft remote sensing of phytoplankton spatial patterns during the 1989 Joint Global Ocean Flux Study (JGOFS) North Atlantic bloom experiment

Mesoscale phytoplankton chlorophyll variability near the Joint Global Ocean Flux study sites along the 20 W meridian at 34 N, 47 N, and 59 N is discussed. The NASA P-3 aircraft and the Airborne Oceanographic Lidar (AOL) system provides remote sensing support for the North Atlantic Bloom Experiment. The principal instrument of the AOL system is the blue-green laser that stimulates fluorescence from photoplankton chlorophyll, the principal photosynthetic pigment. Other instruments on the NASA P-3 aircraft include up- and down-looking spectrometers, PRT-5 for infrared measurements to determine sea surface temperature, and a system to deploy and record AXBTs to measure subsurface temperature structure.

Yoder, James A.↗

Calibration of EOS multispectral imaging sensors and solar irradiance variability

Earth Observation System (EOS) optical multispectral imaging sensors provide images of the earth at various spectral and spatial resolutions, in the visible (VIS) and infrared (IR) regions of the solar spectrum. Accurate knowledge of extraterrestrial solar spectral irradiance and its variations with time, are needed to trace sensor calibration in space, and for the development of terrestrial atmospheric models needed in data validation. A brief review of the extraterrestrial solar VIS/IR spectral irradiance available in the literature will be reviewed, and the need to develop an extraterrestrial solar spectral irradiance for the EOS studies will be pointed out. The solar calibration of the Earth Radiation Budget Experiments (ERBE), earth-viewing sensors will be discussed. Observed variations in the solar constant (solar irradiance, at the mean sun-earth distance of one astronomical unit, integrated over all wavelengths), and solar spectral irradiance with solar activity and its implications for EOS studies also will be discussed.

Mecherikunnel, Ann↗

Validation of Satellite Retrieved Land Surface Variables

The effective use of satellite observations of the land surface is limited by the lack of high spatial resolution ground data sets for validation of satellite products. Recent large scale field experiments include FIFE, HAPEX-Sahel and BOREAS which provide us with data sets that have large spatial coverage and long time coverage. It is the objective of this paper to characterize the difference between the satellite estimates and the ground observations. This study and others along similar lines will help us in utilization of satellite retrieved data in large scale modeling studies.

Lakshmi, Venkataraman↗

Validation of Satellite Retrieved Land Surface Variables

The effective use of satellite observations of the land surface is limited by the lack of high spatial resolution ground data sets for validation of satellite products. Recent large scale field experiments include FIFE, HAPEX-Sahel and BOREAS which provide us with data sets that have large spatial coverage and long time coverage. It is the objective of this paper to characterize the difference between the satellite estimates and the ground observations. This study and others along similar lines will help us in utilization of satellite retrieved data in large scale modeling studies.

Lakshmi, Venkataraman↗

Variable Ion Compositions of Solar Energetic Particle Events in the Inner Heliosphere: A Field Line Braiding Model with Compound Injections

We propose a model for interpreting highly variable ion composition ratios in solar energetic particle (SEP) events recently observed by the Parker Solar Probe (PSP) at 0.3–0.45 au. We use numerical simulations to calculate SEP propagation in a turbulent interplanetary magnetic field with a Kolmogorov power spectrum from large scales down to the gyration scale of energetic particles. We show that when the source regions of different species are offset by a distance comparable to the size of the source regions, the observed energetic particle composition He/H can be strongly variable over more than two orders of magnitude, even if the source ratio is at the nominal value. Assuming a 3 He/ 4 He source ratio of 10% in impulsive 3 He-rich events and the same spatial offset of the source regions, the 3 He/ 4 He ratio at observation sites also vary considerably. The variability of the ion composition ratios depends on the radial distance, which can be tested by observations made at different radial locations. We discuss the implications of these results on the variability of ion composition of impulsive events and on further PSP and Solar Orbiter observations close to the Sun.

79 ASTRONOMY AND ASTROPHYSICS↗

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness - An Introduction to the Open-Source Tool and Use Cases

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility. RAVIS uses a technology suite that is assembled to provide optimum visualization facility while maintaining a wide pool of potential deployment and client environments. The tool is designed to take advantage of web application technologies, open source visualization libraries and tooling. Utilizing this technology will enable deployment in any environment, using any operating system, and is scalable to much higher spatial and temporal scales of visualization. As a prototype of the tool and demonstrating a use case of variable renewable integration, RAVIS currently integrates site-specific solar power forecasts in the California Independent System Operator (CAISO) and Mid-continent ISO (MISO) footprint from the IBM WattSun forecasting platform, and also superimposes market simulation data for CAISO footprint from as in-house NREL market clearing tool. The tool has the ability to alert the viewer for excessive up or down ramps for both individual solar sites as well as regionally aggregated net-load ramps, and alerts can also be qualified with respect to available flexible generation. This report will provide an introduction to the RAVIS tool, and summarize the above mentioned capabilities, typical use cases and possible extensions of the tool. The RAVIS development team believes there are likely to be high economic and reliability benefits of integrating probabilistic forecasts of variable renewables into control center visualizations and improved ramp events situational awareness for system operators and forecasting teams in the ISOs and electric utilities in comparison with their business as usual practices.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

The Climatology of Carbon Monoxide and Water Vapor on Mars as Observed by CRISM and Modeled by the GEM-Mars General Circulation Model

Radiative transfer modeling of near-infrared spectra taken by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) instrument onboard Mars Reconnaissance Orbiter (MRO) enables the column-integrated abundance of carbon monoxide (CO) and water vapor (H 2 O) to be retrieved. These results provide a detailed global description of the seasonal and spatial distribution of CO in the Mars atmosphere and new information about the interannual variability of H2O. The CRISM retrievals show the seasonally and globally averaged carbon monoxide mixing ratio to be near 800 parts per million, but with strong seasonal variations, especially at high latitudes. At low latitudes, the carbon monoxide mixing ratio varies in response to the mean seasonal cycle of surface pressure and shows little variation with topography. At high latitudes, carbon monoxide is depleted in the summer hemisphere by a factor of two or more, while in the winter hemisphere there is relatively higher mixing ratio in regions with low-lying topography. Water vapor shows only modest interannual variations, with the largest observed difference being unusually dry conditions in the wake of the Mars Year 28 global dust storm. Modeling results from the GEM (Global Environmental Multiscale) - Mars general circulation model generally reproduce the observed seasonal and spatial trends and provide insight into the underlying physical processes.

Smith, Michael D.↗