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At least 235 records · Page 13

Enhanced thermal emittance of space radiators by ion-discharge chamber texturing

The discharge chamber of a 30-cm argon ion source was successfully used to texture potential space radiator materials for the purpose of obtaining values of thermal emittance greater than 0.85 at 700 and 900 K. Some samples were also treated in acid prior to texturing. To evaluate the durability of the textured materials to atomic oxygen, samples were exposed to an RF air plasma environment. The spectral emittance between 2.0 anf 15.0 microns was measured before and after the textured materials were exposed to the plasma asher. The results indicate that copper with extremely high values of emittance after texturing (0.978 and 0.983) at 700 and 900 K, respectively,did not change its values of emittance after ashing, whereas the emittance of stainless steel fell below 0.85 after ashing. These data, along with scanning electron photomicrographs, and the results of texturing and ashing titanium and Nb(1)Zr are presented .

Mirtich, Michael J.↗

Radiative Characteristics of Aerosol During Extreme Fire Event over Siberia in Summer 2012

Microphysical and optical properties of aerosol were studied during a mega-fire event in summer 2012 over Siberia using ground-based measurements of spectral solarradiation at the AERONET site in Tomsk and satellite observations. The data were analyzed using multi-year (2003-2013) measurements of aerosol characteristics under back-ground conditions and for less intense fires, differing in burning biomass type, stage of fire, remoteness from observation site, etc. (ordinary smoke). In June-August 2012, the average aerosol optical depth (AOD, 500 nm) had been 0.95+/-0.86, about a factor of 6 larger than background values (0.16+/-0.08), and a factor of 2.5 larger than in ordinary smoke. The AOD values were extremely high on 24-28 July and reached 3-5. A comparison with satellite observations showed that ground-based measurements in the region of Tomsk not only reflect the local AOD features, but are also characteristic for the territory of Western Siberia as a whole. Single scattering albedo (SSA, 440 nm) in this period ranged from 0.91 to 0.99 with an average of approx. 0.96 in the entire wavelength range of 440-1020 nm. The increase in absorptance of aerosol particles (SSA(440 nm)=0.92) and decrease in SSA with wavelength observed in ordinary smoke agree with the data from multi-year observations in analogous situations in the boreal zone of USA and Canada. Volume aerosol size distribution in extreme and ordinary smoke had a bimodal character with significant prevalence of fine-mode particles, but in summer 2012 the mean median radius and the width of the fine-mode distribution somewhat increased. In contrast to data from multi-year observations, in summer 2012 an increase in the volume concentration and median radius of the coarse mode was observed with growing AOD.

Zhuravleva, Tatiana B.↗

High figure of merit extreme bandgap Al 0.87 Ga 0.13 N-Al 0.64 Ga 0.36 N heterostructures over bulk AlN substrates

We report on high-quality n -Al 0.87 Ga 0.13 N-A 0.64 Ga 0.36 N heterostructures over single crystal AlN. For these pseudomorphic heterostructures, high-resolution X-ray and X-ray Topographic analysis was used to establish a threading dislocation density of 7 × 10 3 cm -2 . Using reverse composition graded n + -Al x Ga 1- x N contact layers, we obtained linear ohmic contacts with 4.3 Ω mm specific resistance. A critical breakdown field >11 MV cm -1 was also measured. In combination with the channel resistance of 2400 Ω sq -1 , these translate to a Baliga’s Figure of Merit of 2.27 GW cm -2 . This, to the best of our knowledge is the highest reported value for extreme bandgap AlGaN heterostructures.

42 ENGINEERING↗

Seeing through noise in power laws

Despite widespread claims of power laws across the natural and social sciences, evidence in data is often equivocal. Modern data and statistical methods reject even classic power laws such as Pareto’s law of wealth and the Gutenberg–Richter law for earthquake magnitudes. We show that the maximum-likelihood estimators and Kolmogorov–Smirnov (K-S) statistics in widespread use are unexpectedly sensitive to ubiquitous errors in data such as measurement noise, quantization noise, heaping and censorship of small values. This sensitivity causes spurious rejection of power laws and biases parameter estimates even in arbitrarily large samples, which explains inconsistencies between theory and data. We show that logarithmic binning by powers of λ > 1 attenuates these errors in a manner analogous to noise averaging in normal statistics and that λ thereby tunes a trade-off between accuracy and precision in estimation. Binning also removes potentially misleading within-scale information while preserving information about the shape of a distribution over powers of λ, and we show that some amount of binning can improve sensitivity and specificity of K-S tests without any cost, while more extreme binning tunes a trade-off between sensitivity and specificity. We therefore advocate logarithmic binning as a simple essential step in power-law inference.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Seeing through noise in power laws

Despite widespread claims of power laws across the natural and social sciences, evidence in data is often equivocal. Modern data and statistical methods reject even classic power laws such as Pareto’s law of wealth and the Gutenberg–Richter law for earthquake magnitudes. We show that the maximum-likelihood estimators and Kolmogorov–Smirnov (K-S) statistics in widespread use are unexpectedly sensitive to ubiquitous errors in data such as measurement noise, quantization noise, heaping and censorship of small values. This sensitivity causes spurious rejection of power laws and biases parameter estimates even in arbitrarily large samples, which explains inconsistencies between theory and data. We show that logarithmic binning by powers of λ > 1 attenuates these errors in a manner analogous to noise averaging in normal statistics and that λ thereby tunes a trade-off between accuracy and precision in estimation. Binning also removes potentially misleading within-scale information while preserving information about the shape of a distribution over powers of λ, and we show that some amount of binning can improve sensitivity and specificity of K-S tests without any cost, while more extreme binning tunes a trade-off between sensitivity and specificity. We therefore advocate logarithmic binning as a simple essential step in power-law inference.

97 MATHEMATICS AND COMPUTING↗

Deconstruction of plant biomass by a Cellulomonas strain isolated from an ultra-basic (lignin-stripping) spring

Plant material falling into the ultra-basic (pH 11.5-11.9) springs within The Cedars, an actively serpentinizing site in Sonoma County, California, is subject to conditions that mimic the industrial pretreatment of lignocellulosic biomass for biofuel production. In this research, we sought to obtain hemicellulolytic/cellulolytic bacteria from The Cedars springs that are capable of withstanding the extreme alkaline conditions wherein calcium hydroxide-rich water removes lignin, making cell wall polysaccharides more accessible to microorganisms and their enzymes. We enriched for such bacteria by adding plant debris from the springs into a synthetic alkaline medium with ground tissue of the biofuel crop switchgrass (Panicum virgatum L.) as the sole source of carbon. From the enrichment culture we isolated the facultative anaerobic bacterium Cellulomonas sp. strain FA1 (NBRC 114238), which tolerates high pH and catabolizes the major plant cell wall-associated polysaccharides cellulose, pectin, and hemicellulose. Strain FA1 in monoculture colonized the plant material and degraded switchgrass at a faster rate than the community from which it was derived. Cells of strain FA1 could be acclimated through subculturing to grow at a maximal concentration of 13.4% ethanol. A strain FA1-encoded β-1, 4-endoxylanase expressed in E. coli was active at a broad pH range, displaying near maximal activity at pH 6-9. Discovery of this bacterium illustrates the value of extreme alkaline springs in the search for microorganisms with potential for consolidated bioprocessing of plant biomass to biofuels and other valuable bio-inspired products.

59 BASIC BIOLOGICAL SCIENCES↗

Simulating the Formation of Lunar Floor-Fracture Craters Using Elastoviscoplastic Relaxation

Lunar floor-fracture craters formed during the height of mare basalt emplacement. Due to a general temporal and spatial relation with the maria, these craters, numbering some 200, may be diagnostic of the thermal structure of the crust during this time. As the name suggests, these craters exhibit brittle failure, generally limited to the central floor region. That, and a shallower depth than fresh lunar craters, has led to two main theories as to their formation: laccolith emplacement under the crater and viscous relaxation. The implications of each model for the state of the Moon's crust during this time are quite different, so the viability of each model must be checked. Laccolith emplacement has been treated elsewhere. However, previous attempts to study the relaxation of the craters have assumed only a uniform, Newtonian viscous response of the near surface to the topographic driving forces, and simply postulated that the fractures resulted from tensile stresses associated with floor uplift. Here, we use a more sophisticated rheological model that includes not only non-Newtonian viscous behavior (i.e., the viscosity is stress-dependent), but also incorporates elastic behavior and a plastic component to the rheology to directly simulate the formation of the floor fractures. The results of our simulations show that while elastoviscoplastic relaxation is potentially viable for larger floor-fracture craters, it is not viable for craters with diameters < or = 60 km, the size of the majority of floor-fracture craters. We employ the finite element method, a numerical technique well suited for boundary-value problems, via the commercially available MARC software package. To test the viability of topographic relaxation, our goal is to prepare the simulations as to maximize the amount of relaxation. We take advantage of the natural axisymmetry of craters, simulating one radial plane. Initial shapes are based on data for fresh craters from Pike. To simplify implementation, a fourth order polynomial is used for the basin, while a third order inverse function is used for the rim. This form closely approximates the long-wavelength behavior of complex craters, while ignoring higher-frequency topography, save the rim. This approximation is appropriate because crater relaxation is strongly controlled by long-wavelength topography. Loading is accomplished assuming a uniform gravity field (1.62 m/s-square) and a uniform density of 2900 kg/cubic m. The initial stress state is set to be hydrostatic, with an additional pressure term to account for any overlying topography. This additional pressure term is tapered exponentially with depth. While the simulations quickly settle on a preferred stress state, and while the final solution is fairly insensitive to the choice of the e-folding depth of the taper, selecting an e-folding depth close to the diameter of the crater sets the initial stress state near the preferred state. We assume a diuranally averaged surface temperature of -20 C, and allow temperature to increase with depth at a rate of 50 K//km. Assuming a thermal conductivity of 2 W/in/K, this gradient translates to a heat flow of 100mW/square m, an extremely high value for the Moon. Temperature, of course, will not increase without bound. To maximize relaxation, we allow our temperature profile to increase linearly until it reaches the solidus (assumed to be 1200C) at a depth of 24.4 km, at which point it is kept constant. The presence of melt will drop the bulk viscosity; however, we have no rheological control for partial melts. Therefore, we make no attempt to simulate this situation. Elastoviscoplastic rheological model. In general, geologic materials can behave in three main ways: elastically, viscously (via solid-state creep), and brittly (plasticity is a continuum approach to simulate this phenomenon). We combine these three deformation mechanisms in an extended Maxwell solid, where the total strain can be broken down into a simple summation of the elastic, creep, and plastic strains. In relaxation phenomena in general, the system takes advantage of any means possible to eliminate deviatoric stresses by relaxing away the topography. Previous analyses have only modeled the viscous response. Comparatively, the elastic response in our model can augment the relaxation, to a point. This effect decreases as the elastic response becomes stiffer; indeed, in the limit of infinite elastic Young's modulus (and with no plasticity), the solution converges on the purely viscous solution. Igneous rocks common to the lunar near-surface have Young's modulii in the range of 10-100 GPa. To maximize relaxation, we use a Young's modulus of 10 GPa. (There is negligible sensitivity to the other elastic modulus, the Poisson's ratio; we use 0.25.) For the viscous response, we use a flow law for steady-state creep in thoroughly dried Columbia diabase, because the high plagioclase (about 70 vol%) and orthopyroxene (about 17 vol%) content is similar to the composition of the lunar highland crust as described by remote sensing and sample studies: noritic anorthosite. This flow law is highly non-Newtonian, i.e., the viscosity is highly stress dependent. That, and the variability with temperature, stands in strong contrast to previous examinations of lunar floor-fracture crater relaxation. To model discrete, brittle faulting, we assume "Byerlee's rule," a standard geodynamical technique. We implement this "rule" with an-angle of internal friction of about 40 deg, and a higher-than-normal cohesion of about 3.2 MPa (to approximate the breaking of unfractured rock). The actual behavior of geologic materials is more complex than in our rheological model, so the uncertainties in the plasticity do not represent the state-of-the-art error. Additional information is contained in the original.

Dombard, A. J.↗

Quantifying the influence of natural climate variability on in situ measurements of seasonal total and extreme daily precipitation

Abstract While various studies explore the relationship between individual sources of climate variability and extreme precipitation, there is a need for improved understanding of how these physical phenomena simultaneously influence precipitation in the observational record across the contiguous United States. In this work, we introduce a single framework for characterizing the historical signal (anthropogenic forcing) and noise (natural variability) in seasonal mean and extreme precipitation. An important aspect of our analysis is that we simultaneously isolate the individual effects of seven modes of variability while explicitly controlling for joint inter-mode relationships. Our method utilizes a spatial statistical component that uses in situ measurements to resolve relationships to their native scales; furthermore, we use a data-driven procedure to robustly determine statistical significance. In Part I of this work we focus on natural climate variability: detection is mostly limited to DJF and SON for the modes of variability considered, with the El Niño/Southern Oscillation, the Pacific–North American pattern, and the North Atlantic Oscillation exhibiting the largest influence. Across all climate indices considered, the signals are larger and can be detected more clearly for seasonal total versus extreme precipitation. We are able to detect at least some significant relationships in all seasons in spite of extremely large (> 95%) background variability in both mean and extreme precipitation. Furthermore, we specifically quantify how the spatial aspect of our analysis reduces uncertainty and increases detection of statistical significance while also discovering results that quantify the complex interconnected relationships between climate drivers and seasonal precipitation.

54 ENVIRONMENTAL SCIENCES↗

Time dependent chlorination of CeO 2 , La 2 O 3 and Nd 2 O 3 by ZrCl 4 dissolved in eutectic LiCl–KCl

Partial chlorination of CeO 2 , La 2 O 3 , and Nd 2 O 3 was achieved using ZrCl 4 dissolved in molten LiCl-KCl at 450°C over a period of 4-5 hr. ZrCl 4 was pre-volatilized into an argon stream to maintain a constant vapor pressure for equilibration with the salt. This approach was effective at maintaining the ZrCl 4 concentration at the solubility limit of 1.3 mol% in the molten salt throughout the duration of two of the chlorination experiments and within about 60% of the solubility limit in the third experiment. Based on the analysis of salt samples, fractional conversion after four hours of reaction for CeO 2 , and five hours for La 2 O 3 , and Nd 2 O 3 were calculated to be 0.97, 0.28, and 0.65 respectively. Assuming a shrinking core diffusion-limited model, the diffusivity of ZrCl 4 through the hypothesized ZrO 2 layer was calculated for the chlorination of CeO 2 , La 2 O 3 , and Nd 2 O 3 were 1.76 x 10 -10 cm 2 /sec, 7.85 x 10 -12 cm 2 /sec, and 7.42 x 10 -12 cm 2 /sec, respectively. Given the extremely low values calculated for diffusivity, it was concluded that the process is chemical reaction rate limited and that a complete reaction of each rare earth oxide could be achieved. Furthermore, a chemically controlled shrinking core model was shown to also fit the experimental data closely.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Global rare earth element resources: A concise review

Deposits enriched in rare earth elements (REEs) are abundant and diverse in mineralogy, but those of current economic value have extremely limited geographic distribution. Due to rapidly increasing demand and concerns about supply chain security, new and improved methods of prospecting, beneficiation, separation, purification, and recycling are needed. By overviewing the types and geographic distribution of REE reserves globally, their petrogenesis and major mineralogic assemblages, this review aims to provide a foundation for posing new directions for research and development in these areas. In conclusion, our review also seeks to provide a concise summary of important background information that is accessible to researchers from a variety of disciplines who are seeking to engage in this rapidly expanding field.

58 GEOSCIENCES↗

Laser diagnostics to characterize the in-flame growth of platinum nanoparticles manufactured by the reactive spray deposition technology

Reactive Spray Deposition Technology (RSDT) is an atmospheric pressure, flame-based advanced manufacturing method used to fabricate Membrane Electrode Assemblies (MEAs) for proton exchange fuel cells and water electrolyzers. RSDT combines the flame synthesis of catalyst nanoparticles and their deposition onto the membrane in one step. The properties of the synthesized nanoparticles, such as their Size Distribution Function (SDF), determine the manufactured electrodes’ performance, which can be evaluated when the deposition is complete via ex-situ characterization of the products. Efforts to improve RSDT for manufacturing state-of-the-art MEAs can be significantly enhanced with integrated laser diagnostics that enable in situ measurement of the synthesized catalyst nanoparticles. This paper reports the implementation of laser diagnostics in an RSDT facility and evaluates their potential to assist the manufacturing process. Laser Light Scattering (LS) and Laser-Induced Incandescence (LII) measurements are performed in the oxygen-rich zone of the flame at various distances from the flame fuel jet nozzle downstream of its luminous region. The measurements quantitatively track the evolution in size and volume fraction of platinum-based nanoparticles in two flames that yield different catalytic properties in the manufactured electrodes. The profiles of the measured nanoparticles’ volume fraction along the flame axis can be estimated a priori so that the average nanoparticle sizes can be measured in quasi-real time via LS. Nanoparticles experience an extremely slow growth rate while being convected at distances from 150 nm to 300 nm from the fuel nozzle. Complementary characterizations of the synthesized nanoparticles are performed ex-situ via High-Angle Annular Darkfield Scanning Transmission Electron Microscopy (HAADF-STEM) image analyses of samples collected on grids at a fixed distance from the fuel jet nozzle. Comparing the results from laser and microscopy techniques not only cross-validates the findings but also provides the parameters to infer the bimodal SDF in-situ and yields evidence that the coagulation efficiency of the synthesized nanoparticles has extremely low values in the investigated zone of the flames.

Rayleigh Light Scattering (LS)↗

Climate-extreme modeling framework for sustainable flood management in the Arabian Peninsula

Evaluating extreme precipitation events (EPEs) is essential for building climate-resilient water management strategies, but it remains a major challenge in ungauged basins. Using the 26,070 km 2 Wadi al-Rummah basin in central Saudi Arabia as a case study, we developed an alternative, reliable, cost-effective satellite-based framework that combines empirically derived EPE thresholds, imagery-calibrated 2D hydrodynamic modeling, GRACE water-storage diagnostics, and bias-corrected CMIP6 projections to assess flood hazards and recharge potential under current and future climate scenarios in ungauged basins. The integrated approach and the resulting findings followed four key steps: (1) Identified a 22.5 mm EPE threshold, the 80th percentile of 3-day GPM/IMERG rainfall (2000–2024), aligned with flood-triggering events (Nov 2018: 23–28 mm; Apr, 2023: 42 mm); (2) Developed and calibrated a RiverFlow2D model using Sentinel-2 and PlanetScope imagery for the November 2018 flood, accurately reproducing flood depth and extent (RMSE ≤0.31 m; fuzzy-Dice ≥0.91), and estimating runoff (41 %), infiltration (25 %), and evaporation (34 %); (3) Independently validated the model with the April 2023 event (RMSE ≤0.35 m; fuzzy-Dice ≥0.86); (4) Conducted climate projections (2025–2100) from five bias-corrected NEX-GDDP CMIP6 models that revealed a 34 % increase in EPE intensity under SSP2-4.5 and 48 % under SSP5-8.5 scenarios, relative to 20th-century baselines. Our findings indicate that while intensifying extremes in the 21st century increase flood risk, the results highlight the potential for episodic recharge if effective retention strategies are employed, and offer a transferable model for climate-informed planning in data-scarce arid regions.

CMIP6↗

Thermodynamic approach for enhancing superconducting critical current performance

Abstract The addition of artificial pinning centers has led to an impressive increase in the critical current density ( J c ) of superconductors, enabling record-breaking all-superconducting magnets and other applications. The J c of superconductors has reached ~0.2–0.3 J d , where J d is the depairing current density, and the numerical factor depends on the pinning optimization. By modifying λ and/or ξ, the penetration depth and coherence length, respectively, we can increase J d . For (Y 0.77 Gd 0.23 )Ba 2 Cu 3 O y ((Y,Gd)123), we can achieve this by controlling the carrier density, which is related to λ and ξ. We can also tune λ and ξ by controlling the chemical pressure in Fe-based superconductors, i.e., BaFe 2 (As 1− x P x ) 2 films. The variation in λ and ξ leads to an intrinsic improvement in J c via J d , allowing extremely high values of J c of 130 MA/cm 2 and 8.0 MA/cm 2 at 4.2 K, consistent with an enhancement in J d of a factor of 2 for both incoherent nanoparticle-doped (Y,Gd)123 coated conductors (CCs) and BaFe 2 (As 1− x P x ) 2 films, showing that this new material design is useful for achieving high critical current densities in a wide array of superconductors. The remarkably high vortex-pinning force in combination with this thermodynamic and pinning optimization route for the (Y,Gd)123 CCs reached ~3.17 TN/m 3 at 4.2 K and 18 T ( H || c ), the highest values ever reported for any superconductor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Impact of survey spatial variability on galaxy redshift distributions and the cosmological 3 × 2-point statistics for the Rubin Legacy Survey of Space and Time (LSST)

We investigate the impact of spatial survey non-uniformity on the galaxy redshift distributions for forthcoming data releases of the Rubin Observatory Legacy Survey of Space and Time (LSST). Specifically, we construct a mock photometry data set degraded by the Rubin OpSim observing conditions, and estimate photometric redshifts of the sample using a template-fitting photo-z estimator, BPZ, and a machine learning method, FlexZBoost. We select the Gold sample, defined as $i\lt 25.3$ for 10 yr LSST data, with an adjusted magnitude cut for each year and divide it into five tomographic redshift bins for the weak lensing lens and source samples. We quantify the change in the number of objects, mean redshift, and width of each tomographic bin as a function of the coadd i-band depth for 1-yr (Y1), 3-yr (Y3), and 5-yr (Y5) data. In particular, Y3 and Y5 have large non-uniformity due to the rolling cadence of LSST, hence provide a worst-case scenario of the impact from non-uniformity. We find that these quantities typically increase with depth, and the variation can be $10\!-\!40~{{\rm per\ cent}}$ at extreme depth values. Using Y3 as an example, we propagate the variable depth effect to the weak lensing $3\times 2$ pt analysis, and assess the impact on cosmological parameters via a Fisher forecast. We find that galaxy clustering is most susceptible to variable depth, and non-uniformity needs to be mitigated below 3 per cent to recover unbiased cosmological constraints. There is little impact on galaxy–shear and shear–shear power spectra, given the expected LSST Y3 noise.

cosmology↗

A new way to unravel the $^{12}$C($\alpha $,$\gamma $)$^{16}$O cross section components using neural networks

The $^{12}$C($\alpha $,$\gamma $)$^{16}$O reaction rate is crucial in determining the carbon-to-oxygen abundance ratio in stellar nucleosynthesis. Measuring this reaction’s cross section at stellar energies is challenging due to its extremely small value, approximately 10 -17 barn at E c.m. = 300 keV. To address this, R-matrix calculations are employed to extrapolate data to lower energies, requiring a comprehensive understanding of each contribution to the cross section. The dominant contributions to the cross section at stellar energies arise from electric dipole (E1) and electric quadrupole (E2) transitions to the ground state of 16 O, along with a significant cascade contribution. Traditionally, these contributions have been separated using the γ-ray angular distribution. In this work, we propose a novel technique using the energy distribution of the 16 O recoils at the focal plane. This method involves a neural network trained on detailed Monte Carlo simulations of the energy distribution of recoils transported through the recoil mass separator ERNA. This approach enables the simultaneous determination of all three contributions with errors around 10% in the energy range E c.m. = 1.0–2.2 MeV. In conclusion, by employing this new technique, we aim to significantly improve the accuracy of determining the cross section of the $^{12}$C($\alpha $,$\gamma $)$^{16}$O reaction at astrophysical energies.

Astrochemistry↗

Microstructure Scale Lithium-Ion Battery Modeling: Part II. On In-Plane Heterogeneities and the Mechanisms that Regulate Them

Li-ion batteries performance and degradation are typically modeled at the macroscopic scale, that is neglecting in-plane heterogeneities that can arise from non-uniform electrode microstructures. Herein, a microstructure scale electrochemical model is used to quantify the impact of microstructure heterogeneity on cell performance during fast charging. The model predicts the electrolyte and solid concentration in-plane standard deviation can reach, respectively, ≈200 mol·m −3 and 6–7 kmol·m −3 locally. Further, the intercalation current density in-plane relative standard deviation can reach extremely high values, around 100% in the cathode and well above 100% in the anode graphite. These denote highly non-uniform lithiation rates and material utilization within each slice of the microstructure along the cell thickness. Non-uniform curvatures, at the particle scale (surface roughness) and between particles (size distribution), were found to initiate these in-plane heterogeneities, while an OCP-induced mechanism subsequently regulates them. The present model provides new insights into small length scale heterogeneity impact on battery performance not available with standard macro-scale/P2D modeling.

25 ENERGY STORAGE↗

UFNet: Joint U-Net and Fully Connected Neural Network to Bias Correct Precipitation Predictions from

Paper information. Shuang Yu, Indrasis Chakraborty, Gemma J. Anderson, Donald D. Lucas, Yannic Lops, and Daniel Galea. UFNet: Joint U-Net and fully connected neural network to bias correct precipitation predictions from climate models. Artificial Intelligence for the Earth Systems, 2024. Overview. This work develops the UFNet methodology to correct E3SM historical precipitation projection bias. The UFNet deep learning framework consists of a two-part architecture: a U-Net convolutional network to capture the spatiotemporal distribution of precipitation and a fully connected network to capture the distribution of higher-order statistics. The joint network, termed UFNet, can simultaneously improve the spatial structure of the modeled precipitation and capture the distribution of extreme precipitation values. Below we provide guidance for applying UFNet to correct the Energy Exascale Earth System Model (E3SM; Golaz et al. 2019) daily precipitation projection over the contiguous United States (CONUS). Getting started 1. Obtain the historical climate simulation and observation data. The E3SM historical simulation data are available through https://aims2.llnl.gov/search/cmip6/. The CPC unified gauge-based analysis of daily precipitation can be found through https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html. The ECMWF atmospheric reanalysis of the 20th century (ERA-20C) data are available through https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-20c. The spatial resolution of E3SM and observed datasets are both regridded to a common 1° resolution grid using conservative interpolation. The regridded E3SM, CPC and ERA-20C with 1° resolution can be found throught ./data/. 2. Train the fully connected network (DNN) Python train_dnn.py 3. Train the UFNet Python train_ufnet.py 4. Evaluation and compared with the baseline Python evaluation.py

Lucas, DonaldD↗