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Impacts of Dispatch Strategies and Forecast Errors on the Economics of Behind-the-Meter PV-Battery Systems: Preprint

To assess the economic value of batteries in hybrid PV-battery systems, one must create a dispatch profile for the battery. Many analyses of battery value assume perfect forecasts of PV generation and load, determining an upper limit on the value of the battery. Prior work that accounts for forecast uncertainty often does so in the context of a single dispatch algorithm, which does not provide a baseline for comparison. Furthermore, when multiple dispatch algorithms are assessed with uncertainty, the benefits considered are for diesel generation in a microgrid, not retail rate savings. This work addresses the gaps in the literature by comparing the performance of both heuristic and optimal dispatch algorithms for retail rate savings under forecast uncertainty, and provides comparisons of the robustness of these algorithms and their associated estimates of economic value. We find that using a perfect forecast can overestimate the value of hybrid PV-battery systems between 1% and 8% compared to the reality of using a day-ahead forecast, depending on the dispatch algorithm used. Thus, accounting for forecast uncertainty in system design and analysis will significantly improve the accuracy of modeled system values.

batteries↗

Protocols and methodologies for acquiring and analyzing critical-current versus longitudinal-strain data in Bi 2 Sr 2 CaCu 2 O 8+x wires

Abstract In the literature on Bi 2 Sr 2 CaCu 2 O 8+ x (Bi-2212) superconducting wires, it is evident that measurement protocols for transport critical-current I c versus longitudinal strain ϵ and definitions of the so-called ‘strain limit’ are generally dissimilar. Yet, values obtained for the ‘strain limit’ are frequently assimilated to being those of the irreversible strain limit ϵ irr , regardless of the I c degradation-criterion used to define it. In effect, ϵ irr should correspond specifically to the I c ( ϵ ) irreversibility onset , where crack formation in Bi-2212 filaments presumably starts. Because I c ( ϵ ) degradation remains progressive over a fairly wide strain range beyond ϵ irr , the different I c degradation-criteria in use do not yield to the same result and, thus, are not equivalent from metrology perspective. Indeed, in studying densified samples of a modern Bi-2212 round wire, we found ϵ irr ≈ 0.4% and ϵ 5% ≈ 0.6% ( ϵ 5% being the strain where I c degrades by 5%). In this paper, we outline and suggest I c ( ϵ )-measurement protocols and data-analysis methodologies in the hope to converge the various approaches taken for studying Bi-2212 strain properties and, thus, remove related result discrepancies. A unified approach would enable more objective data comparisons among laboratories and among different Bi-2212 conductors. It would pave the way for more rigorous studies of effects potentially associated with wire design, powder, heat treatments, and other such parameters on the conductor’s strain properties.

protocols↗

Benchmark of the Fe xvv 𝓡 ratio in photoionized plasma during eclipse of Centaurus X-3 with XRISM/Resolve

The $\mathcal {R}$ ratio is a useful diagnostic of the X-ray emitting astrophysical plasmas and is defined as the intensity ratio of the forbidden over the inter-combination lines in the K$\alpha$ line complex of He-like ions. The value is altered by excitation processes (electron impact or UV photoexcitation) from the metastable upper level of the forbidden line, thereby constraining the electron density or UV field intensity. The diagnostic has been applied mostly in electron density constraints in collisionally ionized plasmas using low-Z elements, as was originally proposed for the Sun (Gabriel & Jordan, 1969a, MNRAS, 145, 241), but it can also be used in photoionized plasmas. To make use of this diagnostic, we need to know its value in the limit of no excitation of metastables ($\mathcal {R}_{0}$), which depends on the element, how the plasmas are formed, how the lines are propagated, and the spectral resolution affecting line blending principally with satellite lines from Li-like ions. We benchmark $\mathcal {R}_0$ for photoionized plasmas by comparing calculations using radiative transfer codes and observation data taken with the Resolve X-ray microcalorimeter onboard XRISM. We use the Fe xxv He$\alpha$ line complex of the photo-ionized plasma in Centaurus X-3 observed during eclipse, in which the plasma is expected to be in the limit of no metastable excitation. The measured $\mathcal {R} = 0.65 \pm 0.08$ is consistent with the value calculated using xstar for the plasma parameters derived from other line ratios of the spectrum. We conclude that the $\mathcal {R}$ ratio diagnostic can be used for high-Z elements such as Fe in photoionized plasmas, which has wide applications in plasmas around compact objects at various scales.

X-rays: binaries↗

Critical minerals lists for low-carbon transitions: Reviewing their structure, objectives, and limitations

Critical minerals lists have flourished in the past decade, in particular linked to the importance of critical minerals for low-carbon transitions. We identified 27 critical minerals or materials lists across 15 countries and the European Union (EU). These lists are designed to attract public and private attention and investments to secure both domestic and foreign supplies. This review article fills a gap in the existing literature by analyzing the ways in which these lists are defined and utilized by countries engaged in a mineral rush. We focus our attention on three categories of minerals – battery minerals, platinum-group metals (PGMs), and rare earth elements (REEs) that are particularly important to energy transitions. We situate this research in the broader legal and administrative developments that have driven critical minerals policies in the past decade. We provide an in-depth analysis of the commonalities and variations in the raw materials included in these lists, and identify six core limitations of critical minerals lists: (1) unclear links between criticality assessments and mineral prioritization (2) failure to account for the full mineral value-chain; (3) limited strategic alignment between allied nations; (4) limited flexibility in dynamic environments (5) limited consideration for recycling and by-product sourcing; and (6) reliance on incomplete reserve and resource data.

Battery minerals↗

Highly Recyclable Thermosets for Lightweight Composites: CRADA 517 [Abstract only]

Lightweight composites are of increasing need to enable reduced fuel usage, reduced carbon emissions and increased range in air and ground transportation. The superior weight savings of carbon fiber thermoset composites are impeded by material and production costs and the limited options available for composite repair and recycle. The materials recovery and recycling sector is currently overwhelmed by an abundance of low-value materials and limited market opportunities for downcycled content, rendering landfilling a more attractive alternative. Vitrimers represent a new paradigm for repairable and recyclable thermosets, but this relatively new technology will require development, including government investment, to reduce risks for its adoption by aerospace and automotive OEMs. The overall goal of the project is to create recyclable carbon fiber composites using vitrimer resins that are more energy efficient to produce and have improved properties over baseline technology. The targeted composites will retain their tensile strength after multiple recycling and reprocessing steps. In addition, monomer will be recoverable through depolymerization and re-usable carbon fibers will be retrieved.

36 MATERIALS SCIENCE↗

Seasonal decline in leaf photosynthesis in perennial switchgrass explained by sink limitations and water deficit

Leaf photosynthesis of perennial grasses usually decreases markedly from early to late summer, even when the canopy remains green and environmental conditions are favorable for photosynthesis. Understanding the physiological basis of this photosynthetic decline reveals the potential for yield improvement. We tested the association of seasonal photosynthetic decline in switchgrass (Panicum virgatum L.) with water availability by comparing plants experiencing ambient rainfall with plants in a rainfall exclusion experiment in Michigan, USA. For switchgrass exposed to ambient rainfall, daily net CO 2 assimilation ( A' net ) declined from 0.9 mol CO 2 m -2 day -1 in early summer to 0.43 mol CO 2 m -2 day -1 in late summer (53% reduction; P<0.0001). Under rainfall exclusion shelters, soil water content was 73% lower and A' net was 12% and 26% lower in July and September, respectively, compared to those of the rainfed plants. Despite these differences, the seasonal photosynthetic decline was similar in the season-long rainfall exclusion compared to the rainfed plants; A' net in switchgrass under the shelters declined from 0.85 mol CO 2 m -2 day -1 in early summer to 0.39 mol CO 2 m -2 day -1 (54% reduction; P<0.0001) in late summer. These results suggest that while water deficit limited A' net late in the season, abundant late-season rainfalls were not enough to restore A' net in the rainfed plants to early-summer values suggesting water deficit was not the sole driver of the decline. Alongside change in photosynthesis, starch in the rhizomes increased 4-fold (P<0.0001) and stabilized when leaf photosynthesis reached constant low values. Additionally, water limitation under shelters had no negative effects on the timing of rhizome starch accumulation, and rhizome starch content increased ~6-fold. These results showed that rhizomes also affect leaf photosynthesis during the growing season. Towards the end of the growing season, when vegetative growth is completed and rhizome reserves are filled, diminishing rhizome sink activity likely explained the observed photosynthetic declines in plants under both ambient and reduced water availability.

59 BASIC BIOLOGICAL SCIENCES↗

Fractons with twisted boundary conditions and their symmetries

In this work, we study several exotic systems, including the X-cube model, on a flat three-torus with a twist in the $xy$-plane. The ground state degeneracy turns out to be a sensitive function of various geometrical parameters. Starting from a lattice, depending on how we take the continuum limit, we find different values of the ground state degeneracy. Yet, there is a natural continuum limit with a well-defined (though infinite) value of that degeneracy. We also uncover a surprising global symmetry in $2+1$ and $3+1$ dimensional systems. It originates from the underlying subsystem symmetry, but the way it is realized depends on the twist. In particular, in a preferred coordinate frame, the modular parameter of the twisted two-torus $\tau = \tau_1 + i \tau_2$ has rational $\tau_1 = k / m$. Then, in systems based on $U(1)\times U(1)$ subsystem symmetries, such as momentum and winding symmetries or electric and magnetic symmetries, the new symmetry is a projectively realized $\mathbb{Z}_m\times \mathbb{Z}_m$, which leads to an $m$-fold ground state degeneracy. In systems based on $\mathbb{Z}_N$ symmetries, like the X-cube model, each of these two $\mathbb{Z}_m$ factors is replaced by $\mathbb{Z}_{\gcd(N,m)}$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Performance Assessment for the E-Area Low-Level Radioactive Waste Disposal Facility at the Savannah River Site: Chapter 8

This chapter, together with Appendix H, provides the necessary CWTS inventory limits and trigger values for every parent radionuclide not screened out in Sections 2.3.6, 2.3.7, and 2.3.8. Also provided are details associated with how generic and special waste forms are handled on a DU-specific basis, and a discussion of the conversion of preliminary inventory limits (via transport runs summarized in Chapter 5) into final inventory limits for use in the CWTS limits system. Using the final inventory limits, a projected 2065 CWTS inventory is generated for use in the PA closure analysis outlined in Chapter 9.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Experimental studies of plasma-antenna coupling with the JET Alfvén Eigenmode Active Diagnostic

Here, this paper presents a dedicated study of plasma-antenna (PA) coupling with the Alfvén Eigenmode Active Diagnostic (AEAD) in JET. Stable AEs and their resonant frequencies f, damping rates γ < 0, and toroidal mode numbers n are measured for various PA separations and limiter versus X-point magnetic configurations. Two stable AEs are observed to be resonantly excited at distinct low and high frequencies in limiter plasmas. The values of f and n do not vary with PA separation. However, |γ| increases with PA separation for the low-f, but not high-f, mode, yet this may be due to slightly different edge conditions. The high-f AE is detected throughout the transition from limiter to X-point configuration, though its damping rate increases; the low-f mode, on the other hand, becomes unidentifiable. The linear, resistive MHD code CASTOR is used to simulate the frequency scan of an AEAD-like external antenna. For the limiter pulses, the high-f mode is determined to be an n = 0 GAE, while the low-f mode is likely an n = 2 TAE. During the transition from limiter to X-point configuration, CASTOR indicates that n = 1 and 2 EAEs are excited in the edge gap. These results extend previous experimental studies in JET and Alcator C-Mod; validate the computational work performed by Dvornova et al; and provide guidance for the optimization of PA coupling in upcoming JET energetic particle experiments, for which the AEAD will aim to identify the contribution of alpha particles to AE drive during the DT campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Experimental studies of plasma-antenna coupling with the JET Alfven Eigenmode Active Diagnostic

This paper presents a dedicated study of plasma-antenna (PA) coupling with the Alfven Eigenmode Active Diagnostic (AEAD) in JET. Stable AEs and their resonant frequencies f, damping rates gamma < 0, and toroidal mode numbers n are measured for various PA separations and limiter versus X-point magnetic configurations. Two stable AEs are observed to be resonantly excited at distinct low and high frequencies in limiter plasmas. The values of f and n do not vary with PA separation. However, |gamma| increases with PA separation for the low-f, but not high-f, mode, yet this may be due to slightly different edge conditions. The high-f AE is detected throughout the transition from limiter to X-point configuration, though its damping rate increases; the low-f mode, on the other hand, becomes unidentifiable. The linear resistive MHD code CASTOR is used to simulate the frequency scan of an AEAD-like external antenna. For the limiter pulses, the high-f mode is determined to be an n = 0 GAE, while the low-f mode is likely an n = 2 TAE. During the transition from limiter to X-point configuration, CASTOR indicates that n = 1 and 2 EAEs are excited in the edge gap. These results extend previous experimental studies in JET and Alcator C-Mod; validate the computational work performed by Dvornova et al 2020 Phys. Plasmas 27 012507; and provide guidance for the optimization of PA coupling in upcoming JET energetic particle experiments, for which the AEAD will aim to identify the contribution of alpha particles to AE drive during the DT campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Searching for axionlike time-dependent cosmic birefringence with data from SPT-3G

Ultralight axionlike particles (ALPs) are compelling dark matter candidates because of their potential to resolve small-scale discrepancies between Λ CDM predictions and cosmological observations. Axion-photon coupling induces a polarization rotation in linearly polarized photons traveling through an ALP field; thus, as the local ALP dark matter field oscillates in time, distant static polarized sources will appear to oscillate with a frequency proportional to the ALP mass. We use observations of the cosmic microwave background from SPT-3G, the current receiver on the South Pole Telescope, to set upper limits on the value of the axion-photon coupling constant g φ γ over the approximate mass range 10 - 22 – 10 - 19 eV , corresponding to oscillation periods from 12 hours to 100 days. For periods between 1 and 100 days ( 4.7 × 10 - 22 eV ≤ m φ ≤ 4.7 × 10 - 20 eV ), where the limit is approximately constant, we set a median 95% C.L. upper limit on the amplitude of on-sky polarization rotation of 0.071 deg. Assuming that dark matter comprises a single ALP species with a local dark matter density of 0.3 GeV / cm 3 , this corresponds to g φ γ < 1.18 × 10 - 12 GeV - 1 × ( m φ 1.0 × 10 - 21 eV ) . These new limits represent an improvement over the previous strongest limits set using the same effect by a factor of ~ 3.8 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ORNL Input to GDSA Repository Systems Analysis FY21

This document satisfies the M3 milestone M3SF-21OR010304082 titled “ORNL Input to GDSA Repository Systems.” This document describes the current status of Oak Ridge National Laboratory’s (ORNL’s) efforts related to analyses of dual-purpose canister (DPC) disposal in unsaturated alluvium with a focus on thermal hydrological constraints on criticality timing and power output. This analysis updates previous analyses of thermal hydrological constraints on timing and power output of a potential criticality event in Dual-Purpose Canisters (DPCs) in a hypothetical repository in unsaturated alluvium using a more realistic representation of heat transport inside dry DPCs. PFLOTRAN was used for the simulations of multiphase thermal hydrology near a single DPC. The scenario considers a DPC failure at 9000 years, allowing water to enter and eventually fill the DPC. Once the DPC is filled to a level that could support a criticality event, different values for criticality power output were added to the decay heat. The main objective is to bound the power output that could be produced by a criticality event without driving water out of the package. For the conditions analyzed here, following a package breach, the alluvial formation could supply enough water to allow enough accumulation in the DPC to support a criticality event. However, the power output that would be generated is limited to modest values by loss of water moderator due to evaporation and vapor diffusion. In the reference case scenario, the DPC would not start to fill with water until about 16,000 years post closure and would not fill to a level that allows a criticality event until approximately 25,000 years post closure. The long-term average power output that could be sustained without driving off the water and terminating the criticality event is limited to approximately 100 W. Sensitivity to assumed conditions and parameters in the reference case, especially the deep percolation rate, need to be addressed but could not be undertaken because of numerical failures of the PFLOTRAN code running in general mode in the dry conditions of an unsaturated alluvium repository

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

BETO 2021 Peer Review - Waste Carbon Gas Upgrading via Acetogens 2.3.2.106

Waste carbon gas represents a large and diverse set of feedstocks that could be captured and turned into useful products. This includes waste gas emitted from industrial activity, syngas from burned plant biomass or processed municipal waste, and electrochemical reduction of CO2. Currently, carbon gas is being microbially converted to ethanol as a main product. However, ethanol is a lower value product with a limited market size. While these microbes can make other higher value products, there are no commercial processes for generating these other products, leaving a gap in understanding potential implementation for commercialization. Expanding the products microbially produced from waste carbon gas requires several steps before commercial implementation. We are studying the acetogen Clostridium ljungdahlii as a biocatalyst to convert waste carbon gas to the chemical 3-hydroxybutyrate (3HB), a plastic monomer and fuel precursor. For that, we are studying and engineering microbial characteristics for novel 3HB product formation from waste gas streams. This includes metabolic characterization, genetic engineering, gas fermentation scaling, as well as technoeconomic and life cycle analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Designing reinforcement learning algorithms for building HVAC control: From experimental observation to simulation comparisons

Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action space, DDPG outperformed DQN by requiring fewer computational resources and achieving better thermal comfort, lower energy consumption, and more stable control actions. The findings suggest that the ability of DDPG to handle continuous control variables more effectively allows for faster convergence in training and more precise control in practice, which enhances the overall efficiency and reliability of the HVAC system.

Guo, Fangzhou↗

π-Extended Porphyrin–Phthalocyanine Heterojunction Devices Exhibiting High Ammonia Sensitivity with a Remarkable Light Effect

π-Extended porphyrins represent an attractive class of organic compounds because of their unique photophysical, optoelectronic, and physicochemical properties. Herein, cross-conjugated (Ace-PQ-Ni) and linear-conjugated (AM6) porphyrins are used to build double-layer heterojunction devices by combining them with a lutetium bisphthalocyanine complex (LuPc 2 ). The heterojunction effect at the porphyrin–phthalocyanine interface plays a key role in the charge transport properties. Both devices exhibit exceptionally high ammonia sensitivity at room temperature and under ambient relative humidity, with limit of detection values of 156 and 115 ppb for Ace-PQ-Ni/LuPc 2 and AM6/LuPc 2 sensors, respectively. Interestingly, the Ace-PQ-Ni/LuPc 2 and AM6/LuPc 2 sensors display opposite effects upon light illumination. While the former sensors show largely decreased ammonia sensitivity under light illumination, the current variation of the latter under ammonia is remarkably enhanced with a multiplication factor of 13 and a limit of detection (LOD) of 83 ppb. Here, the striking difference in their sensing properties upon light illumination is attributed to their different π-conjugation pathways (cross-conjugation versus linear conjugation).

conductometric transducer↗

Proteomes reveal metabolic capabilities of Yarrowia lipolytica for biological upcycling of polyethylene into high-value chemicals

ABSTRACT Polyolefins derived from plastic wastes are recalcitrant for biological upcycling. However, chemical depolymerization of polyolefins can generate depolymerized plastic (DP) oil, comprising of a complex mixture of saturated, unsaturated, even, and odd hydrocarbons suitable for biological conversion. While DP oil contains a rich carbon and energy source, it is inhibitory to cells. Understanding and harnessing robust metabolic capabilities of microorganisms to upcycle the hydrocarbons in DP oil, both naturally and unnaturally occurring, into high-value chemicals are limited. Here, we discovered that an oleaginous yeast, Yarrowia lipolytica, undergoing short-term adaptation to DP oil robustly utilized a wide range of hydrocarbons for cell growth and production of citric acid and neutral lipids. When growing on hydrocarbons, Y. lipolytica partitioned into planktonic and oil-bound cells with each exhibiting distinct proteomes and amino acid distributions invested in establishing these proteomes. Significant proteome reallocation toward energy and lipid metabolism, belonging to 2 of the 23 Eukaryotic Orthologous Groups classes C and I, enabled robust growth of Y. lipolytica on hydrocarbons, with n-hexadecane as the preferential substrate. This investment was even higher for growth on DP oil where classes C and I were ranked one and two, respectively, and many associated proteins and pathways were expressed and upregulated including the hydrocarbon degradation pathway, Krebs cycle, glyoxylate shunt and, unexpectedly, propionate metabolism. However, a reduction in proteome allocation for protein biosynthesis, at the expense of the observed increase toward energy and lipid metabolisms, might have caused the inhibitory effect of DP oil on cell growth. IMPORTANCE Sustainable processes for biological upcycling of plastic wastes in a circular bioeconomy are needed to promote decarbonization and reduce environmental pollution due to increased plastic consumption, incineration, and landfill storage. Strain characterization and proteomic analysis revealed the robust metabolic capabilities of Yarrowia lipolytica to upcycle polyethylene into high-value chemicals. Significant proteome reallocation toward energy and lipid metabolisms was required for robust growth on hydrocarbons with n-hexadecane as the preferential substrate. However, an apparent over-investment in these same categories to utilize complex depolymerized plastic (DP) oil came at the expense of protein biosynthesis, limiting cell growth. Taken together, this study elucidates how Y. lipolytica activates its metabolism to utilize DP oil and establishes Y. lipolytica as a promising host for the upcycling of plastic wastes.

1-alkenes↗

Model validation and error attribution for a drifting qubit

Qubit performance is often reported in terms of a variety of single-value metrics, each providing a facet of the underlying noise mechanism limiting performance. However, the value of these metrics may drift over long timescales, and reporting a single number for qubit performance fails to account for the low-frequency noise processes that give rise to this drift. Here, in this work, we demonstrate how we can use the distribution of these values to validate or invalidate candidate noise models. We focus on the case of randomized benchmarking (RB), where typically a single error rate is reported but this error rate can drift over time when multiple passes of RB are performed. We show that using a statistical test as simple as the Kolmogorov-Smirnov statistic on the distribution of RB error rates can be used to rule out noise models, assuming the experiment is performed over a long enough time interval to capture relevant low frequency noise. With confidence in a noise model, we show how care must be exercised when performing error attribution using the distribution of drifting RB error rate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Physics-Informed Deep Learning for Reconstruction of Spatial Missing Climate Information in the Antarctic

Understanding the influence of the Antarctic on the global climate is crucial for the prediction of global warming. However, due to very few observation sites, it is difficult to reconstruct the rational spatial pattern by filling in the missing values from the limited site observations. To tackle this challenge, regional spatial gap-filling methods, such as Kriging and inverse distance weighted (IDW), are regularly used in geoscience. Nevertheless, the reconstructing credibility of these methods is undesirable when the spatial structure has massive missing pieces. Inspired by image inpainting, we propose a novel deep learning method that demonstrates a good effect by embedding the physics-aware initialization of deep learning methods for rapid learning and capturing the spatial dependence for the high-fidelity imputation of missing areas. We create the benchmark dataset that artificially masks the Antarctic region with ratios of 30%, 50% and 70%. The reconstructing monthly mean surface temperature using the deep learning image inpainting method RFR (Recurrent Feature Reasoning) exhibits an average of 63% and 71% improvement of accuracy over Kriging and IDW under different missing rates. With regard to wind speed, there are still 36% and 50% improvements. In particular, the achieved improvement is even better for the larger missing ratio, such as under the 70% missing rate, where the accuracy of RFR is 68% and 74% higher than Kriging and IDW for temperature and also 38% and 46% higher for wind speed. In addition, the PI-RFR (Physics-Informed Recurrent Feature Reasoning) method we proposed is initialized using the spatial pattern data simulated by the numerical climate model instead of the unified average. Compared with RFR, PI-RFR has an average accuracy improvement of 10% for temperature and 9% for wind speed. When applied to reconstruct the spatial pattern based on the Antarctic site observations, where the missing rate is over 90%, the proposed method exhibits more spatial characteristics than Kriging and IDW.

54 ENVIRONMENTAL SCIENCES↗