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DOE OSTI2021

Toroidal modeling of runaway avalanche in DIII-D discharges

Abstract A toroidal modeling tool is developed to study the runaway electron (RE) avalanche production process in tokamak plasmas, by coupling the Rosenbluth–Putvinski avalanche model (Rosenbluth and Putvinski 1997 Nucl. Fusion 37 1355) with an n = 0 magneto-hydrodynamic (MHD) solver. Initial value numerical simulations are carried out for two DIII-D discharges with different plasma shapes (one near circular, and the other with high elongation). It is found that, assuming the same level of about 1% seed current level, the Rosenbluth–Putvinski model somewhat underestimates the RE plateau current for the circular-shaped plasma, as compared with that measured in DIII-D experiments. For an elongated, higher current plasma, simulations find strong runaway current avalanche production despite the lack of measured plateau RE current in experiments. A possible reason for this discrepancy is a lack of additional RE dissipation physics in the present two-dimensional model. Systematic scans of the plasma boundary shape, at fixed pre-disruption plasma current, find that the plasma elongation helps to reduce the RE avalanche production, confirming recent results obtained with an analytic model (Fülöp et al 2020 J. Plasma Phys. 86 474860101). The effect of the plasma triangularity (either positive or negative), on the other hand, has a minor effect. On the physics side, the avalanche process involves two competing mechanisms associated with the electric field. On the one hand, a stronger electric field produces a higher instantaneous avalanche growth rate. On the other hand, a fast growing RE current quickly reduces the fraction of the conduction current together with the electric field, and hence a faster dissipation of the poloidal flux. As a final result of these two dynamic processes, the runaway plateau current is not always the largest with the strongest initial electric field. These results lay the foundation for future self-consistent inclusion of the MHD dynamics and the RE amplification process.

Physics↗

DOE OSTI2020

Interplay of changing irrigation technologies and water reuse: example from the upper Snake River basin, Idaho, USA

Abstract. Careful allotment of water resources for irrigation is critical for ensuring the resiliency of agriculture in semiarid regions, and modernizing irrigation technology to minimize inefficient water losses is an important tool for farmers and agricultural economies. While modernizing irrigation technology can achieve reductions in the nonbeneficial use of water, such as bare soil evaporation and nonconsumptive losses, water returned to the landscape is also reduced, often eliminating flow paths that other users rely on. In basins using a combination of surface and groundwater, replenishing aquifer storage by the managed aquifer recharge (MAR) of seasonally available water can mitigate the aquifer drawdown that results from reduced recharge when irrigation efficiency is improved. We examine the effects of MAR on the system-scale efficiency of modernizing irrigation technology and the resulting changes in the reuse of nonconsumptive losses, using a macroscale hydrologic model applied to the semiarid upper Snake River basin (USRB) of western Wyoming and southern Idaho, USA. Irrigation technologies were represented explicitly in the model, and available data informed baseline parameterizations of the irrigation technology. A suite of parameterizations were simulated that updated the existing technologies to be more efficient, both with and without sufficient MAR to cause a stabilization of the aquifer at the present-day head. As expected, simulated changes in irrigation technology resulted in greater downstream export of pristine water and a higher rate of aquifer drawdown when MAR was not simulated. Under current water use and cropping patterns, we were not able to simulate aquifer stabilization and maintain discharge downstream at any level of irrigation efficiency. We found support for the hypothesis that, as efficiency improves, less MAR is required to maintain a stable aquifer than when return flows are reduced due to increased efficiency. To evaluate the hypothesis, we defined the management benefit as a metric that compared the difference between the change in irrigation's net recharge and the change in MAR required as irrigation technology became more efficient. The metric generally indicated that less MAR was needed than net recharge was lost, but only for the most efficient case did the management benefit exceed the MAR needed at the baseline to stabilize the aquifer. Increasing efficiency of irrigation technology reduced the reuse of the gross irrigation derived from prior nonconsumptive losses, but simulating MAR increased reuse for a given parameterization, leading to higher effective irrigation efficiency. We find that local groundwater storage that users depend on is generally more sensitive to management decisions than downstream flows, and the drawdown of the aquifer without MAR always exceeded any decrease in discharge induced by MAR. Improving resource sufficiency in semiarid systems like the USRB will require an array of solutions that will need to balance benefits to local and downstream users.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Quantum simulations of hydrodynamics via the Madelung transformation

Developing numerical methods to simulate efficiently nonlinear fluid dynamics on universal quantum computers is a challenging problem. In this paper, a generalization of the Madelung transform is defined to solve quantum relativistic charged fluid equations interacting with external electromagnetic forces via the Dirac equation. The Dirac equation is discretized into discrete-time quantum walks which can be efficiently implemented on universal quantum computers. A variant of this algorithm is proposed to implement simulations using current noisy intermediate scale quantum (NISQ) devices in the case of homogeneous external forces. High resolution (up to N=2 17 grid points) numerical simulations of relativistic and nonrelativistic hydrodynamical shocks on current IBM NISQs are performed with this algorithm. Here, this paper demonstrates that fluid dynamics can be simulated on NISQs, and opens the door to simulating other fluids, including plasmas, with more general quantum walks and quantum automata.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2025

Modeling resistive-inductive evolution of currents in Wendelstein 7-X

This research investigates the temporal evolution of the toroidal plasma current in the Wendelstein 7-X (W7-X) stellarator under different heating, fueling, and current drive scenarios. The THRIFT code has been modernized and its predictions of the evolution of the toroidal current have been compared against experimentally measured currents in W7-X. Good agreement is found with respect to the characteristic timescale between experimentally measured and simulated toroidal currents. The total bootstrap current is under-predicted owing to the applicability of the BOOTSJ model for the plasma collisionalities in question. Edge plasma resistivity is found to play an important role in the asymptotic behavior of the evolution of the current, indicating a possible limitation of the minimum plasma temperature when applying this model. Simulations of ECCD and heating power steps show THRIFT is capable of capturing the dynamical evolution of the current in response to changes in current sources. Future uses of THRIFT include validating and benchmarking other non-inductive current models.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Improved melt model for power flow

Accelerators that drive z-pinch experiments transport current densities in excess of 1 MA/cm 2 in order to melt or ionize the target and implode it on axis. These high current densities stress the transmission lines upstream from the target, where rapid electrode heating causes plasma formation, melt, and possibly vaporization. These plasmas negatively impact accelerator efficiency by diverting some portion of the current away from the target, referred to as “current loss”. Simulations that are able to reproduce this behavior may be applied to improving the efficiency of existing accelerators and to designing systems operating at ever higher current densities. The relativistic particle-in-cell code CHICAGO ® is the primary code for modeling power flow on Sandia National Laboratories’ Z accelerator. We report here on new algorithms that incorporate vaporization and melt into the standard power-flow simulation framework. Taking a hybrid approach, the CHICAGO® kinetic/multi-fluid treatment has been expanded to include vaporization while the quasi-neutral equation-of-motion has been updated for melt at high current-densities. For vaporization, a new one-dimensional substrate model provides a more accurate calculation of electrode thermal, mass, and magnetic field diffusion as well as a means of emitting absorbed contaminants and vaporized metal ions. A quasi-fluid model has been implemented expressly to mimic the motion of imploding liners for accurate inductance histories. For melt, a multi-ion Hall-MHD option has been implemented and benchmarked against Alegra MHD. This new model is described with sufficient detail to reproduce these algorithms in any hybrid kinetic code. Physics results from the new code are also presented. A CHICAGO ® Hall-MHD simulation of a radial transmission line demonstrates that Hall physics, not included in Alegra, has no significant impact on the diffusion of electrode material. When surface contaminant desorption is mocked in as a hydrogen surface plasma, both the surface and bulk-material plasmas largely compress under the influence of the j × B force. Similar results are seen in Alegra, which also shows magnetic and material diffusion scaling with peak current. Test vaporization simulations using MagLIF and a power-flow experimental geometry show Fe + ions diffuse only a few hundred µm from the electrodes, so present models of Z power flow remain valid.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

EZ: An efficient, charge conserving current deposition algorithm for electromagnetic particle-in-cell simulations

Here, we present EZ, a novel current deposition algorithm for particle-in-cell (PIC) simulations. EZ calculates the current density on the electromagnetic grid due to macro-particle motion within a time step by solving the continuity equation of electrodynamics. Being a charge conserving hybridization of Esirkepov's method and ZigZag, we refer to it as “EZ” as shorthand for “Esirkepov meets ZigZag”. Simulations of a warm, relativistic plasma with PIConGPU show that EZ achieves the same level of charge conservation as the commonly used method by Esirkepov, yet reaches higher performance for macro-particle assignment-functions up to third-order. In addition to a detailed description of the functioning of EZ, reasons for the expected and observed performance increase are given, and guidelines for its implementation aiming at highest performance on GPUs are provided.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

QuaSiMo: A composable library to program hybrid workflows for quantum simulation

Abstract A composable design scheme is presented for the development of hybrid quantum/classical algorithms and workflows for applications of quantum simulation. The proposed object‐oriented approach is based on constructing an expressive set of common data structures and methods that enables programming of a broad variety of complex hybrid quantum simulation applications. The abstract core of the scheme is distilled from the analysis of the current quantum simulation algorithms. Subsequently, it allows synthesis of new hybrid algorithms and workflows via the extension, specialisation, and dynamic customisation of the abstract core classes defined by the proposed design. The design scheme is implemented using the hardware‐agnostic programming language QCOR into the QuaSiMo library. To validate the implementation, the authors test and show its utility on commercial quantum processors from IBM and Rigetti, running some prototypical quantum simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Measurement of minority carrier diffusion length in p -GaN using electron emission spectroscopy (EES)

Electron emission spectroscopy was performed on metalorganic chemical vapor deposition grown p-n – -n + junctions with p-thicknesses ranging from 50 to 300 nm, doped with [Mg] = 3.5 × 10 19 cm –3 . By measuring the decreasing emitted electron intensity from a cesiated p-GaN surface with increasing p-thickness, we were able to extract the minority carrier diffusion length of electron in p-type GaN, L e = 26 ± 3 nm. The measured value is in good agreement with literature reported values. In conclusion, the extrapolated electron current at the n – region–p-GaN interface is in reasonable agreement with the simulated electron current at the interface.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Role of edge-localized neoclassical tearing modes in quiescent H-mode plasmas in the DIII-D tokamak

The edge-harmonic oscillations (EHOs) in standard quiescent H-mode (QH-mode) plasmas in DIII-D are consistent with edge-localized neoclassical tearing modes (NTMs) based on nonlinear two-fluid MHD simulations. Using kinetic equilibria constrained by edge profile measurements, the MHD simulations show that the n = 1 NTM and its harmonics can be destabilized at the pedestal top of QH-mode plasma by the edge bootstrap current. The simulations further show that the unstable NTMs can saturate either at small (<2% ψ N ) or large (>4% ψ N ) island width depending on the magnitude of the edge bootstrap current, where ψ N is the normalized radius in poloidal flux. The onset of the EHO also results in a prompt decrease in the pedestal width and height, consistent with simulation results for the onset of the NTM at the top of the QH-mode pedestal. This suggests that the avoidance of edge-localized modes (ELMs) in QH-mode can be attributed to the enhanced local transport induced by the NTM that is sufficient to prevent the expansion of the pedestal to an unstable width, analogous to the mechanism explored for ELM suppression by resonant magnetic perturbations. Nonlinear MHD simulations scanning the E × B frequency and the ratio of parallel and perpendicular thermal diffusivity (χ | /χ ⊥ ) at the pedestal top show that edge-localized NTMs are destabilized for conditions of high E × B frequency, high pedestal temperature, and low pedestal density, qualitatively consistent with experimental conditions required for observing the EHO.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Geomagnetically Induced Current Field Test on Large Grid-Connected Power Transformers: Analysis, Model Development, and Simulations

Geomagnetic-induced current (GIC) flow in power grids can cause undesirable effects such as transformer overheating, harmonics, higher reactive power demand, etc. Many simulation models have been developed to study these effects, but real-world verification on modern transformer designs is rare. Here, this paper presents the first long-duration GIC field test in the U.S. performed on high-voltage, grid-connected transformers featuring winding clamps and tie rods instead of conventional tie bars. Field measurements were taken to evaluate GIC effects. These measurements also aided in developing and validating thermal and electromagnetic transient (EMT) models of the transformers. During the test, significant current and voltage distortions were observed along with considerable transformer reactive power losses. Analysis of the field measurements showed that the transformers’ hottest spot was at the inner windings, and their k-factors were close to factory test and software default values. Thermal simulations indicated that the transformers would not violate their thermal limits even for a GIC waveform that peaks at about 200 A/phase. EMT simulations revealed that increased transformer loading may reduce GIC-induced reactive power demand and harmonics in certain scenarios. The study also highlighted potential inaccuracies in using the k-factor method to calculate transformer reactive power losses.

EMTDC↗

DOE OSTI2024

One-dimensional simulation and validation of divertor detachment induced through nitrogen seeding on HL-2A

Divertor detachment is a promising method to solve the power exhaust problem in tokamak devices or even in future magnetic fusion reactors. In this work, a detachment experiment (HL-2A shot #38008) with mixed gas seeding (60% nitrogen and 40% deuterium) is simulated using the SD1D module in BOUT++. In the process from attachment to detachment, the target electron temperature and the target ion saturation current in simulations are found to be consistent with the experimental results measured by Langmuir probes on the target plate. In order to understand the underlying detachment mechanism on HL-2A, this work analyses the role of different particle species in the cases with different seeding rates. It shows that the plasma density varies little and the density of neutrals (D and D 2 ) slightly decreases with the increase of nitrogen seeding rate, such that plasma–neutral interactions cannot effectively reduce plasma energy and plasma momentum in the divertor. The case with a high seeding rate predicts that increasing seeding rate cannot reach a target temperature lower than 2.5 eV, which is the required temperature for strong plasma–molecule interactions. Thus, the plasma–molecule interactions may not be important in the divertor during nitrogen seeding. Here this work also studies the parallel forces including (1) force due to the parallel electric field, (2) friction forces, (3) ion- and electron-thermal forces, and (4) collisional reactions (e.g. charge exchange recombination and ionisation). It is found that the friction force between nitrogen ions and other particle species (primarily D + ) is the dominant force towards the target, while ion- and electron-thermal forces are the dominant force pushing nitrogen ions back to upstream. Parallel forces determine the parallel distribution of nitrogen impurities, and therefore decide the region of nitrogen radiation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Amundsen Sea Embayment ice-sheet mass-loss predictions to 2050 calibrated using observations of velocity and elevation change

Mass loss from the Amundsen Sea Embayment of the West Antarctic Ice Sheet is a major contributor to global sea-level rise (SLR) and has been increasing over recent decades. Predictions of future SLR are increasingly modelled using ensembles of simulations within which model parameters and external forcings are varied within credible ranges. Accurately reporting the uncertainty associated with these predictions is crucial in enabling effective planning for, and construction of defences against, rising sea levels. Calibrating model simulations against current observations of ice-sheet behaviour enables the uncertainty to be reduced. Here we calibrate an ensemble of BISICLES ice-sheet model simulations of ice loss from the Amundsen Sea Embayment using remotely sensed observations of surface elevation and ice speed. Each calibration type is shown to be capable of reducing the 90% credibility bounds of predicted contributions to SLR by 34 and 43% respectively.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Polynomial Scaling Localized Active Space Unitary Selective Coupled Cluster Singles and Doubles

We present a polynomial-scaling algorithm for the localized active space unitary selective coupled cluster singles and doubles (LAS-USCCSD) method. In this approach, cluster excitations are selected based on a threshold ϵ determined by the absolute gradients of the LAS-UCCSD energy with respect to cluster amplitudes. Using the generalized Wick’s theorem for multireference wave functions, we derive the gradient expression as a polynomial function of one-, two-, and three-body reduced density matrices and 1- and 2-electron integrals, valid for any multireference wave function. The resulting gradient implementation exhibits a memory scaling of 𝒪(N 6 ), with N spin orbitals in the combined active space of all fragments. The variational quantum eigensolver is used to optimize the selected cluster excitations on a quantum simulator. Furthermore, by plotting the energy error, defined as the difference between the LAS-USCCSD and corresponding CASCI energies, against the inverse cluster amplitude selection threshold (ϵ –1 ) for polyene chains containing 2 to 5 π-bond units, we establish a relationship between the energy error and the threshold. To further validate the accuracy of LAS-USCCSD, we computed the cis–trans isomerization energy of stilbene (a 20-qubit system) and the magnetic coupling constant of the tris-hydroxo-bridged chromium dimer [Cr 2 (OH) 3 (NH 3 ) 6 ] 3+ (evaluated as both 12- and 20-qubit systems) using the Qiskit-Qulacs simulator. Assessing such examples is important to determine the practical feasibility of quantum simulations for chemically realistic systems. Toward this goal, with the LAS-USCCSD algorithm we estimated the quantum resources required for simulating an active space of (30e,22o) in [Cr 2 (OH) 3 (NH 3 ) 6 ] 3+ , a size that remains beyond the reach of current quantum simulators for accurate treatment.

Algorithms↗

DOE OSTI2025

Simulation study of high-current 7 Li 3+ beam acceleration with laser ion source and RFQ linac using direct plasma injection

Accelerator-based neutron sources (ABNS) utilizing the 7 Li(p,n) 7 Be reaction in inverse kinematics offer strong forward-directed neutron emission, making them attractive for compact and clean neutron source with low background neutrons and unwanted radiation. However, practical use of such systems requires lithium ion beam currents that exceed the capability of conventional ion accelerators by two orders of magnitude. In this study, we numerically designed and evaluated a high-current acceleration system based on a direct plasma injection scheme (DPIS), combining a laser ion source (LIS) and a radio-frequency quadrupole (RFQ) linac. The ion extraction optics and RFQ entrance were optimized using IGUN, OPERA, and GPT, demonstrating that over 1.2 A-class beam current can be injected into the RFQ. The RFQ structure was designed under realistic engineering constraints including surface field strength (Kilpatrick factor) and RF power. GPT simulations showed that a 370 mA 7 Li 3+ beam can be successfully accelerated within a ±10 % energy spread. To validate downstream compatibility, we also designed a simplified medium-energy beam transport (MEBT) section and an interdigital H-type (IH) linac, confirming successful acceleration of a 320 mA beam to the total energy of 14 MeV. These results support the feasibility of the DPIS and RFQ approach as a promising solution for compact neutron sources and other high-intensity ion beam applications.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Active Learning Framework

Machine learning (ML) of interatomic potentials show great promise to accelerate scientific simulation, e.g., by emulating expensive computations at a high accuracy but much reduced computational cost. Training datasets are calculated from computationally expensive ab initio quantum mechanics methods, density functional theory (DFT). Trained on this data, an ML model can be very successful in predicting energy and forces for new atomic configurations. A critical factor is the quality and diversity of the training dataset. Thus, a highly automated approach to dataset construction based on active learning framework is designed suitable for material physics. The active learning scheme begins with fully randomized atomic configurations. Then, many Molecular Dynamics (MD) trajectories are simulated using current ML potentials, where each MD trajectory is initialized to a random disordered configuration. The temperature is varied in order to diversify the sampled configuration during these simulations. The variance of predictions for eight neural networks within an ensemble is analyzed to determine whether the model is operating as expected. This helps in determining whether collecting more data would be helpful to the model by checking the ensemble variance is greater than the threshold. In this case, the MD trajectory is terminated and the final atomic configuration is placed on a queue (SQL database) for DFT calculations and added to training dataset. Periodically, ML model is retrained to the updated training model. This Active Learning loop is iterated until the cost of MD simulations becomes prohibitively expensive. The MD simulations will hopefully be sufficiently robust to support nucleation after many active learning iterations. In this sense, active learning scheme must automatically discover the important low energy and nonequilibrium physics.

Nebgen, Benjamin↗

DOE OSTI2021

Sensitivity and Effective Parameterization of a Multi-Scale Model of Proton-Exchange-Membrane Water Electrolysis

The development of proton-exchange-membrane water electrolysis (PEMWE) is crucial to establishing a green-hydrogen infrastructure. Active research in hydrogen technologies is focused on minimizing costs, improving efficiency, and mitigating safety risks. In this study, sensitivity analyses were performed using a physics-based model and used to identify critical parameters capable of reducing overpotentials and safety risks. These parameters include operational (i.e. temperature), structural (i.e. thickness of the components), and material properties (i.e. exchange current density). Simulated results suggest that better engineering of the membrane electrode assemblies (MEA) can offset intrinsic limitations. Membrane thickness and conductivity yielded the largest percent change on performance. Gas crossover was observed to be sensitive to diffusion, solubility, and bubble formation. Current density regimes were identified, where each crossover parameter was most influential. MEA parameterization serves as a framework for theoretical PEMWE optimization simulations and input for design criteria for future research targets.

Dizon, A↗

DOE OSTI2020

Advanced Simulation and Experiments of Strongly Coupled Geomechanics and Flow for Gas Hydrate Deposits: Validation and Field Application. Final Report

The objectives of the proposed research are (1) to investigate geomechanical responses induced by depressurization experimentally and numerically; (2) to enhance the current numerical simulation technology in order to simulate complex physically coupled processes by depressurization and (3) to perform in-depth numerical analyses of two selected potential production test sites: one based on the deposits observed at the Ulleung basin UBGH2-6 site; and the other based on well-characterized accumulations from the westend Prudhoe Bay. To these ends, the recipient will have the following specific objectives: 1). Information obtained from multi-scale experiments previously conducted at the recipient’s research partner (the Korean Institute of Geoscience and Mineral Resources (KIGAM)) that were designed to represent the most promising known Ulleung Basin gas hydrate deposit as drilled at site UBGH2-6 will be evaluated (Task 2). These findings will be further tested by new experimental studies at Lawrence Berkeley National Laboratory (LBNL) and Texas A&M (TAMU) (Task 3) that are designed capture complex coupled physical processes between flow and geomechanics, such as sand production, capillarity, and formation of secondary hydrates. The findings of Tasks 2 and 3 will be used to further improve numerical codes. 2) Develop (in Tasks 4 through 6) an advanced coupled geomechanics and non-isothermal flow simulator (T+MAM) to account for large deformation and strong capillarity. This new code will be validated using data from the literature, from previous work by the project team, and with the results of the proposed experimental studies. The developed simulator will be applied to both Ulleung Basin and Prudhoe Bay sites, effectively addressing complex geomechanical and petrophysical changes induced by depressurization (e.g., frost-heave, strong capillarity, cryo-suction, induced fracturing, and dynamic permeability).

02 PETROLEUM↗

DOE OSTI2021

Sensitivity of organized convective storms to model grid spacing in current and future climates

Mesoscale convective systems (MCSs) are complexes of thunderstorms that become organized and cover hundreds of kilometres over several hours. MCSs are prolific rain producers in the tropics and mid-latitudes and are the major cause of warm-season flooding. Traditionally, climate models have difficulties in simulating MCSs partly due to the misrepresentation of complex process interactions that operate across a large range of scales. Significant improvements in simulating MCSs have been found in kilometre-scale models that explicitly simulate deep convection. However, these models operate in the grey zone of turbulent motion and have known deficiencies in simulating small-scale processes (e.g. entrainment, vertical mass transport). Here, we perform mid-latitude idealized ensemble MCS simulations under current and future climate conditions in three atmospheric regimes: hydrostatic (12 km horizontal grid spacing; Δx), non-hydrostatic (Δx = 4, 2 and 1 km) and large eddy scale (Δx = 500 m and 250 m). Our results show a dramatic improvement in simulating MCS precipitation, movement, cold pools, and cloud properties when transitioning from 12 km to 4 km Δx. Decreasing Δx beyond 4 km results in modest improvements except for up- and downdraft sizes, average vertical mass fluxes, and cloud top height and temperature, which continue to change. Most important for climate modelling is that Δx = 4 km simulations reliably capture most MCS climate change signals compared to those of the Δx = 250 m runs. Significantly different climate change signals are found in Δx = 12 km runs that overestimate extreme precipitation changes by up to 100%.

54 ENVIRONMENTAL SCIENCES↗