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DOE OSTI2025

Conformal Hierarchical Simulation-Based Inference with Local Validity

Trustworthy and interpretable uncertainty quantification is a long-standing challenge in artificial intelligence. Simulation-based inference (SBI) comprises a broad swath of approaches for estimating latent parameters with uncertainties. Although flexible neural density estimators in SBI can be remark- ably expressive capturing highly structured, high-dimensional posteriors their credible regions can be badly mis-calibrated and are often only accompanied by heuristic coverage checks. We present the first SBI framework that delivers finite-sample local valid coverage guarantees that hold in the neighborhood of each observation. Our framework can couple any off-the-shelf hierarchical SBI engine with a confor- mal Bayesian post-processing step that operates on the posterior predictive density. A kernel-weighted conformity score adapts the conformal quantile to the local geometry of the data, yielding prediction sets that are simultaneously (i) marginally calibrated, (ii) locally valid, and (iii) hierarchical, handling global and observation-specific parameters in a single pass. Through experiments on synthetic data and benchmarks from neuroscience and physics, we show that our approach attains 1 − α coverage, where prior SBI methods under- or over-cover. Our approach also maintains a competitive, credible set size with minimal computational overhead. Finally, our approach can be used to make predictions on real data and give valid credible regions modulo weight-initialization-based model mis-specification.

Trivedi, Shubhendu [Fermilab]↗

NASA NTRS1998

CAPRI (Computational Analysis PRogramming Interface): A Solid Modeling Based Infra-Structure for Engineering Analysis and Design Simulations

CAPRI is a CAD-vendor neutral application programming interface designed for the construction of analysis and design systems. By allowing access to the geometry from within all modules (grid generators, solvers and post-processors) such tasks as meshing on the actual surfaces, node enrichment by solvers and defining which mesh faces are boundaries (for the solver and visualization system) become simpler. The overall reliance on file 'standards' is minimized. This 'Geometry Centric' approach makes multi-physics (multi-disciplinary) analysis codes much easier to build. By using the shared (coupled) surface as the foundation, CAPRI provides a single call to interpolate grid-node based data from the surface discretization in one volume to another. Finally, design systems are possible where the results can be brought back into the CAD system (and therefore manufactured) because all geometry construction and modification are performed using the CAD system's geometry kernel.

Haimes, Robert↗

DOE OSTI2015

SU-F-BRA-15: Physical Aspects and Clinical Applications of Post-Treatment Yttrium-90 PET-Based Dosimetry

Purpose: The accuracy of PET-based post-treatment dosimetry of yttrium-90 microspheres has been improving over the past decade and is now at a stage, permitting volumetric dose-outcome studies. We outline the recent advances and identify the physical limitations to the accuracy of the dose calculations. Methods: Convolution of the measured PET activity density distribution with a pre-calculated voxel-dose-kernel (VDK) is the most widely used method for dose reconstruction. Therefore, accurate knowledge of the beta+ branching ratio as well as the micro-dosimetric characteristics of electron interactions within the microsphere is essential for the computation of the dose kernel. We implement a model of the microspheres used in our clinic to calculate the modified electron energy spectrum at the microsphere’s surface and to determine the impact of self-shielding on the dose reconstruction. The three-dimensional dose distributions obtained for 10 patients treated with radio-embolization with yttrium-90 microspheres are evaluated and various DVH markers are investigated for correlation with outcome. Results: The methods for reducing the overall computation uncertainty are systematically outlined in this presentation. Since the latest experimental data on yttrium-90 beta+ branching ratio has a relative uncertainty of 1.5%, all contributing factors derived from Monte Carlo simulations must be brought to a sub 1% level. The self-shielding within the microspheres is found to be responsible for up to 6% reduction of the reconstructed dose in low-gradient regions and must be taken into account. The contribution of trace amounts of other beta+ emitters introduced during the manufacturing process is also discussed. Conclusion: The accelerating pace of clinical adoption of PET-based post-treatment dosimetry is mainly due to advances in both quantitative PET imaging and physical models of dose deposition. We show that the overall physical dose uncertainty in the convolution step can be further reduced, thus making ongoing multi-institutional dose-outcome studies even more reliable.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2004

Kernel PLS Estimation of Single-trial Event-related Potentials

Nonlinear kernel partial least squaes (KPLS) regressior, is a novel smoothing approach to nonparametric regression curve fitting. We have developed a KPLS approach to the estimation of single-trial event related potentials (ERPs). For improved accuracy of estimation, we also developed a local KPLS method for situations in which there exists prior knowledge about the approximate latency of individual ERP components. To assess the utility of the KPLS approach, we compared non-local KPLS and local KPLS smoothing with other nonparametric signal processing and smoothing methods. In particular, we examined wavelet denoising, smoothing splines, and localized smoothing splines. We applied these methods to the estimation of simulated mixtures of human ERPs and ongoing electroencephalogram (EEG) activity using a dipole simulator (BESA). In this scenario we considered ongoing EEG to represent spatially and temporally correlated noise added to the ERPs. This simulation provided a reasonable but simplified model of real-world ERP measurements. For estimation of the simulated single-trial ERPs, local KPLS provided a level of accuracy that was comparable with or better than the other methods. We also applied the local KPLS method to the estimation of human ERPs recorded in an experiment on co,onitive fatigue. For these data, the local KPLS method provided a clear improvement in visualization of single-trial ERPs as well as their averages. The local KPLS method may serve as a new alternative to the estimation of single-trial ERPs and improvement of ERP averages.

Rosipal, Roman↗

DOE OSTI2026

Conservation laws and effective hadronization models

Hadronization models based on local string-breaking dynamics are typically Markovian by construction, yet the physical ensemble of final states is shaped by global constraints that couple the entire fragmentation trajectory. Recasting hadronization as a conditioned stochastic diffusion process provides a precise mathematical resolution to this tension. In particular, this language reveals explicitly that constraints stemming from conservation laws induce non-Markovian correlations between otherwise independent fragmentation steps, and that these correlations can be absorbed exactly into a renormalization of the local dynamics through a Doob $h$-transform. We develop this formalism for a $q\bar{q}$ string in the chiral limit, where the longitudinal-transverse factorization of the Lund kernel becomes exact, enabling systematic power counting and clean ultraviolet (UV)/infrared (IR) separation. The dynamics organize naturally into a tower of effective theories distinguished by the remaining string mass, spanning a UV fixed point with scale-invariant transport coefficients, an intermediate regime where transverse phase space induces controlled running, and an IR boundary layer where non-local effects enter at leading order. The tower exhibits genuine Wilsonian structure, including $β$-functions, anomalous dimensions, and systematic matching conditions. The resulting framework achieves a clean factorization of universal microscopic fragmentation dynamics from infrared constraint effects, and opens new directions for both the theoretical analysis and practical simulation of hadronization.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗

DOE OSTI2023

Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach. In this work, we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets. Firstly, we develop a novel coarse-graining method, to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets. Inspired by the weighted essentially non-oscillatory (WENO) scheme, the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil, then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities. Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion. In the first phase, we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties. Then, in the second phase, the material damage criterion is learnt as a smoothed step function from the data with fractures. As a result, a peridynamics surrogate is obtained. As a continuum model, our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training, and hence allows for substantial reductions in computational cost compared with MD. We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene. Our tests show that the proposed data-driven model is robust and generalizable, in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Data refactoring↗

DOE OSTI2016

Extreme Scale Plasma Turbulence Simulations on Top Supercomputers Worldwide

The goal of the extreme scale plasma turbulence studies described in this paper is to expedite the delivery of reliable predictions on confinement physics in large magnetic fusion systems by using world-class supercomputers to carry out simulations with unprecedented resolution and temporal duration. This has involved architecture-dependent optimizations of performance scaling and addressing code portability and energy issues, with the metrics for multi-platform comparisons being 'time-to-solution' and 'energy-to-solution'. Realistic results addressing how confinement losses caused by plasma turbulence scale from present-day devices to the much larger $25 billion international ITER fusion facility have been enabled by innovative advances in the GTC-P code including (i) implementation of one-sided communication from MPI 3.0 standard; (ii) creative optimization techniques on Xeon Phi processors; and (iii) development of a novel performance model for the key kernels of the PIC code. Our results show that modeling data movement is sufficient to predict performance on modern supercomputer platforms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Chen, Jieyang↗

DOE OSTI2013

Motion as a perturbation: Measurement-guided dose estimates to moving patient voxels during modulated arc deliveries

Purpose: To present a framework for measurement-guided VMAT dose reconstruction to moving patient voxels from a known motion kernel and the static phantom data, and to validate this perturbation-based approach with the proof-of-principle experiments. Methods: As described previously, the VMAT 3D dose to a static patient can be estimated by applying a phantom measurement-guided perturbation to the treatment planning system (TPS)-calculated dose grid. The fraction dose to any voxel in the presence of motion, assuming the motion kernel is known, can be derived in a similar fashion by applying a measurement-guided motion perturbation. The dose to the diodes in a helical phantom is recorded at 50 ms intervals and is transformed into a series of time-resolved high-density volumetric dose grids. A moving voxel is propagated through this 4D dose space and the fraction dose to that voxel in the phantom is accumulated. The ratio of this motion-perturbed, reconstructed dose to the TPS dose in the phantom serves as a perturbation factor, applied to the TPS fraction dose to the similarly situated voxel in the patient. This approach was validated by the ion chamber and film measurements on four phantoms of different shape and structure: homogeneous and inhomogeneous cylinders, a homogeneous cube, and an anthropomorphic thoracic phantom. A 2D motion stage was used to simulate the motion. The stage position was synchronized with the beam start time with the respiratory gating simulator. The motion patterns were designed such that the motion speed was in the upper range of the expected tumor motion (1-1.4 cm/s) and the range exceeded the normally observed limits (up to 5.7 cm). The conformal arc plans for X or Y motion (in the IEC 61217 coordinate system) consisted of manually created narrow (3 cm) rectangular strips moving in-phase (tracking) or phase-shifted by 90 Degree-Sign (crossing) with respect to the phantom motion. The XY motion was tested with the computer-derived VMAT MLC sequences. For all phantoms and plans, time-resolved (10 Hz) ion chamber dose was collected. In addition, coronal (XY) films were exposed in the cube phantom to a VMAT beam with two different starting phases, and compared to the reconstructed motion-perturbed dose planes. Results: For the X or Y motions with the moving strip and geometrical phantoms, the maximum difference between perturbation-reconstructed and ion chamber doses did not exceed 1.9%, and the average for any motion pattern/starting phase did not exceed 1.3%. For the VMAT plans on the cubic and thoracic phantoms, one point exhibited a 3.5% error, while the remaining five were all within 1.1%. Across all the measurements (N = 22), the average disagreement was 0.5 {+-} 1.3% (1 SD). The films exhibited {gamma}(3%/3 mm) passing rates {>=}90%. Conclusions: The dose to an arbitrary moving voxel in a patient can be estimated with acceptable accuracy for a VMAT delivery, by performing a single QA measurement with a cylindrical phantom and applying two consecutive perturbations to the TPS-calculated patient dose. The first one accounts for the differences between the planned and delivered static doses, while the second one corrects for the motion.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-G-204-05: The Effects of CT Acquisition and Reconstruction Conditions On Computed Texture Feature Values of Lung Lesions

Purpose: Texture features have been investigated as a biomarker of response and malignancy. Because these features reflect local differences in density, they may be influenced by acquisition and reconstruction parameters. The purpose of this study was to investigate the effects of radiation dose level and reconstruction method on features derived from lung lesions. Methods: With IRB approval, 33 lung tumor cases were identified from clinically indicated thoracic CT scans in which the raw projection (sinogram) data were available. Based on a previously-published technique, noise was added to the raw data to simulate reduced-dose versions of each case at 25%, 10% and 3% of the original dose. Original and simulated reduced dose projection data were reconstructed with conventional and two iterative-reconstruction settings, yielding 12 combinations of dose/recon conditions. One lesion from each case was contoured. At the reference condition (full dose, conventional recon), 17 lesions were randomly selected for repeat contouring (repeatability). For each lesion at each dose/recon condition, 151 texture measures were calculated. A paired differences approach was employed to compare feature variation from repeat contours at the reference condition to the variation observed in other dose/recon conditions (reproducibility). The ratio of standard deviation of the reproducibility to repeatability was used as the variation measure for each feature. Results: The mean variation (standard deviation) across dose levels and kernel was significantly different with a ratio of 2.24 (±5.85) across texture features (p=0.01). The mean variation (standard deviation) across dose levels with conventional recon was also significantly different with 2.30 (7.11) (p=0.025). The mean variation across reconstruction settings of original dose has a trend in showing difference with 1.35 (2.60) among all features (p=0.09). Conclusion: Texture features varied considerably with variations in dose and reconstruction condition. Care should be taken to standardize these conditions when using texture as a quantitative feature. This effort supported in part by a grant from the National Cancer Institute’s Quantitative Imaging Network (QIN): U01 CA181156; The UCLA Department of Radiology has a Master Research Agreement with Siemens Healthcare; Dr. McNitt-Gray has previously received research support from Siemens Healthcare.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Meshfree Methods for Modeling Chemo-Mechanical Cathode Cracking in Li-Ion Batteries

Through repeated charging and discharging, the electrodes of a Li-ion battery experience cyclic loading causing swelling and contraction due to the movement of lithium, also known as intercalation. This research focuses specifically on the chemo-mechanical cracking in the cathode. Because cathode particles are comprised of many randomly-oriented grains, which have highly anisotropic material properties, the expansion and contraction is very non-uniform. As a result, stress concentrations tend to form between grains, which necessitates the modeling of crack propagation largely along grain boundaries. Chemo-mechanical models are simulated mainly by two methods: the cohesive zone model (CZM) and the continuous damage model (CDM). The CZM is more accurate at capturing the sharp discontinuities of a crack but is very computationally expensive and intractable for large-scale models as a result. Conversely, the CDM is easily computed but not well-suited to easily allow for discontinuous field variables, which are inherent across a crack. This study aims to improve the CDM's ability to capture discontinuous cracks. Current versions of the CDM use the finite element method (FEM), which is one of the most widely used approaches for spatial discretization. This research investigates the use of the Reproducing Kernel Particle Method (RKPM), a meshfree method, for spatial discretization and aims to achieve a chemo-mechanical crack propagation model that achieves both intermediate accuracy and computational time between a CDM and CZM. To gain a better understanding of how the meshfree model compares to the current FEM model in capturing cathode crack propagation, further investigation is needed.

cathode cracking↗

DOE OSTI2023

Meshfree Multiphysics Damage Modeling of Li-ion Battery Materials

Through repeated charging and discharging cycles, the electrodes of a Li-ion battery experience significant swelling and contraction due to the movement of lithium, also known as intercalation. This research focuses specifically on the chemo-mechanical cracking in the cathode. Because cathode particles are comprised of many randomly-oriented grains, which have highly anisotropic material properties, the expansion and contraction is very non-uniform. As a result, stress concentrations tend to form between grains, which necessitates the modeling of crack propagation largely along grain boundaries and material interfaces. Chemo-mechanical damage models are generally simulated by one of two methods: the cohesive zone model (CZM) and the continuous damage model (CDM). The CZM is more accurate at capturing the sharp discontinuities of a crack but is very computationally expensive and intractable for large-scale models as a result. Conversely, the CDM is easily computed but not well-suited to easily allow for discontinuous field variables, which are inherent across a crack. This study aims to improve the CDM's ability to capture discontinuous cracks. Current versions of the CDM use the finite element method (FEM), which is one of the most widely used approaches for spatial discretization. This research investigates the use of the Reproducing Kernel Particle Method (RKPM), a meshfree method, for spatial discretization and aims to achieve a coupled chemo-mechanical crack propagation model that enhances accuracy while maintaining high computational efficiency. This model features a fully coupled, iterative electrochemistry solution, which informs the meshfree damage model of impending crack formation. To gain a better understanding of how the meshfree model compares to the current FEM model in capturing cathode crack propagation, further investigation is needed.

damage modeling↗

NASA NTRSDate not supplied

Sampling Functions from Gaussian Processes and Structured Covariance Gaussian Networks

When learning aerodynamic models from data, it is critical to incorporate estimates of model uncertainty. This motivates the design of probabilistic aerodynamic databases which can be sampled to generate physically and statistically plausible aerodynamic models. In this talk we discuss how to sample deterministic functions from two different kinds of probabilistic models and demonstrate their use. First, Gaussian Process Regressors (GPRs) are a widely used probabilistic kernel-based model which can be thought of as Gaussian distributions over functions. GPRs are generally trained by maximizing the marginal likelihood of seeing the training data over the kernel parameter space. Sample functions are easily generated by drawing points from the Gaussian distribution at desired input points. However, when the points are not known ahead of time, the classical sampling approach is not possible since successive function samples will generate different function realizations. We present an approach for sampling consistent function evaluations from a GPR over multiple samples. Second, we describe a neural network architecture which learns a conditional Gaussian distribution by maximizing the marginal likelihood at each point in the input space. We then discuss and compare several options for generating sample functions which match this distribution. Finally, we demonstrate the use of these probabilistic aerodynamic models in an atmospheric reentry simulation.

Gaussian process regression↗

DOE OSTI2016

Thermo mechanical analysis of fully ceramic microencapsulated fuel during in-pile operation

A proposed fuel for improved performance in LWRs (Light Water Reactors) is FCM (fully encapsulated micro-ceramic) fuel concept that involves TRISO (Tri-structural-Isotropic) fuel particles embedded in a NITE (Nano Infiltrated Eutectic) silicon carbide matrix. TRISO fuel particles contain a spherical fuel kernel that will likely range from about 500 to in excess of 800 μm in diameter. The kernel and buffer layer are then typically coated with 3 isotropic layers consisting of a dense inner pyrolytic carbon (IPyC), a silicon carbide (SiC) layer, and an outer layer of dense, pyrolytic carbon (OPyC). These layers are typically around 40 μm thick, but can range from 20 to 60 μm. The TRISO particle packing fraction in the NITE-SiC matrix is expected to be 40-45 vol.%. The release of radioactivity into the coolant is dependent on the integrity of the silicon carbide layer of the TRISO particles and the NITE-SiC matrix. BISON, a code under development by Idaho National Laboratory, has been built on the Multi-physics Object Oriented Simulation Environment (MOOSE). MOOSE is a massively parallel, finite element computational system that uses a Jacobian-free, Newton-Krylov (JFNK) method to solve coupled systems and non-linear partial differential equations. A single particle comparison to fuel performance codes such as PARFUME was conducted and demonstrated that BISON is able to simulate the required physics. FCM pellets embedded with homogenous particles were simulated. It was found that the interior matrix temperature was predicted to be considerably lower than for an equivalent UO{sub 2} pellet. The swelling dependence on temperature created a compressive region around the perimeter of the pellet. However, at fluences above 6.10{sup 25} neutrons/m{sup 2}, the swelling of the pyrolytic carbon might cause significant tensile stresses and possible cracks near the surface of the pellet. This suggests that the pyrolytic carbon swelling may be an important factor in the lifetime of this fuel type.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2015

Improved dosimetry for targeted radionuclide therapy using nonrigid registration on sequential SPECT images

Purpose: Voxel-level and patient-specific 3D dosimetry for targeted radionuclide therapy (TRT) typically involves serial nuclear medicine scans. Misalignment of the images can result in reduced dosimetric accuracy. Since the scans are typically performed over a period of several days, there will be patient movement between scans and possible nonrigid organ deformation. This work aims to implement and evaluate the use of nonrigid image registration on a series of quantitative SPECT (QSPECT) images for TRT dosimetry. Methods: A population of 4D extended cardiac torso phantoms, comprised of three In-111 Zevalin biokinetics models and three anatomical variations, was generated based on the patient data. The authors simulated QSPECT acquisitions at five time points. At each time point, individual organ and whole-body deformation between scans were modeled by translating/rotating organs and the body up to 5°/voxels, keeping ≤5% difference in organ volume. An analytical projector was used to generate realistic noisy projections for a medium energy general purpose collimator. Projections were reconstructed using OS-EM algorithm with geometric collimator detector response, attenuation, and scatter corrections. The QSPECT images were registered using organ-based nonrigid image registration method. The cumulative activity in each voxel was obtained by integrating the activity over time. Dose distribution images were obtained by convolving the cumulative activity images with a Y-90 dose kernel. Dose volume histograms (DVHs) for organs-of-interest were analyzed. Results: After nonrigid registration, the mean differences in organ doses compared to the case without misalignment were improved from (−15.50 ± 5.59)% to (−2.12 ± 1.05)% and (−7.28 ± 2.30)% to (−0.23 ± 0.71)% for the spleen and liver, respectively. For all organs, the cumulative DVHs showed improvement after nonrigid registration and the normalized absolute error of differential DVHs ranged from 6.79% to 22.70% for liver and 26.00% to 39.70% for spleen with different segmentation methods. Conclusions: These results demonstrated that nonrigid registration of sequential QSPECT images is feasible for TRT and improves the accuracy of 3D dosimetry.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2004

Structure of Propagating and Attached Hydrocarbon Flames

Direct numerical simulations with C3-chemistry and radiative heat-loss models have been performed to reveal the internal structure of propagating and attached flames in an axisymmetric fuel jet of methane, ethane, ethylene, acetylene, or propane in air under normal and zero gravity. Observations of the flames were also made at the NASA Glenn 2.2-Second Drop Tower. In computations, the fuel issued into quasi-quiescent air for a fixed mixing time before it was ignited along the centerline at stoichiometry. The edge of the flame propagated through a flammable layer at the laminar flame speed of the stoichiometric fuel-air mixture independent of gravity. For all cases, a peak reactivity spot, i.e., reaction kernel, was formed in the flame base, thereby holding a trailing diffusion flame. The location of the reaction kernel in the attached flames depended inversely on the reactivity. The reaction-kernel correlations between the reactivity and the velocity were developed further using variables related to local Damkahler and Peclet numbers.

Takahashi, Fumiaki↗

NASA NTRS2015

The ENSO Effects on Tropical Clouds and Top-of-Atmosphere Cloud Radiative Effects in CMIP5 Models

The El Nino-Southern Oscillation (ENSO) effects on tropical clouds and top-of-atmosphere (TOA) cloud radiative effects (CREs) in Coupled Model Intercomparison Project Phase5 (CMIP5) models are evaluated using satellite-based observations and International Satellite Cloud Climatology Project satellite simulator output. Climatologically, most CMIP5 models produce considerably less total cloud amount with higher cloud top and notably larger reflectivity than observations in tropical Indo-Pacific (60 degrees East - 200 degrees East; 10 degrees South - 10 degrees North). During ENSO, most CMIP5 models considerably underestimate TOA CRE and cloud changes over western tropical Pacific. Over central tropical Pacific, while the multi-model mean resembles observations in TOA CRE and cloud amount anomalies, it notably overestimates cloud top pressure (CTP) decreases; there are also substantial inter-model variations. The relative effects of changes in cloud properties, temperature and humidity on TOA CRE anomalies during ENSO in the CMIP5 models are assessed using cloud radiative kernels. The CMIP5 models agree with observations in that their TOA shortwave CRE anomalies are primarily contributed by total cloud amount changes, and their TOA longwave CRE anomalies are mostly contributed by changes in both total cloud amount and CTP. The model biases in TOA CRE anomalies particularly the strong underestimations over western tropical Pacific are, however, mainly explained by model biases in CTP and cloud optical thickness (tau) changes. Despite the distinct model cloud biases particularly in tau regime, the TOA CRE anomalies from cloud amount changes are comparable between the CMIP5 models and observations, because of the strong compensations between model underestimation of TOA CRE anomalies from thin clouds and overestimation from medium and thick clouds.

Su, Wenying↗